Results 231 to 240 of about 474,933 (300)

Noninvasive Characterization of Tumor Heterogeneity in HNSCC: From Clinical Utility to Biological Correlates

Advanced Science, EarlyView.
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen, Rui Liu, Yuan Zhou, Yin Xiao, Chengmin Feng, Lin Chen, Yanshi Li, Mengna Wang, Zhaobo Cheng, Yuxi Luo, Long Liu, Lijing Niu, Yue Xiang, Juan Peng, Guohua Hu, Min Pan   +15 more
wiley   +1 more source

Platelet Mass Signatures and Thrombin-Activatable Fibrinolysis Inhibitor as Discriminators of Primary Thrombocytosis: Development of a Screening Algorithm in an Eastern Sudanese Cohort. [PDF]

Cureus
Bashir BA.
europepmc   +1 more source

SSR4 sustains Tertiary Lymphoid Structures by Regulation Quality Control of N‐linked Glycosylation During B‐cell Differentiation Into Plasmacyte in Colorectal Cancer

Advanced Science, EarlyView.
SSR4, a TRAP component induced in B cells, governs BAFFR N‐glycosylation via DDOST to sustain NF‐κB signaling, B‐cell differentiation, and TLS maturation. Its loss impairs anti‐tumor immunity, while overexpression improves antibody glycosylation and ADCC, revealing a critical regulator for cancer immunotherapy.
Wei Zhao, Youcai Zhao, Haiyang Li, Bowen Yang, Siyan Lu, Xueting Fu, Caixia Zhang, Yirong Chen, Xiaofeng Bian, Xinghua Ma, Xiaobing Yang, Bin Wang, Yuan Fang, Lulu Yang, Yelin Zhao, Shuli Zhao   +15 more
wiley   +1 more source

A Reproducible MRI-Based Quantitative Feature for Differentiating Dysplastic Nodules from Hepatocellular Carcinoma: A Multicenter Retrospective Study. [PDF]

J Hepatocell Carcinoma
Zhang C, Xie S, Wang C, Ren T, Zhong X, Zhang Y, Li S, Wu W, Sun Y, Xie C.   +9 more
europepmc   +1 more source

Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction

Advanced Science, EarlyView.
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen, Guancen Lin, Chuan‐Shen Hu, Yong Wang   +3 more
wiley   +1 more source

3D intratumoral heterogeneity-based quantitative score from chest CT for preoperative prediction of visceral pleural invasion in lung adenocarcinoma: a multicenter study. [PDF]

Front Oncol
Ouyang Q, Wu Y, Zhou L, Qi W, Zhang S, Zhao Y, Zuo J.   +6 more
europepmc   +1 more source

Mitochondrial Carrier SLC25A13 Drives Ferroptosis Resistance and Immune Evasion via a STAT3–IFI6 Circuit in Breast Cancer

Advanced Science, EarlyView.
SLC25A13 is identified as an immunometabolic driver of triple‐negative breast cancer that sustains ferroptosis resistance and immune evasion through a STAT3–IFI6 circuit. Pharmacologic degradation of SLC25A13 restores ferroptosis sensitivity and enhances anti‐PD‐1 efficacy, highlighting a strategy to convert immune‐cold tumors into immunotherapy ...
Yingze Zhu, Yuhan Tang, Yingcui Chen, Zhuoqi Zhang, Yige Lu, Xinyue Wang, Qiyuan Shi, Wenhui Zhao, Hui Pang   +8 more
wiley   +1 more source

Enhancing Model Generalizability in Medical Artificial Intelligence: Systematic Comparison of Categorical Encoding and Sampling Techniques for Imbalanced Data. [PDF]

JMIR Med Inform
Chuang CW, Wu CK, Wu CH, Shia BC, Chen M.   +4 more
europepmc   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

Machine Learning Models for Predicting Liver Metastasis at Diagnosis and Overall Survival in Ovarian Cancer: A SEER-Based Study. [PDF]

Int J Womens Health
Li C, Huang L, Jiang R.
europepmc   +1 more source