Results 241 to 250 of about 2,011,711 (312)

Longitudinal genome‐wide aneuploidy measurements in circulating cell‐free DNA to predict lack of benefit from pembrolizumab in patients with metastatic urothelial cancer

Molecular Oncology, EarlyView.
Many patients with urothelial cancer do not benefit from treatment with pembrolizumab, while at risk of severe side effects. Changes in the levels of circulating tumor DNA early during treatment, measured by a simple and affordable assay that can be easily implemented in the clinic, can be used as a prognostic tool to identify these patients.
Youssra Salhi, Stavros Makrodimitris, Sandra van Wilpe, Iris te Paske, Vanja de Weerd, Corine M. Beaufort, Hans M. Westgeest, Jens Voortman, Maureen J. B. Aarts, Maud Rijnders, Astrid A. M. van der Veldt, Ronald de Wit, Niven Mehra, Saskia M. Wilting, Debbie G. J. Robbrecht   +14 more
wiley   +1 more source

Automated Evaluation of Urodynamic Examinations Through Local Linear Models: Validation on Spinal Cord Injury Individuals. [PDF]

IEEE J Transl Eng Health Med
Zhang W, Pannek J, Wollner J, Riener R, Paez-Granados D.   +4 more
europepmc   +1 more source

MITF maintains genome stability in nonmelanocyte lineages

Molecular Oncology, EarlyView.
MITF is essential for melanocyte survival and acts as an oncogene in 10%–20% of melanomas. We show that MITF depletion causes genome instability in nonmelanocytic cells, leading to LATS2‐mediated P53 activation, cell cycle arrest, and apoptosis. This study highlights the role of MITF as a genome maintenance factor beyond the melanocyte lineage. Created
Drifa H. Gudmundsdottir, Adrián López García de Lomana, Thejus B. Venkatesh, Kritika Kirty, Snaevar Sigurdsson, Linda Vidarsdottir, Ramile Dilshat, Erla Sveinbjornsdottir, Snaedis Ragnarsdottir, Daniel H Magnusson, Maria R. Bustos, Eirikur Steingrimsson, Thorkell Gudjonsson, Stefan Sigurdsson   +13 more
wiley   +1 more source

A framework for optimal control of oscillations and synchrony applied to non-linear models of neural population dynamics. [PDF]

Front Comput Neurosci
Salfenmoser L, Obermayer K.
europepmc   +1 more source

A novel quinazolinone insulin receptor inhibitor and its synergy with an EGFR inhibitor in glucose‐driven glioblastoma

Molecular Oncology, EarlyView.
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka, Wioleta Cieślik, Wojciech Płaziński, Katarzyna Stępnik, Anna Boguszewska‐Czubara, Elżbieta Kot, Robert Musioł, Mateusz Jasica, Anna Mrozek‐Wilczkiewicz, Katarzyna Malarz   +9 more
wiley   +1 more source

Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization

Molecular Oncology, EarlyView.
In the current study, we demonstrate that the oncogene DMTF1β regulates ULK1 stability by reducing its proteasomal degradation in cancer cells. This stabilization enables ULK1 to induce autophagy, which in turn facilitates cancer cell migration. Consequently, reduced DMTF1β levels lead to decreased autophagy and impaired cancer cell migration.
Jun Xu, Nicolas J. Niklaus, Anna M. Schläfli, Igor Tokarchuk, Magali Humbert, Federico La Manna, Bich Vu, David Maul, Ramin Radpour, Marianna Kruithof‐de Julio, Inti Zlobec, Jörn Dengjel, Bruce E. Torbett, Mario P. Tschan   +13 more
wiley   +1 more source

Doubly Robust Estimation and Semiparametric Efficiency in Generalized Partially Linear Models with Missing Outcomes. [PDF]

Stats (Basel)
Wang L, Ouyang Z, Lin X.
europepmc   +1 more source

Comparing penalization methods for linear models on large observational health data. [PDF]

J Am Med Inform Assoc
Fridgeirsson EA, Williams R, Rijnbeek P, Suchard MA, Reps JM.   +4 more
europepmc   +1 more source

Generalized linear models

, 1989
Nelder, J. A., Mccullagh, P.
core  

Distributed Heterogeneity Learning for Generalized Partially Linear Models with Spatially Varying Coefficients. [PDF]

J Am Stat Assoc
Yu S, Wang G, Wang L.
europepmc   +1 more source