Results 131 to 140 of about 44,252 (262)

Autophagy Orchestrates Anti‐Tumor Immunity to Enhance Chemosensitivity via the FBXW2/C/EBPβ/TIMP‐2 Axis in Colorectal Cancer

Advanced Science, EarlyView.
Chemotherapy leverages tumor‐cell autophagy to reshape the colorectal cancer immune microenvironment. Autophagy degrades FBXW2 to promote C/EBPβ‐mediated TIMP‐2 transcription and MMP‐9 suppression, driving intra‐tumoral CD8+ T‐cell infiltration. Targeting MMP‐2/9 or restoring TIMP‐2 overcomes chemo‐resistance in autophagy‐deficient tumors. ABSTRACT The
Bing Cheng, Chaoying Wei, Zhitong Niu, Jinxin Chen, Guojie Long, Yingzhen Weng, Qiufeng Liu, Yue Jiang, Panpan Wang, Ronghua Zhang, Qiang Yu, Xiaojian Wu, Wenyu Wang   +12 more
wiley   +1 more source

The Mediating Role of Teacher Efficacy Between Academic Self-Concept and Teacher Identity Among Pre-Service Physical Education Teachers: Is There a Gender Difference? [PDF]

Behav Sci (Basel)
Rubio-Valdivia JM, Granero-Gallegos A, Carrasco-Poyatos M, López-García GD.   +3 more
europepmc   +1 more source

The Antidiabetic Potential of Alpha‐Mangostin: A Review of Preclinical and Clinical Evidence

AgriFood: Journal of Agricultural Products for Food, EarlyView.
Alpha‐mangostin is a compound from the pericarp of Garcinia mangostana. The antidiabetic effects of alpha‐mangostin include enhancing insulin secretion, improving glucose uptake through GLUT receptor upregulation, reducing oxidative stress and inflammation, promoting wound healing, reducing HbA1C, reducing HOMA‐IR index, and decreased mRNA expressions ...
Oliver Dean John, Nur Damia Iwani Zulkiflee, Siti Raihanah Shafie, Ramlah George, Melonney Patrick   +4 more
wiley   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

A person-centred examination of inclusive teachers' beliefs about teaching students with intellectual and developmental disabilities: profiles and relations to teacher efficacy. [PDF]

Int J Dev Disabil
Xin W, Liu C, Zhang Z, Yao X.
europepmc   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source