Results 161 to 170 of about 16,915 (258)

The evolution of speech communication devices for anarthria: a review. [PDF]

J Neurol
Jones CT, Hill ER.
europepmc   +1 more source

Fibrillarin Resists Cellular Senescence Via SIRT1‐Dependent Nicotinamide Metabolism and Its Inhibition Sensitizes Senolytic Therapy in Esophageal Squamous Cell Carcinoma

Advanced Science, EarlyView.
FBL directly binds to and stabilizes SIRT1 by blocking its ubiquitin‐proteasome degradation, thereby sustaining nicotinamide metabolism and redox homeostasis to counteract cellular senescence in ESCC. Genetic and pharmacological suppression of FBL sensitizes tumor cells to senolytic therapy.
Xing Jin, Hong Liu, Ling Gao, Lei Liu, Ji‐Bin Liu, Xiaoxia Jin, Ming‐Song Wang, Dan Liu, Li Feng, Wen‐Lian Chen   +9 more
wiley   +1 more source

DSKO: Dancing through DFTB Parametrization. [PDF]

J Chem Theory Comput
Samtsevych A, Song Y, van der Heide T, Aradi B, Hourahine B, Maurer RJ, Reuter K, Scheurer C, Panosetti C.   +8 more
europepmc   +1 more source

TSTScope Unifies Single‐Cell Multi‐Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Advanced Science, EarlyView.
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao, Jinyu Cheng, Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Keyue Wang, Lulu Liu, Junwei Liu, Yixue Li   +8 more
wiley   +1 more source

Sequence-to-sequence models with attention mechanistically map to the architecture of human memory search. [PDF]

Commun Psychol
Salvatore N, Zhang Q.
europepmc   +1 more source

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

Generation of Nasal Cell‐Derived Human Alveolar Organoids and Organoid‐Macrophage Assembloids for in Vitro Lung Modeling

Advanced Science, EarlyView.
This study demonstrates the generation of human alveolar organoids from nasal cells, which, when co‐cultured with monocyte‐derived macrophages, promotes maturation of both components and forms alveolar assembloids resembling native alveoli. These alveolar organoids and assembloids offer accessible, physiologically relevant in vitro systems for ...
Man Chun Chiu, Shuxin Zhang, Cun Li, Yifei Yu, Zhixin Wan, Jingjing Huang, Wei Xue, Ying Zhou, Xiaoxin Zhu, Qiaoshuai Lan, Jiali Wu, Zijun Zhao, Yuhong Liu, Xinjie Meng, Lin Huang, Hin Chu, Honglin Chen, Kelvin Kai‐Wang To, Kwok Yung Yuen, Jie Zhou   +19 more
wiley   +1 more source

Retraction Note: Decoding core genes and intercellular communication in osteosarcoma: bioinformatic investigation and immune cell profiling for diagnostic and therapeutic insights. [PDF]

Discov Oncol
Rong K, Kuang H, Ou L, Fang R, Kuang J, Yang H.   +5 more
europepmc   +1 more source

Livestock Multi‐Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation

Advanced Science, EarlyView.
A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen, Zhongyu Wang, Jieping Huang, Fen Li, Ningbo Chen, Yun Ma   +5 more
wiley   +1 more source

Polar Coding and Early SIC Decoding for Uplink Heterogeneous NOMA. [PDF]

Entropy (Basel)
Wu CJ, Lin CY, Huang YC.
europepmc   +1 more source