Results 41 to 50 of about 103,708 (231)

Crucial parameters for precise copy number variation detection in formalin‐fixed paraffin‐embedded solid cancer samples

Molecular Oncology, EarlyView.
This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris, Vasiliki Siozopoulou, Léon C van Kempen, Anne Sieben, Ella Roelant, Stig Hellemans, Elyne Backx, Laure Sorber, Koen De Winne, Senada Koljenović, Karen Zwaenepoel   +10 more
wiley   +1 more source

Naturalistic reinforcement learning

Trends in Cognitive Sciences
Humans possess a remarkable ability to make decisions within real-world environments that are expansive, complex, and multidimensional. Human cognitive computational neuroscience has sought to exploit reinforcement learning (RL) as a framework within which to explain human decision-making, often focusing on constrained, artificial experimental tasks ...
Wise, Toby, Emery, Kara, Radulescu, Angela   +2 more
openaire   +2 more sources

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Overview of molecular signatures of senescence and associated resources: pros and cons

FEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source

Efficient Hindsight Experience Replay with Transformed Data Augmentation

Journal of Applied Science and Engineering, 2023
Motion control of robots is a high-dimensional, nonlinear control problem that is often difficult to handle using traditional dynamical path planning means.
Jiazheng Sun, Weiguang Li
doaj   +1 more source

Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications

FEBS Open Bio, EarlyView.
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley   +1 more source

Safe Model-Based Reinforcement Learning for Systems With Parametric Uncertainties

Frontiers in Robotics and AI, 2021
Reinforcement learning has been established over the past decade as an effective tool to find optimal control policies for dynamical systems, with recent focus on approaches that guarantee safety during the learning and/or execution phases.
S. M. Nahid Mahmud, Scott A. Nivison, Zachary I. Bell, Rushikesh Kamalapurkar   +3 more
doaj   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

A Qualitative Analysis of Patient Perspectives and Preferences in Lupus Management to Guide Lupus Guidelines Development

Arthritis Care &Research, EarlyView.
Objective A patient‐centered approach for chronic disease management, including systemic lupus erythematosus (SLE), aligns treatment with patients’ values and preferences, leading to improved outcomes. This paper summarizes how patient experiences, perspectives, and priorities informed the American College of Rheumatology (ACR) 2024 Lupus Nephritis (LN)
Shivani Garg, Izzy Hartel, Lisa R. Sammaritano, Anca Askanase, Bonnie L. Bermas, Maria Dall'Era, Alí Duarte‐García, Victoria P. Werth, Brad Rovin, Reem A. Mustafa, Amy S. Turner, Bené Williams, Brian L. Ung, Hiya Bhavsar, Monique C. Gore‐Massy, Nahirannette Pulido, Natacha Guerrero, Natalie M. Smith, Wambui Machua, Linda T. Hiraki, Mary Beth Son   +20 more
wiley   +1 more source

Evaluation of a novel EHR sidecar application to display RA clinical outcomes during clinic visits: results of a stepped‐wedge cluster randomized pragmatic trial

Arthritis Care &Research, Accepted Article.
Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk, Jing Li, Cathy Nasrallah, Cherish Wilson, Alicia Hamblin, Christine Hariz, Cammie Young, Stephen Shiboski, Emma Kersey, Mary Nakamura, Judith F. Ashouri, Mehrdad Matloubian, Andrew J. Gross, Jennifer Barton, Beth Berrean, Jonathan Prugh, Jinoos Yazdany   +16 more
wiley   +1 more source