Results 51 to 60 of about 48,213 (289)

Two Novel S‐methyltransferases Confer Dimethylsulfide Production in Actinomycetota

Advanced Science, EarlyView.
This study identifies two novel S‐adenosine‐methionine‐dependent methyltransferases, MddM1 and MddM2, in actinomycetes from the Mariana Trench. These enzymes can convert toxic hydrogen sulfide (H2S) and methanethiol (MeSH) into dimethylsulfide (DMS), serving as a cellular detoxification and oxidative stress response.
Ruihong Guo, Zihua Guo, Yi Zhou, Yunhui Zhang, Haojin Cheng, Rebecca Devine, Chuang Sun, Ronghua Liu, Yanfen Zheng, Andrew J. Gates, Jonathan D. Todd, Xiao‐Hua Zhang   +11 more
wiley   +1 more source

Rapid Arbitrary‐Shape Microscopy of Unsectioned Tissues for Precise Intraoperative Tumor Margin Assessment

Advanced Science, EarlyView.
This study presents a novel microscopic imaging system capable of rapid, section‐free scanning of irregular tissue surfaces, delivering high sensitivity for detecting cancer cell clusters during intraoperative tumor margin assessment. Abstract Rapid and accurate intraoperative examination of tumor margins is crucial for precise surgical treatment, yet ...
Zhicheng Shao, Xiangwei Meng, Peifen Fu, Keer Huang, Xibei Chen, Yue Ying, Jun Li, Yuxin Zheng, Xiaolong Li, Hyeon Jeong Lee, Jingyi Feng, Yuexin Lu, Runping Cai, Xiongling Jiang, Qing Chen, Hong Zhang, Xiaoyong Man, Li Lin   +17 more
wiley   +1 more source

HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning

Advanced Science, EarlyView.
HiST, a multiscale deep learning framework, reconstructs spatially resolved gene expression profiles directly from histological images. It accurately identifies tumor regions, captures intratumoral heterogeneity, and predicts patient prognosis and immunotherapy response.
Wei Li, Dong Zhang, Eryu Peng, Shijun Shen, Hamid Alinejad‐Rokny, Yao Liu, Junke Zheng, Cizhong Jiang, Youqiong Ye   +8 more
wiley   +1 more source

scPER: A Rigorous Computational Approach to Determine Cellular Subtypes in Tumors Aligned With Cancer Phenotypes From Total RNA Sequencing

Advanced Science, EarlyView.
scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley   +1 more source

Approximate Q-Learning-based (AQL) Network Slicing in Mobile Edge-Cloud environments for Delay-sensitive Services Using Markov Decision Process [PDF]

, 2023
C. Bharanidharan, S. Malathi, Vanlin Sathya, M. Rajakumaran   +3 more
openalex   +1 more source

S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning

Advanced Science, EarlyView.
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu, Penglei Wang, Gaoyuan Xu, Jitao Lu, Qinke Peng, Danyang Wu, Hequan Sun   +6 more
wiley   +1 more source

Mechanism‐Driven Screening of Membrane‐Targeting and Pore‐Forming Antimicrobial Peptides

Advanced Science, EarlyView.
To combat antibiotic resistance, this study employs mechanism‐driven screening with machine learning to identify pore‐forming antimicrobial peptides from amphibian and human metaproteomes. Seven peptides are validated, showing minimal toxicity and membrane disruption.
Jiaxuan Li, Chenguang Yang, Ruihan Dong, Juan Francisco Bada Juarez, Lei Wang, Maximilian Emanuel Wettstein, Dali Wang, Chan Cao, Ying Lu, Chen Song   +9 more
wiley   +1 more source

Research of proactive complex event processing method

Tongxin xuebao, 2016
Based on the preliminary analysis results of the indeterminate event stream that generated by the sensors and control purpose equipment of CPS,the adaptive dynamic Bayesian network and parallel Markov decision process model were used to support the ...
Shao-feng GENG, Yong-heng WANG, Ren-fa LI, Jia ZHANG   +3 more
doaj   +2 more sources

Underwater chemical plume tracing based on partially observable Markov decision process

International Journal of Advanced Robotic Systems, 2019
Chemical plume tracing based on autonomous underwater vehicle uses chemical as a guidance to navigate and search in the unknown environments. To solve the key issue of tracing and locating the source, this article proposes a path-planning strategy based ...
Jiu Hai-Feng, Chen Yu, Deng Wei, Pang Shuo   +3 more
doaj   +1 more source

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