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http://dx.doi.org/10.4103/0019-5545.91910 | DOI Listing |
Mol Biotechnol
January 2025
Medical Biotechnology and Immunotherapy Research Unit, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, 7700, South Africa.
The field of gene therapy has witnessed significant advancements in the utilization of Adeno-associated virus (AAV) owing to its inherent biological advantages. Targeted AAV vectors are generated through genetic or chemical modification of the capsid for user-directed purposes. However, this process can result in imbalances in viral protein sequence homogeneity, stoichiometry, and functional transduction vector units, thereby introducing new challenges.
View Article and Find Full Text PDFAm J Chin Med
January 2025
First Clinical Medical College, Yunnan University of Chinese Medicine, Kunming Yunnan 650500, P. R. China.
Osteoarthritis (OA) is the most common chronic degenerative joint disease, characterized by cartilage damage, synovial inflammation, subchondral bone sclerosis, marginal bone loss, and osteophyte development. Clinical manifestations include inflammatory joint pain, swelling, osteophytes, and limitation of motion. The pathogenesis of osteoarthritis has not yet been fully uncovered.
View Article and Find Full Text PDFJ Struct Biol
January 2025
School of Mathematical Sciences, Tel Aviv University, Tel Aviv, Israel.
The process of particle picking, a crucial step in cryo-electron microscopy (cryo-EM) image analysis, often encounters challenges due to outliers, leading to inaccuracies in downstream processing. In response to this challenge, this research introduces an additional automated step to reduce the number of outliers identified by the particle picker. The proposed method enhances both the accuracy and efficiency of particle picking, thereby reducing the overall running time and the necessity for expert intervention in the process.
View Article and Find Full Text PDFCell Rep Med
January 2025
DiMePRe-J-Department of Precision and Rigenerative Medicine-Jonic Area, University of Bari "Aldo Moro", Bari, Italy.
The diagnosis of autism is currently based on the developmental history, direct observation of behavior, and reported symptoms, supplemented by rating scales/interviews/structured observational evaluations-which is influenced by the clinician's knowledge and experience-with no established diagnostic biomarkers. A growing body of research has been conducted over the past decades to improve diagnostic accuracy. Here, we provide an overview of the current diagnostic assessment process as well as of recent and ongoing developments to support diagnosis in terms of genetic evaluation, telemedicine, digital technologies, use of machine learning/artificial intelligence, and research on candidate diagnostic biomarkers.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
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