42 results about "Metabolic biomarkers" patented technology

Beta-hydroxybutyrate mineral salts in combination with medium chain fatty acids or an ester thereof such as medium chain triglycerides were used to induce ketosis, achieving blood ketone levels of (2-7 mmol / L), with or without dietary restriction. The combination results in substantial improvements in metabolic biomarkers related to insulin resistance, diabetes, weight loss, and physical performance in a short period of time. Further, use of these supplements to achieve ketosis yields a significant elevation of blood ketones and reduction of blood glucose levels. Use of these substances does not adversely affect lipid profiles. By initiating rapid ketosis and accelerating the rate of ketoadaptation, this invention is useful for the avoidance of glucose withdrawal symptoms commonly experienced by individuals initiating a ketogenic diet, and minimizes the loss of lean body mass during dietary restriction.

Beta-hydroxybutyrate mineral salts in combination with medium chain fatty acids or an ester thereof such as medium chain triglycerides were used to induce ketosis, achieving blood ketone levels of (2-7 mmol / L), with or without dietary restriction. The combination results in substantial improvements in metabolic biomarkers related to insulin resistance, diabetes, weight loss, and physical performance in a short period of time. Further, use of these supplements to achieve ketosis yields a significant elevation of blood ketones and reduction of blood glucose levels. Use of these substances does not adversely affect lipid profiles. By initiating rapid ketosis and accelerating the rate of ketoadaptation, this invention is useful for the avoidance of glucose withdrawal symptoms commonly experienced by individuals initiating a ketogenic diet, and minimizes the loss of lean body mass during dietary restriction.

Panels of serum metabolic biomarkers and methods of their use in detecting and diagnosing cancer, especially ovarian cancer, are disclosed. The metabolic biomarker panels include 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 50, 75, 100, 150, or more metabolites. Supervised classification methods, such as trained support vector machines (SVMs) are used to determine whether the levels of metabolic biomarkers in a subject are indicative of the presence of cancer. The disclosed biomarkers and methods preferably allow a diagnosis of cancer with an accuracy, a specificity, and / or a sensitivity of at least 80%, 85%, 90%, 95%, 96%, 97%, 98% or 99%.

The present invention relates to a metabolic biomarker set for assessing kidney disease comprising at least two amino acids, at least two acylcarnitines and at least two biogenic amines. Moreover, the present invention relates to a method for assessing kidney disease in a mammalian subject which comprises obtaining a biological sample, preferably blood and / or urine, from the subject and measuring in the biological sample the amount of at least two amino acids, of at least two acylcarnitines and of at least two biogenic amines, as well as to a kit adapted to carry out the method. By employing the specific biomarkers and the method according to the present invention it becomes possible to more properly and reliably assess kidney disease.

The present invention provides a novel oral cancer and periodontal disease salivary metabolome for use in the diagnosis or for providing a prognosis for oral cancer and periodontal disease in an individual. The present invention also provides novel methods of diagnosing or providing a prognosis for oral cancer or periodontal disease by detecting metabolites found in the saliva of an individual. Finally, the present invention provides kits for the detection of salivary metabolites useful in the diagnosis or prognosis of oral cancer and periodontal disease in an individual.

The present disclosure relates to a panel of a plurality of metabolite species that is useful for the identification or detection of subjects having pancreatic cancer, including methods for identifying such metabolic biomarkers within biological samples. The disclosure also includes a statistical model for predicting the presence of pancreatic cancer in a subject's biofluid by quantifying and comparing positive and negative fold changes in metabolite species' concentration; comparing the subject's metabolite species' concentrations to a predetermined value.

The present invention relates to a metabolic biomarker set for use in assessing breast cancer in a mammalian subject. In particular, the invention relates to a metabolic biomarker set for screening and / or diagnosing breast cancer, the metabolic biomarker set comprising at least (a) one amino acid selected from glutamine, glutamate and serine, and one lipid, or (b) glutamine and glutamate. Further, the invention relates to a metabolic biomarker set for prediction of therapeutic response to breast cancer neoadjuvant chemotherapy. Further, the invention relates to a metabolic biomarker set for assessing biochemical reflection of breast cancer tumor activity. Further, the invention relates to a metabolic biomarker set for subclassification between intrinsic breast cancer tumor subtypes. Moreover, the present invention relates to a method for assessing breast cancer, which comprises obtaining a biological sample, preferably blood, from a mammalian subject and measuring in the biological sample the amount and / or ratios of metabolites. By employing the specific biomarkers and the method according to the present invention it becomes possible to more properly and reliably assess breast cancer.

The invention relates to novel application of small molecule metabolites, namely hypoxanthine, 2-ketoisocaproic acid, glutamic acid and aspartic acid, in a serum sample as combined markers in preparation of a kit for distinguishing patients with esophageal squamous carcinoma and esophageal epithelial atypical hyperplasia in subjects. The invention further relates to a kit for detecting patients with esophageal squamous cell carcinoma in subjects. The relative concentration of the combined markers in serum samples from the subjects is detected, the variables P of the combined marker are calculated based on a linear regression equation, and whether the subjects suffer from esophageal squamous cell carcinoma or not is judged based on a determined threshold value. The kit can realize high-sensitivity and high-efficiency detection of several metabolites involved in the invention, and has the advantages of low detection cost and good repeatability. The kit can be applied to clinical auxiliary diagnosis of the esophageal squamous cell carcinoma, has the advantages of high diagnosis sensitivity and capability of effectively distinguishing the esophageal squamous cell carcinoma from precancerous lesions, and has a relatively good application prospect.

The invention belongs to the technical field of functional analysis methods of disease metabolism biomarkers, and provides a biomarker metabolic pathway and an analysis method. The metabolic biomarker is stearic acid, phytosphingosine, glycine, glutamine and phospholipids; an acting target spot of the metabolic biomarker is a target protein related to a depression nervous system, immune response and endocrine; and the metabolic pathway is a PI3K-Akt signaling pathway, an mTOR signaling pathway, an MAPK signaling pathway, an erbB signaling pathway, a neurenergen signaling pathway, an Rap1 signaling pathway and an Ras signaling pathway. A functional network analysis method suitable for depression characteristics is established, and the clinical application of these biomarkers helps to optimize the diagnosis of depression, and can provide some valuable clues for the subsequent depression network function researches.

A novel method of diagnosing cystic fibrosis in a human subject is provided. The method includes the steps of: i) determining in a biological sample from the subject the level of one or more metabolic biomarkers; ii) comparing the level of the biomarker to a control level and determining the difference between the biomarker level and the control level; and iii) determining that the subject has cystic fibrosis or a related disorder when the difference in the level of the biomarker in the sample is statistically different from the control level.

This application discloses a method of differentiating stable angina pectoris from acute coronary syndrome, including: obtaining a blood plasma sample from a patient; measuring a relative concentration of at least one metabolic biomarker in the blood plasma sample, wherein the at least one metabolic biomarker is selected from the group consisting of malic acid, taurine, arachidonic acid, citramalic acid, methionine, and pentadecanoic acid; calculating a value according to the relative concentration of at least one metabolic biomarker; comparing the value with a predefined critical value, if the value is more than the predefined critical value, the patient has the acute coronary syndrome, otherwise, the patient has the stable angina pectoris. The method and a diagnostic kit thereof is capable of differential diagnosis of SA and ACS and it can improve the diagnostic convenience and promote the diagnostic standardization.

Disclosed is a method for detection of 24S-hydroxycholesterol in hair. More specifically, a trace amount of hair is hydrolyzed under basic condition and metabolites including 24S-hydroxycholesterol are purified and extracted by solid-phase extraction (SPE). Then, after derivatization of the resulting extract with trimethylsilyl (TMS), 24S-hydroxycholesterol is detected by gas chromatography-mass spectrometry (GC-MS).

The present invention relates to methods of determining if a subject has an increased risk of suffering from memory impairment. The methods comprise analyzing at least one plasma sample from the subject to determine a value of the subject's metabolite profile and comparing the value of the subject's metabolite profile with the value of a normal metabolite profile. A change in the value of the subject's metabolite profile, over normal values is indicative that the subject has an increased risk of suffering from memory impairment compared to a normal individual.

A panel of metabolic biomarkers for differential diagnosis of stable angina pectoris and acute coronary syndrome is published herein. The panel comprises one or more of the metabolic biomarkers, including malic acid, taurine, arachidonic acid, citramalic acid, methionine, pentadecanoic acid. Single use of the 6 differential metabolites provided clinically diagnostic value of SA vs. ACS with AUC>0.7. When combined, the more metabolites, the larger of AUC. The highest AUC of 0.987 was obtained when all of the six metabolites were combined to distinguish SA vs. ACS with sensitivity 96.8% and specificity 97.7% using optimal cut-off value. The metabolic biomarkers provided by the invention can be used for differential diagnosis of SA vs. ACS of high accuracy, sensitivity and specificity.

The invention discloses a method for identifying metabolic markers based on heart Yang deficiency syndrome of coronary heart diseases. The method solves the problem that the existing clinical diagnosis method of heart Yang deficiency syndrome of coronary heart diseases has poor sensitivity so that the relationship between ingredients in the formula and curative effects is difficult to recover. Themethod comprises 1, carrying out UPLC analysis on n healthy subjects and n patient subjects suffering from heart Yang deficiency syndrome of coronary heart diseases through a UPLC-G2-Si-HDMS method to determine endogenous metabolites in serum samples, 2, carrying out full scanning on the endogenous metabolites in a positive and negative ion mode through a G2-Si-HDMS method to determine endogenousmetabolite structures and 3, identifying blood metabolic biomarkers of subjects suffering from heart Yang deficiency syndrome of coronary heart diseases. The method is used in the field of metabolicmarker identification.

Embodiments of the disclosure include methods and compositions for treatment of prostate cancer, including metastatic prostate cancer or prostate cancer at risk for developing into metastatic prostate cancer, by providing an effective therapy to an individual that has been determined to have elevated levels of SRC-2 (also known as NCOA2, GRIP1 TIF2). In particular cases, sample from an individual known to have prostate cancer is assayed for the risk for developing metastatic prostate cancer and the individual is provided an effective therapy upon determination of elevated levels of SRC-2.

The invention, which belongs to the technical field of gene engineering, provides a metabolic biomarker in a metabolic biomarker in a senescence process of sepiella maindroni. The metabolic biomarkercomprises uric acid. The screening method of the metabolic biomarker includes the following steps: collecting serum samples of individuals at different reproductive stages; preprocessing the serum samples; carrying out liquid chromatography-mass spectrometry analysis on the serum samples successively; screening LC-MS data processing to obtain metabolic biomarkers; carrying out comparison and identification on the metabolic biomarkers; and constructing a metabolic pathway of the biomarkers and carrying out analysis. According to the invention, micro metabonomics analysis is carried out on the serum of sepiella maindroni at different reproductive stages by using the high performance liquid chromatography-tandem mass spectrometry technology and screening is carried out; the content of uric acid is greatly reduced after spawning by being compared with the content before spawning. The following formulas are used: the content before spawning / the content after spawning=2.16; VIP=1.5385. The provided metabolic biomarker is a potential metabolic biomarker.

A metabolic biomarker set for use in assessing, screening, and / or diagnosing breast cancer in a mammalian subject includes at least (a) one amino acid selected from glutamine, glutamate and serine, and one lipid, or (b) glutamine and glutamate. Described further, is a metabolic biomarker set for prediction of therapeutic response to breast cancer neoadjuvant chemotherapy; a metabolic biomarker set for assessing biochemical reflection of breast cancer tumor activity; and a metabolic biomarker set for subclassification between intrinsic breast cancer tumor subtypes. Moreover, a method for assessing breast cancer is described, which includes obtaining a biological sample, preferably blood, from a mammalian subject and measuring in the biological sample the amount and / or ratios of metabolites. By employing the specific biomarkers and the method it becomes possible to more properly and reliably assess breast cancer.

The present invention relates to new biomarkers for assessing ovarian cancer being more sensitive, particularly at early stage of disease. Moreover, the present invention relates to a method for assessing ovarian cancer from a patient to be examined, and to a kit for carrying out the method.

The invention discloses the use of a metabolic biomarker in acute pancreatitis. The invention is characterized by collecting normal acute pancreatitis and samples of drug therapy of the acute pancreatitis, performing metabolomics analysis, and discovering the metabolites which exhibit significant differences in different treatment groups, thereby using the metabolites to predict acute pancreatitis, and further achieving individualized treatment of patients.

The present invention relates to biomarkers associated with the clinical response to an FGF-18 compound before or during treatment of a cartilage disorder. The present invention more particularly relates to specific proteins present in the blood, serum, synovial fluid or in the urine, which can be used for the diagnosis and treatment of cartilage disorders. The invention further discloses specific proteins that are related to cartilage response to an FGF-18 compound treatment as well as diagnostic tools and kits based on their expression profile. Thus, the invention can be used in predicting the response to an FGF-18 compound treatment, before starting the treatment with FGF-18 or during the treatment. It could be used for selecting / identifying subjects to be treated by intra-articular administration of an FGF-18 compound. The use of these biomarkers in diagnostics could result in increased benefit and reduced risk in subjects.

The invention relates to a suicide tendency and suicide behavior prediction method and system based on metabonomics data. The method comprises the following steps: S1, collecting metabolite data in blood of a to-be-detected user or data of a final metabolic biomarker of the to-be-detected user; the metabolite data comprises data of a plurality of metabolite categories; the data of the metabolite large class comprises data of various metabolites; the data of the final biomarker is data of preset metabolites; s2, recognizing the metabolite data of the to-be-detected user or the data of the final metabolic biomarker by adopting the final neural network classifier model, and determining a corresponding recognition result; the final neural network classifier model is a classifier model obtained after a preset initial neural network classifier model is trained by a preset metabolite data training sample.

Provided herein, inter alia, are methods for measuring and assessing intestinal health in poultry. The disclosed metabolic biomarkers and associated methods for identifying and quantifying the same are reliable, rapid and, in some embodiments, non-invasive, and can be used to provide information with respect to the gut health of poultry, such as chickens.

The invention discloses a construction method of an autoimmune disease model based on serum metabolism fingerprints, and relates to the technical field of matrix-assisted laser desorption ionization mass spectrometry, biological sample metabolism molecule analysis and machine learning. Detecting and extracting serum metabolism fingerprints of the autoimmune diseases; constructing a model aiming at the autoimmune diseases by adopting a machine learning algorithm based on the serum metabolism fingerprint spectrum; and screening to obtain the metabolic biomarker. According to the method, the autoimmune disease model is successfully constructed based on the serum metabolism fingerprints by adopting a machine learning method. The defects of a nuclear magnetic resonance technology, a traditional mass spectrum technology (GC / LC-MS) and the like are effectively overcome through nano-assisted laser desorption ionization mass spectrometry (nano-assisted LDI MS), and rapid, high-throughput and high-sensitivity detection of the metabolic fingerprints of the serum low-molecular-weight segment of the autoimmune diseases is effectively achieved.

The present invention relates to metabolic biomarker sets for assessing HIV. In preferred embodiments, the present invention relates to the use of biomarker sets for screening and / or diagnosing HIV infection, for prediction of immunologic response of a mammalian subject to antiretroviral therapy and / or prognosis of HIV disease progression, and for monitoring of HIV disease activity in a mammalian subject. In other embodiments, the invention relates to methods for screening and / or diagnosing HIV infection, for prediction of immunologic response of a mammalian subject to antiretroviral therapy and / or prognosis of HIV disease progression, and for monitoring of HIV disease activity in a mammalian subject, as well as to a kit adapted to carry out the methods. By employing the specific biomarkers and the method according to the present invention it becomes possible to more properly and reliably assess HIV. In particular, it becomes possible to screen for and diagnose HIV in a patient with high accuracy and predict early in advance the patient's therapeutic response to antiretroviral therapy.