Results 81 to 90 of about 42,893 (255)
The epigenetic trajectory of type 1 regulatory T cells
The epigenome of T follicular helper cells prepares them for conversion into type 1 regulatory T cells.
David P Turicek, Xiaoxiao Wan
doaj +1 more source
IL-21 is central to follicular helper T cell function and germinal centre responses. Here the authors show that IL-21 signalling directly inhibits T follicular regulatory cells by limiting Bcl-6-dependent IL-2 receptor expression.
Christoph Jandl +14 more
doaj +1 more source
Treatment‐resistant wounds caused by polymicrobial biofilms are refractory to conventional therapies due to the dense extracellular matrices. We developed μBLAST, a microblasting wound dressing that combines MnO2‐doped biosilica and a H2O2‐releasing mesh to generate localized oxygen microbubbles that mechanically disrupt biofilms.
Yujin Ahn +12 more
wiley +1 more source
This study develops 16:0 LPC‐modified lipid nanoparticles (LPC‐LNPs) with cancer cell specificity by exploiting altered tumor lipid metabolism. LPC‐LNPs encapsulating Cd28 small interfering RNA (LPC‐LNP‐Cd28) knock down cancer cell CD28 without affecting T cells, inflame the tumor microenvironment, and overcome anti‐PD‐1 resistance.
Yangyang Chai +12 more
wiley +1 more source
Regulation of T follicular helper cells by ICOS
T follicular helper (TFH) cells are gatekeepers of the humoral immune response. Without help from this CD4+ T cell subset, B cells cannot differentiate into high-affinity memory B cells and antibody-producing long-lived plasma cells which are the basis of protective immune responses.
openaire +2 more sources
Nanomaterials offer dual applications in allergy management. For diagnosis, nanomaterials enhance analytical sensitivity and improve detection in specific IgE and functional assays such as the basophil activation test (BAT). For allergen‐specific immunotherapy, nanomaterials enable allergen masking and controlled release, and effectively modulate the ...
Madiha Habib +8 more
wiley +1 more source
Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo +14 more
wiley +1 more source
Summary: Invariant natural killer T (iNKT) cells are activated by glycolipids presented on CD1d. When iNKT cells interact with and activate B cells, they can differentiate into iNKT follicular helper (iNKTfh) cells, and here, we investigate how this, in ...
Chenfei He +13 more
doaj +1 more source
A dual‐color pseudo‐menstrual mouse model enables real‐time tracing of circulating endometrial cells (CECs) from uterine and ectopic sources. The study reveals menstrual‐phase‐dependent, burst‐like CEC release, distinct postoperative behaviors of different CEC origins, and a potential association with prolactin fluctuations, providing an in vivo ...
Shang Wang +15 more
wiley +1 more source
CD4+T Cells: Differentiation and Functions
CD4+T cells are crucial in achieving a regulated effective immune response to pathogens. Naive CD4+T cells are activated after interaction with antigen-MHC complex and differentiate into specific subtypes depending mainly on the cytokine milieu of the ...
Rishi Vishal Luckheeram +3 more
doaj +1 more source

