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Neural stem cell-derived extracellular vesicles purified by monolith chromatography retain stimulatory effect in in vitro scratch assay.
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Institute of Immunology and Immunotherapy, College of Medicine and Health, University of Birmingham, Birmingham, UK. Electronic address:
Background Aims: Extracellular vesicles (EVs) have gained traction as potential cell-free therapeutic candidates. Development of purification methods that are scalable and robust is a major focus of EV research. Yet there is still little in the literature that evaluates purification methods against potency of the EV product.
View Article and Find Full Text PDFThe impact of weight loss after bariatric surgeries on the patient's body image, quality of life, and self-esteem.
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Department of Public Health and Community Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Objectives: The objective of this web-based study is to analyze the attributes of bariatric surgery cases ensuing health implications. Additionally, the study seeks to delve into the factors influencing post-bariatric psychological evaluations and the impact of various bariatric surgeries on weight loss and psycho-social assessment scores for patients who had undergone bariatric surgeries within a specific bariatric surgery center in Egypt between January 2017 and January 2024.
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An integrated DEA-fuzzy AHP method for prioritization of renewable energy sources in India.
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Department of Mathematics, Birla Institute of Technology and Science Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India.
As India's population grows and urbanization accelerates, energy demand is increasing sharply while conventional sources fall behind. To tackle energy shortages and climate change, India must prioritize renewable energy sources (RES), which offer sustainable solutions. The country is rich in RES, which can enhance fuel mix for electricity generation.
View Article and Find Full Text PDFOpen challenges and opportunities in federated foundation models towards biomedical healthcare.
BioData Min
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School of Computer Science, Fudan University, Shanghai, China.
This survey explores the transformative impact of foundation models (FMs) in artificial intelligence, focusing on their integration with federated learning (FL) in biomedical research. Foundation models such as ChatGPT, LLaMa, and CLIP, which are trained on vast datasets through methods including unsupervised pretraining, self-supervised learning, instructed fine-tuning, and reinforcement learning from human feedback, represent significant advancements in machine learning. These models, with their ability to generate coherent text and realistic images, are crucial for biomedical applications that require processing diverse data forms such as clinical reports, diagnostic images, and multimodal patient interactions.
View Article and Find Full Text PDFNegotiating a physically active life in tune with ageing: a grounded theory study of older persons' experiences of participating in high-intensity interval training.
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Community Medicine and Rehabilitation, Physiotherapy, Umeå University, Umeå, Sweden.
Background: Physical activity and exercise are promoted worldwide as effective interventions for healthy ageing. Various exercise initiatives have been developed and evaluated for their efficacy and effectiveness among older populations. However, a deeper understanding of participants' experiences with these initiatives is crucial to foster long-term activity and exercise among older persons.
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