Results 61 to 70 of about 15,550,459 (307)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Outcomes in relapsed or refractory pediatric and AYA bone sarcomas remain poor, and the impact of early referral to specialized sarcoma centers on survival is unclear. Early centralization of care may improve local and systemic treatment quality, but evidence in this population is limited.
Justyna Antoniuk‐Majchrzak +9 more
wiley +1 more source
FEBS Letters, EarlyView.Obesity raises blood levels of PAI‐1, a protein linked to metabolic dysfunction‐associated steatotic liver disease in people with obesity. In female mice fed a high‐fat diet, partially lowering PAI‐1 led to smaller subcutaneous fat cells and lower liver cholesterol, without changing body weight or insulin sensitivity.
Claudia E. Ramirez Bustamante +10 more
wiley +1 more source
Molecular Oncology, EarlyView.In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera +11 more
wiley +1 more source
Healthcare Analytics, 2023 There are potentially infinite gene expression markers for Lung Squamous Cell Carcinoma. This results in a high-dimensional data with a large number of features. The selection of relevant markers for analysis is thus, of utmost importance.
Atanu Bhattacharjee +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Covariates included in Cox proportional hazard model.
, 2016 Covariates included in Cox proportional hazard model.
Klaas H. Groenier (153074) +5 more
core +1 more source
Estimates of the Cox proportional hazard model of nonusage attrition.
, 2022 Estimates of the Cox proportional hazard model of nonusage attrition.
Mohamed Mubasher (14008700) +7 more
core +1 more source
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Employee’s attrition prediction using survival analysis and cox proportional hazard model
JITCE (Journal of Information Technology and Computer Engineering), 2019 In any industry attrition is a big problem, whether it is about employee attrition of an organization or customer attrition of an e-commerce site. If we can accurately predict that which customer or employee can leave their current company/organization ...
Krishna Kumar Mohbey
doaj
Cox proportional hazard regression model analysis.
, 2014 Cox proportional hazard regression model analysis.
Yi Zhang (9093) +12 more
core +1 more source