Results 151 to 160 of about 25,040,689 (239)

Deterministic and ANN-based modelling of measles transmission using real epidemiological data. [PDF]

Sci Rep
Shah K, Du C, Akgül A, Alshammari FS, Bajri SA, Khalifa HAE.   +5 more
europepmc   +1 more source

NAPRT loss promotes lung tumor initiation and growth through AKT signaling independently of NAD+ biosynthesis

Molecular Oncology, EarlyView.
Loss of NAPRT promotes lung tumor initiation and growth through a noncanonical mechanism, independent of its role in NAD+ biosynthesis. Mechanistically, NAPRT depletion activates the mTORC2‐driven AKT/β‐catenin signaling axis to enhance clonogenic and invasive phenotypes. Furthermore, lung‐specific Naprt deletion significantly increases tumor burden in
Myung Joon Oh, Ji Yun Jang, Yoon Jeon, Gi‐Cheon Kim, Hwanho Lee, Jooyoung Lee, Ju‐Hwa Kim, Hakhyun Kim, Minjee Kim, Ho‐Keun Kwon, Ho Lee, Hyun Seok Kim   +11 more
wiley   +1 more source

Predictive processing as a scalable computational principle for embodied multitask intelligence. [PDF]

Sci Adv
Idei H, Miyake T, Ogata T, Yamashita Y.
europepmc   +1 more source

p190A/ARHGAP35 and p190B/ARHGAP5 proteins in endometrial cancer: a novel cancer‐relevant paralog interplay

Molecular Oncology, EarlyView.
This study identifies ARHGAP5, in addition to the frequently mutated ARHGAP35, as significantly mutated in endometrial cancer. Mutations in both genes co‐occur and are associated with their correlated downregulation. Functional CRISPR studies show that both paralogs regulate similar pathways, including actin cytoskeleton organization.
Mathilde Pinault, Capucine Heraud, Mélissa Correia de Oliveira, Véronique Neaud, Valérie Valesco, Valérie Prouzet‐Mauleon, Béatrice Turcq, Jean‐William Dupuy, Anne‐Aurélie Raymond, Sabrina Croce, Frédéric Saltel, Valérie Lagrée, Violaine Moreau   +12 more
wiley   +1 more source

Regret and Conservatism of Constrained Stochastic Model Predictive Control

We analyse conservatism and regret of stochastic model predictive control (SMPC) when using moment-based ambiguity sets for modeling unknown uncertainties.
Findeisen, Rolf,, Lund University., Pfefferkorn, Maik,, Renganathan, Venkatraman,   +3 more
core  

Predictive value of nutritional biomarkers for immune checkpoint inhibitor efficacy in patients with non-small cell lung cancer. [PDF]

Front Nutr
Zhang W, Liu X.
europepmc   +1 more source

Bridging the gap: a genetically validated avian chorioallantoic membrane platform for investigation of spontaneous circulating tumor cells

Molecular Oncology, EarlyView.
We established the avian chorioallantoic membrane (CAM) assay as a scalable in vivo model for studying circulating tumor cells (CTCs). Human gastrointestinal tumors spontaneously released genetically validated CTCs that were detected across multiple platforms, demonstrating that the CAM model provides an accessible tool for investigating early cancer ...
Dennis Roth, Rui P. L. Neves, Julia Geheb, Christian Ballmeyer, Nathalie Gaßmann, Kiki C. Andree, Monica Sudarsanam, Christiane Driemel, Celine Örencik, Andrè Franken, Eslam Elmaghraby, Sven H. Loosen, Roderburg Christoph, Sebastian Schoelch, Hans Neubauer, Wolfram T. Knoefel, Nikolas H. Stoecklein, Georg Fluegen   +17 more
wiley   +1 more source

Spatially resolved longitudinal changes in tibial subchondral trabecular bone texture for exploratory prediction of incident knee osteoarthritis. [PDF]

Front Physiol
Almhdie-Imjabbar A, Toumi H, Lespessailles E.   +2 more
europepmc   +1 more source

Unique circulating miRNAome signatures captured with distinct molecular states in Lynch syndrome and sporadic colorectal cancer

Molecular Oncology, EarlyView.
Circulating microRNA profiles distinguish nonmalignant Lynch syndrome from cancer‐associated Lynch syndrome, sporadic colorectal cancer, and healthy controls. Age‐stratified analysis reveals disease‐specific regulatory states, and a six‐miRNA panel shows concordant separation in an independent colorectal tissue cohort.
Ramadhani Salum Chambuso, Md Shohel Ul Islam, Rosa M Xicola, Raj Ramesar, Xavier Llor, Sinclair Steele   +5 more
wiley   +1 more source

How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions. [PDF]

Bull Math Biol
Rabiei K, Rempala GA, Laubenbacher R, Hao W.   +3 more
europepmc   +1 more source