Results 181 to 190 of about 14,153,398 (236)
ESCC‐derived exosomal circAP2B1 promotes tumor progression by reprogramming mitochondrial metabolism via the ESRRA/KPNA1/MFN2 axis to induce M2 polarization of macrophages. ABSTRACT Esophageal squamous cell carcinoma (ESCC) remodels the immunosuppressive tumor microenvironment via exosome‐mediated intercellular communication.
Yiru Wang +5 more
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In glioblastoma, M2‐polarized macrophages secrete IL‐6, which activates STAT3 signaling in tumor cells to upregulate CTSB. Tumor‐derived CTSB binds the C‐terminus of macrophage S100A10, reinforcing M2 polarization and further IL‐6 secretion, thereby establishing a feedforward IL‐6/STAT3/CTSB/S100A10 loop. This cascade drives tumor growth, invasion, and
Hao Zhang +11 more
wiley +1 more source
Redirecting Monocyte Differentiation With Engineered Extracellular Vesicles for Glioma Immunotherapy
A dual‐targeting engineered extracellular vesicles (M1‐CS‐EVs) platform is developed to redirect monocytes differentiation into anti‐tumor macrophages for glioma immunotherapy. This nanoplatform combines CAR‐mediated tumor recognition with localized CD47 blockade, leading to synergistic immune activation and potent suppression of tumor progression in ...
Yuanwei Pan +9 more
wiley +1 more source
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An Extension of Cox's Regression Model
International Statistical Review / Revue Internationale de Statistique, 1983Summary It is shown how one can construct a model for a jump process depending on an arbitrary intensity measure with the property that if the measure is absolutely continuous it reduces to Cox's regression model for survival data. The model has the property that the maximum likelihood estimator of the parameters are Cox's estimate for the regression ...
Søren Johansen, Soren Johansen
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Scandinavian Journal of Statistics, 2000
The purpose of this paper is to consider the problem of statistical inference about a hazard rate function that is specified as the product of a parametric regression part and a non‐parametric baseline hazard. Unlike Cox's proportional hazard model, the baseline hazard not only depends on the duration variable, but also on the starting date of the ...
Pons, O., Visser, M.
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The purpose of this paper is to consider the problem of statistical inference about a hazard rate function that is specified as the product of a parametric regression part and a non‐parametric baseline hazard. Unlike Cox's proportional hazard model, the baseline hazard not only depends on the duration variable, but also on the starting date of the ...
Pons, O., Visser, M.
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2000
The Cox proportional hazards model [36] has become by a wide margin the most used procedure for modeling the relationship of covariates to a survival or other censored outcome.
Terry M. Therneau, Patricia M. Grambsch
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The Cox proportional hazards model [36] has become by a wide margin the most used procedure for modeling the relationship of covariates to a survival or other censored outcome.
Terry M. Therneau, Patricia M. Grambsch
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Adaptive Regression Splines in the Cox Model
Biometrics, 1999Summary.We develop a method for constructing adaptive regression spline models for the exploration of survival data. The method combines Cox's (1972,Journal of the Royal Statistical Society, Series B34, 187–200) regression model with a weighted least‐squares version of the multivariate adaptive regression spline (MARS) technique of Friedman (1991 ...
LeBlanc, Michael, Crowley, John
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Normal Approximation Diagnostics for the Cox Model
Biometrics, 1999Summary.We discuss two diagnostic methods for assessing the accuracy of the normal approximated confidence region to the likelihood‐based confidence region for the Cox proportional hazards model with censored data. The proposed diagnostic methods are extensions of the contour measures of Hodges (1987,Journal of the American Statistical Association82 ...
Chang, Chung-Chou H., Weissfeld, Lisa A.
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Diagnostic Plots in Cox's Regression Model
Biometrics, 1991Two diagnostic plots are presented for validating the fitting of a Cox proportional hazards model. The added variable plot is developed to assess the effect of adding a covariate to the model. The constructed variable plot is applied to detect nonlinearity of a fitted covariate. Both plots are also useful for identifying influential observations on the
Chen, Chen-Hsin, Wang, P. C.
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