AIMC Topic: T-Lymphocytes
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Exploring T-cell exhaustion features in Acute myocardial infarction for a Novel Diagnostic model and new therapeutic targets by bio-informatics and machine learning.
BMC cardiovascular disorders
May 24, 2024
BACKGROUND: T-cell exhaustion (TEX), a condition characterized by impaired T-cell function, has been implicated in numerous pathological conditions, but its role in acute myocardial Infarction (AMI) remains largely unexplored. This research aims to i...
Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells.
Nature communications
Apr 13, 2024
T cells have the ability to eliminate infected and cancer cells and play an essential role in cancer immunotherapy. T cell activation is elicited by the binding of the T cell receptor (TCR) to epitopes displayed on MHC molecules, and the TCR specific...
Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma.
International immunopharmacology
Apr 9, 2024
BACKGROUND: Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-c...
Inference of Developmental Hierarchy and Functional States of Exhausted T Cells from Epigenetic Profiles with Deep Learning.
Journal of chemical information and modeling
Mar 28, 2024
Exhausted T cells are a key component of immune cells that play a crucial role in the immune response against cancer and influence the efficacy of immunotherapy. Accurate assessment and measurement of T-cell exhaustion (TEX) are critical for understa...
An integrative machine learning model for the identification of tumor T-cell antigens.
Bio Systems
Mar 6, 2024
The escalating global incidence of cancer poses significant health challenges, underscoring the need for innovative and more efficacious treatments. Cancer immunotherapy, a promising approach leveraging the body's immune system against cancer, emerge...
iTTCA-MVL: A multi-view learning model based on physicochemical information and sequence statistical information for tumor T cell antigens identification.
Computers in biology and medicine
Jan 1, 2024
Immunotherapy is an emerging treatment method aimed at activating the human immune system and relying on its own immune function to kill cancer cells and tumor tissues. It has the advantages of wide applicability and minimal side effects. Effective i...
Broadening the horizon: potential applications of CAR-T cells beyond current indications.
Frontiers in immunology
Nov 27, 2023
Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed condit...
Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.
PloS one
Jul 21, 2023
Clinical prognostic scoring systems have limited utility for predicting treatment outcomes in lymphomas. We therefore tested the feasibility of a deep-learning (DL)-based image analysis methodology on pre-treatment diagnostic computed tomography (dCT...
RCMNet: A deep learning model assists CAR-T therapy for leukemia.
Computers in biology and medicine
Sep 11, 2022
Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of ...
CD147-specific chimeric antigen receptor T cells effectively inhibit T cell acute lymphoblastic leukemia.
Cancer letters
May 31, 2022
T cell acute lymphoblastic leukemia (T-ALL) is invasive and heterogeneous, and existing therapies are sometimes unsuccessful. Chimeric antigen receptor (CAR) T cell therapy is a breakthrough tumor treatment method, particularly for B cell acute lymph...
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