Results 191 to 200 of about 48,589 (309)

Full‐Body AI Agent: A Perspective on Multi‐Scale Collaborative AI for Systemic Biology and Precision Medicine

Advanced Science, EarlyView.
We propose the Full‐Body AI Agent, a multi‐scale collaborative framework with 7 biological‐layer agents. It unifies multi‐omics/clinical data via standardized protocols, enabling phenotype‐guided closed‐loop reasoning, quantitative evaluation, and LLM safeguards, with promising applications in tumor metastasis modeling and precision drug development ...
Aoqi Wang, Jiajia Liu, Jianguo Wen, Yangyang Luo, Zhiwei Fan, Liren Yang, Xi Hu, Ruihan Luo, Yankai Yu, Sophia Li, Weiling Zhao, Xiaobo Zhou   +11 more
wiley   +1 more source

Contextualización de la bioestadística a situaciones biológicas para la formación inicial de profesores de Biología/Contextualization of biostatistics to biological situations for the initial training of Biology teachers

Pedagogía y Sociedad
Introducción: La estadística es muy importante para analizar fenómenos biológicos, por esta razón es necesaria su enseñanza de manera contextualizada y relacionada con los problemas profesionales, en la formación de profesores de biología.
Yusimí Guerra Véliz , Julio Leyva Haza , Yasmani Alonso Rojas   +2 more
doaj  

A Call for Contextualization: Is Cardiopulmonary Exercise Testing the Gold Standard for Exercise Capacity? [PDF]

Cureus
Sitko S, Cirer-Sastre R, López-Laval I, Barrajón C.   +3 more
europepmc   +1 more source

A Pollen‐Enhanced Bionic Mechanoreceptor Induced by Asymmetric Ionic Convection in Hydrogel for Sensory‐Augmented Prostheses

Advanced Science, EarlyView.
This work proposed a pollen‐enhanced bionic mechanoreceptor based on ionic convection. Leveraging the ion anchoring effect of the pollen particle, the output performance could be ∼12 times higher than the original state. By employing deep learning models as AI brains, the feasibility of a sensory‐augmented prosthesis consisting of a pollen‐enhanced ...
Zi Hao Guo, Jingyu Deng, Yanzhang Xu, Chenchen Zhou, Yangshi Shao, Xiong Pu, Munho Kim, Namjoon Cho   +7 more
wiley   +1 more source

Contextual Barriers to Health Information Systems Optimization in Underserved Communities in Kenya: Qualitative Study Informed by Frugal Innovation and Information and Communication Technologies for Development. [PDF]

JMIR Form Res
Nyatuka D, Jabin MSR, Dionne-Morris L.
europepmc   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Sieving for gold: external comparator studies to prioritize drugs for late-stage clinical trial. [PDF]

J Comp Eff Res
Vennin S, Sopwith W, Calvo E, Cantoni C, Del Valle PC, Maissenhaelter B, Rippin G, Ryll B, Osterwalder B.   +8 more
europepmc   +1 more source

Contextual Emergence

Scholarpedia, 2009
openaire   +2 more sources

Pharmacologic Modulation of ARID3A with Rimegepant Reactivates Type I Interferon Signaling and Sensitizes Triple‐Negative Breast Cancer to PD‐1 Blockade

Advanced Science, EarlyView.
This study identifies ARID3A as a key immunosuppressive transcription factor in TNBC. Its inhibition activates the type I IFN pathway, boosting CD8+ T cell infiltration and sensitizing tumors to anti‐PD‐1. The FDA‐approved migraine drug Rimegepant targets ARID3A, enhances immunotherapy efficacy in preclinical models, and establishes a druggable axis to
Teng Zhou, Yifei Zhu, Cheng Zeng, Jinlu Han, Huiying Huang, Doudou Li, Mingxi Lin, Yizi Jin, Qin Guo, Yuxin Yan, Xinhui Mao, Yifei Zhou, Jian Zhang   +12 more
wiley   +1 more source

When AI joins the table: evaluating large language model performance in soft tissue sarcoma tumor board decisions. [PDF]

J Cancer Res Clin Oncol
Dehdab R, Afat S, Mankertz F, Brendel JM, Maalouf N, Werner S, Brendlin A, Herrmann J, Nikolaou K, Kloker LD, Calukovic B, Benzler K, Zender L, Deinzer CKW.   +13 more
europepmc   +1 more source