Results 111 to 120 of about 302,402 (283)

Cause and effect relationship between acid reflux and symptoms: a reappraisal using ROC curves [PDF]

, 2000
J. H. Steinbach, J. Liu, Cheryl Beaumont, Ravinder K. Mittal   +3 more
openalex   +1 more source

The Evolutionary Trajectory and Prognostic Value of GITR+ Tregs Reprogramed by Tumor‐Intrinsic PD‐1/c‐MET Signaling in Pancreatic Cancer

Advanced Science, EarlyView.
In pancreatic ductal adenocarcinoma (PDAC), tumor‐intrinsic PD‐1 signaling activates the MET pathway, leading to the establishment of an immunosuppressive tumor microenvironment (TME). This MET‐driven signaling cascade promotes the selective accumulation of GITR+ regulatory T cells (Tregs), a highly immunosuppressive subset.
Jiande Han, Hanlin Yin, Taochen He, Junyi He, Zhenlai Jiang, Qiangda Chen, Zhihang Xu, Yuqi Xie, Yaolin Xu, Haibo Wang, Wenquan Wang, Wenchuan Wu, Yun Jin, Wenhui Lou, Jun Yu, Ning Pu, Liang Liu   +16 more
wiley   +1 more source

Plasma DNMT1 Activity for Assessing Tumor Burden and Predicting Neoadjuvant Therapy Response in Breast Cancer

Advanced Science, EarlyView.
In this work, a detection method is presented for the activity of plasma DNA methyltransferase 1 (DNMT1), namely DNMT1 Identification by Variable Activity (DIVA). DIVA can detect plasma DNMT1 at levels as low as 10−7 U mL−1, also it successfully evaluated tumor burden and predicted the neoadjuvant therapy responses of breast cancer patients.
Yingran Wang, Guozhi Zhang, Zhizhao Zhang, Mengsi Zhang, Jiao Chen, Ke Wang, Lu Liu, Jing Bao, Ming Chen, Xiaowei Qi, Mingxuan Gao   +10 more
wiley   +1 more source

The receiver operating characteristic (ROC) curve

Southwest Respiratory and Critical Care Chronicles, 2017
Shengping Yang, Gilbert Berdine
doaj   +1 more source

MALMPS: A Machine Learning‐Based Metabolic Gene Prognostic Signature for Stratifying Clinical Outcomes and Molecular Heterogeneity in Stage II/III Colorectal Cancer

Advanced Science, EarlyView.
Chen et al. identified a metabolic gene prognostic signature with machine‐learning framework and assessed the prognostic value in independent CRC cohorts. The metabolic signature subtypes are characterized by specific metabolic and proteomic characteristics, and associated with distinct molecular pathway and therapeutic potential.
Hao Chen, Ze Wang, Chenglong Sun, Yang Zhong, Yuan Liu, Yikun Li, Tongchao Zhang, Yuan Zhang, Xingyu Zhu, Leping Li, Feifei Teng, Ming Lu, Wei Chong   +12 more
wiley   +1 more source

Testosterone Delays Bone Microstructural Destruction via Osteoblast‐Androgen Receptor‐Mediated Upregulation of Tenascin‐C

Advanced Science, EarlyView.
This study reveals that Testosterone–Androgen Receptor signaling delays elderly male bone destruction by upregulation of the osteoblastic extracellular tenascin‐C (TNC). The osteoprotective effect of fibrinogen C‐terminus of TNC is demonstrated in male osteoporotic mice model that osteoblast‐specific Ar‐knockout, potentially via inhibition of ...
Yong Xie, Meng Pan, Zeyuan Zhang, Licheng Zhang, Haotian Liu, Xia Wang, William W Lu, Peifu Tang, Wei Ge   +8 more
wiley   +1 more source

ROC-curves and evaluation of radiation-induced side-effects in breast cancer [PDF]

, 2003
Pehr Lind, Berit Wennberg, G. Gagliardi, Stefan Rosfors, Gunilla Svane   +4 more
openalex   +1 more source

Gompertz Law‐Based Biological Age (GOLD BioAge): A Simple and Practical Measurement of Biological Ageing to Capture Morbidity and Mortality Risks

Advanced Science, EarlyView.
The Gompertz law‐based biological age metric (GOLD BioAge) introduces interpretable convenient and interpretable calculations to capture mortality, disease, and frailty risks. Its applications to proteomics and metabolomics (ProtAge and MetAge) demonstrate clinical potential to enhance aging evaluation and prevent age‐related diseases.
Meng Hao, Hui Zhang, Jingyi Wu, Yaqi Huang, Xiangnan Li, Meijia Wang, Shuming Wang, Jiaofeng Wang, Jie Chen, Zhi jun Bao, Li Jin, Xiaofeng Wang, Zixin Hu, Shuai Jiang, Yi Li   +14 more
wiley   +1 more source

Nonparametric bootstrap methods for interval estimation of the area under the ROC curve with correlated diagnostic test data: application to whole-virus ELISA testing in swine. [PDF]

Front Vet Sci, 2023
Pang J, Ju W, Welch M, Gauger P, Liu P, Zhang Q, Wang C.   +6 more
europepmc   +1 more source

Comprehensive Characterization of the Immune Microenvironment Based on Nested Resampling Machine Learning Framework Identifies TRAF3 Interacting Protein 3 as a Promising Regulator to Improve the Resistance to Immunotherapy in Glioma

Advanced Science, EarlyView.
This study develops a nested resampling machine learning framework to establish the Immune Glioma Survival Signature (IGLoS), which stratifies glioma patients and predicts immunotherapy resistance. Multi‐omics analyses reveal TRAF3IP3 as a pivotal regulator of PD‐L1 expression and T‐cell exhaustion via ERK‐NFATC2 signaling.
Yanbo Yang, Fei Wang, Yulian Zhang, Run Huang, Chuanpeng Zhang, Lu Zhao, Hanhan Dang, Xinyu Tao, Yue Lu, Dengfeng Lu, Yunsheng Zhang, Kun He, Jiancong Weng, Zhouqing Chen, Zhong Wang, Yanbing Yu   +15 more
wiley   +1 more source