AIMC Topic: T-Lymphocytes

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An immune-inspired swarm aggregation algorithm for self-healing swarm robotic systems.

Bio Systems May 10, 2016
Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the u...
Computer Simulation Animals T-Lymphocytes Immune System Chemokines Robotics Granuloma Artificial Intelligence Algorithms Macrophages Humans Models, Immunological
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Selenium supplementation has beneficial and detrimental effects on immunity to influenza vaccine in older adults.

Clinical nutrition (Edinburgh, Scotland) Dec 24, 2015
BACKGROUND & AIMS: Mortality resulting from influenza (flu) virus infections occurs primarily in the elderly through declining immunity. Studies in mice have suggested beneficial effects of selenium (Se) supplementation on immunity to flu but similar...
Diet Influenza, Human Dietary Supplements Immunoglobulins Selenium Influenza Vaccines Double-Blind Method Body Mass Index Immunoglobulin A Immunity, Cellular T-Lymphocytes Antibodies, Viral Saliva Dose-Response Relationship, Drug Male Cell Proliferation Middle Aged Humans Cytokines Female
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NIEluter: Predicting peptides eluted from HLA class I molecules.

Journal of immunological methods Apr 7, 2015
The immune system has evolved to make a diverse repertoire of peptides processed from self and foreign proteomes, which are displayed in antigen-binding grooves of major histocompatibility complex (MHC) proteins at cell surface for surveillance by T ...
Peptides Protein Binding Immunity, Cellular Support Vector Machine Humans Histocompatibility Antigens Class I Algorithms Markov Chains T-Lymphocytes
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PSR-MAPMS: A new approach for the interpretable prediction of myelin autoantigenic peptides in multiple sclerosis using multi-source propensity scores.

Protein science : a publication of the Protein Society Aug 1, 2025
Within the central nervous system, the myelin sheath is composed of elements known as myelin autoantigens that are mistakenly targeted by the immune system in multiple sclerosis (MS). This autoimmune attack leads to the destruction of myelin, resulti...
Humans Autoantigens Multiple Sclerosis Myelin Sheath Machine Learning Propensity Score T-Lymphocytes Peptides
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Multi-positive contrastive learning-based cross-attention model for T cell receptor-antigen binding prediction.

Computer methods and programs in biomedicine Aug 1, 2025
BACKGROUND AND OBJECTIVE: T cells play a vital role in the immune system by recognizing and eliminating infected or cancerous cells, thus driving adaptive immune responses. Their activation is triggered by the binding of T cell receptors (TCRs) to ep...
Receptors, Antigen, T-Cell Protein Binding Computational Biology Major Histocompatibility Complex Algorithms T-Lymphocytes Peptides Humans Machine Learning
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Advancing T-cell immunotherapy for cellular senescence and disease: Mechanisms, challenges, and clinical prospects.

Ageing research reviews Jul 1, 2025
Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent cells promotes chronic inflammation, tissue dysfunction, age-related diseases, and tumor suppression. ...
Immunotherapy Cellular Senescence Immunotherapy, Adoptive T-Lymphocytes Aging Neoplasms Tumor Microenvironment Animals Humans
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Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Journal of biomolecular structure & dynamics May 1, 2025
Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherapy. The development of novel HPK1 inhibitors is challenging yet promising. In this study, we used a c...
T-Lymphocytes Signal Transduction Humans Molecular Dynamics Simulation Thermodynamics Machine Learning Protein Serine-Threonine Kinases Molecular Docking Simulation Protein Kinase Inhibitors Structure-Activity Relationship Drug Discovery Protein Binding
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Understanding TCR T cell knockout behavior using interpretable machine learning.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2025
Genetic perturbation of T cell receptor (TCR) T cells is a promising method to unlock better TCR T cell performance to create more powerful cancer immunotherapies, but understanding the changes to T cell behavior induced by genetic perturbations rema...
Humans Neoplasms Receptors, Antigen, T-Cell Computational Biology CRISPR-Cas Systems Neural Networks, Computer Machine Learning T-Lymphocytes Gene Knockout Techniques
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The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood.

Cancer research Jun 4, 2024
UNLABELLED: T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in...
Deep Learning Receptors, Antigen, T-Cell Early Detection of Cancer Biomarkers, Tumor T-Lymphocytes Neoplasms Humans
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Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Cancer immunology research May 2, 2024
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multipl...
Treatment Outcome Neoadjuvant Therapy Lymphocytes, Tumor-Infiltrating CD40 Antigens Pancreatic Neoplasms Carcinoma, Pancreatic Ductal T-Lymphocytes Male Immunotherapy Machine Learning Female Tumor Microenvironment Humans
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