Study Design: Nonrandomized clinical trial (NCT02354625).
Objectives: As a part of a Phase I clinical trial to assess the safety of autologous human Schwann cells (ahSC) in persons with chronic spinal cord injury (SCI), participants engaged in a multimodal conditioning program pre- and post-ahSC transplantation. The program included a home-based strength and endurance training program to prevent lack of fitness and posttransplantation detraining from confounding potential ahSC therapeutic effects. This paper describes development, deployment, outcomes, and challenges of the home-based training program.
Setting: University-based laboratory.
Methods: Development phase: two men with paraplegia completed an 8-week laboratory-based 'test' of the home-based program. Deployment phase: the first four (two males, two females) participant cohort of the ahSC trial completed the program at home for 12 weeks pre and 20 weeks post ahSC transplant.
Results: Development phase: both participants improved their peak aerobic capacity (VO) (≥17%), peak power output (PO) (≥8%), and time to exhaustion (TTE) (≥7%). Deployment phase: pretransplant training minimally increased fitness in the two male participants (≥6% PO and ≥9% TTE). The two women had no PO changes and slight TTE changes (+2.6 and -1.2%, respectively.) All four participants detrained during the posttransplant recovery period. After posttransplant retraining, all four participants increased TTE (4-24%), three increased VO (≥11%), and two increased PO (≥7%) CONCLUSIONS: Home-based strength and condition programs can be effective and successfully included in therapeutic SCI trials. However, development of these programs requires substantial content knowledge and experience.
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http://dx.doi.org/10.1038/s41393-020-0486-7 | DOI Listing |
J Health Organ Manag
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Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, India.
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January 2025
School of Physics, Mathematics and Computing, The University of Western Australia, Crawley, WA, Australia.
Artificial Intelligence (AI) based auto-segmentation has demonstrated numerous benefits to clinical radiotherapy workflows. However, the rapidly changing regulatory, research, and market environment presents challenges around selecting and evaluating the most suitable solution. To support the clinical adoption of AI auto-segmentation systems, Selection Criteria recommendations were developed to enable a holistic evaluation of vendors, considering not only raw performance but associated risks uniquely related to the clinical deployment of AI.
View Article and Find Full Text PDFCurr Psychiatry Rep
January 2025
Center for Military Medicine Research, University of Pittsburgh, Pittsburgh, PA, USA.
Purpose Of Review: Medicine and specifically mental health have been affected by emerging technologies advancing mental health treatment while at the same time bringing new challenges and stressors to the battlefield, military systems, and the warfighter.
Recent Findings: This article reviews the evolving positive and negative impacts of technology on combat mental health and treatment. A history of technology and military mental health concerns and services is followed by an overview of present benefits and risks.
Taiwan J Ophthalmol
November 2024
Sirindhorn International Institute of Technology, Thammasat University, Bangkok, Thailand.
Recent advances of artificial intelligence (AI) in retinal imaging found its application in two major categories: discriminative and generative AI. For discriminative tasks, conventional convolutional neural networks (CNNs) are still major AI techniques. Vision transformers (ViT), inspired by the transformer architecture in natural language processing, has emerged as useful techniques for discriminating retinal images.
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December 2024
Emergency Medicine Department, Aga Khan University, Karachi, PAK.
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