Results 61 to 70 of about 3,443,781 (274)

PARP inhibition and pharmacological ascorbate demonstrate synergy in castration‐resistant prostate cancer

open access: yesMolecular Oncology, EarlyView.
Pharmacologic ascorbate (vitamin C) increases ROS, disrupts cellular metabolism, and induces DNA damage in CRPC cells. These effects sensitize tumors to PARP inhibition, producing synergistic growth suppression with olaparib in vitro and significantly delayed tumor progression in vivo. Pyruvate rescue confirms ROS‐dependent activity.
Nicolas Gordon   +13 more
wiley   +1 more source

On the Connection Between the Distribution of Eigenvalues in Multiple Correspondence Analysis and Log-Linear Models

open access: yesRevstat Statistical Journal, 2003
Multiple Correspondence Analysis (MCA) and log-linear modeling are two techniques for multi-way contingency table analysis having different approaches and fields of applications.
S. Ben Ammou , G. Saporta
doaj   +1 more source

Mean-parametrized Conway-Maxwell-Poisson regression models for dispersed counts

open access: yes, 2017
Conway-Maxwell-Poisson (CMP) distributions are flexible generalizations of the Poisson distribution for modelling overdispersed or underdispersed counts.
Huang, Alan
core   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

open access: yesMolecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix   +13 more
wiley   +1 more source

Model-based Prediction of Length of Stay for Rehabilitating Stroke Patients

open access: yesJournal of the Formosan Medical Association, 2009
Accurate length-of-stay (LOS) estimates have an impact on medical costs for stroke patients. Most studies have reported only descriptive sample means or have provided linear-model-based estimates for LOS.
Chien-Lin Lin   +6 more
doaj   +1 more source

Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin

open access: yesMolecular Oncology, EarlyView.
The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla   +10 more
wiley   +1 more source

Therapeutic strategies for MMAE‐resistant bladder cancer through DPP4 inhibition

open access: yesMolecular Oncology, EarlyView.
We established monomethyl auristatin E (MMAE)‐resistant bladder cancer (BC) cell lines by exposure to progressively increasing concentrations of MMAE in vitro. RNA sequencing showed DPP4 expression was increased in MMAE‐resistant BC cells. Both si‐DPP4 and the DPP4 inhibitor sitagliptin suppressed the viability of MMAE‐resistant BC cells.
Gang Li   +10 more
wiley   +1 more source

Local Riemannian geometry of model manifolds and its implications for practical parameter identifiability.

open access: yesPLoS ONE, 2019
When non-linear models are fitted to experimental data, parameter estimates can be poorly constrained albeit being identifiable in principle. This means that along certain paths in parameter space, the log-likelihood does not exceed a given statistical ...
Daniel Lill, Jens Timmer, Daniel Kaschek
doaj   +1 more source

Power estimation of tests in log-linear non-uniform association models for ordinal agreement

open access: yesBMC Medical Research Methodology, 2011
Background Log-linear association models have been extensively used to investigate the pattern of agreement between ordinal ratings. In 2007, log-linear non-uniform association models were introduced to estimate, from a cross-classification of two ...
Mary Jean-Yves, Valet Fabien
doaj   +1 more source

Linear and Parallel Learning of Markov Random Fields [PDF]

open access: yes, 2014
We introduce a new embarrassingly parallel parameter learning algorithm for Markov random fields with untied parameters which is efficient for a large class of practical models. Our algorithm parallelizes naturally over cliques and, for graphs of bounded
de Freitas, Nando   +2 more
core   +1 more source

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