AIMC Topic: Lymphocyte Activation

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Label-free estimation of regulatory T cell activation markers using Raman spectroscopy with machine learning.

Scientific reports
Regulatory T cells are a class of T lymphocytes which respond to activation signals by expanding their cell numbers, and whose culturing and expansion are of significant clinical interest. Cellular activation states are used to inform process control...

DDX55 safeguards naïve T cell homeostasis by suppressing activation-promoting transposable elements.

Science immunology
Naïve T cells are maintained in a homeostatic state to preserve a stable T cell pool with diverse T cell receptor (TCR) repertoires, ensuring preparedness for priming. However, the underlying mechanisms controlling naïve T cell homeostasis and primin...

Inflammation and B cell activation define a plasma proteome signature predicting tuberculosis in people with HIV.

mBio
Improved biomarkers for predicting progression to active tuberculosis (TB) are urgently needed, especially in people with HIV, who are at elevated risk. We used high-throughput plasma proteomics and machine learning to identify signatures associated ...

Machine learning approach to single cell transcriptomic analysis of Sjogren's disease reveals altered activation states of B and T lymphocytes.

Journal of autoimmunity
Sjogren's Disease (SjD) is an autoimmune disorder characterized by salivary and lacrimal gland dysfunction and immune cell infiltration leading to gland inflammation and destruction. Although SjD is a common disease, its pathogenesis is not fully und...

Concentration-dependent effects of immunomodulatory cocktails on the generation of leukemia-derived dendritic cells, DC mediated T-cell activation and on-target/off-tumor toxicity.

Frontiers in immunology
Acute myeloid leukemia (AML) remains a devastating diagnosis in clear need of therapeutic advances. Both targeted dendritic cells (DC) and particularly leukemia-derived dendritic cells (DC) can exert potent anti-leukemic activity. By converting AML b...

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion.

Biotechnology and bioengineering
Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T-cell activation by antigen-presenting beads and their ...

Science fact vs science fiction: A ChatGPT immunological review experiment gone awry.

Immunology letters
Artificial intelligence (AI) has made great progress in recent years. The latest chatbot to make a splash is ChatGPT. To see if this type of AI could also be helpful in creating an immunological review article, I put a planned review on different cla...

A structural-based machine learning method to classify binding affinities between TCR and peptide-MHC complexes.

Molecular immunology
The activation of T cells is triggered by the interactions of T cell receptors (TCRs) with their epitopes, which are peptides presented by major histocompatibility complex (MHC) on the surfaces of antigen presenting cells (APC). While each TCR can on...

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning.

Frontiers in immunology
Expression of CCR5 and its cognate ligands have been implicated in COVID-19 pathogenesis, consequently therapeutics directed against CCR5 are being investigated. Here, we explored the role of CCR5 and its ligands across the immunologic spectrum of CO...