Results 31 to 40 of about 25,524 (260)

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

Pharmacological inhibition of the PERK pathway modulates hepatocellular carcinoma growth and immune signaling

FEBS Open Bio, EarlyView.
Pharmacological inhibition of PERK in a DEN‐induced mouse model of liver cancer does not reduce tumor burden but alters cellular stress signaling. Despite blocking PERK activity, downstream stress responses, including CHOP expression, remain active, suggesting compensatory mechanisms within the unfolded protein response that may influence tumor ...
Ada Lerma‐Clavero, Maria Kopsida, Nathalie Arendt, Hans Lennernäs, Markus Sjöblom, Femke Heindryckx   +5 more
wiley   +1 more source

Derivative-Free Nonlinear Kalman Filtering for MIMO Dynamical Systems: Application to Multi-DOF Robotic Manipulators

International Journal of Advanced Robotic Systems, 2011
The paper proposes derivative-free nonlinear Kalman Filtering for MIMO nonlinear dynamical systems. The considered nonlinear filtering scheme which is based on differential flatness theory extends the class of systems to which Kalman Filtering can be ...
Gerasimos G. Rigatos
doaj   +1 more source

DETERMINISTIC LEARNING OF NONLINEAR DYNAMICAL SYSTEMS

International Journal of Bifurcation and Chaos, 2009
In this paper, we investigate the problem of identifying or modeling nonlinear dynamical systems undergoing periodic and period-like (recurrent) motions. For accurate identification of nonlinear dynamical systems, the persistent excitation condition is normally required to be satisfied.
Cong Wang 0007, Tianrui Chen, Guanrong Chen, David J. Hill 0001   +3 more
openaire   +2 more sources

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data

Entropy, 2019
Recurrent neural networks (RNNs) are nonlinear dynamical models commonly used in the machine learning and dynamical systems literature to represent complex dynamical or sequential relationships between variables.
Patrick L. McDermott, Christopher K. Wikle   +1 more
doaj   +1 more source

Optimizing photoexcitation conditions for time‐resolved X‐ray solution scattering experiments

FEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering (TR‐XSS) is a powerful technique to visualize how proteins change their structure in real time after light activation. Selecting the right laser photoexcitation conditions—fluence, excitation geometry, and sample refresh rate—is critical to maximize the experimental signal while avoiding unwanted side effects ...
Matteo Levantino
wiley   +1 more source

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

Evaluation of Dried Plasma Spot‐Based Quantification of Glial Fibrillary Acidic Protein as a Disease‐Associated Biomarker in Neuromyelitis Optica Spectrum Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the diagnostic accuracy of glial fibrillary acidic protein (GFAP) measured in dried plasma spots versus conventional plasma‐ and serum‐GFAP testing for assessment of disease severity in aquaporin‐4 immunoglobulin G–positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD).
Felix Wohlrab, Evelyn Alvarez, Roua Hamdi, Bingqing Zhang, Hayeun Ji, Niyati Jhaveri, Patrick Schindler, Pedro Sanchez, Pia S. Sperber, Tanja Schmitz‐Hübsch, Frederike C. Oertel, Nisa Vorasoot, Najib Kissani, Falko Böhringer, Jens Kuhle, Anne‐Katrin Pröbstel, Xiao‐Jun Ma, Péter Körtvelyessy, Patrick Waters, Friedemann Paul   +19 more
wiley   +1 more source

Dimensionality reduction of complex dynamical systems

iScience, 2021
Summary: One of the outstanding problems in complexity science and engineering is the study of high-dimensional networked systems and of their susceptibility to transitions to undesired states as a result of changes in external drivers or in the ...
Chengyi Tu, Paolo D'Odorico, Samir Suweis   +2 more
doaj   +1 more source