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Psychological resilience and perceived stress among Chinese medical students: mediation between optimistic intelligence quotient and adversity quotient.
BMC Med Educ
November 2024
Institute of Medical Humanities, Wenzhou Medical University, Wenzhou, China.
Background: Chinese medical students face rigorous academic demands and exacting professional challenges, which lead to significant psychological stress. Understanding perceived stress and psychological resilience is key to enhancing emotional regulation and empathy. This study explores the hypothesis that psychological resilience impacts the perceived stress of medical students, with the Optimistic Intelligence Quotient (OQ) and the Adversity Quotient (AQ) acting as serial mediators, thereby promoting students' mental health.
View Article and Find Full Text PDFEffectiveness of a Structured Trauma Template in Improving Clinical Examination Accuracy in Maxillofacial Trauma: A Prospective Study.
Craniomaxillofac Trauma Reconstr
August 2024
Department of Dentistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India.
Article Synopsis
- The study was a prospective pre-post design aimed at improving the quality of documentation for maxillofacial trauma in the emergency department using a structured template.
- By evaluating 220 patients, it found an 18.95% improvement in record completeness when using the template, particularly in key areas like time of evaluation and ophthalmic assessments.
- The findings suggest that the structured template enhances thoroughness and accuracy in documenting injuries, leading to better clinical care and reduced risk of medical negligence.
Multifunctional Porous Bilayer Artificial Skin for Enhanced Wound Healing.
ACS Appl Mater Interfaces
July 2024
State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China.
Meeting the exacting demands of wound healing encompasses rapid coagulation, superior exudate absorption, high antibacterial efficacy, and imperative support for cell growth. In this study, by emulating the intricate structure of natural skin, we prepare a multifunctional porous bilayer artificial skin to address these critical requirements. The bottom layer, mimicking the dermis, is crafted through freeze-drying a gel network comprising carboxymethyl chitosan (CMCs) and gelatin (GL), while the top layer, emulating the epidermis, is prepared via electrospinning poly(l-lactic acid) (PLLA) nanofibers.
View Article and Find Full Text PDFPrioritizing Clinically Significant Lung Cancer Somatic Mutations for Targeted Therapy Through Efficient NGS Data Filtering System.
AMIA Jt Summits Transl Sci Proc
May 2024
UTHealth Houston McWilliams School of Biomedical Informatics, Texas, USA.
In the realm of lung cancer treatment, where genetic heterogeneity presents formidable challenges, precision oncology demands an exacting approach to identify and hierarchically sort clinically significant somatic mutations. Current Next-Generation Sequencing (NGS) data filtering pipelines, while utilizing various external databases for mutation screening, often fall short in comprehensive integration and flexibility needed to keep pace with the evolving landscape of clinical data. Our study introduces a sophisticated NGS data filtering system, which not only aggregates but effectively synergizes diverse data sources, encompassing genetic variants, gene functions, clinical evidence, and an extensive body of literature.
View Article and Find Full Text PDFIn the context of the burgeoning progression of wireless network technology and the corresponding escalation in the demand for mobile Internet-based multimedia transmission services, the task of preserving and augmenting user satisfaction has emerged as an imperative concern. This necessitates a sophisticated and accurate evaluation of multimedia service quality within the sphere of wireless networks. To systematically address the nuanced issue of user experience quality, the present study introduces a novel method for evaluating multimedia Quality of Experience (QoE) in wireless networks, employing an advanced deep learning model as the underlying analytical framework.
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