Results 171 to 180 of about 2,452,838 (337)

Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

Molecular Oncology, EarlyView.
The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg, Joachim von Braun, Julio Celis, Anton Berns, Michael Baumann, Tit Albreht, Nancy Abou‐Zeid, Vanderlei Bagnato, Christian Brandts, Chien‐Jen Chen, Massimiliano di Pietro, Manjit Dosanjh, Thomas Dubois, Alexander Eggermont, Angelika Eggert, Ingemar Ernberg, Sara Faithfull, Johannes Förner, Stefan Fröhling, Manuel Heitor, Leroy Hood, Wei Jiang, Bengt Jönsson, Ravi Kannan, Maria Leptin, Su Li, Peter Lindgren, Douglas Lowy, Jun Ma, Alex Markham, Péter Nagy, Simon Oberst, M. Iqbal Parker, Danielle Rodin, Kevin Ryan, Joachim Schüz, Richard Sullivan, Josep Tabernero, Peter Turkson, Oliver Várhelyi, Harold Varmus, Chijie Wang, Elisabete Weiderpass, Nils Wilking   +43 more
wiley   +1 more source

FlexLMM: a Nextflow linear mixed model framework for GWAS. [PDF]

Bioinformatics
Pierotti S, Fitzgerald T, Birney E.
europepmc   +1 more source

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations. [PDF]

Comput Struct Biotechnol J, 2023
Li G, Zhou YH, Li HF, Zhang YM.
europepmc   +1 more source

Cell surface interactome analysis identifies TSPAN4 as a negative regulator of PD‐L1 in melanoma

Molecular Oncology, EarlyView.
Using cell surface proximity biotinylation, we identified tetraspanin TSPAN4 within the PD‐L1 interactome of melanoma cells. TSPAN4 negatively regulates PD‐L1 expression and lateral mobility by limiting its interaction with CMTM6 and promoting PD‐L1 degradation.
Guus A. Franken, Andrea Abel Gutierrez, Imke van Rossum, Cornelia G. Spruijt, Michiel Vermeulen, Guido van Mierlo, Blanca Scheijen, Annemiek B. van Spriel   +7 more
wiley   +1 more source

Comparison between linear mixed model and threshold model in the estimation of variance components in age at first calving and milk production in buffaloes. [PDF]

Front Vet Sci
Camargo-Júnior RNC, de Araújo CV, Gomes MNB, Marques JRF, da Silva WC, Sousa CEL, de Andrade RL, de Oliveira AS, da Silva ÉBR, Cara JRF, Lourenço-Júnior JB, Santos AM, Silva AGME.   +12 more
europepmc   +1 more source

Assessment of influencing factors of hospitalization expenses for Crohn's disease patients: Based on LASSO and linear mixed model. [PDF]

Front Public Health, 2022
Wu L, Lv Z, Lai L, Zhou P.
europepmc   +1 more source

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

Molecular 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, Peter T. Gallagher, Orly I. Richter, Neermala Poudel Neupane, Amy C. Mandigo, Jennifer J. McCann, Emanuela Dylgjeri, Irina Vasilevskaya, Christopher McNair, Channing J. Paller, Wm. Kevin Kelly, Karen E. Knudsen, Matthew J. Schiewer, Ayesha A. Shafi   +13 more
wiley   +1 more source

Generalized linear mixed model approach for analyzing water, sanitation, and hygiene facilities in Bangladesh: Insights from BDHS 2022 data. [PDF]

PLoS One
Mim MS, Rahaman ML, Sajib AH.
europepmc   +1 more source

RPackagewgaim: QTL Analysis in Bi-Parental Populations Using Linear Mixed Models

, 2011
Julian Taylor, A. P. Verbyla
openalex   +1 more source

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

Molecular 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, Daniel Samaga, Katharina Gehr, Benedek Dankó, Mohamed Schumann, Guido Drexler, Ahmed Alnatsha, Georg Beyer, Ujjwal Mahajan, Martin Selmansberger, Julia Mayerle, Claus Belka, Horst Zitzelsberger, Kirsten Lauber   +13 more
wiley   +1 more source