Results 11 to 20 of about 138,439 (148)

Elucidating prognostic significance of purine metabolism in colorectal cancer through integrating data from transcriptomic, immunohistochemical, and single‐cell RNA sequencing analysis

Molecular Oncology, EarlyView.
Low expression of five purine metabolism‐related genes (ADSL, APRT, ADCY3, NME3, NME6) was correlated with poor survival in colorectal cancer. Immunohistochemistry analysis showed that low NME3 (early stage) and low ADSL/NME6 (late stage) levels were associated with high risk.
Sungyeon Kim, Myunghee Kang, Soyeon Jeong, Jisup Kim, Kyoung Oh Kim, Won‐Suk Lee, Jeong‐Heum Baek, Jung Ho Kim, Seungyoon Nam   +8 more
wiley   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

A review of artificial intelligence in brachytherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen, Richard L. J. Qiu, Tonghe Wang, Shadab Momin, Xiaofeng Yang   +4 more
wiley   +1 more source

Effects of Pharmacologic and Nonpharmacologic Interventions for the Management of Sleep Problems in People With Fibromyalgia: Systematic Review and Network Meta‐Analysis of Randomized Controlled Trials

Arthritis Care &Research, EarlyView.
Objective Fibromyalgia is a chronic condition characterized by widespread musculoskeletal pain and fatigue. Almost everyone with fibromyalgia has sleep problems. We aimed to evaluate the effectiveness and safety of current interventions for the management of fibromyalgia‐related sleep problems.
Jemma Hudson, Mari Imamura, Clare Robertson, Daniel Whibley, Lorna Aucott, Katie Gillies, Paul Manson, Debra Dulake, Abhishek Abhishek, Nicole K. Y. Tang, Gary J. Macfarlane, Miriam Brazzelli   +11 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Advanced Air Electrodes for Reversible Protonic Ceramic Electrochemical Cells: A Comprehensive Review

Advanced Materials, EarlyView.
Reversible protonic ceramic electrochemical cells (R‐PCECs) face challenges from sluggish and unstable oxygen reduction and evolution reactions in the air electrode. This review discusses recent progress in triple‐conducting air electrodes, emphasizing mechanisms, performance factors, and design strategies, offering guidance for creating efficient and ...
Xi Chen, Yeshu Tan, Zheng Li, Tong Liu, Yinghao Song, Shuo Zhai, Na Yu, Zongping Shao, Meng Ni   +8 more
wiley   +1 more source

Machine Learning‐Driven Multi‐Objective Optimization of Microchannel Reactors for CO₂ Conversion

Advanced Sustainable Systems, EarlyView.
This study introduces a novel method that combines CFD, RSM, and ML to improve a microreactor's performance utilizing the Sabatier reaction. A range of ML models is assessed, and the best one is selected to predict optimal reactor conditions. ML shows the ability to predict performance in just milliseconds, leading to a decrease in computational time ...
Sandeep Kumar, Parmod Kumar, Kuljeet Singh Grewal   +2 more
wiley   +1 more source

Activation of Glutamatergic Neurons in the Supramammillary Nucleus Promotes the Recovery of Consciousness under Sevoflurane Anesthesia

Advanced Science, EarlyView.
Selective lesioning of SuM glutamatergic neurons promoted the induction of and delayed emergence from sevoflurane anesthesia and increased sevoflurane sensitivity. Optogenetic stimulation of SuM glutamatergic neurons or the SuM‐MS projection promoted behavioral arousal and cortical activation under steady‐state sevoflurane anesthesia and reduced the ...
Jiayan Li, Yehui Wu, Yihan Wang, Yumin Wu, Rong Hu, Si Long, Wenqi Huang, Liming Nie, Zhongxing Wang   +8 more
wiley   +1 more source

Microbiome Single Cell Atlases Generated with a Commercial Instrument

Advanced Science, EarlyView.
Single cell sequencing is valuable for dissecting complex systems and uncovering unique features in individual cell types. However, tools for single cell microbial analysis are limited. Easily Accessible Single microbe sequencing (EASi‐seq), which adapts a commercially available single cell platform for efficient sequencing of single microbial genomes ...
Xiangpeng Li, Linfeng Xu, Benjamin Demaree, Cecilia Noecker, Jordan E. Bisanz, Daniel W. Weisgerber, Cyrus Modavi, Peter J. Turnbaugh, Adam R. Abate   +8 more
wiley   +1 more source

Accurate Transcription Factor Activity Inference to Decipher Cell Identity from Single‐Cell Transcriptomic Data with MetaTF

Advanced Science, EarlyView.
MetaTF is a new computational framework that uses single‐cell RNA sequencing (scRNA‐seq) data to infer transcription factor activity with the aim to help in deciphering cells identity starting from a heterogeneous population, and apply it to characterize mouse hematopoietic stem cells and breast cancer epithelial cells, thus identifying a novel subset ...
Yongfei Hu, Yuanyuan Zhu, Guangjue Tang, Ming Shan, Puwen Tan, Ying Yi, Xiyuan Zhang, Man Liu, Xinyu Li, Le Wu, Jia Chen, Hailong Zheng, Yan Huang, Zhuan Li, Xiaobo Li, Dong Wang   +15 more
wiley   +1 more source