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Co-Designing a Digital Brief Intervention to Reduce the Risk of Prescription Opioid-Related Harm Among People With Chronic Noncancer Pain: Qualitative Analysis of Patient Lived Experiences.
JMIR Form Res
January 2025
Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Background: Opioid medications are important for pain management, but many patients progress to unsafe medication use. With few personalized and accessible behavioral treatment options to reduce potential opioid-related harm, new and innovative patient-centered approaches are urgently needed to fill this gap.
Objective: This study involved the first phase of co-designing a digital brief intervention to reduce the risk of opioid-related harm by investigating the lived experience of chronic noncancer pain (CNCP) in treatment-seeking patients, with a particular focus on opioid therapy experiences.
High Areal Loading Silicon Nanoparticle-Based Lithium-Ion Batteries.
ACS Appl Mater Interfaces
January 2025
Electrical & Computer Engineering Department, Montana State University, Bozeman, Montana 59717, United States.
Interfacial mechanical stability between silicon (Si) and the current collector is crucial when high areal-loading of Si is demanded as intense stress develops at the interface due to its extreme volume alteration during the lithiation-delithiation process. Therefore, we propose using a thin, rough, porous, and highly conductive carbon nanotube network (CNT-N) as a buffer layer between the Si and current collector that provides abundant anchor sites for Si nanoparticles. The strong and elastic CNT-N, which is not involved directly in the lithiation process, reduces stress at interfaces between the Si and CNT-N and the CNT-N and current collector.
View Article and Find Full Text PDFCoevolutionary dynamics in the grass-livestock social-ecological system of China's alpine pastoral areas: A case study of the Qilian Mountains region in China.
PLoS One
January 2025
Department of Geography, University College London, London, England, United Kingdom.
Evaluating the dynamic co-evolution and feedback mechanisms within socio-ecological systems is crucial for determining the resilience and sustainability of environmental governance strategies. The grass-livestock system, as a complex entity encompassing livestock nutrition, foraging behavior, vegetation ecology, pastoralists' economic income, and policy interventions, indicates that any change in a single element may trigger a chain reaction within the system. This paper uses a system dynamics approach to construct a simulation model of the grass-livestock system in alpine pastoral areas, simulating the long-term dynamic co-evolution of the socio-ecological system in the Qilian Mountains region of China.
View Article and Find Full Text PDFEstablishment of subcutaneous transplantation platform for delivering induced pluripotent stem cell-derived insulin-producing cells.
PLoS One
January 2025
Faculty of Veterinary Science, Veterinary Clinical Stem Cell and Bioengineering Research Unit, Chulalongkorn University, Bangkok, Thailand.
Potential trend of regenerative treatment for type I diabetes has been introduced for more than a decade. However, the technologies regarding insulin-producing cell (IPC) production and transplantation are still being developed. Here, we propose the potential IPC production protocol employing mouse gingival fibroblast-derived induced pluripotent stem cells (mGF-iPSCs) as a resource and the pre-clinical approved subcutaneous IPC transplantation platform for further clinical confirmation study.
View Article and Find Full Text PDFISLRWR: A network diffusion algorithm for drug-target interactions prediction.
PLoS One
January 2025
Shanghai Xinhao Information Technology Co., Ltd., Shanghai, China.
Machine learning techniques and computer-aided methods are now widely used in the pre-discovery tasks of drug discovery, effectively improving the efficiency of drug development and reducing the workload and cost. In this study, we used multi-source heterogeneous network information to build a network model, learn the network topology through multiple network diffusion algorithms, and obtain compressed low-dimensional feature vectors for predicting drug-target interactions (DTIs). We applied the metropolis-hasting random walk (MHRW) algorithm to improve the performance of the random walk with restart (RWR) algorithm, forming the basis by which the self-loop probability of the current node is removed.
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