Results 251 to 260 of about 4,823,404 (316)

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

Immunonutrition Decreases Postoperative Complications in Gastrointestinal Cancer-A Systematic Review and Meta-analysis of Randomized Controlled Trials. [PDF]

open access: yesAdv Nutr
Budai BC   +12 more
europepmc   +1 more source

NSUN3‐Associated m5C Modification of tRF5‐GlyTCC Suppresses Colorectal Cancer Progression via RPL23‐Linked Nucleolar Stress and p53‐Associated Autophagy and Enhances 5‐FU Sensitivity

open access: yesAdvanced Science, EarlyView.
This study identifies that NSUN3‐mediated m5C modification stabilizes tRF5‐GlyTCC, linking ribosomal homeostasis, nucleolar stress responses, and p53 signaling changes. This regulatory axis suppresses colorectal cancer and enhances chemotherapy response to 5‐FU, positioning tRF5‐GlyTCC as a potential therapeutic target for improving drug sensitivity in
Xinhui Lv   +8 more
wiley   +1 more source

Noninvasive Detection and Subtyping of Esophageal Cancer by Circulating Cell‐Free mtDNA Fragmentomics: A Multi‐Center Validation Study

open access: yesAdvanced Science, EarlyView.
Circulating cell‐free mitochondrial DNA provides a robust, noninvasive platform for early detection and histological subtyping of esophageal cancer. This large multi‐center study validates consistently high accuracy across ethnically and geographically diverse cohorts, demonstrating strong potential to transform clinical management. ABSTRACT Esophageal
Yue Liu   +15 more
wiley   +1 more source

Prevalence and Prognostic Role of Nutrition Impact Symptoms in Patients With Gastrointestinal Cancer: A Multicenter Cohort Study. [PDF]

open access: yesIn Vivo
Zhang HY   +20 more
europepmc   +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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