Results 221 to 230 of about 11,240,337 (302)

The Characteristics of Tumor Microenvironment by the Single Cell Profile in Endometrial Cancer of no Specific Molecular Profile (NSMP) Subtype

open access: yesAdvanced Science, EarlyView.
A subset of tumor‐associated macrophages (TAMs) characterized by SPP1 expression is discovered, which may remodel the tumor microenvironment by potentially promoting CD4+ T cell stress and maintaining epithelial cell stemness through SPP1‐CD44, thereby potentially contributing to the proliferation and migration of tumor cells, which has been verified ...
Xinhui Yuan   +5 more
wiley   +1 more source

Effects of two immunosuppression regimens on T-lymphocyte subsets in elderly kidney transplant recipients. [PDF]

open access: yesFront Immunol
Freitas GRR   +7 more
europepmc   +1 more source

HECTD1 Directs HIF‐1α to Facilitate Intestinal Inflammation and Carcinogenesis via Promoting Th17 Differentiation and Glycolysis

open access: yesAdvanced Science, EarlyView.
HECTD1 emerges as an upstream amplifier of Th17 metabolic programming by promoting K63‐linked ubiquitination of IGF2BP3 and enhancing HIF‐1α translation. HIF‐1α reciprocally drives HECTD1 transcription, establishing a positive regulatory loop that sustains glycolysis and Th17 differentiation.
Shuiyu Xu   +12 more
wiley   +1 more source

Gut microbiota regulation of T lymphocyte subsets during systemic lupus erythematosus. [PDF]

open access: yesBMC Immunol
Lian FP   +8 more
europepmc   +1 more source

Large Oncosomes Induce Pro‐Metastatic Stromal‐Myeloid Reprogramming

open access: yesAdvanced Science, EarlyView.
Large oncosomes systemically reprogram bone marrow mesenchymal stem cells through innate nucleic acid sensing, driving inflammatory and immunosuppressive remodeling that supports a metastasis‐permissive bone marrow environment, revealing a novel tumor‐host communication axis in cancer. ABSTRACT Bone metastasis can be facilitated by systemic remodeling,
Taylon Felipe Silva   +18 more
wiley   +1 more source

An Explainable Multimodal Deep‐Learning Model Using Histopathological Image and Clinical Information for Prognosis Prediction in Colorectal Cancer: A Multi‐Center Cohort Study

open access: yesAdvanced Science, EarlyView.
This study develops a multimodal deep‐learning model that integrates clinical variables and histopathological images to predict survival outcomes in colorectal cancer. The multimodal model effectively stratifies patients into low‐ and high‐risk groups, demonstrating superior accuracy and generalizability across multiple independent cohorts.
Zhihan Jiang   +12 more
wiley   +1 more source

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