Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
The effect of dynamic neuromuscular stabilization technique combined with Kinesio Taping on neuromuscular function and pain self-efficacy in individuals with chronic nonspecific low back pain: A randomized trial.
Medicine (Baltimore)
January 2025
Second Hospital of the Air Force Medical University, Xi 'an, China.
Background: This study investigates the therapeutic efficacy of dynamic neuromuscular stabilization (DNS) technology paired with Kinesio Taping in patients with persistent nonspecific low back pain, as well as the effect on neuromuscular function and pain self-efficacy.
Methods: A randomized controlled clinical study was conducted to collect clinical data on DNS combined with KT for the treatment of chronic nonspecific low back pain from November 2023 to April 2024. The inclusion criteria were patients with chronic nonspecific lower back pain, aged between 18 and 30 years old, and without serious underlying medical conditions, such as cardiac disease, hypertension, and diabetes.
Distinct neural computations scale the violation of expected reward and emotion in social transgressions.
Commun Biol
January 2025
Department of Psychology, The University of Hong Kong, Hong Kong, China.
Traditional decision-making models conceptualize humans as adaptive learners utilizing the differences between expected and actual rewards (prediction errors, PEs) to maximize outcomes, but rarely consider the influence of violations of emotional expectations (emotional PEs) and how it differs from reward PEs. Here, we conducted a fMRI experiment (n = 43) using a modified Ultimatum Game to examine how reward and emotional PEs affect punishment decisions in terms of rejecting unfair offers. Our results revealed that reward relative to emotional PEs exerted a stronger prediction to punishment decisions.
View Article and Find Full Text PDFMotion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.
Invest Radiol
January 2025
From the Department of Radiology, Stanford University, Stanford, CA (K.W., M.J.M., A.M.L., A.B.S., A.J.H., D.B.E., R.L.B.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA (K.W.); GE HealthCare, Houston, TX (X.W.); GE HealthCare, Boston, MA (A.G.); and GE HealthCare, Menlo Park, CA (P.L.).
Objectives: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal.
View Article and Find Full Text PDFUnraveling the Role of Oxygen Pulse Variability in Endurance Exercise Training in Individuals with COPD: A Novel Approach to Response of Oxygen Pulse and Quality of Life in Pulmonary Rehabilitation.
Int J Chron Obstruct Pulmon Dis
January 2025
Division of Pulmonary Medicine, Taipei Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, New Taipei City, Taiwan, Republic of China.
Background: Chronic obstructive pulmonary disease (COPD) is characterized by airway inflammation, airflow limitation, reduced health-related quality of life (HRQL), and exercise intolerance. Pulmonary rehabilitation (PR) is essential for COPD management, but outcomes may be influenced by individual physiological factors. Cardiopulmonary exercise testing (CPET) measures oxygen pulse (O2P), an indicator of stroke volume, yet the impact of baseline O2P on PR effectiveness remains unclear.
View Article and Find Full Text PDFContrastive Graph Representation Learning with Adversarial Cross-View Reconstruction and Information Bottleneck.
Neural Netw
January 2025
School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China; Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an, 710049, China. Electronic address:
Graph Neural Networks (GNNs) have received extensive research attention due to their powerful information aggregation capabilities. Despite the success of GNNs, most of them suffer from the popularity bias issue in a graph caused by a small number of popular categories. Additionally, real graph datasets always contain incorrect node labels, which hinders GNNs from learning effective node representations.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!