Results 171 to 180 of about 15,959 (250)

Global Research Trends in Dietary Polyphenols for Preventing Non‐Communicable Chronic Diseases: A Bibliometric Study

Food Science &Nutrition, Volume 14, Issue 3, March 2026.
This graphical abstract summarizes a bibliometric study on dietary polyphenols for preventing non‐communicable chronic diseases. It shows publication growth from 1998 to 2024, highlights core themes (oxidative stress, inflammation) and hotspots (metabolic syndrome, gut microbiota), and outlines future priorities like long‐term human studies.
Xinjiang Huang, Pengyuan Kang, Haiying Chen, Jie Li, Jie Liu   +4 more
wiley   +1 more source

In silico interactome analysis reveals distinct and complementary metabolic roles of bacteria in stingless bee larval food. [PDF]

Comput Struct Biotechnol J
de Avila NB, Costa Santos AC, Correa JL, Bonetti AM, Ueira-Vieira C, Dos Santos AR.   +5 more
europepmc   +1 more source

PD‐1/PD‐L1 in Hepatocellular Carcinoma (2014–2024): A Combined Macro and Micro Analysis of Immunotherapy Implications

iNew Medicine, Volume 2, Issue 1, March 2026.
ABSTRACT Hepatocellular carcinoma (HCC) represents a significant global health issue, with the PD‐1/PD‐L1 axis serving a pivotal target for immunotherapy in this malignancy. However, a comprehensive bibliometric analysis of PD‐1/PD‐L1 research in HCC is lacking.
Xingyu Zhu, Lin Tang, Hongyan Li, Hao Li, Jiamei Wang   +4 more
wiley   +1 more source

Application of network pharmacology in traditional Chinese medicine for the treatment of cardiac diseases. [PDF]

Front Pharmacol
Zhai X, Chen X, Xiao X, Wu L.
europepmc   +1 more source

Chromatin Accessibility in Cancer: Biological Functions, Mechanisms, Therapeutic Potential, and Future Directions

MedComm, Volume 7, Issue 3, March 2026.
Cancer remains the leading cause of mortality worldwide, and drug resistance further underscores the urgent need for innovative therapeutic strategies. Chromatin, a stable yet highly dynamic nucleoprotein complex, serves as the primary carrier of genetic material in eukaryotic cells.
Wentao Xia, Min Jiang, Yefei Huang, Kun Ding, Yansu Chen   +4 more
wiley   +1 more source

Revealing hidden regulatory dependencies: multi-perspective graph learning for single-cell gene regulatory network inference. [PDF]

Brief Bioinform
He W, Zhang R, Zhu Y, Zhou H, Zuo Y, Bai Y, Yang L, Guo F.   +7 more
europepmc   +1 more source

A Network‐Based Association of IBD and Colorectal Cancer Using Proteomics Data

PROTEOMICS – Clinical Applications, Volume 20, Issue 2, March 2026.
ABSTRACT Background Colorectal cancer (CRC) is a major cause of morbidity and mortality, with chronic inflammation from inflammatory bowel disease (IBD) representing a well‐established risk factor. Clarifying shared molecular mechanisms may facilitate early detection and prevention strategies.
Jaiya Dhami, Swarnima Kollampallath Radhakrishnan, Dominic Russ, Sudip Mondal, Abdulrahman Alzarooni, Laura Bravo Merodio, Niharika A. Duggal, Ruchi Gupta, Animesh Acharjee   +8 more
wiley   +1 more source

Topology-aware functional similarity: integrating extended neighborhoods via exponential attenuation. [PDF]

BMC Bioinformatics
Wang P.
europepmc   +1 more source

Unraveling the Link Between Azathioprine and Acute Pancreatitis: Integrating Network Toxicology, Machine Learning, and Mendelian Randomization

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 3, March 2026.
ABSTRACT Azathioprine (AZA), a widely used immunosuppressant, can induce acute pancreatitis (AP), yet the underlying molecular mechanisms remain unclear. This study employed an integrative multiomics strategy—combining network toxicology, machine learning, Mendelian randomization (MR), and molecular docking—to elucidate the biological basis of AZA ...
Zhijun Xie, Hang Lei, Pengcheng Zhang, Zhi Li, Wenfu Tang   +4 more
wiley   +1 more source

A comprehensive review of cluster methods for drug–drug interaction network

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract The detection of drug–drug interaction (DDI) is crucial to the rational use of drug combinations. Experimentally, DDI detection is time‐consuming and laborious. Currently, researchers have developed a variety of computational methods to predict DDI.
Shuyuan Cao, Guixia Liu, Xiangrun Zhou, Ji Lv   +3 more
wiley   +1 more source