AIMC Topic: T-Lymphocytes, Regulatory

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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...

Immune system development-related signature predicts prognosis and sorafenib-treatment resistance of hepatocellular carcinoma by intergrating machine learning and single-cell analyses.

Scientific reports
The development of the immune system (ISD) plays a pivotal role in both the genesis and progression of tumors, yet its specific functions in hepatocellular carcinoma (HCC) and the mechanisms behind sorafenib resistance remain elusive. In our investig...

Multi-omics insights of immune cells in the risk and prognosis of idiopathic membranous nephropathy.

Communications biology
Idiopathic membranous nephropathy (IMN) is the major cause of autoimmune-related nephrotic syndrome. The role immune cells play in the risk and prognosis of IMN remains elusive. We employ multi-omics data and a variety of approaches to evaluate the c...

Regulatory T cells and matrix-producing cancer associated fibroblasts contribute on the immune resistance and progression of prognosis related tumor subtypes in ccRCC.

Scientific reports
Clear cell renal cell carcinoma (ccRCC) is a prevalent malignant tumor in the field of urology. The effect of cell heterogeneity on the prognosis and reaction to treatment of ccRCC in large populations is still unclear. By analyzing public single cel...

Machine learning-assisted decoding of temporal transcriptional dynamics via fluorescent timer.

Nature communications
Investigating the temporal dynamics of gene expression is crucial for understanding gene regulation across various biological processes. Using the Fluorescent Timer protein, the Timer-of-cell-kinetics-and-activity system enables analysis of transcrip...

Machine learning developed regulatory T cells-related signature for prognosis and immunotherapy benefit in oral squamous cell carcinoma.

American journal of otolaryngology
BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common malignancies with poor clinical outcome. Regulatory T cells (Tregs) have a dual role in maintaining immune homeostasis and suppressing anti-tumor immunity. The role of Tregs re...

Unveiling the power of Treg.Sig: a novel machine-learning derived signature for predicting ICI response in melanoma.

Frontiers in immunology
BACKGROUND: Although immune checkpoint inhibitor (ICI) represents a significant breakthrough in cancer immunotherapy, only a few patients benefit from it. Given the critical role of Treg cells in ICI treatment resistance, we explored a Treg-associate...

Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients.

International journal of molecular sciences
Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult...

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...

Role of α-fetoprotein in differentiation of regulatory T lymphocytes.

Doklady biological sciences : proceedings of the Academy of Sciences of the USSR, Biological sciences sections
The effect of native α-fetoprotein (AFP) on the expression of T-regulatory lymphocyte (Treg) markers by activated CD4 lymphocytes with different proliferative status was studied. α-Fetoprotein did not affect the ratio of proliferating and non-prolife...