66 results about "Pathologic" patented technology

A system and method for analysis of a vessel automatically detects a pathology in a first image of the vessel and attaches a virtual mark to the pathology in the first image. The system may detect the same pathology in a second image of the vessel, based on the virtual mark, and may then provide analysis (e.g., determine an FFR value) of the pathology based on the pathology detected in the first and second images.

The present invention relates to compositions comprising a microbial consortium for treating or preventing medical disorders and pathologies through microbiome modulation, including medical disorders associated with a dysbiosis or a loss of gut microbial function.

The invention aims to provide a multi-modal cancer prognosis evaluation method based on a graph. The method comprises the following steps: S1, pre-processing multi-modal data, segmenting a pathological tissue part into patches, extracting patch features, and performing surrounding type composition on the patches according to cell migration continuity; the omics data is subjected to GSEA enrichment classification, wherein five cancer development processes are included; s2, single-modal features are obtained, and modal corresponding features are obtained by using a modal enhanced and shared graph mask auto-encoder; s3, cross-modal interaction is carried out, and multi-modal data distribution mapping alignment is realized by using a cross-modal alignment module; s4, performing multi-modal fusion, and fusing the cross-modal interaction feature and each single-modal feature by using a Hyperdge-Mixer module to obtain a modal fusion feature; and S5, risk prediction: inputting the final multi-modal representation into a risk prediction module, and finally obtaining a risk prediction result. The cancer prognosis is realized by effectively fusing pathology, genes and clinical data, an end-to-end prognosis analysis framework is realized by utilizing a deep learning technology, the method has good performance and relatively high interpretability, and the clinical application practicability is enhanced.

The invention provides a method and a system for evaluating various liver pathologies based on machine learning. The method comprises the following steps: acquiring weight information, clinical examination information and evaluation results of liver tissue samples of a plurality of historical patients; performing data preprocessing based on the acquired information, and constructing a training set and a test set; training a Logistic regression model and a Ridge regression model by using the training set, determining the performance of the model in predicting balloon sample deformation, fatty degeneration, lobular inflammation, significant fibrosis and NASH, and determining final prediction index parameters and a prediction model; and obtaining weight information, clinical examination information and an evaluation result of the liver tissue sample of the patient, extracting related values of prediction index parameters in the evaluation result, and processing the prediction index parameters by the determined trained prediction model aiming at the corresponding prediction index parameters to obtain a final prediction result. According to the method, the simple model is constructed by obtaining the clinical indexes, and all aspects of the liver pathology of the chronic liver disease can be comprehensively evaluated.

The invention belongs to the technical field of biological medicines, and provides application of an ILDR3 gene and / or protein in preparation of medicines and diagnostic products for preventing and / or treating Tau-related diseases. The ILDR3 provided by the invention is a key therapeutic target of Tau-related diseases, and can simultaneously intervene a plurality of core links of Tau pathology, including promotion of Tau protein degradation, inhibition of excessive phosphorylation and blocking of abnormal aggregation of Tau protein. Test data show that expression of the ILDR3 in Tau related diseases is reduced, Tau pathology and cognitive impairment are aggravated by knocking out the ILDR3, and learning and memory functions of a Tau pathology model are remarkably improved and nerve injury is relieved by over-expression of the ILDR3. Therefore, the ILDR3 gene and / or protein can be applied to preparation of drugs and diagnostic products for preventing and / or treating Tau-related diseases.

The exemplified methods and systems facilitate the configuration and training of a neural network (e.g., a deep neural network, a convolutional neural network (CNN), etc.), or ensemble(s) thereof, with a biophysical signal data set to ascertain estimate for the presence or non-presence of disease or pathology in a subject as well as to assess and / or classify disease or pathology, including for example in some cases the severity of such disease or pathology, in a subject. In the context of the heart, the methods and systems described herein facilitate the configuration and training of a neural network, or ensemble(s) thereof, with a cardiac signal data set to ascertain estimate for the presence or non-presence of coronary artery disease or coronary pathology.

Methods and compositions for the treatment of rhinosinusitis in a subject using topical verapamil.

A method for the diagnosis of diseases, in particular hematological malignancies or solid tumors, in a subject comprises the steps of isolating (21,61) an extracellular vesicle pellet (3a,3b) obtained from a sample (2) of a biological fluid previously taken from the subject; measuring (31,41,51-52), from said pellet, parameters representative of the six biomarkers (I) size, (II) total amount of the extracellular vesicles, (III) amount of the extra- cellular vesicles expressing on their own surface (III) a first antigen and (IV) a first and a second antigen, (V) mean fluorescence intensity for each of said antigens and (VI) nucleic acid content of the extracellular vesicles; performing a first comparison of the biomarker-representative parameters with respective cut-off values; assigning a partial score to each parameter or to the six biomarkers on the basis of the above first comparison step; calculating a final score, i.e. a subject score, as the sum of the partial scores; performing a second comparison of the final score with at least one predetermined diagnostic threshold value, preferably with two diagnostic upper and lower values; estimating the probability diagnosis of said pathology on the basis of the above second comparison step. The combination of the six biomarkers, in the context of personalized medicine, overcomes the prior art method limitations due to the high clinical heterogeneity between subjects, in terms of sensitivity, with reference to a given pathology, for one rather than the other biomarkers and their relative parameters selected from the six.

The disclosure features chemical entities (e.g., compounds, or pharma- ceutically acceptable salts, and / or hydrates, and / or cocrystals, and / or combinations with drugs) that inhibit (e.g., antagonize) Stimulator of Interferon Genes (STING). The chemical entities are useful, for example, to treat conditions, diseases, or disorders in which increased (e.g., excessive) STING activity (e.g., STING signaling) contributes to the pathology and / or symptoms and / or progression of the condition, disease, or disorder (e.g., cancer) in a subject (e.g., a human). The disclosure also features compositions comprising same, as well as methods of using and making same. TIFF2025504415000110.tif24170

The present invention provides a method and system for evaluating various liver pathologies based on machine learning, which obtains the weight information, clinical examination information, and evaluation results of liver tissue samples of multiple historical patients; based on the obtained information, performs data preprocessing to construct a training set and a test set; uses the training set to train Logistic regression and Ridge regression models to determine the performance of the models in predicting ballooning degeneration, steatosis, lobular inflammation, significant fibrosis, and NASH, and determines the final prediction index parameters and prediction models; obtains the weight information, clinical examination information, and evaluation results of liver tissue samples of a patient, extracts the numerical values related to the prediction index parameters therefrom, and processes them with the determined trained prediction models for the corresponding prediction index parameters to obtain the final prediction results. The present invention constructs a simple model by obtaining clinical indicators and can comprehensively evaluate all aspects of the liver pathology of chronic liver diseases.

Disclosed herein are embodiments of compositions, methods and kits that describe ancillary reagent constructs for simultaneous immunological and morphological investigation of pathology specimens. The kits include reagents, possibly organized in panels, which give the pathologist additional confidence in making a diagnosis based on the morphology of a cell. Reagents can be used or selected to identify specific antigens or a class of antigens. The reagents further comprise detection agents, which are visible under standard microscopy in the presence of standard stains. The reagents, used on their own or as part of a kit, make possible immunological analysis simultaneously with pathology performed in the presence of standard stains.

The invention relates to automatic pathology analysis by ultrasound imaging. Methods and systems for automatic classification, detection, assessment and / or diagnosis of pathologies in a subject determine the presence or absence and / or severity of various pathologies in the subject, such as the presence, absence and / or severity of aortic valve stenosis in the heart of the subject.

This is a monitoring approach that respects privacy (no routine biometric recognition) to continuously extract multimodal markers from individuals / patients. The system can use various modules, including cameras, microphones, connected objects, wearables, sensors, etc . . .. This allows for the early detection of ANY pathology whatsoever that can be detected in the continuous extraction of multimodal markers from individuals / patients and the rapid transmission of alerts to emergency medical services. The multimodal monitoring supported by AI algorithms will not only detect the QUALIFICATION of the onset of a pathology, but especially the QUANTIFICATION of this onset of pathology, and even more so to provide a KINETIC MEASURE OF THIS QUANTIFICATION over a significant period of time.ONLY in cases where a detected pathology requires urgent and absolute medical intervention, and if the precision levels of the methods employed have been validated by medical professionals, the approval of the protocol's performance by the medical authority can trigger the use of biometric recognition. The use of biometric recognition allows for access to the patient's medical history, which can strengthen the diagnosis to send an alarm AND / OR accelerate patient care by already having knowledge of their medical files upon arrival in the emergency room. THIS IS A CASE OF FORCE MAJEURE THAT REQUIRES URGENT TREATMENT, GOVERNED BY MEDICAL ETHICS, AND THEREFORE EXEMPT FROM ANY PRIOR AUTHORISATION.The use of biometric recognition may also be employed without prior approval from an authority ( MEDICAL OR OTHERWISE ), if and only if the state reliably detected by multimodal monitoring falls within the framework of the "OBLIGATION TO ASSIST A PERSON IN DANGER" according to the LAW, biometric recognition can then be used without prior authorization if it provides assistance in the diagnosis. Outside of the two cases mentioned above, "FORCE MAJEURE" AND / OR "OBLIGATION TO ASSIST A PERSON IN DANGER", the "Life Tracking Medicine", (LTM) which gives citizens the ability to create their own data heritage, allows for the CONSIDERATION OF THE PERSON’S PRIOR CONSENT at the time of the device's activation, ONLY IN CASE OF SUSPICION OF THE ARRIVAL / DETECTION OF ANY PATHLOGY, and without prior approval from an authority (MEDICAL OR OTHERWISE), for the use of biometric recognition.This case also includes persons who, being minors or lacking the capacity to make decisions, are represented by a Parent or legal guardian. In this context, the initial consent of the legal guardian will be taken into account, only in case of suspicion of the arrival / detection of any pathology.

Isoquinoline compounds for treating various diseases and pathologies are disclosed. More particularly, the present invention concerns the use of an isoquinoline compound or analogs thereof, in the treatment of disorders characterized by the activation of Wnt pathway signaling (e.g., cancer, abnormal cellular proliferation, angiogenesis, fibrotic disorders, bone or cartilage diseases, and osteoarthritis), the modulation of cellular events mediated by Wnt pathway signaling, as well as genetic diseases and neurological conditions / disorders / diseases due to mutations or dysregulation of the Wnt pathway and / or of one or more of Wnt signaling components. Also provided are methods for treating Wnt-related disease states.

Systems and methods for the improved quantitative assessment of airway mucus plug pathology are provided herein which provide a quantitative suite of mucus imaging metrics that objectively quantifies features of mucus plug pathology in the lungs. Systems and methods for generating a subject-level mucus plug map that illustrates the position of one or more whole mucus plugs, or the absence of mucus plugs in an airway tree are discussed. Systems and methods for the determination of a subject-level mucus plug phenotype are provided herein.

A non-invasive ophthalmic light-based detection device for detecting pathologies associated with Alzheimer's disease (AD) in the retina of an eye. The device uses two imaging modalities, one of which directs a specific area to be interrogated by the second imaging modality. A hyperspectral reflectance imaging unit detects light reflected and / or backscattered from the retina from a broadband light source, which is used to determine one or more regions of interest. A Raman spectroscopy unit detects light from a laser that is re-emitted by the retina through the phenomenon of Raman scattering, which is targeted to the region of interest determined based on the hyperspectral reflectance information. The detection information from the hyperspectral reflectance imaging unit and the Raman spectroscopy unit is used to determine the presence of the one or more pathologies associated with AD. The detection device allows identification of high-risk groups, diagnosis and tracking of patient response to treatment.

The present invention relates to methods for characterising the pathology or state of a vascular region of a subject by: providing medical imaging data gathered along a length of a blood vessel and: determining radial segments of the vessel extending from a point in the centre of the vessel to a distance extending beyond the outer wall of the vessel to the perivascular region; determining a value for the radiodensity and / or one or more radiomic features of the radial segment; and comparing each value determined to a pre-determined value or using the absolute value, in order to generate an output value that indicates the pathology or state of the vascular region, or the inflammation of a plaque. At least one method step is computer implemented. The invention also provides a computer program product configured to carry out these methods, and to a system comprising one or processors to configured to perform the methods.

As used herein, a compound of formula (II): TIFF2025503737001579.tif73165 or a stereoisomer or tautomer thereof, or a pharma- ceutically acceptable salt of any of the foregoing, 1 , R 2 , R 3 , L 1 , L 2 , L 3 , R 4 , X 1 , X 2 , X 3 , and X 4 (wherein R is as defined herein). Also provided are methods of preparing a compound of formula (II), or a stereoisomer or tautomer thereof, or a pharma- ceutically acceptable salt of any of the foregoing. Also provided are methods of inhibiting APOL1 and methods of treating an APOL1-mediated disease, disorder, or condition in an individual.

The present disclosure relates to a method of treating, preventing or delaying an age-related condition or pathology in a mammal using extracellular vesicles (EVs) derived from a young mammal.

The invention relates to negative functional modulators of at least one variant of the non-erythrogenic erythropoietin (V-EPO) and pharmaceutical compositions or kits containing them. Such functional negative modulators of V-EPO may be a mono- or multi-specific antibody anti-EV3, anti-EV4, anti-EV1-4, anti-EV1-5, anti-EV1-1, or EV2-1, or anti-Epo receptor (EpoR) anti-EPHB4, anti-CSF2RB, an antisense oligonucleotide, DNA decoy, RNA decoy, a ribozyme, an antagomiR, a shRNA, LNA or siRNA.Several uses of these functional modulators are described, which have been advantageously employed as a medicament and for the treatment of an oncological pathology, a proliferative pathology, chronic inflammatory diseases on an autoimmune and non-autoimmune basis, of neurodegenerative diseases, and in the treatment of patients undergoing organ or tissue transplantation.The invention also describes variants of EPO for use in the diagnosis and in the treatment of an oncological pathology, a proliferative pathology, chronic inflammatory diseases on an autoimmune and non-autoimmune basis, of neurodegenerative diseases, and in the treatment of patients undergoing an organ or tissue transplantation and as a diagnostic agent.According to another aspect, a monoclonal antibody to at least one of the variants of the erythropoietin is described.According to yet another aspect, the use of at least one alternative splicing variant of non-erythrogenic EPO and the measurement thereof at tissue and / or systemic level is described, as well as the study of the methylation status of the promoters of the genes involved in the EPO signalling pathway (by way of example EPO, EPOR, EPHB4, CSF2RB), as diagnostic, prognostic and predictive markers of an oncological pathology, a proliferative pathology, neurodegenerative or inflammatory pathology.

Described herein are EphA4 receptor antagonists, pharmaceutical compositions containing EphA4 antagonists, and methods and uses of treating an EphA4-based disease, disorder or pathology in an individual using EphA4 receptor antagonists.

A system is provided that includes a display and a processor in communication with the display. The processor is configured to receive an ultrasound video comprising a plurality of frames of an anatomical structure obtained by the ultrasound probe. The processor is further configured to generate at least one frame level metric for each frame detected to include a pathology based on the ultrasound video, and generate at least one video level metric related to the pathology based on the frame level metrics for the frames including the pathology. The processor is further configured to generate a video level classification of the pathology based on the video level metric related to the pathology and output it to the display.

A benzene sulfonamide compound of formula I or one of its addition salts with pharmaceutically acceptable acids, for use in a method of treating a pathology related to an excessive effect of TNF and for use in a method of treating the human or animal body.

The present invention pertains to a novel treatment of pathologies caused by an increased synthesis or accumulation of sulfolipids such as sulfatide. The invention provides mutated arylsulfatase A (ARSA or ASA, EC 3.1.6.8) enzymes with increased activity towards sulfatide metabolization. The invention provides nucleic acids encoding the mutant ARSA, the use of the proteins and nucleic acids, as well as pharmaceutical compositions comprising them, in the treatment of lysosomal storage disorders (LSDs) such as metachromatic leukodystrophy (MLD).

In some aspects, the described systems and methods provide for a method for training a deep learning model to assess liver pathology, including accessing annotated liver pathology images associated with a group of patients in one or more randomized controlled clinical trials of nonalcoholic steatohepatitis therapy, each of the annotated liver pathology images including at least one annotation describing one or more tissue characteristic categories for a portion of the image, and training the deep learning model based on the annotated liver pathology images to predict the tissue characteristic categories, selected from a group comprising steatosis, lobular inflammation, hepatocyte ballooning, and fibrosis stage.

Described herein are various embodiments of techniques for determining reference values / ranges for diagnostic markers for patients during treatment and recovery during and / or after illness or injury. Some methods may include obtaining a patient's medical information (including any diagnosed medical conditions) and calculating, based on the medical condition and an elapsed time since onset or start of treatment, expected reference ranges for one or more diagnostic markers. These methods may also include outputting an indication of whether the measurements for the diagnostic marker or markers fall outside the reference range(s). In some embodiments, the reference values can be adjusted depending on additional pathologies indicated in the patient's medical information. Some such patient- and / or pathology-specific reference values / ranges can also be displayed to medical professionals to aid in patient care and / or leveraged in automated patient monitoring systems to alert doctors that a patient is not recovering according to the expected trajectory.

Determining vascular region pathology by: gathering medical imaging data along a length of a blood vessel; determining radial segments of the vessel, extending from the vessel centre to the perivascular region beyond the vessel’s outer wall; determining values for radiodensity and radiomic features of the radial segment; comparing the determined values with a pre-determined value to generate an output indicating pathology of the vascular region. Also disclosed: using the determined absolute value of radiodensity or radiomic features to generate the pathology indicating output. Also disclosed: identifying plaque voxels by their radiodensity. Computed tomography (CT) attenuation in perivascular adipose tissue (PVAT) may be determined. Vascular region texture or inflammation may be measured. Sub-clinical plaques, pre-plaque states or atherosclerotic disease may be identified. Calcified plaques may not be classified as inflamed. Inflamed plaques may be classified as fibrous, non-fibrous, hot, unstable, high risk. Threshold values may be adjusted based on age, gender, ethnicity, background adipocyte size, partial volume effects, blood vessel type, heart rate, heart rhythm, blood pressure, CT scanner tube voltage, reconstruction algorithms, iodinated contrast agent, contrast type, injection rate, aortic contrast opacification, left ventricular blood pool opacification, signal-to-noise, contrast-to-noise, milliamps, cardiac gating method, single and multiple energy image acquisition.

In certain embodiments, a system, computer-implemented method, and computer-readable medium for performing a comprehensive analysis of MSI and OCT images to diagnose ocular disorders are disclosed. The MSI and OCT are processed using separate input machine learning models to create input feature maps that are input to the intermediate machine learning model. An intermediate machine learning model processes the input feature map and outputs a final feature map processed by one or more output machine learning models that output one or more estimated representations of a pathology of the patient's eye.

The present application discloses, as an embodiment of the invention, a compound, or a pharmaceutically acceptable salt thereof, that is useful as an agent for preventing or treating a disease caused by a decrease in autophagy function or a disease in which a pathological condition is suppressed or improved by the enhancement of autophagy function, and that is represented by formula (I) (in formula, the symbols are as described in the specification).