AIMC Topic: CD4-Positive T-Lymphocytes
Clear Filters Showing 1 to 10 of 25 articles
Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.
Cancer genetics
Dec 22, 2024
CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-related immune responses exhibit diverse characteristics in different diseases. This study utilizes g...
Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.
Frontiers in immunology
Dec 4, 2024
BACKGROUND: Diabetic retinopathy (DR) is a major complication of diabetes, leading to severe vision impairment. Understanding the molecular mechanisms, particularly PANoptosis, underlying DR is crucial for identifying potential biomarkers and therape...
ROC Curve
RNA-Seq
Gene Regulatory Networks
Diabetic Retinopathy
Machine Learning
Biomarkers
CD4-Positive T-Lymphocytes
Gene Expression Regulation
Molecular Targeted Therapy
Memory T Cells
Nomograms
Human Umbilical Vein Endothelial Cells
Random Forest
Humans
Fatty Acid Synthase, Type I
Phospholipid Transfer Proteins
Regulated Cell Death
Machine learning approaches identify immunologic signatures of total and intact HIV DNA during long-term antiretroviral therapy.
eLife
Sep 9, 2024
Understanding the interplay between the HIV reservoir and the host immune system may yield insights into HIV persistence during antiretroviral therapy (ART) and inform strategies for a cure. Here, we applied machine learning (ML) approaches to cross-...
Immune modulation by nutritional intervention in malnourished children: Identifying the phenotypic distribution and functional responses of peripheral blood mononuclear cells.
Scandinavian journal of immunology
Jun 7, 2023
Malnourished children are susceptible to an increased risk of mortality owing to impaired immune functions. However, the underlying mechanism of altered immune functions and its interaction with malnutrition is poorly understood. This study investiga...
Machine learning based deconvolution of microarray atrial samples from atrial fibrillation patients reveals increased fractions of follicular CD4+ T lymphocytes and gamma-delta T cells.
Journal of physiology and pharmacology : an official journal of the Polish Physiological Society
Apr 24, 2022
A potential relationship between T cell immunity and development of atrial fibrillation (AF) has been proposed. Historically in AF patients it has been reported that peripheral blood had elevated CD4+ T cells. However few studies have explored whethe...
Statistical and machine learning methods to study human CD4 T cell proteome profiles.
Immunology letters
Apr 2, 2022
Mass spectrometry proteomics has become an important part of modern immunology, making major contributions to understanding protein expression levels, subcellular localizations, posttranslational modifications, and interactions in various immune cell...
Deep Learning of Morphologic Correlations To Accurately Classify CD4+ and CD8+ T Cells by Diffraction Imaging Flow Cytometry.
Analytical chemistry
Jan 10, 2022
The two major subtypes of human T cells, CD4+ and CD8+, play important roles in adaptive immune response by their diverse functions. To understand the structure-function relation at the single cell level, we isolated 2483 CD4+ and 2450 CD8+ T cells f...
Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.
eLife
Aug 5, 2021
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrai...
Voting-based integration algorithm improves causal network learning from interventional and observational data: An application to cell signaling network inference.
PloS one
Feb 8, 2021
In order to increase statistical power for learning a causal network, data are often pooled from multiple observational and interventional experiments. However, if the direct effects of interventions are uncertain, multi-experiment data pooling can r...
Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.
Frontiers in immunology
Jun 23, 2020
Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adve...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823