Biomarkers indicative of neurological events

Abstract

Disclosed herein are methods and systems useful for identifying, diagnosing, and evaluating a subject that has sustained or may have sustained a neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration). In particular, the present disclosure identifies various biomarkers related to stroke-related neurodegeneration and stroke-related inflammation, the detection and / or differential expression of which can be used to assess the presence or absence of a neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration) in a subject, and can be used as a basis for diagnosing a subject as having a specific type of neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration). The various biomarkers related to stroke-related neurodegeneration and stroke-related inflammation can be detected individually or in combination and can be used as an important diagnostic and therapeutic tool for assessing a subject's neurological status.

Description

[0001]Attorney Docket No. UAZ-43247.601 BIOMARKERS INDICATIVE OF NEUROLOGICAL EVENTS CROSS REFERENCE TO RELATED APPLICATIONS The present application claims priority to U.S. Provisional Application No. 63 / 676,727, filed July 29, 2024, which is incorporated herein by reference in its entirety. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT This invention was made with government support under Grant Nos. NS131110 awarded by National Institutes of Health. The government has certain rights in the invention. FIELD OF THE INVENTION Disclosed herein are methods and systems useful for identifying, diagnosing, and evaluating a subject that has sustained or may have sustained a neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration). In particular, the present disclosure identifies various biomarkers related to stroke-related neurodegeneration and stroke-related inflammation, the detection and / or differential expression of which can be used to assess the presence or absence of a neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration) in a subject, and can be used as a basis for diagnosing a subject as having a specific type of neurological event (e.g., stroke, stroke- related inflammation, stroke-related neurodegeneration). The various biomarkers related to stroke-related neurodegeneration and stroke-related inflammation can be detected individually or in combination and can be used as an important diagnostic and therapeutic tool for assessing a subject’s neurological status. INTRODUCTION Ischemic stroke remains a leading cause of mortality and long-term disability worldwide, emphasizing the need for advancements in diagnostic methodologies to enhance patient outcomes (1). Importantly, ischemic stroke is characterized by complex spatial and temporal events that develop for hours and days (2). Traditional diagnostic approaches in ischemic stroke often rely on clinical assessments and neuroimaging techniques, such as computed tomography (CT) or MRI. While invaluable, these methodologies often present limitations in their ability to provide rapid, sensitive, and comprehensive insights into the Attorney Docket No. UAZ-43247.601 dynamic metabolic perturbations underlying stroke onset and progression. For these reasons, the identification and validation of plasma biomarkers is necessary for improving stroke diagnosis, prognosis, and therapeutic interventions. The present invention addresses these needs. SUMMARY OF THE INVENTION Experiments conducted during the course of identifying embodiments for the present invention were implemented with an objective to identify novel plasma biomarkers of neurodegeneration and inflammation in aged male mice subjected to a distal middle cerebral artery (MCA) occlusion model of ischemic stroke. To accomplish this objective, experiments employed differential mobility spectroscopy and ultrahigh performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS / MS), coincident with advanced bioinformatic analyses, to conduct targeted lipidomic profiling and global untargeted metabolomic profiling in plasma collected temporally at 24 h, 1 wk, 2 wk, 3 wk, 4 wk, 5 wk, 6 wk, and 7 wk after stroke, using plasma collected from naïve mice as controls. An acute signature of brain lipid catabolism in the plasma 24 h after stroke was discovered. Notably, a substantial portion of these elevated lipids and metabolites were essential components of myelin. An ancillary biphasic signature of lipid metabolism was further discovered, with elevations in acyl carnitines, eicosanoids, and fatty acids occurring in the acute and chronic phases after stroke. We also identified acute and subacute signatures of amino acid metabolism 24 h and 1 wk after stroke and a prolonged chronic signature of nucleotide metabolism 3 wk, 4 wk, 5 wk, and 6 wk after stroke. Myelin breakdown products, including SM and HCER lipid species, were indicated as plasma biomarkers of neurodegeneration.12-HETE, an eicosanoid generated through the enzymatic oxidation of arachidonic acid, in addition to other arachidonic acid derivatives, were indicated as plasma biomarkers of inflammation. Accordingly, disclosed herein are methods and systems useful for identifying, diagnosing, and evaluating a subject that has sustained or may have sustained a neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration). In particular, the present disclosure identifies various biomarkers related to stroke-related neurodegeneration and stroke-related inflammation, the detection and / or differential expression of which can be used to assess the presence or absence of a neurological event (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration) in a subject, and can be used as a basis for diagnosing a subject as having a specific type of neurological event Attorney Docket No. UAZ-43247.601 (e.g., stroke, stroke-related inflammation, stroke-related neurodegeneration). The various biomarkers related to stroke-related neurodegeneration and stroke-related inflammation can be detected individually or in combination and can be used as an important diagnostic and therapeutic tool for assessing a subject’s neurological status. In certain embodiments, the present invention provides a method of measuring or detecting at least one biomarker, the method comprising: obtaining a sample from a subject suffering from or suspected of suffering from a neurological event; and measuring or detecting at least one stroke-related neurodegeneration biomarkers selected from one or more myelin-breakdown products, wherein the one or more myelin-breakdown products are selected from sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides, or any combinations thereof in the sample. In some embodiments, the measurement or detection of the at least one stroke-related neurodegeneration biomarkers indicates that the subject has sustained a stroke. In some embodiments, the measurement or detection of the at least one stroke-related neurodegeneration biomarkers indicates that the subject has sustained stroke-related neurodegeneration. In some embodiments, the method further comprises treating the subject with either tPA or 2-hydroxypropyl-^-cyclodextrin (HP^CD) if the subject is indicated as having sustained a stroke or stroke-related neurodegeneration. In some embodiments, the sample is a plasma sample. In some embodiments, the subject is a human subject. In some embodiments, the subject is a human subject suffering from or at risk of suffering from a stroke and / or stroke- related neurodegeneration. In some embodiments, the neurological event is a stroke and / or stroke-related neurodegeneration. In certain embodiments, the present invention provides a method of measuring or detecting at least one biomarker, the method comprising: obtaining a sample from a subject suffering from or suspected of suffering from a neurological event; and measuring or detecting at least one stroke-related inflammation biomarkers selected from one or more eicosanoids derived from an arachidonic acid cascade, wherein the one or more eicosanoids derived from an arachidonic acid cascade are selected from prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15- Attorney Docket No. UAZ-43247.601 HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)), or any combinations thereof in the sample. In some embodiments, the measurement or detection of the at least one stroke-related inflammation biomarkers indicates that the subject has sustained a stroke. In some embodiments, the measurement or detection of the at least one stroke-related inflammation biomarkers indicates that the subject has sustained stroke-related inflammation. In certain embodiments, the method further comprises treating the subject with either tPA or 2-hydroxypropyl-^-cyclodextrin (HP^CD) if the subject is indicated as having sustained a stroke or stroke-related inflammation. In some embodiments, the sample is a plasma sample. In some embodiments, the subject is a human subject. In some embodiments, the subject is a human subject suffering from or at risk of suffering from a stroke and / or stroke-related inflammation. In some embodiments, the neurological event is a stroke and / or stroke-related inflammation. In certain embodiments, the present invention provides a biomarker panel for determining stroke-related neurodegeneration status of a subject, the panel comprising at least one stroke-related neurodegeneration biomarker selected from one or more myelin- breakdown products, wherein the one or more myelin-breakdown products are selected from sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides, or any combinations thereof; wherein measurement or detection of the at least one stroke-related neurodegeneration biomarker indicates that the subject has sustained stroke-related neurodegeneration. In some embodiments, the levels of the stroke-related neurodegeneration biomarker are higher compared to levels of stroke-related neurodegeneration biomarkers in a sample obtained from a healthy subject. In certain embodiments, the present invention provides a biomarker panel for determining stroke-related neurodegeneration status of a subject, the panel comprising at least one stroke-related inflammation biomarker selected from one or more eicosanoids derived from an arachidonic acid cascade, wherein the one or more eicosanides derived from an arachidonic acid cascade are selected from prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15-HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, Attorney Docket No. UAZ-43247.601 8,9-EET, 11,12-EET, and 14,15-EET)), or any combinations thereof; wherein measurement or detection of the at least one stroke-related inflammation biomarker indicates that the subject has sustained stroke-related inflammation. In some embodiments, levels of the stroke-related inflammation biomarker are higher compared to levels of stroke-related inflammation biomarkers in a sample obtained from a healthy subject. Additional embodiments will be apparent to persons skilled in the relevant art based on the teachings contained herein. BRIEF DESCRIPTION OF DRAWINGS FIG.1A-E: NfL is a plasma biomarker of neurodegeneration after stroke in aged mice. A, Experimental design, 20- to 23-month-old male mice were subjected to distal middle cerebral artery occlusion + hypoxia (DH) stroke. Plasma was collected 24 h after stroke and weekly thereafter for 7 wk. T2-weighted MRI was performed at 24 h and 7 wk after stroke to assess acute and chronic pathological sequelae (i.e., infarct expansion, hippocampal edema, and ventricle enlargement). Representative T2- weighted MR images captured 24 h after stroke illustrate an infarct centered on the somatosensory cortex, extending to the corpus callosum. Representative T2-weighted MR images captured 7 wk after stroke illustrate enlargement of the ipsilateral ventricle and hippocampus. B, Plasma NfL levels remain elevated for at least 7 wk after stroke in aged mice (n = 5-10; ANOVA, ****P < 0.0001; Dunnett’s multiple comparisons test, **P < 0.01, ****P < 0.0001). Data are presented as mean ± SD. C, Plasma NfL levels significantly correlated with infarct volume 24 h after stroke (n = 13; Spearman r = 0.7637, **P < 0.01). D, Infarct volume 24 h after stroke significantly correlated with ventricle enlargement 7 wk after stroke (n = 16; Spearman r = 0.5353, *P < 0.05). E, Infarct volume 24 h after stroke weakly correlated with hippocampal edema 7 wk after stroke (n = 16; Spearman r = 0.4235, P > 0.05). Curved lines represent 95% confidence bands for the linear fit. FIG.2A-G. Plasma lipidome 24 h after stroke in aged mice. A, Volcano plot illustrating significant differences in lipid abundance between plasma from naïve mice and mice 24 h after stroke (FDR-adjusted P < 0.05; FC > |2|). B, Hierarchical clustering heatmap depicting the top 30 plasma lipids ranked by t-test (Euclidean; Ward). C, Lipid classes, reported as summations of all species of CE, SM, and TAG, respectively, are significantly altered in the plasma 24 h after stroke (CE: n = 10-11; unpaired t-test, *P < 0.05; SM: n = 10- 11; Mann-Whitney U test, ****P < 0.0001; TAG: n = 10-11; unpaired t-test, *P < 0.05). D, Attorney Docket No. UAZ-43247.601 SM are significantly elevated in the plasma 24 h after stroke (n = 10-11; unpaired t-tests, ****P < 0.0001). E, HCER are significantly elevated in the plasma 24 h after stroke (n = 10- 11; unpaired t-tests, ****P < 0.0001). F, CE are significantly elevated in the plasma 24 h after stroke (n = 10-11; unpaired t-tests, **P < 0.01, ***P < 0.001). G, TAG are significantly decreased in the plasma 24 h after stroke (n = 10-11; Mann-Whitney U tests, ***P < 0.001, ****P < 0.0001). Data are presented as box and whisker plots, with boxes extending from the 25th to 75th percentiles and whiskers extending from the minimum to maximum values. FIG.3A-E. Temporal profile of the plasma lipidome after stroke in aged mice. A, Heatmap depicting group averages of the top 30 plasma lipids altered 24 h after stroke compared to naïve controls. B, TAG60:12-FA22:6 is significantly elevated in the plasma 24 h, 5 wk, and 7 wk after stroke (n = 4-11; ANOVA, ****P < 0.0001; Dunnett’s multiple comparisons test, *P < 0.05, **P < 0.01, ****P < 0.0001). C, HCER(16:0) is transiently elevated in the plasma 24 h after stroke (n = 4-11; Kruskal-Wallis test, ****P < 0.0001; Dunn’s multiple comparisons test, ****P < 0.0001). D, SM(16:0) is transiently elevated in the plasma 24 h after stroke (n = 4-11; ANOVA, ****P < 0.0001; Dunnett’s multiple comparisons test, ****P < 0.0001). E, TAG56:4-FA18:1 is transiently decreased in the plasma 24 h after stroke (n = 4-11; Kruskal-Wallis test, ***P < 0.001; Dunn’s multiple comparisons test, **P < 0.01). Data are presented as box and whisker plots, with boxes extending from the 25th to 75th percentiles and whiskers extending from the minimum to maximum values. FIG.4A-D. Plasma metabolome 24 h after stroke in aged mice. A, Volcano plot illustrating significant differences in metabolite abundance between plasma from naïve mice and mice 24 h after stroke (FDR- adjusted P < 0.05; FC > |2|). B, Hierarchical clustering heatmap depicting the top 30 plasma metabolites ranked by t-test (Euclidean; Ward). C, D, Lipid metabolism, represented by 3-hydroxyadipate, 12-HETE, and stearoylcarnitine (C18), and amino acid metabolism, represented by indolepropionate and glycine, are altered 24 h after stroke (12-HETE, indolepropionate, glycine: n = 10-12; unpaired t-tests, ****P < 0.0001; 3-hydroxyadipate, stearoylcarnitine (C18): n = 8-12; Mann-Whitney U test, ****P < 0.0001). Data are presented as box and whisker plots, with boxes extending from the 25th to 75th percentiles and whiskers extending from the minimum to maximum values. FIG.5A-C. Temporal profile of the plasma metabolome after stroke in aged mice. A, Heatmap depicting group averages of the top 30 plasma metabolites altered 24 h after stroke compared to naïve controls. B, C, Lipid metabolism, represented by 12-HETE and eicosenoylcarnitine (C20:1), and amino acid metabolism, represented by isobutyrylcarnitine Attorney Docket No. UAZ-43247.601 (C4) and N6-methyllysine, are dysregulated for at least 24 h after stroke in aged mice (12- HETE, N6-methyllysine: n = 4-12; ANOVA, ****P < 0.0001; Dunnett’s multiple comparisons tests, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; eicosenoylcarnitine (C20:1): n = 4-12; Kruskal-Wallis test, **P < 0.01; Dunn’s multiple comparisons test, **P < 0.01; isobutyrylcarnitine (C4): n = 4-12; Kruskal-Wallis test, ****P < 0.0001; Dunn’s multiple comparisons test, **P < 0.01, ****P < 0.0001). Data are presented as box and whisker plots, with boxes extending from the 25th to 75th percentiles and whiskers extending from the minimum to maximum values. FIG.6A-C. Temporal profile of the plasma metabolome in the subacute and chronic phases after stroke in aged mice. A, Hierarchical clustering heatmap depicting the top 30 plasma metabolites ranked by ANOVA (Euclidean; Ward). Isobutyrylcarnitine (C4), 12- HETE, and N6-methyllysine represent novel plasma biomarkers in the acute, subacute, and chronic phases after stroke. B, C, Lipid metabolism, represented by phosphoethanolamine, 14-HDoHE / 17-HDoHE, and sphinganine, and nucleotide metabolism, represented by ADP, are significantly elevated in the subacute and chronic phases after stroke (phosphoethanolamine, ADP: n = 4-12; ANOVA, ****P < 0.0001; Dunnett’s multiple comparisons tests, *P < 0.05, **P < 0.01, ****P < 0.0001; 14-HDoHE / 17-HDoHE: n = 4-12; Kruskal-Wallis ***P < 0.001; Dunn’s multiple comparisons test, *P < 0.05, **P < 0.01; sphinganine: n = 4- 12; Kruskal-Wallis test, **P < 0.01; Dunn’s multiple comparisons test, *P < 0.05). Data are presented as box and whisker plots, with boxes extending from the 25th 75th percentiles and whiskers extending from the minimum to maximum values. FIG.7. Biosynthesis and biological actions of 12-HETE. Arachidonic acid, released from cellular membranes, serves as the precursor for 12-HETE synthesis. The enzymatic conversion of arachidonic acid by 12-lipoxygenase (12-LOX), occurring predominantly in leukocytes, platelets, and vascular endothelial cells, results in the formation of 12-HETE.12- HETE, a bioactive lipid mediator, acts as a signaling molecule in various physiological and pathological processes, such as angiogenesis, efferocytosis, and platelet activation, and plays a pivotal role in the inflammatory cascade by promoting leukocyte chemotaxis and adhesion to endothelial cells. Additionally, 12-HETE contributes to the synthesis of pro-inflammatory cytokines, exacerbating the inflammatory response. [Created with BioRender.com] DETAILED DESCRIPTION OF THE INVENTION Ischemic stroke remains a leading cause of mortality and long-term disability worldwide, necessitating efforts to identify biomarkers for determining diagnosis, assessing Attorney Docket No. UAZ-43247.601 prognosis, and monitoring treatment responses. Neurofilament light (NfL) has been identified as a predictive biomarker of neuroaxonal injury and mortality after stroke; however, the complexity of stroke pathophysiology warrants a more comprehensive approach to capture the range of biological alterations that occur in response to ischemia. Experiments described herein (see, Examples 1-9) were conducted to identify novel plasma biomarkers of neurodegeneration and inflammation in a mouse model of stroke induced by distal middle cerebral artery (MCA) occlusion. By integrating differential mobility spectroscopy and ultrahigh performance liquid chromatography coupled to tandem mass spectrometry (UPLC- MS / MS) with advanced bioinformatic analyses, targeted lipidomic profiling and global untargeted metabolomic profiling were performed to screen for lipids and metabolites in the plasma of aged male mice 24 hours after stroke and weekly thereafter for 7 weeks, using naïve mice as controls. An acute signature of brain lipid catabolism in the plasma 24 hours after stroke was discovered. Notably, a substantial proportion of these elevated lipids and metabolites were essential components of myelin. In addition, 12-hydroxyeicosatetraenoic acid (12-HETE), a bioactive lipid mediator produced through the enzymatic oxidation of arachidonic acid by 12-lipoxygenase (12-LOX), was discovered as a putative biomarker of chronic inflammation after stroke. These results offer insight into the metabolic alterations that occur in the plasma after stroke and highlight the potential of myelin degradation products as biomarkers of neurodegeneration and arachidonic acid derivatives as biomarkers of inflammation. Accordingly, disclosed herein are methods and systems useful for identifying a subject having suffered a neurological event (e.g, stroke; stroke-related inflammation; stroke- related neurodegeneration), and evaluating the therapeutic efficacy of a treatment of a subject having suffered a neurological event. In particular, the present invention provides novel biomarkers indicative of neurodegeneration (e.g., stroke-related neurodegeneration) (e.g., myelin-breakdown products (e.g., sphingomyelins, hexosyl ceramides, dihydroceramides, ceramides)). In addition, the present invention provides novel biomarkers indicative of inflammation (e.g., stroke-related inflammation) (e.g., eicosanoids derived from arachidonic acid cascade (e.g., prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15-HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)). Section headings as used in this section and the entire disclosure herein are merely for organizational purposes and are not intended to be limiting. Attorney Docket No. UAZ-43247.601 1. Definitions Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. In case of conflict, the present document, including definitions, will control. Preferred methods and materials are described below, although methods and materials similar or equivalent to those described herein can be used in practice or testing of the present disclosure. All publications, patent applications, patents and other references mentioned herein are incorporated by reference in their entirety. The materials, methods, and examples disclosed herein are illustrative only and not intended to be limiting. The terms “comprise(s),” “include(s),” “having,” “has,” “can,” “contain(s),” and variants thereof, as used herein, are intended to be open-ended transitional phrases, terms, or words that do not preclude the possibility of additional acts or structures. The singular forms “a,” “and” and “the” include plural references unless the context clearly dictates otherwise. The present disclosure also contemplates other embodiments “comprising,” “consisting of” and “consisting essentially of,” the embodiments or elements presented herein, whether explicitly set forth or not. For the recitation of numeric ranges herein, each intervening number there between with the same degree of precision is explicitly contemplated. For example, for the range of 6- 9, the numbers 7 and 8 are contemplated in addition to 6 and 9, and for the range 6.0-7.0, the number 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, and 7.0 are explicitly contemplated. The term “about” or “approximately” means an acceptable error for a particular value as determined by one of ordinary skill in the art, which depends in part on how the value is measured or determined. In certain embodiments, the term “about” or “approximately” means within 1, 2, 3, or 4 standard deviations. In certain embodiments, the term “about” or “approximately” means within 30%, 25%, 20%, 15%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, or 0.05% of a given value or range. Whenever the term “about” or “approximately” precedes the first numerical value in a series of two or more numerical values, it is understood that the term “about” or “approximately” applies to each one of the numerical values in that series. The term “amelioration” as used herein refers to any improvement of a condition (for example stroke) of a patient suffering therefrom, by the administration of one or more treatments, drugs, and / or compositions, according to the present disclosure, to such patient or subject in need thereof. Such an improvement may be seen as a slowing down of the Attorney Docket No. UAZ-43247.601 progression, or a cessation of the progression, of the patient’s condition, a decrease in the frequency, duration, and / or severity of any symptom, and / or an increase in frequency or duration of symptom-free periods or a prevention of impairment or disability due to the condition. A "biomarker" is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. Biomarkers may be of several types: indicative, predictive, prognostic, or pharmacodynamics (PD). Indictive biomarkers indicate whether a subject is suffering from or has suffered a specific condition. Predictive biomarkers predict which patients are likely to respond or benefit from a particular therapy. Prognostic biomarkers predict the likely course of the patient's condition and may guide treatment. Pharmacodynamic biomarkers confirm drug activity and enable optimization of dose and administration schedule. The term “biological sample” or “sample” refers to a specimen obtained from a subject for use in the present methods, and includes urine, whole blood, blood component (such as plasma, peripheral blood mononuclear cells, and / or extracellular vesicle), serum, saliva, sputum, tissue biopsies, cerebrospinal fluid, gut lavage, bronchioalveolar lavage, nasal lavage, and induced sputum. The term "effective amount" refers to an amount of a compound of the invention or other active ingredient sufficient to provide a therapeutic or prophylactic benefit in the treatment or prevention of a condition or to delay or minimize symptoms associated with a condition. Further, a therapeutically effective amount with respect to a compound of the invention means that amount of therapeutic agent alone, or in combination with other therapies, that provides a therapeutic benefit in the treatment or prevention of a condition. Used in connection with a compound disclosed herein, the term can encompass an amount that improves overall therapy, reduces or avoids symptoms, causes, or progression of the condition, or enhances the therapeutic efficacy or synergies with another therapeutic agent. The term “mammal” includes, but is not limited to, humans, mice, rats, guinea pigs, monkeys, dogs, cats, horses, cows, pigs, and sheep. A “patient” or “subject” includes a mammal or animal, such as a human, cow, horse, sheep, lamb, pig, chicken, turkey, quail, cat, dog, mouse, rat, rabbit, or guinea pig. The animal can be a mammal such as a non-primate or a primate (e.g., monkey and human). In one embodiment, a patient is a human, such as a human infant, child, adolescent, or adult of any or indeterminant sex. Attorney Docket No. UAZ-43247.601 “Patient in need,” “subject in need,” or those “in need of treatment” include those already with existing condition (i.e., stroke, for example, without limitation, acute stroke), as well as those at risk of or susceptible to the condition. The terms also include human and other mammalian subjects that receive either prophylactic or therapeutic treatments as disclosed herein. The terms "treat", "treating" and "treatment" refer to eliminating, reducing, suppressing, or ameliorating, either temporarily or permanently, either partially or completely, a clinical symptom, manifestation or progression of an event or condition associated with the disorders and conditions described herein. As is recognized in the pertinent field, methods and drugs employed as therapies may reduce the severity of a given condition but need not abolish every manifestation of the condition to be regarded as useful. Similarly, a prophylactically administered treatment need not be completely effective in preventing the onset of a condition to constitute a viable prophylactic method or agent. Simply reducing the impact of a condition (for example, as disclosed herein, stroke, etc. and / or reducing the number or severity of associated symptoms, or by increasing the effectiveness of another treatment, or by producing another beneficial effect), or reducing the likelihood that the condition will reoccur and / or worsen in a subject, is sufficient. One embodiment of the invention is directed to a method for determining the efficacy of treatment comprising administering to a patient therapeutic treatment in an amount, duration, and repetition sufficient to induce a sustained improvement over pre-existing conditions, or a baseline indicator that reflects the severity of the particular disorder. A stroke, as used herein refers to an ischemic or hemorrhagic condition affecting a patient or subject. Occurrence of a stroke means either occlusion of a blood vessel in the brain in the case of ischemic stroke, or hemorrhage from a blood vessel in the brain in the case of hemorrhagic stroke. Onset time of a stroke means the time of occlusion of a blood vessel (ischemic stroke) or the time of hemorrhage, as reflected immediately or shortly thereafter by the presence of stroke symptoms. These symptoms may involve a range of deficits, including motor function, speech, vision, and cognitive function. Treating an ischemic stroke refers to, in the case of medical therapy in most cases, administering an anti-clotting or “thrombolytic” therapeutic compound, for example tissue plasminogen activator (tPA) or Tenecteplase (TNK). Both tPA and TNK are tissue plasminogen activators. tPA (alteplase) is typically administered via bolus and infusion. TNK is an alteplase variant with three amino acid substitutions and may be administered by a single bolus in acute stroke. Treatment for acute ischemic stroke may also include mechanical thrombectomy. Treatment for intracranial Attorney Docket No. UAZ-43247.601 hemorrhage may involve medical and surgical interventions for alleviating or stopping the bleeding. A reference level, as used herein refers to an established level and / or range of a biomarker in healthy adults. Biomarker levels may vary by age and in association with underlying, premorbid medical conditions. 2. Diagnosing and Evaluating Whether a Subject Has Sustained a Stroke The present disclosure relates to methods of aiding in the diagnosis, prognosis, risk stratification, and evaluation of whether a subject has sustained or may have sustained a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration). These methods can aid in determining the extent and / or severity of a stroke, stroke-related inflammation, and / or stroke-related neurodegeneration. More specifically, the biomarkers of the present disclosure can be used in diagnostic tests to determine, qualify, and / or assess neurological event status, for example, to diagnose stroke, stroke-related inflammation, and / or stroke-related neurodegeneration in an individual, subject or patient. In some embodiments, neurological status can include determining if a patient has suffered from a stroke. In some embodiments, neurological status can include determining if a patient is suffering from chronic stroke infarct induced neurodegeneration. In some embodiments, neurological status can include determining if a patient is suffering from prolonged stroke-related inflammation. The present disclosure provides various biomarkers useful in determining whether a subject has suffered or is suffering from neurodegeneration (e.g., neurodegeneration related to a stroke). In some embodiments, the biomarker is selected from a protein or a peptide, and fragments thereof. In some embodiments, the biomarkers may be one or more myelin- breakdown products. In some embodiments, the one or more myelin-breakdown products include, but are not limited to, sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides. The present disclosure provides various biomarkers useful in determining whether a subject has suffered or is suffering from inflammation (e.g., stroke-related inflammation). In some embodiments, the biomarker is selected from a protein or a peptide, and fragments thereof. In some embodiments, the biomarkers may be one or more eicosanoids derived from arachidonic acid cascade. In some embodiments, the one or more one or more eicosanoids derived from arachidonic acid cascade include, but are not limited to, prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., Attorney Docket No. UAZ-43247.601 5-HETE, 15-HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)). Determining whether a subject has suffered a neurological event (e.g, stroke; stroke- related inflammation; stroke-related neurodegeneration) can include measuring or detecting one or more stroke-related neurodegeneration biomarkers and / or stroke-related inflammation biomarkers and integrating that information with other information (e.g., clinical assessment data), to determine that the subject is more likely than not to have sustained a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration), and if so, what type of neurological event was sustained. The method can include performing an assay on a sample obtained from the human subject within about 24 hours, such as within about 2 hours, after a suspected stroke to measure or detect a level of one or more of such biomarkers in the sample and determining whether the subject has sustained a mild or a moderate or a severe to neurological event (e.g., mild stroke, moderate stroke, severe stroke). In some embodiments, the subject is determined as having a mild or a moderate or a severe to neurological event (e.g., mild stroke, moderate stroke, severe stroke) when the level of one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers in a sample is altered (e.g., higher or lower expression level), as compared to a reference level of one or more of such biomarkers (e.g., level of the biomarker in a control sample). The sample can be a biological sample. “Sample,” as used herein may be used interchangeably (e.g., sample, test sample, or biological sample) and may be a sample of blood, such as whole blood, tissue, urine, serum, plasma, amniotic fluid, cerebrospinal fluid, placental cells or tissue, endothelial cells, leukocytes, or monocytes. In some embodiments, the biological sample is a plasma sample. Generally, a reference level of a stroke-related inflammation biomarker and / or stroke- related neurodegeneration biomarker can also be employed as a benchmark against which to assess results obtained upon assaying a test sample for such a biomarker. Generally, in making such a comparison, the reference level of a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker is obtained by running a particular assay a sufficient number of times and under appropriate conditions such that a linkage or association of analyte presence, amount or concentration with a particular stage or endpoint of a neurological event (e.g., stroke) or with particular indicia can be made. Typically, the reference level of a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker is obtained with assays of reference subjects (or populations of Attorney Docket No. UAZ-43247.601 subjects). The measured a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker can include fragments thereof, degradation products thereof, and / or enzymatic cleavage products thereof. In certain embodiments, the reference level may be correlated with control subjects that have not sustained a neurological event. The biological samples may be obtained shortly after onset of a neurological event or in the weeks and months afterwards (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration). In many embodiments, the biological samples are obtained within about 133 minutes after neurological event (e.g, stroke) onset, for example less than 150 min, 140 min, 130 min, 120 min, 110 min, 100 min, 90 min, 80 min, 70 min, 60 min, 50 min, 40 min, or 30 min, and greater than about 10 min, 20 min, 30 mm, 40 min, 50 min, 60 min, 70 min, 80 min, 90 min, 100 min, 110 min, 120 min, 130 min, or 140 min. In many embodiments a second sample may be obtained at a second time. In many embodiments, the second sample is obtained more than about 30 min after the first sample, for example more than 10 min, 20 min, 30 min, 40 min, 50 min, 60 min, 70 mm, 80 min, 90 min, 100 min, 200 min, 400 min, 500 min, 750 min, 1000 min, 1250 min, or 1500 min, and less than about 1750 min, 1500 min, 1250 min, 1000 min, 750 min, 500 min, 400 min, 300 min, 250 min, 100 min, 90 min, 80 min, 70 min, 60 min, 50 min, 40 min, 30 min, or 20 min after the first sample. In some embodiments, a third sample may be obtained at a third time. In some embodiments, the third sample is obtained more than about 1 week after the first sample, for example more than 1 week, 2 weeks, 3 week, 4 weeks, 5 weeks, 6 weeks, 7 weeks, 8 weeks, 9 weeks, 10 weeks, 11 weeks, or 12 weeks after the first sample. Confirmation of a neurological event (e.g, stroke; stroke-related inflammation; stroke- related neurodegeneration) in a subject may be associated with an elevated level of one or more of the disclosed biomarkers relative to at least one reference level. In some embodiments, the reference level may be predetermined from a study of healthy controls, for example subjects that have not suffered a a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration). The levels of biomarkers may increase over time after a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration). In many embodiments, the level of biomarker may increase more than 1.5X over a period of time. In some embodiments, the level may increase more than 1.2X, 1.3X, 1.4X, 1.5X, 1.6X, 1.7X, 1.8X, 1.9X, 2.0X, 2.1X, 2.2X, 2.3v2.4X, 2.5X, 2.6X, 2.7X, 2.8X, 2.9X, 3X, 4X, 5X, 6X, 7X, 8X, 9X, or 10X, and less than about 15X, 12X, 10X, 9X, 8X, 7X, 6X, 5X, 4X, 3X, 2X, 1.9X, 1.8X, 1.7X, 1.6X, 1.5X, 1.4X, or 1.3X, and the period may be between 24 hours and 12 Attorney Docket No. UAZ-43247.601 weeks. In some embodiments, the period of time reflecting the increase in biomarker level may be less than 12 weeks, 11 weeks, 10 weeks, 9 weeks, 8 weeks, 7 weeks, 6 weeks, 5 weeks, 4 weeks, 3 weeks, 2 weeks, 30h, 29h, 28h, 27h, 26h, 25h, 24h, 23h, 22h, 21h, 20h, 19h, 18h, 17h, 16h, 15h, 14h, 13h, 12h, 11h, 10h, 9h, 8h, 7h, 6h, 5h, 4h, 3h, or 2h, and more than about 1h, 2h, 3h, 4h, 5h, 6h, 7h, 8h, 9h, 10h, 12h, 15h, 18h, 20h, 24h, 28h, 30h, 2 weeks, 3 weeks, 4 weeks, 5 weeks, 6 weeks, 7 weeks, 8 weeks, 9 weeks, 10 weeks, 11 weeks or 12 weeks. Various disclosed methods include obtaining a second biological sample, after a period of time from obtaining a first biological sample, analyzing the first and second biological samples for the presence of one or more biomarkers, and determining concentration levels of the one or more biomarkers in each biological sample, and comparing the level of the one or more biomarkers in the first biological sample to the level of the one or more biomarkers in the second biological sample, wherein a change in biomarker level may be useful in determining the occurrence of a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) and / or determining its onset, and wherein the time between obtaining the first and second biological samples is within the 4.5 hr cutoff for administering an anti-clotting agent. In some embodiments, the biomarker may be one or more biomarkers indicative of neurodegeneration (e.g., stroke-related neurodegeneration). In some embodiments, the one or more biomarkers indicative of neurodegeneration (e.g., stroke- related neurodegeneration) include myelin-breakdown products including, but are not limited to, sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides. In some embodiments, the biomarker may be one or more biomarkers indicative of inflammation (e.g., stroke-related inflammation). In some embodiments, the one or more biomarkers indicative of inflammation (e.g., stroke-related inflammation) include eicosanoids derived from arachidonic acid cascade including, but are not limited to, prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15- HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)). In some embodiments, the biomarker may be one or more biomarkers indicative of neurodegeneration (e.g., stroke-related neurodegeneration), and / or one or more biomarkers indicative of inflammation (e.g., stroke- related inflammation). In many embodiments the second biological sample may be collected 10 or more minutes after the first, for example, more than about 5 min, 6 min, 7 min, 8 min, 9 min, 10 min, 15 min, 20 min, 25 min, 30 min, 40 min, 50 min, 60 min, 70 min, 80 min, 90 min, 120 min, 180 min and 240 min and less than about 270 min, 240 min, 200 min, 180 min, Attorney Docket No. UAZ-43247.601 160 min, 140 min, 130 min, 120 min, 110 min, 100 min, 90 min, 80 min, 70 min, 60 min, 50 min, 45 min, 40 min, 35 min, 30 min, 25 min, 20 min, 15 min, 10 min, 9 min, 8 min, 7 min, or 6 min after collecting the first biological sample. In some embodiments, a third sample may be obtained at a third time. In some embodiments, the third sample is obtained more than about 1 week after the first sample, for example more than 1 week, 2 weeks, 3 week, 4 weeks, 5 weeks, 6 weeks, 7 weeks, 8 weeks, 9 weeks, 10 weeks, 11 weeks, or 12 weeks after the first sample. The change in biomarker levels may be an increase over time of about 1% and 1000%, for example greater than about 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 36%, 37%, 38%, 39%, 40%, 41%, 42%, 43%, 44%, 45%, 46%, 47%, 48%, 49%, 50%, 60%, 70%, 80%, 90%, 100%, 110%, 120%, 130%, 140%, 150%, 200%, 250%, 300%, 350%, 400%, 450%, 500%, 550%, 600%, 650%, 700%, 750%, 800%, 850%, 900%, or 950%, and less than about 1000%, 950%, 900%, 850%, 800%, 750%, 700%, 650%, 600%, 550%, 500%, 450%, 400%, 350%, 300%, 250%, 200%, 150%, 140%, 130%, 120%, 110%, 100%, 90%, 80%, 70%, 60%, 50%, 49%, 48%, 47%, 46%, 45%, 44%, 43%, 42%, 41%, 40%, 39%, 38%, 37%, 36%, 35%, 34%, 33%, 32%, 31%, 30%, 29%, 28%, 27%, 26%, 25%, 24%, 23%, 22%, 21%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, and 3%. The nature of the assay employed in the methods described herein is not critical and the test can be any assay known in the art such as, for example, immunoassays, protein immunoprecipitation, immunoelectrophoresis, Western blot, or protein immunostaining, or spectrometry methods, such as high-performance liquid chromatography (HPLC), liquid chromatography–mass spectrometry (LC / MS), DIA-MS, DDA-MS, PRM-MS or SRM / MRM-MS mass spectrometry assays directly or with enrichment (e.g., enrichment can be via an antibody to the target protein(s)). Capture reagents used to selectively enrich samples for candidate biomarker proteins prior to mass spectroscopic analysis include but are not limited to aptamers, antibodies, nucleic acid probes, chimeras, small molecules, an F(ab')2 fragment, a single chain antibody fragment, an Fv fragment, a single chain Fv fragment, a nucleic acid, a lectin, a ligand-binding receptor, affybodies, nanobodies, ankyrins, domain antibodies, alternative antibody scaffolds (e.g., diabodies etc.) imprinted polymers, avimers, peptidomimetics, peptoids, peptide nucleic acids, threose nucleic acid, a hormone receptor, a cytokine receptor, and synthetic receptors, and modifications and fragments of these. With enrichment, matrix assisted laser desorption / ionization time-of-flight (MALDI- Attorney Docket No. UAZ-43247.601 TOF MS or MALDI-TOF) can also be used. Also, the assay can be employed in clinical chemistry format such as would be known by one skilled in the art. 3. Stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers The present disclosure provides various biomarkers useful in determining whether a subject has suffered or is suffering from neurodegeneration (e.g., neurodegeneration related to a stroke). In some embodiments, the biomarker is selected from a protein or a peptide, and fragments thereof. In some embodiments, the biomarkers may be one or more myelin- breakdown products. In some embodiments, the one or more myelin-breakdown products include, but are not limited to, sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides. The present disclosure provides various biomarkers useful in determining whether a subject has suffered or is suffering from inflammation (e.g., stroke-related inflammation). In some embodiments, the biomarker is selected from a protein or a peptide, and fragments thereof. In some embodiments, the biomarkers may be one or more eicosanoids derived from arachidonic acid cascade. In some embodiments, the one or more one or more eicosanoids derived from arachidonic acid cascade include, but are not limited to, prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15-HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeiosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)). Biomarkers of the present disclosure (e.g., stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers) can be used in diagnostic tests to assess, determine, and / or qualify (used interchangeably herein) brain injury status in a patient, such as neurological event status (e.g., stroke status, stroke-related inflammation status, stroke- related inflammation status). The phrase “brain injury status” includes any distinguishable manifestation of the condition, including not having brain injury. For example, brain injury status includes, without limitation, the presence or absence of brain injury in a patient, the risk of developing brain injury, the stage or severity of brain injury, the progress of brain injury (e.g., progress of brain injury over time), the effectiveness or response to treatment of brain injury (e.g., clinical follow up and surveillance of brain injury after treatment), and type of brain injury, such as stroke, stroke-related inflammation, and stroke-related neurodegeneration. Based on this status, further procedures may be indicated, including additional diagnostic tests or therapeutic procedures or regimens. Attorney Docket No. UAZ-43247.601 The power of a diagnostic test to correctly predict status is commonly measured as the sensitivity of the assay, the specificity of the assay or the area under a receiver operated characteristic (“ROC”) curve. Sensitivity is the percentage of true positives that are predicted by a test to be positive, while specificity is the percentage of true negatives that are predicted by a test to be negative. A ROC curve provides the sensitivity of a test as a function of 1- specificity. The greater the area under the ROC curve, the more powerful the predictive value of the test. Other useful measures of the utility of a test are positive predictive value and negative predictive value. Positive predictive value is the percentage of people who test positive that are actually positive. Negative predictive value is the percentage of people who test negative that are actually negative. Analysis of the data described in the present disclosure in the generation of various stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers that can be used individually, or in various combinations with each other and with other biomarkers in the form of a panel, to diagnose and / or evaluate a brain injury in a subject (e.g, a neurological event such as a stroke). Stroke-related inflammation biomarker panels and stroke-related neurodegeneration biomarker panels may include any one of the biomarkers disclosed herein, and may include more than one and up to 20 different biomarkers corresponding to distinct proteins. Stroke-related inflammation biomarker panels and stroke- related neurodegeneration biomarker panels can also include non-stroke biomarkers (e.g., assay control biomarkers), and biomarkers previously identified to be associated with stroke (e.g., NfL, S100B, GFAP, CRP, and D-dimer). In some embodiments, the biomarker panels of the present disclosure may show a statistical difference in different stroke statuses. Diagnostic tests that use these biomarkers may show an ROC of at least 0.6, at least about 0.7, at least about 0.8, or at least about 0.9. Stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers can be differentially present / expressed depending on the type or subclass of neurological event (e.g., stroke) and, therefore, panels of more than one biomarker can be useful in aiding in the determination of brain injury status. In some embodiments, biomarkers are measured in a patient sample using the methods described herein and compared, for example, to predefined biomarker levels and correlated to stroke status, stroke-related neurodegeneration status, and / or stroke-related inflammation status. In some embodiments, the measurement(s) may then be compared with a relevant diagnostic amount(s), cut-off(s), or multivariate model scores that distinguish a positive status from a negative status. The diagnostic amount(s) represents a measured amount of a biomarker(s) above which or below Attorney Docket No. UAZ-43247.601 which a patient is classified as having a particular neurological event status (e.g., stroke status, stroke-related neurodegeneration status, and / or stroke-related inflammation status). For example, if the biomarker(s) is / are up-regulated compared to a control subject (e.g., a subject that has not sustained a stroke) during brain injury, then a measured amount(s) above the diagnostic cutoff(s) can provide a diagnosis of stroke status, stroke-related neurodegeneration status, and / or stroke-related inflammation status. Additionally, if the biomarker(s) is / are present during brain injury and not detectable in controls, then any detectably measured amount(s) can provide a diagnosis of brain injury. Alternatively, if the biomarker(s) is / are down-regulated during brain injury, then a measured amount(s) at or below the diagnostic cutoff(s) can provide a diagnosis of non-brain injury. Additionally, if the biomarker(s) is / are not present during brain injury and are detectable in controls, then any detectably measured amount(s) can provide a diagnosis of non-brain injury. As is well understood in the art, by adjusting the particular diagnostic cut-off(s) used in an assay, one can increase sensitivity or specificity of the diagnostic assay depending on the preference of the diagnostician. In particular embodiments, the particular diagnostic cut-off can be determined, for example, by measuring the amount of biomarkers in a statistically significant number of samples from patients with the different brain injury statuses, and drawing the cut-off to suit the desired levels of specificity and sensitivity. Indeed, as the skilled artisan will appreciate there are many ways to use the measurements of two or more biomarkers in order to improve the diagnostic question under investigation. In a quite simple, but nonetheless often effective approach, a positive result is assumed if a sample is positive for at least one of the markers investigated. Furthermore, in certain embodiments, the values measured for markers of a biomarker panel are mathematically combined and the combined value is correlated to the underlying diagnostic question. Biomarker values may be combined by any appropriate state of the art mathematical method. Well-known mathematical methods for correlating a marker combination to a disease status employ methods like discriminant analysis (DA) (e.g., linear-, quadratic-, regularized-DA), Discriminant Functional Analysis (DFA), Kernel Methods (e.g., SVM), Multidimensional Scaling (MDS), Nonparametric Methods (e.g., k-Nearest-Neighbor Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting / Bagging Methods), Generalized Linear Models (e.g., Logistic Regression), Principal Components based Methods (e.g., SIMCA), Generalized Additive Models, Fuzzy Logic based Methods, Neural Networks and Genetic Algorithms based Methods. The skilled artisan will have no problem in selecting an appropriate method Attorney Docket No. UAZ-43247.601 to evaluate a biomarker combination of the present invention. In one embodiment, the method used in a correlating a biomarker combination of the present invention, e.g. to diagnose brain injury, is selected from DA (e.g., Linear-, Quadratic-, Regularized Discriminant Analysis), DFA, Kernel Methods (e.g., SVM), MDS, Nonparametric Methods (e.g., k-Nearest-Neighbor Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting Methods), or Generalized Linear Models (e.g., Logistic Regression), and Principal Components Analysis. Details relating to these statistical methods are found in the following references: Ruczinski et al., 12 J. OF COMPUTATIONAL AND GRAPHICAL STATISTICS 475-511 (2003); Friedman, J. H., 84 J. OF THE AMERICAN STATISTICAL ASSOCIATION 165-75 (1989); Hastie, Trevor, Tibshirani, Robert, Friedman, Jerome, The Elements of Statistical Learning, Springer Series in Statistics (2001); Breiman, L., Friedman, J. H., Olshen, R. A., Stone, C. J. Classification and regression trees, California: Wadsworth (1984); Breiman, L., 45 MACHINE LEARNING 5-32 (2001); Pepe, M. S., The Statistical Evaluation of Medical Tests for Classification and Prediction, Oxford Statistical Science Series, 28 (2003); and Duda, R. O., Hart, P. E., Stork, D. G., Pattern Classification, Wiley Interscience, 2nd Edition (2001). Various methods of analyzing a biological sample for the presence of a biomarker are disclosed. In some embodiments, the method of analysis may be one or more of ECL, ELISA, Ella, Surface Plasmon Resonance, molecular array, SIMOA, PCR. In many embodiments, the analysis may include capturing the biomarker with an antigen binding protein or monoclonal antibody specific for the biomarker, wherein the capturing may be permanent or semipermanent. In some embodiments, the antigen binding protein or antibody may be immobilized on a substrate. In most embodiments, the analysis may result in a value that reflects the concentration of the biomarker in the biological sample. In other embodiments, the level of the biomarker may be relative to other biomarkers, for example a reference biomarker. In one embodiment, the biological sample is a blood sample, for example peripheral blood from a venipuncture, or a fraction thereof, for example peripheral blood mononuclear cells, serum, or extracellular vesicles, for example extracellular vesicles displaying one or more factors associated with stress conditions, for one example heat shock proteins. In some embodiments, the biological sample is a plasma sample. 4. Assessment of Neurological Event Characteristics Using Biomarkers Attorney Docket No. UAZ-43247.601 In some embodiments, the present disclosure provides methods for characterizing and / or categorizing a neurological event (e.g, stroke; stroke-related inflammation; stroke- related neurodegeneration) based on the detection, non-detection, and / or detection levels of one or more stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers, such as characterizing the severity of such a neurological event. Each class or subclass of neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) likely has a characteristic level of a biomarker or relative levels of a set of biomarkers (a signature). In one embodiment, the present disclosure provides methods for evaluating the progress of neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) status in a patient over time, including progression (worsening) and regression (improvement). Over time, the amount or relative amount (e.g., the pattern or signature) of the stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers may change. For example, biomarker “X” may be increased with brain injury (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration), while biomarker “Y” may be decreased with brain injury. Therefore, the trend of these biomarkers, either increased or decreased over time toward brain injury or non-brain injury indicates the course of the condition. Accordingly, this method involves measuring the level of one or more biomarkers in a patient at least two different time points (e.g., a first time and a second time, and comparing the change, if any). In some embodiments, a class or subclass of neurological event (e.g, stroke; stroke- related inflammation; stroke-related neurodegeneration) can be characterized by measuring the relevant biomarkers and then either submitting them to a classification algorithm or comparing them with a reference amount (e.g., a predefined level or pattern of biomarkers that is associated with the particular class or subclass). In some embodiments, data that are generated using samples such as “known samples” can then be used to “train” a classification model. A “known sample” is a sample that has been pre-classified. The data that are used to form the classification model can be referred to as a “training data set.” The training data set that is used to form the classification model may comprise raw data or pre-processed data. Once trained, the classification model can recognize patterns in data generated using unknown samples. The classification model can then be used to classify the unknown samples into classes. This can be useful, for example, in predicting whether or not a particular biological sample is associated with a certain biological condition (e.g., diseased versus non-diseased). Attorney Docket No. UAZ-43247.601 Classification models can be formed using any suitable statistical classification or learning method that attempts to segregate bodies of data into classes based on objective parameters present in the data. Classification methods may be either supervised or unsupervised. Examples of supervised and unsupervised classification processes are described in Jain, “Statistical Pattern Recognition: A Review”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, No.1, January 2000, the teachings of which are incorporated by reference. In supervised classification, training data containing examples of known categories are presented to a learning mechanism, which learns one or more sets of relationships that define each of the known classes. New data may then be applied to the learning mechanism, which then classifies the new data using the learned relationships. Examples of supervised classification processes include linear regression processes (e.g., multiple linear regression (MLR), partial least squares (PLS) regression and principal components regression (PCR)), binary decision trees (e.g., recursive partitioning processes such as CART), artificial neural networks such as back propagation networks, discriminant analyses (e.g., Bayesian classifier or Fischer analysis), logistic classifiers, and support vector classifiers (support vector machines). Another supervised classification method is a recursive partitioning process. Recursive partitioning processes use recursive partitioning trees to classify data derived from unknown samples. Further details about recursive partitioning processes are provided in U.S. Patent Application No.20020138208 A1 to Paulse et al., “Method for analyzing mass spectra.” In other embodiments, the classification models that are created can be formed using unsupervised learning methods. Unsupervised classification attempts to learn classifications based on similarities in the training data set, without pre-classifying the spectra from which the training data set was derived. Unsupervised learning methods include cluster analyses. A cluster analysis attempts to divide the data into “clusters” or groups that ideally should have members that are very similar to each other, and very dissimilar to members of other clusters. Similarity is then measured using some distance metric, which measures the distance between data items, and clusters together data items that are closer to each other. Clustering techniques include the MacQueen's K-means algorithm and the Kohonen's Self-Organizing Map algorithm. Learning algorithms asserted for use in classifying biological information are described, for example, in PCT International Publication No. WO 01 / 31580 (Barnhill et al., Attorney Docket No. UAZ-43247.601 “Methods and devices for identifying patterns in biological systems and methods of use thereof”), U.S. Patent Application Publication No.2002 / 0193950 (Gavin et al. “Method or analyzing mass spectra”), U.S. Patent Application Publication No.2003 / 0004402 (Hitt et al., “Process for discriminating between biological states based on hidden patterns from biological data”), and U.S. Patent Application Publication No.2003 / 0055615 (Zhang and Zhang, “Systems and methods for processing biological expression data”). The classification models can be formed on and used on any suitable digital computer. Suitable digital computers include micro, mini, or large computers using any standard or specialized operating system, such as a Unix, Windows® or Linux™ based operating system. In embodiments utilizing a mass spectrometer, the digital computer that is used may be physically separate from the mass spectrometer that is used to create the spectra of interest, or it may be coupled to the mass spectrometer. The training data set and the classification models according to embodiments of the invention can be embodied by computer code that is executed or used by a digital computer. The computer code can be stored on any suitable computer readable media including optical or magnetic disks, sticks, tapes, etc., and can be written in any suitable computer programming language including R, C, C++, visual basic, etc. The learning algorithms described above are useful both for developing classification algorithms for the biomarkers already discovered, and for finding new biomarker biomarkers. The classification algorithms, in turn, form the base for diagnostic tests by providing diagnostic values (e.g., cut-off points) for biomarkers used singly or in combination. 5. Treatment and Monitoring of Subjects Suffering from a Neurological Event The subject identified or assessed as having suffered a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) may be treated or monitored based on the assessment, which can include detecting or measuring various stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers. In some embodiments, the method further includes treating the human subject assessed as having suffered a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) with a treatment, which can take a variety of forms depending on the severity of the neurological event. For example, for subjects suffering from a mild stroke, the treatment may include one or more of rest, abstaining from physical activities, such as sports, avoiding light or wearing sunglasses when out in the light, medication for relief of a headache or migraine, anti-nausea medication, etc. Treatment for patients suffering from a severe stroke Attorney Docket No. UAZ-43247.601 might include administration of one or more appropriate medications (such as, for example, tissue-type plasminogen activator (tPA), diuretics, anti-convulsant medications, medications to sedate and put an individual in a drug-induced coma, or other pharmaceutical or biopharmaceutical medications (either known or developed in the future for treatment of neurological events), one or more surgical procedures (such as, for example, removal of a hematoma, repairing a skull fracture, decompressive craniectomy, etc.) and one or more therapies (such as, for example one or more rehabilitation, cognitive behavioral therapy, anger management, counseling psychology, etc.). In some embodiments, the subject identified or assessed as having suffered a neurological event (e.g., stroke; stroke-related inflammation; stroke-related neurodegeneration) is treated with tPA and / or a lipid chelating agent (e.g., 2-hydroxypropyl-^-cyclodextrin (HP^CD)). In one embodiment, the present disclosure provides methods for determining the risk of developing a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) in a patient. Stroke-related inflammation biomarker and stroke-related neurodegeneration biomarker percentages, amounts or patterns are characteristic of various risk states (e.g., high, medium or low). The risk of developing a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) can be determined by measuring the relevant biomarkers and then either submitting them to a classification algorithm or comparing them with a reference amount (e.g., a predefined level or signature of biomarkers that is associated with the particular risk level). In some embodiments, treating a subject that has sustained a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) can include managing patient treatment based on neurological event status as established using one or more stroke- related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers. Such management can include the actions of the physician or clinician subsequent to determining neurological status. In another embodiment, the present disclosure provides methods for determining the therapeutic efficacy of a pharmaceutical drug in the context of a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) treatment. These methods can be useful in performing clinical trials of a drug, as well as monitoring the progress of a patient on a drug. Therapy or clinical trials involve administering the drug in a particular regimen. The regimen may involve a single dose of the drug or multiple doses of the drug over time. The doctor or clinical researcher monitors the effect of the drug on the Attorney Docket No. UAZ-43247.601 patient or subject over the course of administration. If the drug has a pharmacological impact on the condition, the amounts or relative amounts (e.g., the pattern or signature) of one or more of the stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers of the present invention may change toward a non-brain injury profile. Therefore, one can follow the course of one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers in the patient during the course of treatment. Accordingly, this method may involve measuring one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers in a patient receiving drug therapy, and correlating the biomarker levels with the neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration) status of the patient (e.g., by comparison to predefined levels of the biomarkers that correspond to different brain injury statuses). One embodiment of this method can involve determining the levels of one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers at least two different time points during a course of drug therapy (e.g., a first time and a second time, and comparing the change in levels of the biomarkers, if any). For example, the levels of one or more stroke-related inflammation biomarkers and / or stroke- related neurodegeneration biomarkers can be measured before and after drug administration or at two different time points during drug administration. The effect of therapy is determined based on these comparisons. If a treatment is effective, then the one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers will trend toward normal, while if treatment is ineffective, the one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers will trend toward brain injury indications. 6. Methods for measuring the level of a stroke-related inflammation biomarker and / or a stroke-related neurodegeneration biomarker In the methods described above, stroke-related inflammation biomarker and / or a stroke-related neurodegeneration biomarker levels can be measured by any means, such as antibody dependent methods, such as immunoassays, protein immunoprecipitation, immunoelectrophoresis, chemical analysis, SDS-PAGE and Western blot analysis, protein immunostaining, electrophoresis analysis, a protein assay, a competitive binding assay, a functional protein assay, or chromatography or spectrometry methods, such as high- performance liquid chromatography (HPLC), mass spectrometry, or liquid chromatography– mass spectrometry (LC / MS) or capillary electrophoresis (CE)-MS, or direct infusion, or any Attorney Docket No. UAZ-43247.601 separating front end coupled with MS. Also, the assay can be employed in clinical chemistry format such as would be known by one skilled in the art. In some embodiments, measuring the level of a stroke-related inflammation biomarker and / or a stroke-related neurodegeneration biomarker includes contacting the sample with a first specific binding member and second specific binding member. In some embodiments the first specific binding member is a capture antibody and the second specific binding member is a detection antibody. In some embodiments, measuring the level of a stroke- related inflammation biomarker and / or a stroke-related neurodegeneration biomarker includes contacting the sample, either simultaneously or sequentially, in any order: (1) a capture antibody (e.g., a biomarker-capture antibody), which binds to an epitope on a biomarker or a biomarker fragment to form a capture antibody-biomarker antigen complex (e.g., biomarker- capture antibody-biomarker antigen complex), and (2) a detection antibody (e.g., biomarker- detection antibody), which includes a detectable label and binds to an epitope on a biomarker that is not bound by the capture antibody, to form a biomarker antigen-detection antibody complex (e.g., biomarker antigen-biomarker-detection antibody complex), such that a capture antibody-biomarker antigen-detection antibody complex (e.g., biomarker-capture antibody- biomarker antigen-biomarker-detection antibody complex) is formed, and measuring the amount or concentration of a biomarker in the sample based on the signal generated by the detectable label in the capture antibody-biomarker antigen-detection antibody complex. In some embodiments, the first specific binding member is immobilized on a solid support. In some embodiments, the second specific binding member is immobilized on a solid support. In some embodiments, the first specific binding member is a biomarker antibody as described below. In some embodiments, the sample is diluted or undiluted. The sample can be from about 1 to about 25 microliters, about 1 to about 24 microliters, about 1 to about 23 microliters, about 1 to about 22 microliters, about 1 to about 21 microliters, about 1 to about 20 microliters, about 1 to about 18 microliters, about 1 to about 17 microliters, about 1 to about 16 microliters, about 15 microliters or about 1 microliter, about 2 microliters, about 3 microliters, about 4 microliters, about 5 microliters, about 6 microliters, about 7 microliters, about 8 microliters, about 9 microliters, about 10 microliters, about 11 microliters, about 12 microliters, about 13 microliters, about 14 microliters, about 15 microliters, about 16 microliters, about 17 microliters, about 18 microliters, about 19 microliters, about 20 microliters, about 21 microliters, about 22 microliters, about 23 microliters, about 24 Attorney Docket No. UAZ-43247.601 microliters or about 25 microliters. In some embodiments, the sample is from about 1 to about 150 microliters or less or from about 1 to about 25 microliters or less. A. Detection by Mass Spectrometry As used herein, “MS data” generally refers to raw MS data obtained from a mass spectrometer and / or processed MS data in which peptides and their fragments (e.g., transitions and MS peaks) are already identified, analyzed and / or quantified. In some embodiments of the present disclosure, methods based on MRM-MS or SRM-MS and / or PRM-MS allow for the detection and accurate quantification of specific peptides in complex mixtures. SRM / MRM-MS is a technology with the potential for reliable and comprehensive quantification of substances of low abundance in complex samples. SRM / MRM-MS is performed on triple quadrupole-like instruments, in which increased selectivity is obtained through collision-induced dissociation. It is a non-scanning mass spectrometry technique, where two mass analyzers (Q1 and Q3) are used as static mass filters, to monitor a particular fragment of a selected precursor. On triple quadrapole instruments, various ionization methods can be used, including without limitation, electrospray ionization, chemical ionization, electron ionization, atmospheric pressure chemical ionization, and matrix-assisted laser desorption ionization. Both the first mass analyzer and the collision cell are continuously exposed to ions from the source in a time dependent manner. Once the ions move into the third mass analyzer time dependence becomes a factor. On triple quadrupole instruments, the first quadrapole mass filter, Q1, is the primary m / z selector after the sample leaves the ionization source. Any ions with mass-to-charge ratios other than the one selected for will not be allowed to infiltrate Q1. The collision cell, denoted as “q2”, located between the first quadrapole mass filter Q1 and second quadrapole mass filter Q3, is where fragmentation of the sample occurs in the presence of an inert gas like argon, helium, or nitrogen. Upon exiting the collision cell, the fragmented ions then travel onto the second quadrapole mass filter Q3, where m / z selection can occur again. The specific pair of mass-over-charge (m / z) values associated to the precursor and fragment ions selected is referred to as a “transition.” The detector acts as a counting device for the ions matching the selected transition thereby returning an intensity distribution over time. MRM-MS is when multiple SRM-MS transitions are measured within the same experiment on the chromatographic time scale by rapidly switching between the different precursor / fragment pairs. Typically, the triple quadrupole instrument cycles through a series of transitions and records the signal of each transition as a function of the elution time. The Attorney Docket No. UAZ-43247.601 method allows for additional selectivity by monitoring the chromatographic co-elution of multiple transitions for a given analyte. For general references on mass spectrometry and proteomics, see e.g., Salvatore Sechi, Quantitative Proteomics by Mass Spectrometry (Methods in Molecular Biology) 2nd ed.2016 Edition, Humana Press (New York, NY, 2009); Daniel Martins-de-Souza, Shotgun Proteomics: Methods and Protocols 2014 edition, Humana Press (New York, NY, 2014); Jörg Reinders and Albert Sickmann, Proteomics: Methods and Protocols (Methods in Molecular Biology) 2009 edition, Humana Press (New York, NY, 2009); and Jörg Reinders, Proteomics in Systems Biology: Methods and Protocols (Methods in Molecular Biology) 1sted.2016 edition, Humana Press (New York, NY, 2009). In addition to PRM-MS is also an application of SRM with parallel detection of all transitions in a single analysis using a high resolution mass spectrometer. PRM-MS provides high selectivity, high sensitivity and high-throughput to quantify selected peptide (Q1), hence quantify proteins (MS1). Again, multiple peptides can be specifically selected for each protein. PRM-MS methodology uses the quadrupole of a mass spectrometer to isolate a target precursor ion, fragments the targeted precursor ion in the collision cell, and then detects the resulting product ions in the Orbitrap mass analyzer. Quantification is carried out after data acquisition by extracting one or more fragment ions with 5–10 ppm mass windows. PRM-MS uses a quadrupole time-of-flight (QTOF) or hybrid quadrupole-orbitrap (QOrbitrap) mass spectrometer to carry out the peptides / proteins quantitation. Examples of QTOF include but are not limited to: TripleTOF 6600 or 5600 System (Sciex); X500R QTOF System (Sciex); 6500 Series Accurate-Mass Quadrupole Time-of-Flight (Q-TOF) (Agilent); or Xevo G2-XS QTof Quadrupole Time-of-Flight Mass Spectrometry (Waters). Examples of QObitrap include but are not limited to: Q Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer (Thermo Scientific); or Orbitrap Fusion Tribrid (Thermo Scientific). In some embodiments, the developed methods herein can be applied to the quantification of polypeptides(s) or protein(s) in biological sample(s). Any kind of biological samples comprising polypeptides or proteins can be the starting point and be analyzed by the methods disclosed herein. Indeed, any protein / peptide containing sample can be used for and analyzed by the methods produced here (e.g., tissues, cells). The methods herein can also be used with peptide mixtures obtained by digestion. Digestion of a polypeptide or protein includes any kind of cleavage strategies, such as, enzymatic, chemical, physical or combinations thereof. According to some embodiments, the following parameters of the methods provided herein are determined: trypsin (or other protease) digestion and peptide Attorney Docket No. UAZ-43247.601 clean up, best responding polypeptides, best responding proteins, best responding peptides, best responding fragments, fragment intensity ratios (increased high and reproducible peak intensities), optimal collision energies, and all the optimal parameters to maximize sensitivity and / or specificity of the methods. In other embodiments, quantification of the polypeptides and / or of the corresponding proteins or activity / regulation of the corresponding proteins is desired. A selected peptide is labeled with a stable-isotope and used as an internal standard (SIL) to achieve absolute quantification of a protein of interest. The addition of a quantified stable-labeled peptide analogue of the tag to the peptide sample in known amount; and subsequently the tag and the peptide of interest is quantified by mass spectrometry and absolute quantification of the endogenous levels of the proteins is obtained. In some embodiments, biomarkers of the present disclosure can be detected by mass spectrometry, a method that employs a mass spectrometer to detect gas phase ions, as described above. Examples of mass spectrometers are time-of-flight, magnetic sector, quadrupole filter, ion trap, ion cyclotron resonance, electrostatic sector analyzer, hybrids or combinations of the foregoing, and the like. In one embodiment, the mass spectrometric method comprises matrix assisted laser desorption / ionization time-of-flight (MALDI-TOF MS or MALDI-TOF). In another embodiment, method comprises MALDI-TOF tandem mass spectrometry (MALDI-TOF MS / MS). In yet another embodiment, mass spectrometry can be combined with another appropriate method(s) as may be contemplated by one of ordinary skill in the art. For example, MALDI-TOF can be utilized with trypsin digestion and tandem mass spectrometry as described herein or with enrichment. In another embodiment, the mass spectrometric technique is multiple reaction monitoring (MRM) or quantitative MRM. In some embodiments, the mass spectrometry method involves first enrichment by capturing one or more biomarkers on a chromatographic resin having chromatographic properties that bind the biomarkers. For example, one could capture the biomarkers on a cation exchange resin, such as CM Ceramic HyperD F resin, wash the resin, elute the biomarkers and detect by MALDI. Alternatively, this method could be preceded by fractionating the sample on an anion exchange resin before application to the cation exchange resin. In one embodiment, one could fractionate on an anion exchange resin and detect by MALDI directly. In another embodiment, one could capture the biomarkers on an immuno- chromatographic resin that comprises antibodies that bind the biomarkers, wash the resin to remove unbound material, elute the biomarkers from the resin and detect the eluted biomarkers by MALDI or on to another MS instrument (using any method for quantification). Attorney Docket No. UAZ-43247.601 The biomarkers of the present disclosure can also be detected by other suitable methods. Detection paradigms that can be employed to this end include optical methods, electrochemical methods (voltametry and amperometry techniques), atomic force microscopy, and radio frequency methods, e.g., multipolar resonance spectroscopy. Illustrative of optical methods, in addition to microscopy, both confocal and non-confocal, are detection of fluorescence, luminescence, chemiluminescence, absorbance, reflectance, transmittance, and birefringence or refractive index (e.g., surface plasmon resonance, ellipsometry, a resonant mirror method, a grating coupler waveguide method or interferometry) or by mass spectrometry using any MS instrument and any MS method. B. Biomarker-Recognizing Antibodies The methods described herein may use an isolated antibody that specifically binds to a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker or fragments thereof, referred to as “a stroke-related inflammation biomarker antibody” and / or “a stroke-related neurodegeneration biomarker antibody.” Such biomarker antibodies can be used to assess the status of a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker as a measure of a neurological event (e.g, stroke; stroke-related inflammation; stroke-related neurodegeneration), detect the presence of a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker in a biological sample, quantify the amount of a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker present in a biological sample, or detect the presence of and quantify the amount of a a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker in a biological sample. Biomarker antibodies include any antibody that binds to a biomarker, a fragment thereof, an epitope of a biomarker, or a variant thereof. The antibody may be a fragment of the anti-biomarker antibody or a variant or a derivative thereof. The antibody may be a polyclonal or monoclonal antibody. The antibody may be a chimeric antibody, a single chain antibody, an affinity matured antibody, a human antibody, a humanized antibody, a fully human antibody or an antibody fragment, such as a Fab fragment, or a mixture thereof. Antibody fragments or derivatives may comprise F(ab’)2, Fv or scFv fragments. The antibody derivatives can be produced by peptidomimetics. Further, techniques described for the production of single chain antibodies can be adapted to produce single chain antibodies. The anti-biomarker antibodies may be a chimeric anti-biomarker antibody or a humanized anti-biomarker antibody. In one embodiment, both the humanized antibody and Attorney Docket No. UAZ-43247.601 chimeric antibody are monovalent. In one embodiment, both the humanized antibody and chimeric antibody comprise a single Fab region linked to an Fc region. Human antibodies may be derived from phage-display technology or from transgenic mice that express human immunoglobulin genes. The human antibody may be generated as a result of a human in vivo immune response and isolated. See, for example, Funaro et al., BMC Biotechnology, 2008(8):85. Therefore, the antibody may be a product of the human and not animal repertoire. Because it is of human origin, the risks of reactivity against self- antigens may be minimized. Alternatively, standard yeast display libraries and display technologies may be used to select and isolate human anti-biomarker antibodies. For example, libraries of naïve human single chain variable fragments (scFv) may be used to select human anti-biomarker I antibodies. Transgenic animals may be used to express human antibodies. Humanized antibodies may be antibody molecules from non-human species antibody that binds the desired antigen having one or more complementarity determining regions (CDRs) from the non-human species and framework regions from a human immunoglobulin molecule. The antibody is distinguishable from known antibodies in that it possesses different biological function(s) than those known in the art. The antibody may immunospecifically bind to the peptide of a biomarker, a fragment thereof, or a variant thereof. The antibody may immunospecifically recognize and bind at least three amino acids, at least four amino acids, at least five amino acids, at least six amino acids, at least seven amino acids, at least eight amino acids, at least nine amino acids, or at least ten amino acids within an epitope region. The antibody may immunospecifically recognize and bind to an epitope that has at least three contiguous amino acids, at least four contiguous amino acids, at least five contiguous amino acids, at least six contiguous amino acids, at least seven contiguous amino acids, at least eight contiguous amino acids, at least nine contiguous amino acids, or at least ten contiguous amino acids of an epitope region. C. Antibody Preparation / Production Antibodies may be prepared by any of a variety of techniques, including those well known to those skilled in the art. In general, antibodies can be produced by cell culture techniques, including the generation of monoclonal antibodies via conventional techniques, or via transfection of antibody genes, heavy chains, and / or light chains into suitable bacterial or mammalian cell hosts, in order to allow for the production of antibodies, wherein the Attorney Docket No. UAZ-43247.601 antibodies may be recombinant. The various forms of the term “transfection” are intended to encompass a wide variety of techniques commonly used for the introduction of exogenous DNA into a prokaryotic or eukaryotic host cell, e.g., electroporation, calcium-phosphate precipitation, DEAE-dextran transfection and the like. Although it is possible to express the antibodies in either prokaryotic or eukaryotic host cells, expression of antibodies in eukaryotic cells is preferable, and most preferable in mammalian host cells, because such eukaryotic cells (and in particular mammalian cells) are more likely than prokaryotic cells to assemble and secrete a properly folded and immunologically active antibody. Exemplary mammalian host cells for expressing the recombinant antibodies include Chinese Hamster Ovary (CHO cells) (including dhfr-CHO cells, described in Urlaub and Chasin, Proc. Natl. Acad. Sci. USA, 77: 4216-4220 (1980)), used with a DHFR selectable marker, e.g., as described in Kaufman and Sharp, J. Mol. Biol., 159: 601-621 (1982), NS0 myeloma cells, COS cells, and SP2 cells. When recombinant expression vectors encoding antibody genes are introduced into mammalian host cells, the antibodies are produced by culturing the host cells for a period of time sufficient to allow for expression of the antibody in the host cells or, more preferably, secretion of the antibody into the culture medium in which the host cells are grown. Antibodies can be recovered from the culture medium using standard protein purification methods. Host cells can also be used to produce functional antibody fragments, such as Fab fragments or scFv molecules. It will be understood that variations on the above procedure may be performed. For example, it may be desirable to transfect a host cell with DNA encoding functional fragments of either the light chain and / or the heavy chain of an antibody. Recombinant DNA technology may also be used to remove some, or all, of the DNA encoding either or both of the light and heavy chains that is not necessary for binding to the antigens of interest. The molecules expressed from such truncated DNA molecules are also encompassed by the antibodies. In addition, bifunctional antibodies may be produced in which one heavy and one light chain are an antibody (i.e. binds human troponin I) and the other heavy and light chain are specific for an antigen other than a human biomarker by crosslinking an antibody to a second antibody by standard chemical crosslinking methods. In a preferred system for recombinant expression of an antibody, or antigen-binding portion thereof, a recombinant expression vector encoding both the antibody heavy chain and the antibody light chain is introduced into dhfr-CHO cells by calcium phosphate-mediated transfection. Within the recombinant expression vector, the antibody heavy and light chain genes are each operatively linked to CMV enhancer / AdMLP promoter regulatory elements to Attorney Docket No. UAZ-43247.601 drive high levels of transcription of the genes. The recombinant expression vector also carries a DHFR gene, which allows for selection of CHO cells that have been transfected with the vector using methotrexate selection / amplification. The selected transformant host cells are cultured to allow for expression of the antibody heavy and light chains and intact antibody is recovered from the culture medium. Standard molecular biology techniques are used to prepare the recombinant expression vector, transfect the host cells, select for transformants, culture the host cells, and recover the antibody from the culture medium. Still further, the method of synthesizing a recombinant antibody may be by culturing a host cell in a suitable culture medium until a recombinant antibody is synthesized. The method can further comprise isolating the recombinant antibody from the culture medium. Methods of preparing monoclonal antibodies involve the preparation of immortal cell lines capable of producing antibodies having the desired specificity. Such cell lines may be produced from spleen cells obtained from an immunized animal. The animal may be immunized with a biomarker or a fragment and / or variant thereof. The peptide used to immunize the animal may comprise amino acids encoding human Fc, for example the fragment crystallizable region or tail region of human antibody. The spleen cells may then be immortalized by, for example, fusion with a myeloma cell fusion partner. A variety of fusion techniques may be employed. For example, the spleen cells and myeloma cells may be combined with a nonionic detergent for a few minutes and then plated at low density on a selective medium that supports that growth of hybrid cells, but not myeloma cells. One such technique uses hypoxanthine, aminopterin, thymidine (HAT) selection. Another technique includes electrofusion. After a sufficient time, usually about 1 to 2 weeks, colonies of hybrids are observed. Single colonies are selected and their culture supernatants tested for binding activity against the polypeptide. Hybridomas having high reactivity and specificity may be used. Monoclonal antibodies may be isolated from the supernatants of growing hybridoma colonies. In addition, various techniques may be employed to enhance the yield, such as injection of the hybridoma cell line into the peritoneal cavity of a suitable vertebrate host, such as a mouse. Monoclonal antibodies may then be harvested from the ascites fluid or the blood. Contaminants may be removed from the antibodies by conventional techniques, such as chromatography, gel filtration, precipitation, and extraction. Affinity chromatography is an example of a method that can be used in a process to purify the antibodies. The proteolytic enzyme papain preferentially cleaves IgG molecules to yield several fragments, two of which (the F(ab) fragments) each comprise a covalent heterodimer that Attorney Docket No. UAZ-43247.601 includes an intact antigen-binding site. The enzyme pepsin is able to cleave IgG molecules to provide several fragments, including the F(ab’)2fragment, which comprises both antigen- binding sites. The Fv fragment can be produced by preferential proteolytic cleavage of an IgM, and on rare occasions IgG or IgA immunoglobulin molecules. The Fv fragment may be derived using recombinant techniques. The Fv fragment includes a non-covalent VH::VL heterodimer including an antigen-binding site that retains much of the antigen recognition and binding capabilities of the native antibody molecule. The antibody, antibody fragment, or derivative may comprise a heavy chain and a light chain complementarity determining region (“CDR”) set, respectively interposed between a heavy chain and a light chain framework (“FR”) set which provide support to the CDRs and define the spatial relationship of the CDRs relative to each other. The CDR set may contain three hypervariable regions of a heavy or light chain V region. Other suitable methods of producing or isolating antibodies of the requisite specificity can be used, including, but not limited to, methods that select recombinant antibody from a peptide or protein library (e.g., but not limited to, a bacteriophage, ribosome, oligonucleotide, RNA, cDNA, yeast or the like, display library); e.g., as available from various commercial vendors such as Cambridge Antibody Technologies (Cambridgeshire, UK), MorphoSys (Martinsreid / Planegg, Del.), Biovation (Aberdeen, Scotland, UK) BioInvent (Lund, Sweden), using methods known in the art. See U.S. Patent Nos.4,704,692; 5,723,323; 5,763,192; 5,814,476; 5,817,483; 5,824,514; 5,976,862. Alternative methods rely upon immunization of transgenic animals (e.g., SCID mice, Nguyen et al. (1997) Microbiol. Immunol.41:901-907; Sandhu et al. (1996) Crit. Rev. Biotechnol.16:95-118; Eren et al. (1998) Immunol.93:154- 161) that are capable of producing a repertoire of human antibodies, as known in the art and / or as described herein. Such techniques, include, but are not limited to, ribosome display (Hanes et al. (1997) Proc. Natl. Acad. Sci. USA, 94:4937-4942; Hanes et al. (1998) Proc. Natl. Acad. Sci. USA, 95:14130-14135); single cell antibody producing technologies (e.g., selected lymphocyte antibody method (“SLAM”) (U.S. Patent No.5,627,052, Wen et al. (1987) J. Immunol.17:887-892; Babcook et al. (1996) Proc. Natl. Acad. Sci. USA 93:7843- 7848); gel microdroplet and flow cytometry (Powell et al. (1990) Biotechnol.8:333-337; One Cell Systems, (Cambridge, Mass).; Gray et al. (1995) J. Imm. Meth.182:155-163; Kenny et al. (1995) Bio / Technol.13:787-790); B-cell selection (Steenbakkers et al. (1994) Molec. Biol. Reports 19:125-134 (1994)). Attorney Docket No. UAZ-43247.601 An affinity matured antibody may be produced by any one of a number of procedures that are known in the art. For example, see Marks et al., BioTechnology, 10: 779-783 (1992) describes affinity maturation by VH and VL domain shuffling. Random mutagenesis of CDR and / or framework residues is described by Barbas et al., Proc. Nat. Acad. Sci. USA, 91: 3809- 3813 (1994); Schier et al., Gene, 169: 147-155 (1995); Yelton et al., J. Immunol., 155: 1994- 2004 (1995); Jackson et al., J. Immunol., 154(7): 3310-3319 (1995); Hawkins et al, J. Mol. Biol., 226: 889-896 (1992). Selective mutation at selective mutagenesis positions and at contact or hypermutation positions with an activity enhancing amino acid residue is described in U.S. Patent No.6,914,128 B1. Antibody variants can also be prepared using delivering a polynucleotide encoding an antibody to a suitable host such as to provide transgenic animals or mammals, such as goats, cows, horses, sheep, and the like, that produce such antibodies in their milk. These methods are known in the art and are described for example in U.S. Patent Nos.5,827,690; 5,849,992; 4,873,316; 5,849,992; 5,994,616; 5,565,362; and 5,304,489. Antibody variants also can be prepared by delivering a polynucleotide to provide transgenic plants and cultured plant cells (e.g., but not limited to tobacco, maize, and duckweed) that produce such antibodies, specified portions or variants in the plant parts or in cells cultured therefrom. For example, Cramer et al. (1999) Curr. Top. Microbiol. Immunol. 240:95-118 and references cited therein, describe the production of transgenic tobacco leaves expressing large amounts of recombinant proteins, e.g., using an inducible promoter. Transgenic maize have been used to express mammalian proteins at commercial production levels, with biological activities equivalent to those produced in other recombinant systems or purified from natural sources. See, e.g., Hood et al., Adv. Exp. Med. Biol. (1999) 464:127- 147 and references cited therein. Antibody variants have also been produced in large amounts from transgenic plant seeds including antibody fragments, such as single chain antibodies (scFv’s), including tobacco seeds and potato tubers. See, e.g., Conrad et al. (1998) Plant Mol. Biol.38:101-109 and reference cited therein. Thus, antibodies can also be produced using transgenic plants, according to known methods. Antibody derivatives can be produced, for example, by adding exogenous sequences to modify immunogenicity or reduce, enhance or modify binding, affinity, on-rate, off-rate, avidity, specificity, half-life, or any other suitable characteristic. Generally, part or all of the non-human or human CDR sequences are maintained while the non-human sequences of the variable and constant regions are replaced with human or other amino acids. Attorney Docket No. UAZ-43247.601 Small antibody fragments may be diabodies having two antigen-binding sites, wherein fragments comprise a heavy chain variable domain (VH) connected to a light chain variable domain (VL) in the same polypeptide chain (VH VL). See for example, EP 404,097; WO 93 / 11161; and Hollinger et al., (1993) Proc. Natl. Acad. Sci. USA 90:6444-6448. By using a linker that is too short to allow pairing between the two domains on the same chain, the domains are forced to pair with the complementary domains of another chain and create two antigen-binding sites. See also, U.S. Patent No.6,632,926 to Chen et al. which is hereby incorporated by reference in its entirety and discloses antibody variants that have one or more amino acids inserted into a hypervariable region of the parent antibody and a binding affinity for a target antigen which is at least about two fold stronger than the binding affinity of the parent antibody for the antigen. The antibody may be a linear antibody. The procedure for making a linear antibody is known in the art and described in Zapata et al., (1995) Protein Eng.8(10):1057-1062. Briefly, these antibodies comprise a pair of tandem Fd segments (VH-CH1-VH-CH1) which form a pair of antigen binding regions. Linear antibodies can be bispecific or monospecific. The antibodies may be recovered and purified from recombinant cell cultures by known methods including, but not limited to, protein A purification, ammonium sulfate or ethanol precipitation, acid extraction, anion or cation exchange chromatography, phosphocellulose chromatography, hydrophobic interaction chromatography, affinity chromatography, hydroxylapatite chromatography and lectin chromatography. High performance liquid chromatography (“HPLC”) can also be used for purification. It may be useful to detectably label the antibody. Methods for conjugating antibodies to these agents are known in the art. For the purpose of illustration only, antibodies can be labeled with a detectable moiety such as a radioactive atom, a chromophore, a fluorophore, or the like. Such labeled antibodies can be used for diagnostic techniques, either in vivo, or in an isolated test sample. They can be linked to a cytokine, to a ligand, to another antibody. Suitable agents for coupling to antibodies to achieve an anti-tumor effect include cytokines, such as interleukin 2 (IL-2) and Tumor Necrosis Factor (TNF); photosensitizers, for use in photodynamic therapy, including aluminum (III) phthalocyanine tetrasulfonate, hematoporphyrin, and phthalocyanine; radionuclides, such as iodine-131 (131I), yttrium-90 (90Y), bismuth-212 (212Bi), bismuth-213 (213Bi), technetium-99m (99mTc), rhenium-186 (186Re), and rhenium-188 (188Re); antibiotics, such as doxorubicin, adriamycin, daunorubicin, methotrexate, daunomycin, neocarzinostatin, and carboplatin; bacterial, plant, and other toxins, such as diphtheria toxin, pseudomonas exotoxin A, staphylococcal Attorney Docket No. UAZ-43247.601 enterotoxin A, abrin-A toxin, ricin A (deglycosylated ricin A and native ricin A), TGF-alpha toxin, cytotoxin from chinese cobra (naja naja atra), and gelonin (a plant toxin); ribosome inactivating proteins from plants, bacteria and fungi, such as restrictocin (a ribosome inactivating protein produced by Aspergillus restrictus), saporin (a ribosome inactivating protein from Saponaria officinalis), and RNase; tyrosine kinase inhibitors; ly207702 (a difluorinated purine nucleoside); liposomes containing anti cystic agents (e.g., antisense oligonucleotides, plasmids which encode for toxins, methotrexate, etc.); and other antibodies or antibody fragments, such as F(ab). Antibody production via the use of hybridoma technology, the selected lymphocyte antibody method (SLAM), transgenic animals, and recombinant antibody libraries is described in more detail below. D. Biomarker-Recognizing Aptamers The methods of the present disclosure include the use of aptamers to detect or identify one or more stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers. Aptamers are suitable for use in developing probes having high affinity and selectivity for target molecules, such as peptide biomarkers. Aptamers include single-stranded DNA (ssDNA), RNA, or modified nucleic acids, which have the ability to bind specifically to their targets, which range from small organic molecules to proteins and peptides. The basis for target recognition is the tertiary structures formed by the single-stranded oligonucleotides, as known in the art. In some embodiments, aptamers used to detect or identify one or more stroke-related inflammation biomarkers and stroke-related neurodegeneration biomarkers can be obtained through an in vitro selection process known as SELEX, in which aptamers are selected from a library of random sequences of synthetic DNA or RNA by repetitive binding of the oligonucleotides to target molecules. In some embodiments, nucleic acids that constitute an aptamer library mixture used for screening for candidate biomarker capture agents can be single-stranded DNA or RNA with or without chemical modifications. The introduction of additional chemical entities into DNA during the selection process can include, for example, the use of a 5-alkyne modified nucleobase, (e.g., thymine). Additionally, 5-C8-alkyne modified nucleotide-triphosphates, for example deoxythymidines, are commercially available or can be synthesized. Such 5-C8- alkyne modified nucleobases can be introduced into DNA by PCR. Such modifications can be further derivatized with so called bio-orthogonal chemistry, for example, using the Cu(I) catalyzed 1,3-dipolar cycloaddition of respective azides with the alkyne. Beside the Cu(I) Attorney Docket No. UAZ-43247.601 catalysed azide-alkyne cycloaddition (CuAAC), copper-free strain-promoted azide-alkyne cycloaddition (SPAAC) reactions also are useful. In some embodiments involving cellular or living systems, the strain-promoted azide-alkyne cycloaddition can overcome toxicity issues associated with the use of Cu(I). Any number of desirable chemical modifications can be added to the oligonucleotide library used for screening purposes. Examples of such modifications include without limitation aliphatic- aromatic-, charged-, basic-, acidic, heteroaromatic-, sugar-kind of-, metal-containing- or peptide- residues. In some embodiments, a nucleobase that is to be modified to contain an azide-alkyne chemical group can include an ethynyl-, propynyl- or butynyl- dU, dA, dC or dG nucleotide. In other embodiments, a nucleobase that is to be modified to contain an azide-alkyne chemical group may be an ethynyl-dU nucleotide, or an ethynyl-dA nucleotide, an ethynyl- dC nucleotide or an ethynyl-dG nucleotide. Nucleotide aptamer libraries with these example modifications can be used in various SELEX-based selection methods, in order to enhance the chemical diversity of DNA aptamer libraries. The starting, or candidate, mixture of nucleic acids can be modified such that at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, at least 99%, or 100% of the members of the mixture are modified to comprise the functionalization introduced by click chemistry, for example. Less than 100% modification may allow for enhanced diversity by allowing certain positions in an oligonucleotide to be modified but not others, whereas 100% modification ensures consistency during the selection process. In some embodiments, different modifications are made at different positions in the oligonucleotide to further enhance diversity. Biomarker-recognizing aptamers can be used in various methods to detect a presence or level of one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers in a biological sample (e.g., biological entities of interest such as proteins, nucleic acids, or microvesicles). The aptamer can function as a binding agent or capture agent to assess presence or level of the cognate biomarker. In various embodiments of the present disclosure directed to diagnostics and / or prognostics, one or more aptamers can be configured in a ligand-target based assay, where one or more aptamer can be contacted with a selected biological sample to allow the or more aptamer to associate with or binds to its target biomarker molecule. Aptamers can also be used to identify a profile of multiple biomarkers (a “biomarker” profile or signature) based on the biological samples assessed and biomarkers detected. A biomarker profile of a biological sample may comprise a presence, level or other characteristic of one or more biomarker of interest that can be assessed, including without Attorney Docket No. UAZ-43247.601 limitation a presence, level, sequence, mutation, rearrangement, translocation, deletion, epigenetic modification, methylation, post-translational modification, allele, activity, complex partners, stability, half -life, and the like. Biomarker profiles or signatures can be used to evaluate diagnostic and / or prognostic criteria such as presence of disease, disease staging, disease monitoring, disease stratification, or surveillance for detection, metastasis or recurrence or progression of disease. E. Variations on Methods The disclosed methods of determining the presence or amount of analyte of interest (e.g., stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers) present in a sample may be as described herein. The methods may also be adapted in view of other methods for analyzing analytes. Examples of well-known variations include, but are not limited to, immunoassay, such as sandwich immunoassay (e.g., monoclonal-monoclonal sandwich immunoassays, monoclonal-polyclonal sandwich immunoassays, including enzyme detection (enzyme immunoassay (EIA) or enzyme-linked immunosorbent assay (ELISA), competitive inhibition immunoassay (e.g., forward and reverse), enzyme multiplied immunoassay technique (EMIT), a competitive binding assay, bioluminescence resonance energy transfer (BRET), one-step antibody detection assay, homogeneous assay, heterogeneous assay, capture on the fly assay, etc. The analyte of interest, and / or peptides of fragments thereof (e.g., biomarker and / or peptides or fragments thereof), may be analyzed using biomarker antibodies in an immunoassay. The presence or amount of analyte (e.g., biomarker) can be determined using antibodies and detecting specific binding to the analyte. For example, the antibody, or antibody fragment thereof, may specifically bind to the analyte. If desired, one or more of the antibodies can be used in combination with one or more commercially available monoclonal / polyclonal antibodies. Such antibodies are available from companies such as R&D Systems, Inc. (Minneapolis, MN) and Enzo Life Sciences International, Inc. (Plymouth Meeting, PA). The presence or amount of analyte (e.g., biomarker) present in a body sample may be readily determined using an immunoassay, such as sandwich immunoassay (e.g., monoclonal- monoclonal sandwich immunoassays, monoclonal-polyclonal sandwich immunoassays, including radioisotope detection (radioimmunoassay (RIA)) and enzyme detection (enzyme immunoassay (EIA) or enzyme-linked immunosorbent assay (ELISA) (e.g., Quantikine ELISA assays, R&D Systems, Minneapolis, MN)). An example of a point-of-care device that Attorney Docket No. UAZ-43247.601 can be used is i-STAT® (Abbott, Laboratories, Abbott Park, IL). Other methods that can be used include a chemiluminescent microparticle immunoassay, in particular one employing the ARCHITECT® automated analyzer (Abbott Laboratories, Abbott Park, IL), as an example. Other methods include, for example, mass spectrometry, and immunohistochemistry (e.g., with sections from tissue biopsies), using anti-analyte (e.g., anti-biomarker) antibodies (monoclonal, polyclonal, chimeric, humanized, human, etc.) or antibody fragments thereof against analyte (e.g., biomarker). Other methods of detection include those described in, for example, U.S. Patent Nos.6,143,576; 6,113,855; 6,019,944; 5,985,579; 5,947,124; 5,939,272; 5,922,615; 5,885,527; 5,851,776; 5,824,799; 5,679,526; 5,525,524; and 5,480,792, each of which is hereby incorporated by reference in its entirety. Specific immunological binding of the antibody to the analyte can be detected via direct labels, such as fluorescent or luminescent tags, metals and radionuclides attached to the antibody or via indirect labels, such as alkaline phosphatase or horseradish peroxidase. The use of immobilized antibodies or antibody fragments thereof may be incorporated into the immunoassay. The antibodies may be immobilized onto a variety of supports, such as magnetic or chromatographic matrix particles, the surface of an assay plate (such as microtiter wells), pieces of a solid substrate material, and the like. An assay strip can be prepared by coating the antibody or plurality of antibodies in an array on a solid support. This strip can then be dipped into the test sample and processed quickly through washes and detection steps to generate a measurable signal, such as a colored spot. A homogeneous format may be used. For example, after the test sample is obtained from a subject, a mixture is prepared. The mixture contains the test sample being assessed for analyte (e.g., biomarker) and a specific binding partner. The order in which the test sample and the specific binding partner are added to form the mixture is not critical. The test sample is simultaneously contacted with the specific binding partner. In some embodiments, the specific binding partner and any biomarker contained in the test sample may form a specific binding partner-analyte (e.g., biomarker)-antigen complex. The specific binding partner may be an anti-analyte antibody (e.g., anti-biomarker antibody that binds to an epitope having an amino acid sequence comprising at least three contiguous (3) amino acids of the biomarker. Moreover, the specific binding partner may be labeled with or contains a detectable label as described above. A heterogeneous format may be used. For example, after the test sample is obtained from a subject, a first mixture is prepared. The mixture contains the test sample being assessed for analyte (e.g., biomarker) and a first specific binding partner, wherein the first Attorney Docket No. UAZ-43247.601 specific binding partner and any biomarker contained in the test sample form a first specific binding partner-analyte (e.g., biomarker)-antigen complex. The first specific binding partner may be an anti-analyte antibody (e.g., anti-biomarker antibody that binds to an epitope having an amino acid sequence comprising at least three contiguous (3) amino acids of the biomarker. The order in which the test sample and the first specific binding partner are added to form the mixture is not critical. The first specific binding partner may be immobilized on a solid phase. The solid phase used in the immunoassay (for the specific binding partner) can be any solid phase known in the art, such as, but not limited to, a magnetic particle, a bead, a test tube, a microtiter plate, a cuvette, a membrane, a scaffolding molecule, a film, a filter paper, a disc, and a chip. In those embodiments where the solid phase is a bead, the bead may be a magnetic bead or a magnetic particle. Magnetic beads / particles may be ferromagnetic, ferrimagnetic, paramagnetic, superparamagnetic or ferrofluidic. Exemplary ferromagnetic materials include Fe, Co, Ni, Gd, Dy, CrO2, MnAs, MnBi, EuO, and NiO / Fe. Examples of ferrimagnetic materials include NiFe2O4, CoFe2O4, Fe3O4 (or FeO.Fe2O3). Beads can have a solid core portion that is magnetic and is surrounded by one or more non-magnetic layers. Alternately, the magnetic portion can be a layer around a non-magnetic core. The solid support on which the first specific binding member is immobilized may be stored in dry form or in a liquid. The magnetic beads may be subjected to a magnetic field prior to or after contacting with the sample with a magnetic bead on which the first specific binding member is immobilized. After the mixture containing the first specific binding partner-analyte (e.g., biomarker) antigen complex is formed, any unbound analyte (e.g., biomarker) is removed from the complex using any technique known in the art. For example, the unbound analyte can be removed by washing. Desirably, however, the first specific binding partner is present in excess of any analyte present in the test sample, such that all analyte that is present in the test sample is bound by the first specific binding partner. After any unbound analyte (e.g., biomarker) is removed, a second specific binding partner is added to the mixture to form a first specific binding partner-analyte of interest (e.g., biomarker)-second specific binding partner complex. The second specific binding partner may be an anti-analyte antibody (e.g., biomarker antibody that binds to an epitope having an amino acid sequence comprising at least three contiguous (3) amino acids of the biomarker. Moreover, the second specific binding partner is labeled with or contains a detectable label as described above. Attorney Docket No. UAZ-43247.601 The use of immobilized antibodies or antibody fragments thereof may be incorporated into the immunoassay. The antibodies may be immobilized onto a variety of supports, such as magnetic or chromatographic matrix particles (such as a magnetic bead), latex particles or modified surface latex particles, polymer or polymer film, plastic or plastic film, planar substrate, the surface of an assay plate (such as microtiter wells), pieces of a solid substrate material, and the like. An assay strip can be prepared by coating the antibody or plurality of antibodies in an array on a solid support. This strip can then be dipped into the test sample and processed quickly through washes and detection steps to generate a measurable signal, such as a colored spot. A sandwich immunoassay measures the amount of antigen between two layers of antibodies (i.e. at least one capture antibody) and a detection antibody (i.e. at least one detection antibody). The capture antibody and the detection antibody bind to different epitopes on the antigen, e.g., analyte of interest such as a biomarker). Desirably, binding of the capture antibody to an epitope does not interfere with binding of the detection antibody to an epitope. Either monoclonal or polyclonal antibodies may be used as the capture and detection antibodies in the sandwich immunoassay. Generally, at least two antibodies are employed to separate and quantify analyte (e.g., biomarker) in a test sample. More specifically, the at least two antibodies bind to certain epitopes of analyte forming an immune complex which is referred to as a “sandwich.” One or more antibodies can be used to capture the analyte in the test sample (these antibodies are frequently referred to as a “capture” antibody or “capture” antibodies) and one or more antibodies is used to bind a detectable (namely, quantifiable) label to the sandwich (these antibodies are frequently referred to as the “detection” antibody or “detection” antibodies). In a sandwich assay, the binding of an antibody to its epitope desirably is not diminished by the binding of any other antibody in the assay to its respective epitope. Antibodies are selected so that the one or more first antibodies brought into contact with a test sample suspected of containing analyte do not bind to all or part of an epitope recognized by the second or subsequent antibodies, thereby interfering with the ability of the one or more second detection antibodies to bind to the analyte. The antibodies may be used as a first antibody in said immunoassay. The antibody immunospecifically binds to epitopes on analyte (e.g., biomarker). In addition to the antibodies of the present disclosure, said immunoassay may comprise a second antibody that immunospecifically binds to epitopes that are not recognized or bound by the first antibody. Attorney Docket No. UAZ-43247.601 A test sample suspected of containing analyte (e.g., biomarker) can be contacted with at least one first capture antibody (or antibodies) and at least one second detection antibodies either simultaneously or sequentially. In the sandwich assay format, a test sample suspected of containing analyte is first brought into contact with the at least one first capture antibody that specifically binds to a particular epitope under conditions which allow the formation of a first antibody-analyte antigen complex. If more than one capture antibody is used, a first multiple capture antibody-biomarker antigen complex is formed. In a sandwich assay, the antibodies, preferably, the at least one capture antibody, are used in molar excess amounts of the maximum amount of analyte expected in the test sample. For example, from about 5 µg / mL to about 1 mg / mL of antibody per ml of microparticle coating buffer may be used. Optionally, prior to contacting the test sample with the at least one first capture antibody, the at least one first capture antibody can be bound to a solid support which facilitates the separation the first antibody-analyte (e.g., biomarker) complex from the test sample. Any solid support known in the art can be used, including but not limited to, solid supports made out of polymeric materials in the forms of wells, tubes, or beads (such as a microparticle). The antibody (or antibodies) can be bound to the solid support by adsorption, by covalent bonding using a chemical coupling agent or by other means known in the art, provided that such binding does not interfere with the ability of the antibody to bind analyte. Moreover, if necessary, the solid support can be derivatized to allow reactivity with various functional groups on the antibody. Such derivatization requires the use of certain coupling agents such as, but not limited to, maleic anhydride, N-hydroxysuccinimide and 1-ethyl-3-(3- dimethylaminopropyl)carbodiimide. After the test sample suspected of containing analyte (e.g., biomarker) is incubated in order to allow for the formation of a first capture antibody (or multiple antibody)-analyte complex. The incubation can be carried out at a pH of from about 4.5 to about 10.0, at a temperature of from about 2°C to about 45°C, and for a period from at least about one (1) minute to about eighteen (18) hours, from about 2-6 minutes, from about 7 -12 minutes, from about 5-15 minutes, or from about 3-4 minutes. After formation of the first / multiple capture antibody-analyte (e.g., biomarker) complex, the complex is then contacted with at least one second detection antibody (under conditions that allow for the formation of a first / multiple antibody-analyte antigen-second antibody complex). In some embodiments, the test sample is contacted with the detection antibody simultaneously with the capture antibody. If the first antibody-analyte complex is contacted with more than one detection antibody, then a first / multiple capture antibody- Attorney Docket No. UAZ-43247.601 analyte-multiple antibody detection complex is formed. As with first antibody, when the at least second (and subsequent) antibody is brought into contact with the first antibody-analyte complex, a period of incubation under conditions similar to those described above is required for the formation of the first / multiple antibody-analyte-second / multiple antibody complex. Preferably, at least one second antibody contains a detectable label. The detectable label can be bound to the at least one second antibody prior to, simultaneously with or after the formation of the first / multiple antibody-analyte-second / multiple antibody complex. Any detectable label known in the art can be used. Chemiluminescent assays can be performed in accordance with the methods described in Adamczyk et al., Anal. Chim. Acta 579(1): 61-67 (2006). While any suitable assay format can be used, a microplate chemiluminometer (Mithras LB-940, Berthold Technologies U.S.A., LLC, Oak Ridge, TN) enables the assay of multiple samples of small volumes rapidly. The chemiluminometer can be equipped with multiple reagent injectors using 96- well black polystyrene microplates (Costar #3792). Each sample can be added into a separate well, followed by the simultaneous / sequential addition of other reagents as determined by the type of assay employed. Desirably, the formation of pseudobases in neutral or basic solutions employing an acridinium aryl ester is avoided, such as by acidification. The chemiluminescent response is then recorded well-by-well. In this regard, the time for recording the chemiluminescent response will depend, in part, on the delay between the addition of the reagents and the particular acridinium employed. The order in which the test sample and the specific binding partner(s) are added to form the mixture for chemiluminescent assay is not critical. If the first specific binding partner is detectably labeled with an acridinium compound, detectably labeled first specific binding partner-antigen (e.g., biomarker) complexes form. Alternatively, if a second specific binding partner is used and the second specific binding partner is detectably labeled with an acridinium compound, detectably labeled first specific binding partner-analyte-second specific binding partner complexes form. Any unbound specific binding partner, whether labeled or unlabeled, can be removed from the mixture using any technique known in the art, such as washing. Hydrogen peroxide can be generated in situ in the mixture or provided or supplied to the mixture before, simultaneously with, or after the addition of an above-described acridinium compound. Hydrogen peroxide can be generated in situ in a number of ways such as would be apparent to one skilled in the art. Attorney Docket No. UAZ-43247.601 Alternatively, a source of hydrogen peroxide can be simply added to the mixture. For example, the source of the hydrogen peroxide can be one or more buffers or other solutions that are known to contain hydrogen peroxide. In this regard, a solution of hydrogen peroxide can simply be added. Upon the simultaneous or subsequent addition of at least one basic solution to the sample, a detectable signal, namely, a chemiluminescent signal, indicative of the presence of analyte (e.g., biomarker) is generated. The basic solution contains at least one base and has a pH greater than or equal to 10, preferably, greater than or equal to 12. Examples of basic solutions include, but are not limited to, sodium hydroxide, potassium hydroxide, calcium hydroxide, ammonium hydroxide, magnesium hydroxide, sodium carbonate, sodium bicarbonate, calcium hydroxide, calcium carbonate, and calcium bicarbonate. The amount of basic solution added to the sample depends on the concentration of the basic solution. Based on the concentration of the basic solution used, one skilled in the art can easily determine the amount of basic solution to add to the sample. Other labels other than chemiluminescent labels can be employed. For instance, enzymatic labels (including but not limited to alkaline phosphatase) can be employed. The chemiluminescent signal, or other signal, that is generated can be detected using routine techniques known to those skilled in the art. Based on the intensity of the signal generated, the amount of analyte of interest (e.g., stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers) in the sample can be quantified. Specifically, the amount of analyte in the sample is proportional to the intensity of the signal generated. The amount of analyte present can be quantified by comparing the amount of light generated to a standard curve for analyte or by comparison to a reference standard. The standard curve can be generated using serial dilutions or solutions of known concentrations of analyte by mass spectroscopy, gravimetric methods, and other techniques known in the art. In a forward competitive format, an aliquot of labeled analyte of interest (e.g., biomarker) having a fluorescent label, a tag attached with a cleavable linker, etc.) of a known concentration is used to compete with analyte of interest in a test sample for binding to analyte of interest antibody (e.g., a biomarker antibody). In a forward competition assay, an immobilized specific binding partner (such as an antibody) can either be sequentially or simultaneously contacted with the test sample and a labeled analyte of interest, analyte of interest fragment or analyte of interest variant thereof. The analyte of interest peptide, analyte of interest fragment or analyte of interest variant can be labeled with any detectable label, including a detectable label comprised of tag attached Attorney Docket No. UAZ-43247.601 with a cleavable linker. In this assay, the antibody can be immobilized on to a solid support. Alternatively, the antibody can be coupled to an antibody, such as an antispecies antibody, that has been immobilized on a solid support, such as a microparticle or planar substrate. The labeled analyte of interest, the test sample and the antibody are incubated under conditions similar to those described above in connection with the sandwich assay format. Two different species of antibody-analyte of interest complexes may then be generated. Specifically, one of the antibody-analyte of interest complexes generated contains a detectable label (e.g., a fluorescent label, etc.) while the other antibody-analyte of interest complex does not contain a detectable label. The antibody-analyte of interest complex can be, but does not have to be, separated from the remainder of the test sample prior to quantification of the detectable label. Regardless of whether the antibody-analyte of interest complex is separated from the remainder of the test sample, the amount of detectable label in the antibody-analyte of interest complex is then quantified. The concentration of analyte of interest (such as membrane-associated analyte of interest, soluble analyte of interest, fragments of soluble analyte of interest, variants of analyte of interest (membrane-associated or soluble analyte of interest) or any combinations thereof) in the test sample can then be determined, e.g., as described above. In a reverse competition assay, an immobilized analyte of interest (e.g., stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers) can either be sequentially or simultaneously contacted with a test sample and at least one labeled antibody. The analyte of interest can be bound to a solid support, such as the solid supports discussed above in connection with the sandwich assay format. The immobilized analyte of interest, test sample and at least one labeled antibody are incubated under conditions similar to those described above in connection with the sandwich assay format. Two different species analyte of interest-antibody complexes are then generated. Specifically, one of the analyte of interest-antibody complexes generated is immobilized and contains a detectable label (e.g., a fluorescent label, etc.) while the other analyte of interest-antibody complex is not immobilized and contains a detectable label. The non-immobilized analyte of interest-antibody complex and the remainder of the test sample are removed from the presence of the immobilized analyte of interest-antibody complex through techniques known in the art, such as washing. Once the non-immobilized analyte of interest antibody complex is removed, the amount of detectable label in the immobilized analyte of interest-antibody complex is then quantified following cleavage of the tag. The Attorney Docket No. UAZ-43247.601 concentration of analyte of interest in the test sample can then be determined by comparing the quantity of detectable label as described above. In a capture on the fly immunoassay, a solid substrate is pre-coated with an immobilization agent. The capture agent, the analyte (e.g., stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers) and the detection agent are added to the solid substrate together, followed by a wash step prior to detection. The capture agent can bind the analyte and comprises a ligand for an immobilization agent. The capture agent and the detection agents may be antibodies or any other moiety capable of capture or detection as described herein or known in the art. The ligand may comprise a peptide tag and an immobilization agent may comprise an anti-peptide tag antibody. Alternately, the ligand and the immobilization agent may be any pair of agents capable of binding together so as to be employed for a capture on the fly assay (e.g., specific binding pair, and others such as are known in the art). More than one analyte may be measured. In some embodiments, the solid substrate may be coated with an antigen and the analyte to be analyzed is an antibody. This method can also be coupled with MS detection and quantification. In certain other embodiments, in a one-step immunoassay or “capture on the fly”, a solid support (such as a microparticle) pre-coated with an immobilization agent (such as biotin, streptavidin, etc.) and at least a first specific binding member and a second specific binding member (which function as capture and detection reagents, respectively) are used. The first specific binding member comprises a ligand for the immobilization agent (for example, if the immobilization agent on the solid support is streptavidin, the ligand on the first specific binding member may be biotin) and also binds to the analyte of interest (e.g., stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers). The second specific binding member comprises a detectable label and binds to an analyte of interest. The solid support and the first and second specific binding members may be added to a test sample (either sequentially or simultaneously). The ligand on the first specific binding member binds to the immobilization agent on the solid support to form a solid support / first specific binding member complex. Any analyte of interest present in the sample binds to the solid support / first specific binding member complex to form a solid support / first specific binding member / analyte complex. The second specific binding member binds to the solid support / first specific binding member / analyte complex and the detectable label is detected. An optional wash step may be employed before the detection. In certain embodiments, in a one-step assay more than one analyte may be measured. In certain other embodiments, more than two specific binding members can be employed. In certain other embodiments, multiple Attorney Docket No. UAZ-43247.601 detectable labels can be added. In certain other embodiments, multiple analytes of interest can be detected, or their amounts, levels or concentrations, measured, determined or assessed, including using mass spectrometry. The use of a capture on the fly assay can be done in a variety of formats as described herein, and known in the art. For example the format can be a sandwich assay such as described above, but alternately can be a competition assay, can employ a single specific binding member, or use other variations such as are known. This method can also be coupled with MS detection and quantification. 7. Kits Provided herein is a kit, which may be used for assaying or assessing a test sample for one or more stroke-related inflammation biomarkers and / or stroke-related neurodegeneration biomarkers and / or fragments thereof. The kit comprises at least one component for assaying the test sample for such a biomarker and instructions for assaying the test sample for such a biomarker. For example, the kit can comprise instructions for assaying the test sample for a biomarker by immunoassay (e.g., chemiluminescent microparticle immunoassay) or by mass spectrometry assay (e.g., PRM-MS or MRM / SRM-MS). Instructions included in kits can be affixed to packaging material or can be included as a package insert. While the instructions are typically written or printed materials they are not limited to such. Any medium capable of storing such instructions and communicating them to an end user is contemplated by this disclosure. Such media include, but are not limited to, electronic storage media (e.g., magnetic discs, tapes, cartridges, chips), optical media (e.g., CD ROM), and the like. As used herein, the term “instructions” can include the address of an internet site that provides the instructions. The at least one component may include at least one composition comprising one or more isolated antibodies or antibody fragments thereof that specifically bind to a stroke- related inflammation biomarker and / or stroke-related neurodegeneration biomarker. The antibody may be a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker detection antibody and / or capture antibody. Alternatively or additionally, the kit can comprise a calibrator or control (e.g., purified, and optionally lyophilized, stroke-related inflammation biomarker and / or stroke- related neurodegeneration biomarker) and / or at least one container (e.g., tube, microtiter plates or strips, which can be already coated with an anti-biomarker antibody) for conducting the assay, and / or a buffer, such as an assay buffer or a wash buffer, either one of which can be Attorney Docket No. UAZ-43247.601 provided as a concentrated solution, a substrate solution for the detectable label (e.g., an enzymatic label), or a stop solution. Preferably, the kit comprises all components, i.e. reagents, standards, buffers, diluents, etc., which are necessary to perform the assay. The instructions also can include instructions for generating a standard curve. The kit may further comprise reference standards for quantifying a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker. The reference standards may be employed to establish standard curves for interpolation and / or extrapolation of stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker concentrations. Standards cans include proteins or peptide fragments composed of amino acids residues or N15 stable isotopic labeled proteins or peptide fragments for various analytes, as well as standards for sample processing, including standards involving spikes in proteins and quantitative peptides. In some embodiments, the reference standards for a stroke- related inflammation biomarker and / or stroke-related neurodegeneration biomarker can correspond to the 99th percentile derived from a healthy reference population. Such reference standards can be determined using routine techniques known in the art. Any antibodies, which are provided in the kit, such as recombinant antibodies specific for a stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker, can incorporate a detectable label, such as a fluorophore, radioactive moiety, enzyme, biotin / avidin label, chromophore, chemiluminescent label, or the like, or the kit can include reagents for labeling the antibodies or reagents for detecting the antibodies (e.g., detection antibodies) and / or for labeling the analytes (e.g., stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker) or reagents for detecting the analyte (e.g., stroke-related inflammation biomarker and / or stroke-related neurodegeneration biomarker). The antibodies, standard peptides or peptide fragments, calibrators, and / or controls can be provided in separate containers or pre-dispensed into an appropriate assay format, for example, into microtiter plates. Optionally, the kit includes quality control components (for example, sensitivity panels, calibrators, and positive controls). Preparation of quality control reagents is well- known in the art and is described on insert sheets for a variety of immunodiagnostic products. Sensitivity panel members optionally are used to establish assay performance characteristics, and further optionally are useful indicators of the integrity of the immunoassay kit reagents, and the standardization of assays. The kit can also optionally include other reagents required to conduct a diagnostic assay or facilitate quality control evaluations, such as buffers, salts, enzymes, enzyme co- Attorney Docket No. UAZ-43247.601 factors, substrates, detection reagents, and the like. Other components, such as buffers and solutions for the isolation and / or treatment of a test sample (e.g., pretreatment reagents), also can be included in the kit. The kit can additionally include one or more other controls. One or more of the components of the kit can be lyophilized, in which case the kit can further comprise reagents suitable for the reconstitution of the lyophilized components. The various components of the kit optionally are provided in suitable containers as necessary, e.g., a microtiter plate. The kit can further include containers for holding or storing a sample (e.g., a container or cartridge for a urine, whole blood, plasma, or serum sample). Where appropriate, the kit optionally also can contain reaction vessels, mixing vessels, and other components that facilitate the preparation of reagents or the test sample. The kit can also include one or more instrument for assisting with obtaining a test sample, such as a syringe, pipette, forceps, measured spoon, or the like. If the detectable label is at least one acridinium compound, the kit can comprise at least one acridinium-9-carboxamide, at least one acridinium-9-carboxylate aryl ester, or any combination thereof. If the detectable label is at least one acridinium compound, the kit also can comprise a source of hydrogen peroxide, such as a buffer, solution, and / or at least one basic solution. If desired, the kit can contain a solid phase, such as a magnetic particle, bead, test tube, microtiter plate, cuvette, membrane, scaffolding molecule, film, filter paper, disc, or chip. If desired, the kit can further comprise one or more components, alone or in further combination with instructions, for assaying the test sample for another analyte, which can be a biomarker, such as a biomarker of traumatic brain injury or disorder. EXAMPLES The following examples are illustrative, but not limiting, of the compounds, compositions, and methods of the present invention. Other suitable modifications and adaptations of the variety of conditions and parameters normally encountered in clinical therapy and which are obvious to those skilled in the art are within the spirit and scope of the invention. The use of pronouns such as “I”, “we”, and “our”, for example, refer to one or more of the inventors. Example 1. This example provides the materials and methods implemented in conducting the experimens described in Examples 2-8. Attorney Docket No. UAZ-43247.601 Animals Aged (20- to 23-month-old) wild-type male C57BL / 6 mice were obtained from the National Institute on Aging. Mice were housed in a temperature-controlled suite with a 12- hour light-dark regimen and ad libitum access to food and water. All experimental procedures were conducted in accordance with the animal care standards of the National Institutes of Health and approved by the University of Arizona Institutional Animal Care and Use Committee. Upon termination of each experiment, mice were anesthetized by isoflurane inhalation and secured in a supine position. For terminal intracardiac bleeding, the thoracic cavity was sterilized with 70% ethanol, and a midline incision was performed to expose the heart. A sterile syringe, equipped with a fine-gauge needle, was inserted into the left ventricle of the heart, and blood was drawn by gentle aspiration. Following exsanguination by intracardiac bleeding, mice were perfused with 0.9% saline. Collected blood samples were immediately placed on ice in EDTA-coated microcentrifuge tubes and centrifuged at 4°C for 10 min at 5000 x g to separate plasma. Plasma samples were stored at -80°C until further analysis. Retro-orbital Bleeding A heparinized microhematocrit capillary tube was gently inserted into the retro-orbital sinus, positioned at the medial canthus of the eye. Blood was collected by capillary action into an EDTA-coated microcentrifuge tube. Collected blood samples were immediately placed on ice and centrifuged at 4°C for 10 min at 5000 x g to separate plasma. Plasma samples were stored at -80°C until further analysis. Stroke Surgeries Stroke was induced in mice using the distal MCA occlusion + hypoxia (DH) model. The DH stroke model generates a sizable infarct (24% of the ipsilateral hemisphere centered on the somatosensory cortex), has low variability, and has exceptional long-term survivability. The addition of hypoxia is necessary because C57BL / 6 mice that undergo DH stroke without hypoxia have much smaller infarcts. The methodology of the DH stroke model and validation of the controls has been previously published (3,4). To induce stroke, mice were anesthetized by isoflurane inhalation and kept at 37°C throughout the surgical procedure. For all experiments, mice were injected subcutaneously (s.c.) with a single dose of buprenorphine hydrochloride (0.1 mg / kg) dissolved in sterile saline. Following pre-operative Attorney Docket No. UAZ-43247.601 preparation, an incision was made to expose the right temporoparietal skull between the orbit and the ear. Under an operating microscope, a small hole was made with a high-speed microdrill through the outer surface of the semi-translucent skull over the visually identified MCA at the level of the parietal cerebral artery. Permanent occlusion of the MCA was performed by electrocoagulation with a small vessel cauterizer. Surgical wounds were closed using Surgi-lock 2oc tissue adhesive. Mice were then immediately transferred to a hypoxia chamber containing 11% oxygen and 89% nitrogen for 45 min. Extended-release buprenorphine (Ethiqa XR, 3.25 mg / kg s.c.) was administered 24 h after surgery as post- operative analgesia. MRI Infarct, ventricle, and hippocampus volumes were assessed by MRI using a Bruker Biospec 70 / 207.0T scanner with ParaVision-360.3.2 software and a 4-channel phase array mouse coil. Mice were placed in a cradle equipped with a stereotaxic frame, an integrated heating system to maintain body temperature at 37±1°C, and a pressure probe to monitor respiration. During MRI acquisition, anesthesia was maintained by inhalation of 1.5-3% isoflurane. High-resolution structural images were acquired using a T2-weighted RARE Bruker pulse sequence with the following parameters: repetition time (TR) = 2500 ms; flip angle = 30°; RARE factor = 8; matrix size = 256 x 256; averages = 2; field of view = 20 mm x 20 mm; slice thickness = 0.8 mm; number of slices = 15; acquisition time = 2 min 40 s. Infarcts, ventricles, hippocampi, and hemispheric cross sections were manually delineated on T2-weighted MR images using Mango v4.1. Plasma Neurofilament Light Quantification (Quanterix®) NfL was quantified using the Simoa® (Single Molecule Array) NF-Light v2 Advantage Assay (Quanterix®, Cat. No.104073) according to manufacturer instructions. Each control, calibrator, and experimental plasma sample was measured in duplicate on the Simoa® SR-X Instrument. In the two-step immunoassay, paramagnetic beads, pre-coated with an anti-NfL antibody, are incubated with the sample and biotinylated detector antibody. Target molecules present in the sample are captured by the antibody coated beads and bind with the biotinylated detector antibody simultaneously. Following a wash, a conjugate of streptavidin-ß-galactosidase (SBG) is mixed with the beads. SBG binds to biotinylated detector antibodies, labeling captured targets. Following a final wash, the beads are resuspended in a resorufin ß-D-galactopyranoside (RGP) substrate solution and transferred to Attorney Docket No. UAZ-43247.601 the Simoa® disc. Individual beads are then sealed within microwells in the array. If the target has been captured and labeled on the bead, ß-galactosidase hydrolyzes the RGP substrate into a fluorescent product that provides the signal for measurement. A single labeled target molecule results in sufficient fluorescent signal in 30 s to be detected and counted by the Simoa® optical system. Plasma Targeted Lipidomic and Global Untargeted Metabolomic Analyses (Metabolon, Inc.) Plasma samples for targeted lipidomic and global untargeted metabolomic analyses were transported on dry ice to Metabolon, Inc. and subsequently preserved at -80°C. Targeted lipidomics specifically detects lipids from a predetermined panel. Untargeted metabolomics is a comprehensive technique that impartially and systematically detects and identifies metabolites within a biological sample. Metabolomics generally captures polar, water-soluble metabolites, including polar lipids (5). Targeted lipidomic analysis was performed using differential mobility spectroscopy. Differential mobility spectroscopy not only distinguishes species based on variations in mass- to-charge ratio (m / z) and retention time / index (RI) but also considers size and shape, thereby enabling identification of closely related lipid species. Briefly, lipids were extracted from plasma in the presence of deuterated internal standards by butanol-methanol extraction (6), concentrated under nitrogen, and reconstituted in a dichloromethane:methanol solution containing ammonium acetate. Samples were analyzed via both positive and negative mode electrospray MS. Individual lipid species were quantified by multiplying peak area ratios of target compounds and their assigned internal standards by the internal standard concentration in the sample. Each lipid class concentration was calculated by summing all lipids belonging to that class. Each fatty acid composition was calculated through the proportion of each class composed of individual fatty acids. Global untargeted metabolomic analysis was performed using ultrahigh performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS / MS). Briefly, recovery and internal standards were added to plasma samples for evaluation of extraction efficiency and instrument performance, respectively. Metabolites were extracted with methanol and analyzed by reverse-phase (RP) / UPLC-MS / MS (positive and negative ion modes) and hydrophilic interaction liquid chromatography (HILIC) / UPLC-MS / MS. Metabolites were identified by automated ion peak comparison from each sample to library entries of purified standards or recurrent unknown entities. Metabolon, Inc. maintains a Attorney Docket No. UAZ-43247.601 reference library based on authenticated standards that contains the RI, m / z, and fragmentation data for all molecules. Biochemical identifications were based on three criteria: RI within a narrow window of the proposed identification, accurate mass switch to the library + / - 10 ppm, and the MS / MS forward and reverse scores between the experimental data and authentic standards. Each metabolite within a biological sample was quantified by area- under-the-curve and normalized to account for day-to-day variation. Statistical Analyses Statistical analyses were performed using GraphPad Prism 10.0. Data were tested first for outliers with the ROUT method (Q = 1%) and then for normal distribution with the Shapiro-Wilk (W) test. For data demonstrating normal distribution, parametric tests were applied, specifically: (1) a two-tailed, unpaired t-test for comparisons between two groups, or (2) an ordinary one-way ANOVA followed by Dunnett’s multiple comparisons test for comparisons between multiple groups. In cases where data did not exhibit normal distribution, nonparametric tests were utilized: (1) a Mann-Whitney U test for comparisons between two groups, or (2) a Kruskal-Wallis test followed by Dunn’s multiple comparisons test for comparisons between multiple groups. Spearman correlation analysis was conducted to assess the association between MRI parameters, and results were represented graphically using curves indicating 95% confidence intervals. Mean with SD was reported for NfL analysis. In all other analyses, data were presented as box plots, where the boxes depict the 25th to 75th percentile range, whiskers denote the minimum to maximum data span, and horizontal lines indicate the median value. Individual values for each mouse are plotted on their respective graphs. MetaboAnalyst 5.0 was used to create volcano plots and heatmaps from lipid species concentrations and metabolite peak areas. Prior to analysis, a variance filter (SD) was applied, filtering out 20% of all features. Subsequently, data underwent normalization by sum, followed by log transformation. Auto scaling was employed for data scaling. Hierarchical clustering heatmaps were generated, offering an intuitive visualization of log- normalized concentrations. Euclidean correlations and Ward clustering algorithms were used to measure distances between data points. Volcano plots were generated using a fold change (FC) threshold of 2.0 and false discovery rate (FDR)-adjusted P value threshold of 0.05. These comprehensive analyses provide insights into the distribution, patterns, and relationships within the lipid and metabolite datasets. Attorney Docket No. UAZ-43247.601 Example 2. This example demonstrates that NfL is a plasma biomarker of neurodegeneration after stroke in aged mice. NfL has emerged as a prospective biomarker for ischemic stroke, reflecting the dynamic and ongoing process of neuroaxonal damage (7). To assess the temporal dynamics of NfL accumulation in the plasma after stroke, we performed blood sample collections at 24 h, 1 wk, 2 wk, 3 wk, 4 wk, 5 wk, 6 wk, and 7 wk after induction of DH stroke in aged (20- to 23-month-old) male mice. Concomitantly, we performed T2-weighted MRI at 24 h to assess infarct expansion and at 7 wk to assess hippocampal edema and lateral ventricle enlargement as measures of chronic neurodegeneration (Fig.1A). We discovered that NfL was significantly elevated in the plasma of aged male mice at 24 h, 1 wk, 2 wk, 3 wk, 4 wk, 6 wk, and 7 wk after DH stroke compared to naïve controls (Fig.1B). These results are in accordance with clinical studies demonstrating elevated levels of serum NfL in the first few days after stroke onset and in follow-up assessments at 3 months (8). We also observed a significant positive correlation between plasma NfL levels and infarct volumes 24 h after stroke (Fig.1C). To further evaluate the connection between acute and chronic pathological sequelae, we conducted Spearman correlation analyses on MRI-based volumetric measures. We discovered a significant positive correlation between infarct volumes 24 h after stroke and lateral ventricle volumes 7 wk after stroke (Fig.1D). In addition, we observed a positive correlation between infarct volumes 24 h after stroke and hippocampus volumes 7 wk after stroke; however, the relationship was not significant (Fig.1E). Example 3. This example describes the plasma lipidome 24 h after stroke in aged mice. To determine whether the plasma lipidome expresses a signature of brain lipid catabolism in the acute phase after stroke, we collected plasma samples from aged (20- to 23- month-old) male mice 24 h after stroke and from naïve mice. These samples were sent to Metabolon, Inc. for targeted lipidomic analysis using the Complex Lipid Panel (CLP), which provides quantitation of up to 1,100 individual lipid species from 14 lipid classes. The resultant volcano plot illustrates the distribution of 18 increased and 177 decreased lipid species. These altered lipid species consisted primarily of hexosylceramides (HCER), sphingomyelins (SM), phosphatidylethanolamines (PE), and triacylglycerols (TAG), broadly indicating an increase in sphingolipids and phospholipids and a decrease in neutral lipids 24 h Attorney Docket No. UAZ-43247.601 after stroke (Fig.2A). To further assess these alterations in an unbiased manner, we constructed a hierarchical clustering heatmap depicting the top 30 lipids ranked by t-test. Consistent with the volcano plot, the heatmap illustrates an elevation in HCER and SM lipid species and a reduction in lysophosphatidylcholine (LPC), phosphatidylcholine (PC), and TAG lipid species 24 h after stroke (Fig.2B). Upon assessment of lipid classes, which were quantified by summing categories of lipids, we discovered that cholesteryl esters (CE) and SM were increased, and TAG were decreased in the plasma 24 h after stroke (Fig.2C). These alterations were confirmed in analyses of individual lipid species, including SM(18:0), SM(18:1), HCER(18:0), HCER(20:0), CE(18:1), CE(20:4), TAG56:3-FA18:1, and TAG56:4-FA18:1 (Fig.2D-G). These results indicate that there is a distinct signature of lipid catabolism in the plasma lipidome 24 h after stroke, with a substantial proportion of altered lipids constituting essential components of myelin. Notably, nearly all quantified SM and HCER lipid species were significantly elevated in the plasma 24 h after stroke (Table 1). Example 4. This example describes the temporal profile of the plasma lipidome after stroke in aged mice. To assess whether the acute signature of brain lipid catabolism was sustained in the weeks after stroke, we collected plasma samples at 1 wk, 2 wk, 3 wk, 4 wk, 5 wk, 6 wk, and 7 wk after stroke in aged (20- to 23-month-old) male mice. These samples were also sent to Metabolon, Inc. for targeted lipidomic analysis using the CLP. To visualize the temporal profiles of the top 30 lipids altered 24 h after stroke, we expanded the hierarchical clustering heatmap in Fig.2B to include the subacute and chronic phases after stroke. The resultant heatmap demonstrates that the acute alterations in the plasma lipidome 24 h after stroke are transient; within 1 wk after stroke, most plasma lipids have reverted to baseline levels (Fig. 3A). Interestingly, the temporal profile of TAG60:12-FA22:6 was biphasic, with acute elevation at 24 h and chronic elevation at 5 wk and 7 wk after stroke (Fig.3B). However, the temporal profiles of HCER(16:0), SM(16:0), and TAG56:4-FA18:1 were monophasic, with acute alterations 24 h after stroke that returned to baseline levels by 1 wk (Fig.3C-E). These results indicate that there is a distinct signature of brain lipid catabolism in the plasma in the acute phase after stroke; however, these circulating lipids return to baseline levels within 1 wk. Example 5. Attorney Docket No. UAZ-43247.601 This example describes the plasma metabolome 24 h after stroke in aged mice. To determine whether the plasma metabolome reflects a concomitant signature of dysregulated lipid metabolism in the acute phase after stroke, we collected additional plasma samples from aged (20- to 23- month-old) male mice 24 h after stroke and from naïve mice. These samples were sent to Metabolon, Inc. for global untargeted metabolomic analysis using the Global Discovery Panel, which provides an assessment of more than 5,400 metabolites across 70 metabolic pathways, including amino acid metabolism, energy metabolism, and lipid metabolism. The resultant volcano plot illustrates the distribution of 73 increased and 59 decreased metabolites (Fig.4A). To further assess these alterations in an unbiased manner, we constructed a hierarchical clustering heatmap depicting the top 30 metabolites ranked by t-test. Consistent with the volcano plot, the heatmap illustrates an elevation in metabolites involved in lipid metabolism, including 3-hydroxyadipate, 12-HETE, and stearoylcarnitine (C18), and a reduction in metabolites involved in amino acid metabolism, including N6- methyllysine, indolepropionate, and glycine, 24 h after stroke (Fig.4B). These alterations were confirmed in analyses of individual metabolites, including 3-hydroxyadipate, 12-HETE, stearoylcarnitine (C18), indolepropionate, and glycine (Fig.4C-D). Based on the signature of brain lipid catabolism in the plasma lipidome 24 h after stroke, we hypothesized that metabolites involved in lipid metabolism, such as fatty acids, acyl carnitines, and eicosanoids, would be elevated in the plasma 24 h after stroke. Accordingly, the elevation of 3-hydroxyadipate, a dicarboxylic acid, and 2-aminooctanoate, an α-amino fatty acid, signifies fatty acid mobilization in the plasma. In addition, we observed an increase in fatty acid metabolism, indicated by the elevation of eicosenoylcarnitine (C20:1), a monounsaturated acyl carnitine, and stearoylcarnitine (C18), a long chain saturated acyl carnitine. Notably, nearly all quantified acyl carnitines were elevated in the plasma 24 h after stroke (Table 2). Example 6. This example describes the temporal profile of the plasma metabolome after stroke in aged mice. To assess whether the acute signature of dysregulated lipid metabolism was sustained in the weeks after stroke, we collected additional plasma samples at 1 wk, 2 wk, 3 wk, 4 wk, 5 wk, 6 wk, and 7 wk after stroke in aged (20- to 23-month-old) male mice. These samples were also sent to Metabolon, Inc. for global untargeted metabolomic analysis using the Global Discovery Panel. To visualize the temporal profiles of the top 30 metabolites altered Attorney Docket No. UAZ-43247.601 24 h after stroke, we expanded the hierarchical clustering heatmap in Fig.4B to include the subacute and chronic phases after stroke. The resultant heatmap demonstrates that the acute alterations in the plasma metabolome 24 h after stroke are transient; within 1 wk after stroke, most plasma metabolites have reverted to baseline levels, with some exceptions (Fig.5A). Interestingly, we determined that 12-HETE, an eicosanoid derived from arachidonic acid, exhibited a biphasic temporal profile, with acute elevation at 24 h and chronic elevation at 3 wk and 5 wk after stroke; contrastingly, eicosenoylcarnitine (C20:1), a monounsaturated acyl carnitine involved in fatty acid metabolism, exhibited a monophasic temporal profile, with transient elevation occurring 24 h after stroke (Fig.5B). To evaluate amino acid metabolism in the plasma after stroke, we performed individual analyses of isobutyrylcarnitine (C4) and N6-methyllysine. Isobutyrylcarnitine (C4), an acyl carnitine intermediate generated following the breakdown of valine, a branched- chain amino acid (BCAA), was abundantly elevated in the plasma 24 h after stroke and remained elevated until 2 wk. Surprisingly, N6-methyllysine, a methylated form of lysine, an amino acid, was reduced in the plasma 24 h after stroke but was elevated at 1 wk. By 2 wk after stroke, N6-methyllysine had returned to baseline levels (Fig.5C). These results indicate that amino acid metabolism is altered in the acute and subacute phases after stroke, exhibiting a monophasic paradigm that differs considerably from the biphasic paradigm exhibited by metabolites involved in lipid metabolism. Example 7. This example describes the temporal profile of the plasma metabolome in the subacute and chronic phases after stroke in aged mice. To further assess the subacute and chronic plasma metabolomes in an unbiased manner, we constructed a hierarchical clustering heatmap depicting the top 30 metabolites ranked by ANOVA and included plasma samples from aged (20- to 23-month-old) male mice at 1 wk, 2 wk, 3 wk, 4 wk, 5 wk, 6 wk, and 7 wk after stroke and from naïve mice. With the exclusion of plasma samples collected 24 h after stroke, we were able to determine which metabolites were elevated or reduced specifically in the subacute and chronic phases without bias of transient acute alterations. The resultant heatmap illustrates dynamic alterations in metabolites involved in lipid metabolism, including phosphoethanolamine, 12-HETE, 12- HHTrE, 14-hydroxydocosahexaenoic acid / 17-hydroxydocosahexaenoic acid (14-HDoHE / 17- HDoHE), and sphinganine, and nucleotide metabolism, including ADP and AMP. Notably, isobutyrylcarnitine (C4), 12-HETE, and N6-methyllysine were conserved in hierarchical Attorney Docket No. UAZ-43247.601 clustering heatmaps of metabolites altered in the acute, subacute, and chronic phases after stroke (Fig.6A). These metabolites represent novel plasma biomarkers for stroke recovery in aged mice. In analyses of individual metabolites, we determined that phosphoethanolamine, a phospholipid derivative involved in cellular membrane structure, exhibited a biphasic temporal profile akin to that of 12-HETE, with subacute elevation at 1 wk and chronic elevation at 3 wk and 5 wk after stroke.14-HDoHE / 17-HDoHE, a docosanoid derived from the autooxidation of DHA, and sphinganine, a fundamental component of sphingolipids, were also elevated in the plasma at 3 wk and 5 wk after stroke (Fig.6B). These results provide evidence that lipid metabolism is perturbed in both the acute and chronic phases after stroke, exhibiting a biphasic paradigm. To determine whether nucleotide metabolism followed a synonymous pattern, we performed an individual analysis of ADP. We determined that ADP exhibited prolonged elevation in the plasma at 3 wk, 4 wk, 5 wk, and 6 wk after stroke (Fig.6C). Example 8. This example provides a discussion related to Examples 1-7. NfL is a structural scaffolding protein expressed abundantly and exclusively in neurons. Upon neuroaxonal injury, NfL is released into the cerebrospinal fluid (CSF) and peripheral blood, underscoring its value in neurological disorders such as ischemic stroke, Alzheimer’s disease (AD), and multiple sclerosis (9,10). Using a Simoa® NfL assay, we confirmed that NfL was significantly elevated in the plasma of aged male mice at 24 h, 1 wk, 2 wk, 3 wk, 4 wk, 6 wk, and 7 wk after stroke compared to naïve controls. Correspondingly, we also observed a positive correlation between plasma NfL levels and infarct volumes 24 h after stroke. Khalil et al. hypothesize that the prolonged release of NfL after acute neuronal injury could be attributed to persistent blood-brain barrier (BBB) breakdown or chronic immunological or inflammatory processes (10). To further assess chronic sequalae, we performed Spearman correlation analyses on infarct volumes 24 h after stroke compared to lateral ventricle and hippocampus volumes 7 wk after stroke. We observed a positive correlation between infarct volumes 24 h after stroke and lateral ventricle volumes 7 wk after stroke, which indicates that NfL not only reflects acute neuroaxonal damage but also predicts long-term structural alterations within the brain. Importantly, lateral ventricle enlargement was associated with cognitive impairment in nondemented elderly persons (11). This dual predictive capability of NfL enhances its potential as a comprehensive tool for assessing stroke progression and evaluating therapeutic interventions. Attorney Docket No. UAZ-43247.601 Early after stroke onset in patients, there are marked alterations in circulating lipids (12–15); however, these clinical studies are limited by conventional lipid profiling (i.e., targeted analyses of HDL-C, LDL-C, total cholesterol, and triglycerides, also known as triacylglycerols). We hypothesized that the plasma lipidome 24 h after stroke also consists of an abundance of lipids derived from the breakdown of myelin and other cell membranes. These lipids, originating from plasma membranes of glial cells and neurons or myelin sheaths surrounding axons, enter the circulation via the damaged BBB. Accordingly, we have demonstrated that chronic stroke infarcts amass CE, SM, and sulfatides in young adult and aged mouse models (16). Using targeted lipidomic analysis, we discovered an acute signature of brain lipid catabolism in the plasma of aged male mice 24 h after stroke, reflected by the elevation of SM and HCER lipid species. These complex sphingolipids are primarily present in two locations within the brain: (i) lipid rafts in neurons, astrocytes, and microglia and (ii) myelin sheaths surrounding axons (17). Therefore, the accumulation of these sphingolipids in the plasma 24 h after stroke signifies neuronal cell death (18). Importantly, SM and HCER have been implicated in neurodegenerative diseases, including AD, Parkinson’s disease (PD), and Lewy body dementia (LBD); HCER lipid species are abnormally elevated in the plasma of PD patients with cognitive impairment (19–21). Interestingly, Iqbal et al. discovered that ABCA1 determines HCER and SM levels in human and mouse plasma (22). We also observed a substantial reduction in plasma TAG lipid species 24 h after stroke. Interestingly, Jain et al. addressed the triglyceride paradox in stroke survivors and concluded that low triglyceride levels in serum collected within 24 h of admission were associated with increased stroke severity, reduced functional outcome at discharge, and increased 3-month mortality. It is presumed that low triglyceride levels reflect poor nutritional status, which leads to adverse outcomes after stroke (23,24). Therefore, it is plausible that the reduction in plasma TAG lipid species 24 h after stroke reflects a transitory period of inadequate food and water intake previously identified in mice subjected to intraluminal filament MCA occlusion (25). Using targeted lipidomic analysis on plasma collected temporally after stroke, we determined that the acute alterations in the plasma lipidome were transient; SM, HCER, and TAG lipid species returned to baseline levels within 1 wk. These results indicate that there is a distinct signature of brain lipid catabolism in the acute phase after stroke. Although neuroaxonal injury persists in the weeks after stroke, we hypothesize that partial restoration of the BBB and phagocytic uptake of lipid debris by resident microglia and infiltrating macrophages lead to a reduction in brain lipid species detectable in the plasma. More Attorney Docket No. UAZ-43247.601 sensitive detection methods may reveal prolonged elevation akin to the sustained elevation of plasma NfL observed with the Simoa® method. To date, ischemic stroke pathogenesis has been associated with disturbances in various biological processes, including energy failure, excitatory amino acid toxicity, oxidative stress, apoptosis, and inflammation (26,27). These processes involve a multitude of metabolites, the qualitative and quantitative expression of which constitutes the central focus of metabolomic analyses. Using global untargeted metabolomic analysis, we discovered acute alterations in lipid metabolism and amino acid metabolism 24 h after stroke. Specifically, we detected increases in acyl carnitines, such as eicosenoylcarnitine (C20:1) and stearoylcarnitine (C18). Acyl carnitines facilitate the transportation of fatty acids for mitochondrial fatty acid β-oxidation. We have previously shown that increased fatty acid metabolism occurs in the brain in response to degenerating myelin (28). Therefore, the accumulation of acyl carnitines in the plasma 24 h after stroke may signify the metabolism of myelin debris. These results are in accordance with several studies demonstrating elevated levels of acyl carnitines in the blood of ischemic stroke patients (29). Using global untargeted metabolomic analysis on plasma collected temporally after stroke, we determined that alterations in amino acid metabolism were apparent 24 h and 1 wk after stroke but returned to baseline levels by 2 wk. We also detected alterations in lipid metabolism in the acute and chronic phases after stroke. These results are in accordance with our previous studies that revealed a biphasic cytokine response to ischemia in the mouse brain, with the second phase initiated between 4 and 8 wk after stroke. In these studies, we also discovered that the second phase of inflammation coincided with an accumulation of foamy macrophages, T lymphocytes, and intracellular and extracellular cholesterol crystals in the stroke infarct (30). To reduce bias of drastic acute disturbances in the plasma metabolome, we performed a subsequent analysis on plasma collected temporally after stroke but excluded samples collected at 24 h. We discovered chronic alterations in lipid metabolism and nucleotide metabolism that emerged 3 wk after stroke. Specifically, sphinganine, a precursor in the biosynthesis of complex sphingolipids, was elevated in the plasma 3 and 5 wk after stroke; sphinganine has been previously identified as a diagnostic biomarker for ischemic stroke (2). We also observed a prolonged alteration in nucleotide metabolism; specifically, ADP was elevated in the plasma 3 wk, 4 wk, 5 wk, and 6 wk after stroke. The sustained presence of ADP in the plasma after stroke may reflect various underlying processes associated with the response to ischemic injury. ADP, generated via hydrolysis of extracellular ATP released Attorney Docket No. UAZ-43247.601 following cell damage, induces interleukin-1β release from microglia and macrophages and mediates inflammation in the CNS after injury, infection, and ischemia (31). Additionally, ADP, released from activated platelets at sites of vascular injury, contributes to the repair of damaged blood vessels and tissues (32,33). In these global untargeted metabolomic analyses on plasma collected temporally after stroke, we identified a novel plasma biomarker significantly altered throughout stroke recovery: 12-HETE. Arachidonic acid, released from cellular membranes upon encounter of inflammatory stimuli, serves as the precursor for 12-HETE synthesis. The enzymatic conversion of arachidonic acid by 12-lipoxygenase (12-LOX), occurring predominantly in leukocytes, platelets, and vascular endothelial cells, results in the formation of 12-HETE.12- HETE, a bioactive lipid mediator, acts as a signaling molecule in various physiological and pathological processes, such as angiogenesis, efferocytosis, and platelet activation, and plays a pivotal role in the inflammatory cascade by promoting leukocyte chemotaxis and adhesion to endothelial cells. Additionally, 12-HETE contributes to the synthesis of pro-inflammatory cytokines, exacerbating the inflammatory response (Fig.7). Correspondingly, Yoon et al. reported that 12-HETE was elevated in the plasma of young adult (10- to 12-week-old) male mice at 1 month and 6 months after transient MCA occlusion. We propose that 12-HETE, in addition to other bioactive eicosanoids derived from the arachidonic acid cascade (i.e., prostaglandins (PG), such as PGI2, PGE2, PGD2, and PGF2α, thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE), such as 5-HETE, 8-HETE, 15-HETE, and 20-HETE, leukotrienes (LT), and epoxyeicosatrienoic acids (EET), such as 5,6-EET, 8,9-EET, 11,12- EET, and 14,15-EET), could function as plasma biomarkers of inflammation after stroke. In conclusion, we have validated that NfL is elevated in the plasma of aged (20- to 23-month-old) male mice for at least 7 wk after stroke. We have also discovered an acute signature of brain lipid catabolism in the plasma 24 h after stroke. These lipids, including SM and HCER lipid species, could function as putative plasma biomarkers of neurodegeneration. In addition, we identified 12-HETE, a bioactive lipid mediator produced through the enzymatic oxidation of arachidonic acid by 12-LOX, as a putative plasma biomarker of inflammation. To our knowledge, extensive longitudinal lipid and metabolite profiling has not been previously reported or investigated in the context of stroke. These results offer valuable insights into the metabolic alterations that occur in the plasma after stroke and underscore the utility of myelin degradation products as biomarkers of neurodegeneration and arachidonic acid derivatives as biomarkers of inflammation. Attorney Docket No. UAZ-43247.601 Having now fully described the invention, it will be understood by those of skill in the art that the same can be performed within a wide and equivalent range of conditions, formulations, and other parameters without affecting the scope of the invention or any embodiment thereof. All patents, patent applications and publications cited herein are fully incorporated by reference herein in their entirety. EQUIVALENTS The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting the invention described herein. Scope of the invention is thus indicated by the appended claims rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are intended to be embraced therein. INCORPORATION BY REFERENCE The entire disclosure of each of the patent documents and scientific articles referred to herein is incorporated by reference for all purposes. Complete citations for the references cited within the application are provided within the following reference list. Indeed, each of the following references are herein incorporated by reference in their entireties: 1. Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, et al. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation [Internet].2024 Feb 20 [cited 2024 Apr 10];149(8):E347–913. Available from: https: / / www.ahajournals.org / doi / abs / 10.1161 / CIR.0000000000001209 2. Chumachenko MS, Waseem T V., Fedorovich S V. Metabolomics and metabolites in ischemic stroke. Rev Neurosci [Internet].2022 Feb 1 [cited 2024 Apr 10];33(2):181–205. Available from: https: / / www.degruyter.com / document / doi / 10.1515 / revneuro-2021-0048 / html 3. Doyle KP, Fathali N, Siddiqui MR, Buckwalter MS. Distal hypoxic stroke: A new mouse model of stroke with high throughput, low variability and a quantifiable functional deficit. J Neurosci Methods [Internet].2012;207(1):31–40. 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Claims

Attorney Docket No. UAZ-43247.601 CLAIMS What Is Claimed Is:

1. A method of measuring or detecting at least one biomarker, the method comprising: obtaining a sample from a subject suffering from or suspected of suffering from a neurological event; and measuring or detecting at least one stroke-related neurodegeneration biomarkers selected from one or more myelin-breakdown products, wherein the one or more myelin- breakdown products are selected from sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides, or any combinations thereof in the sample.

2. The method according to claim 1, wherein the measurement or detection of the at least one stroke-related neurodegeneration biomarkers indicates that the subject has sustained a stroke.

3. The method according to claim 1, wherein the measurement or detection of the at least one stroke-related neurodegeneration biomarkers indicates that the subject has sustained stroke-related neurodegeneration.

4. The method of claims 2 or 3, further comprising treating the subject with either tPA or 2-hydroxypropyl-^-cyclodextrin (HP^CD) if the subject is indicated as having sustained a stroke or stroke-related neurodegeneration.

5. The method of claim 1, wherein the sample is a plasma sample.

6. The method of claim 1, wherein the subject is a human subject.

7. The method of claim 1, wherein the subject is a human subject suffering from or at risk of suffering from a stroke and / or stroke-related neurodegeneration.Attorney Docket No. UAZ-43247.601 8. The method of claim 1, wherein the neurological event is a stroke and / or stroke- related neurodegeneration.

9. A method of measuring or detecting at least one biomarker, the method comprising: obtaining a sample from a subject suffering from or suspected of suffering from a neurological event; and measuring or detecting at least one stroke-related inflammation biomarkers selected from one or more eicosanoids derived from an arachidonic acid cascade, wherein the one or more eicosanoids derived from an arachidonic acid cascade are selected from prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15-HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)), or any combinations thereof in the sample.

10. The method according to claim 9, wherein the measurement or detection of the at least one stroke-related inflammation biomarkers indicates that the subject has sustained a stroke.

11. The method according to claim 9, wherein the measurement or detection of the at least one stroke-related inflammation biomarkers indicates that the subject has sustained stroke-related inflammation.

12. The method of claims 10 or 11, further comprising treating the subject with either tPA or 2-hydroxypropyl-^-cyclodextrin (HP^CD) if the subject is indicated as having sustained a stroke or stroke-related inflammation.

13. The method of claim 9, wherein the sample is a plasma sample.

14. The method of claim 9, wherein the subject is a human subject.

15. The method of claim 9, wherein the subject is a human subject suffering from or at risk of suffering from a stroke and / or stroke-related inflammation.Attorney Docket No. UAZ-43247.601 16. The method of claim 9, wherein the neurological event is a stroke and / or stroke- related inflammation.

17. A biomarker panel for determining stroke-related neurodegeneration status of a subject, the panel comprising at least one stroke-related neurodegeneration biomarker selected from one or more myelin-breakdown products, wherein the one or more myelin- breakdown products are selected from sphingomyelins, hexosyl ceramides, dihydroceramides, and ceramides, or any combinations thereof; wherein measurement or detection of the at least one stroke-related neurodegeneration biomarker indicates that the subject has sustained stroke-related neurodegeneration.

18. The biomarker panel according to claim 17, wherein levels of the stroke-related neurodegeneration biomarker are higher compared to levels of stroke-related neurodegeneration biomarkers in a sample obtained from a healthy subject.

19. A biomarker panel for determining stroke-related neurodegeneration status of a subject, the panel comprising at least one stroke-related inflammation biomarker selected from one or more eicosanoids derived from an arachidonic acid cascade, wherein the one or more eicosanides derived from an arachidonic acid cascade are selected from prostaglandins (e.g., PGI2, PGE2 PGF2a), thromboxane A2 (TXA2), hydroxyeicosatetraenoic acids (HETE) (e.g., 5-HETE, 15-HETE, 12-HETE, 20-HETE), leukotrienes (LT), and epoxyeicosatrienoic acids (EET) (e.g., 5,6-EET, 8,9-EET, 11,12-EET, and 14,15-EET)), or any combinations thereof; wherein measurement or detection of the at least one stroke-related inflammation biomarker indicates that the subject has sustained stroke-related inflammation.

20. The biomarker panel according to claim 19, wherein levels of the stroke-related inflammation biomarker are higher compared to levels of stroke-related inflammation biomarkers in a sample obtained from a healthy subject.

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