Results 91 to 100 of about 451,157 (262)

Multimodal AI‐Driven Identification of Dehydrocostus Lactone as a Potent Renal Fibrosis Attenuator Targeting IQGAP1

Advanced Science, EarlyView.
Renal fibrosis, a hallmark of CKD, lacks effective treatments. Herein, we developed a multimodal AI model (TCM‐SPred) to identify anti‐fibrotic agents and found that dehydrocostus lactone (DCL) targets IQGAP1 to inhibit Wnt signaling, blocking the interaction between IQGAP1 and CCT3, demonstrating potent anti‐fibrotic activity in vitro and in vivo ...
Weijiang Lin, Wenzhuo Xu, Kang Liu, Ping Wang, Zhenzhen Zhu, Wenyu Lu, Zhe Zheng, Xiaoqian Peng, Xunkai Yin, Shulan Mei, An Pan, Jian Liu, Lihong Hu   +12 more
wiley   +1 more source

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

Deficits of knowledge versus executive control in semantic cognition: Insights from cued naming [PDF]

, 2007
Deficits of semantic cognition in semantic dementia and in aphasia consequent on CVA (stroke) are qualitatively different. Patients with semantic dementia are characterised by progressive degradation of central semantic representations, whereas ...
Baayen, Berthier, Bozeat, Burgess, Burgess, Chertkow, Crutch, Damasio, Damasio, Dell, Dell, Demb, Elizabeth Jefferies, Folstein, Forde, Foygel, Funnell, Gloor, Gold, Goodglass, Graham, Hart, Hodges, Howard, Jefferies, Jefferies, Jefferies, Jefferies, Kaplan, Karalyn Patterson, Kay, Lambon Ralph, Lambon Ralph, Lambon Ralph, Lambon Ralph, Martin, Matthew A. Lambon Ralph, Milner, Mummery, Myers Pease, Nestor, Parker, Patterson, Peers, Podraza, Raven, Robertson, Robinson, Robinson, Rogers, Saffran, Saygin, Schwartz, Snodgrass, Snowden, Stuss, Thompson-Schill, Thompson-Schill, Wagner, Warrington, Warrington, Wechsler, Wernicke   +62 more
core   +3 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Episodic and semantic memory impairments in (very) early Alzheimer’s disease: The diagnostic accuracy of paired-associate learning formats

Cogent Psychology, 2016
Paired-associate learning (PAL) paradigms measure memory processes sensitive to the medial temporal lobe, which shows atrophy in early Alzheimer’s disease (AD).
Pauline E.J. Spaan
doaj   +1 more source

A Computational Model of Children's Semantic Memory [PDF]

, 2004
A computational model of children's semantic memory is built from the Latent Semantic Analysis (LSA) of a multisource child corpus. Three tests of the model are described, simulating a vocabulary test, an association test and a recall task. For each one,
Denhière, Guy, Lemaire, Benoît
core   +2 more sources

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Mapping the Memory Structure of High-Knowledge Students: A Longitudinal Semantic Network Analysis

Journal of Intelligence
Standard learning assessments like multiple-choice questions measure what students know but not how their knowledge is organized. Recent advances in cognitive network science provide quantitative tools for modeling the structure of semantic memory ...
Simone A. Luchini, Shuyao Wang, Yoed N. Kenett, Roger E. Beaty   +3 more
doaj   +1 more source

Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

Advanced Intelligent Discovery, EarlyView.
This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando, Naoto Watanabe, Chihiro Sekine, Shogen Sekiguchi, Ohmi Fuchiwaki   +4 more
wiley   +1 more source

Episodic and semantic memory functioning in very old age: Explanations from executive functioning and processing speed theories

Cogent Psychology, 2015
Structural equation modeling was used to investigate whether age-related episodic and semantic memory impairments are better explained by decline in processing speed or executive functioning (or both), rather than directly in terms of memory components ...
Pauline E.J. Spaan
doaj   +1 more source