Clinical research is of major importance to today's society, as scientific evidence is increasingly demanded as a basis for progress, whether this involves developing new healthcare products, improving clinical practice and care protocols or progress in prevention. Clinical research therefore requires professionals who are both experienced and increasingly well trained. Against this background, allied health professionals are becoming involved more and more, both as team members supporting clinical research projects and as managers or coordinators of projects in their own field. Clinical research activities provide an ideal opportunity for continuing professional development. All of this means that the professional skills of the allied health professions and clinical research support professions must be enhanced, their role promoted in the context of lecturer status and in the longer term, their status recognised by the supervisory authorities.
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http://dx.doi.org/10.2515/therapie/2014041 | DOI Listing |
Adv Skin Wound Care
January 2025
In the Oncology Department of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province, China, Meichen Du, MD, is Senior Practical Nurse and Mei Liu, MD, is Head Nurse.
Objective: To evaluate research on medical adhesive-related skin injury (MARSI), focusing on its incidence, prevalence, risk factors, causes, assessments, and prevention.
Data Sources: Searches were conducted on Wanfang Data, China National Knowledge Infrastructure, PubMed, Web of Science Core Collection, MEDLINE, EMBASE, and the Cumulative Index of Nursing and Allied Health Literature Plus with Full Text.
Study Selection: Using search terms "medical adhesive related skin injury", "MARSI", "adhesive skin injury", and "medical tape-induced skin injury", the authors selected 43 original articles published between January 1, 2001, and May 12, 2022, in English or Chinese.
Viral Immunol
January 2025
Faculty of Allied Health Sciences, Burapha University, Muang, Thailand.
Chronic hepatitis C virus (HCV) infection poses a major health risk worldwide, with patients susceptible to liver cirrhosis and hepatocellular carcinoma. This study focuses on the development of effective therapeutic strategies for HCV infection through the investigation of immunogenic properties of a DNA construct based on the NS3/4A gene of HCV genotype (g)3a. Gene expression of the mutagenized (mut) NS3/4A target genes was assessed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western blot analysis.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Department of Pediatrics, University of Minnesota, Minneapolis.
Mol Neurobiol
January 2025
Hebei Medical University-Galway University Stem Cell Research Center, Hebei Medical University, Shijiazhuang, 050017, Hebei Province, China.
This study utilises amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) human brain samples from the GEO database and employs differential expression gene (DEG) analysis to identify genes that are pivotal in both neurodegenerative diseases. Through in depth GO and KEGG enrichment analyses, we elucidated the biological functions and potential pathways associated with these DEGs. Furthermore, by constructing protein‒protein interaction networks, we highlight the significance of shared DEGs in both cellular physiology and disease contexts.
View Article and Find Full Text PDFCurr Res Transl Med
January 2025
Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, United Kingdom.
This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.
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