Results 151 to 160 of about 203,481 (279)

Optimal criteria of metabolic syndrome - consensus of the Russian filial of Metabolic Syndrome Institute. On behalf of experts of Russian filial of Metabolic Syndrome Institute

, 2007
N. V. Kosiolova, A. O. Konrady
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Toward a consensus in the laboratory diagnostics of Fabry disease ‐ recommendations of a European expert group [PDF]

, 2011
Andreas Gal, Derralynn Hughes, Bryan Winchester   +2 more
openalex   +1 more source

Radiomics‐Based Unsupervised Clustering Identifies Subtypes Associated With Prognosis and Immune Microenvironment in Clear Cell Renal Cell Carcinoma: A Multicenter Study

Advanced Science, EarlyView.
This study developed an unsupervised radiomics system integrating CT imaging and multi‐omics data to stratify clear cell renal cell carcinoma into two subtypes with distinct clinical outcomes. Cluster 1 showed lower recurrence risk and active immunity, while Cluster 2 exhibited higher recurrence risk, enriched VHL/KDM5C mutations, immunosuppressive ...
Yusheng Guo, Bingxin Gong, Yi Li, Jie Lou, Shuai Shan, Xiaodong Zhang, Qiang Lu, Dongyong Zhu, Qing Sun, Lianwei Miao, Yuanxi Li, Yu‐Dong Zhang, Wei Tan, Lian Yang, Chuansheng Zheng   +14 more
wiley   +1 more source

Recommendations for the treatment of Crohnʼs disease with tumor necrosis factor antagonists: An expert consensus report [PDF]

, 2011
Brian G. Feagan, Marc Lémann, Ragnar Befrits, William Connell, Geert D’Haens, Subrata Ghosh, Pierre Michetti, Thomas Ochsenkühn, Remo Panaccione, Stefan Schreiber, Mark S. Silverberg, Dario Sorrentino, C. Janneke van der Woude, Séverine Vermeire, Paul Rutgeerts   +14 more
openalex   +1 more source

A Network‐Driven Framework for Drug Response Precision Prediction of Acute Myeloid Leukemia

Advanced Science, EarlyView.
A network‐based precision medicine platform, named NetAML is offered for personalized treatment of AML. It combines network analysis and machine learning to develop 87 models predicting drug sensitivity for clinical drugs. NetAML identifies interpretable gene signatures that drive differential drug responses, enabling the prediction of individual ...
Yinyin Wang, Rui Liu, Yinnan Zhang, Xiang Luo, Chengzhuang Yu, Shentong Fang, Ninghua Tan, Jing Tang   +7 more
wiley   +1 more source

Chinese Expert Consensus on Leptomeningeal Metastases of Lung Cancer. [PDF]

Thorac Cancer
Lin G, Wang Y, Xin T, Zhang D, Zhang Q, Li Y, Chi Y, Fan Y, Liu A, Xu H, Shi L, Zhang L, Miao Q, Zheng X, Li L, Zhou K, Yao Q, Zou Z, Miao K, Hong Y.   +19 more
europepmc   +1 more source

Le réajustement du rapport juge/expert : entre consensus et domination

, 2008
Caroline Protais
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EHRA Expert Consensus Statement on the management of cardiovascular implantable electronic devices in patients nearing end of life or requesting withdrawal of therapy [PDF]

, 2011
Luigi Padeletti, Davíð O. Arnar, Lorenzo Boncinelli, J. Brachman, A. John Camm, Jean‐Claude Daubert, Sarah Hassam, Luc Deliëns, M. Glikson, David L. Hayes, Carsten W. Israel, Rachel Lampert, Trudie Lobban, Pekka Raatikainen, Gene P. Siegal, Panos Vardas   +15 more
openalex   +1 more source

Inhibition of FOXM1 Synergizes with BH3 Mimetics Venetoclax and Sonrotoclax in Killing Multiple Myeloma Cells through Repressing MYC Pathway

Advanced Science, EarlyView.
Relapsed and refractory multiple myeloma remains a major clinical challenge. This study shows that FOXM1 contributes to resistance against BH3 mimetics in multiple myeloma cells. The FOXM1 inhibitor NB73 enhances the effectiveness of BH3 mimetics by reducing FOXM1 expression and suppressing the MYC pathway.
Zhi Wen, Yidan Wang, Kathryn C. Fox, Adam M. Bissonnette, Luke F. Moat, Terrie E. Kitchner, Kelsey Springstroh, Sung Hoon Kim, Dagna S. Sheerar, Patcharon Tanawattanacharoen, Chady A. Leon, Seth O. Fagbemi, John A. Katzenellenbogen, Scott J. Hebbring, Benita S. Katzenellenbogen, Siegfried Janz, Adedayo A. Onitilo   +16 more
wiley   +1 more source

Expert consensus on the prevention and treatment of radiochemotherapy-induced oral mucositis. [PDF]

Int J Oral Sci
Xia J, Tao X, Hu Q, Luo W, Tong X, Zhou G, Zhou H, Hua H, Tang G, Wu T, Chen Q, Fan Y, Guan X, Liu H, Hu C, Zhou Y, Shen X, Wu L, Zeng X, Liu Q, Tao R, He Y, Cai Y, Wang W, Zhang Y, Wu Y, Nie M, Jin X, Wei X, Nie Y, Yuan C, Cheng B.   +31 more
europepmc   +1 more source