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Conservation breeding and assisted reproductive technologies (ARTs) are invaluable tools to save wild animal species that are on the brink of extinction. Microfluidic devices recently developed for human or domestic animal reproductive medicine could significantly help to increase knowledge about fertility and contribute to the success of ART in wildlife. Some of these microfluidic tools could be applied to wild species, but dedicated efforts will be necessary to meet specific needs in animal conservation; for example, they need to be cost-effective, applicable to multiple species, and field-friendly. Microfluidics represents only one powerful technology in a complex toolbox and must be integrated with other approaches to be impactful in managing wildlife reproduction.
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http://dx.doi.org/10.1016/j.tibtech.2020.08.012 | DOI Listing |
Int J Plant Anim Environ Sci
August 2025
Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA.
Neurological disorders, such as Alzheimer's disease, Parkinson's disease, epilepsy, spinal cord injuries, and traumatic brain injuries, represent substantial global health challenges due to their chronic and often progressive nature. While allopathic medicine offers a range of pharmacological interventions aimed at managing symptoms and mitigating disease progression, it is accompanied by limitations, including adverse side effects, the development of drug resistance, and incomplete efficacy. In parallel, phytochemicals-bioactive compounds derived from plants-are receiving increased attention for their potential neuroprotective, antioxidant, and anti-inflammatory properties.
View Article and Find Full Text PDFJ Healthc Sci Humanit
January 2024
Program Manager, Center for Biomedical Research/Research Centers in Minority Institutions (TU CBR/RCMI), Department of Biology, College of Arts and Sciences (CAS), Tuskegee University, Phone: (334) 724-4391, Email:
The emergence of the Novel COVID-19 Pandemic has undoubtedly impacted the lives of individuals across the globe. It has drawn the attention of major public health agencies as they work intensely towards understanding the behavior of the virus causing the disease, while simultaneously establishing ways to curb the spread of the virus among populations. As of the time of writing, 7,949,973 confirmed cases have been reported globally; with the United States (US) contributing to 26.
View Article and Find Full Text PDFCase Rep Ophthalmol Med
September 2025
Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
A 62-year-old female with retinitis pigmentosa presented for a low vision rehabilitation evaluation. An updated spectacle prescription, filters, and task lighting were beneficial, but the patient was left with outstanding needs. She noted that she had lost her independence and felt trapped within her own home with nobody around who could fully understand her situation.
View Article and Find Full Text PDFRev Cardiovasc Med
August 2025
Cardiovascular Surgery Department, Ankara Bilkent City Hospital, 06800 Ankara, Turkey.
Background: This study aimed to investigate the performance of two versions of ChatGPT (o1 and 4o) in making decisions about coronary revascularization and to compare the recommendations of these versions with those of a multidisciplinary Heart Team. Moreover, the study aimed to assess whether the decisions generated by ChatGPT, based on the internal knowledge base of the system and clinical guidelines, align with expert recommendations in real-world coronary artery disease management. Given the increasing prevalence and processing capabilities of large language models, such as ChatGPT, this comparison offers insights into the potential applicability of these systems in complex clinical decision-making.
View Article and Find Full Text PDFMed Phys
September 2025
School of Computer, Electronics and Information, Guangxi University, Nanning, China.
Background: Deformable medical image registration is a critical task in medical imaging-assisted diagnosis and treatment. In recent years, medical image registration methods based on deep learning have made significant success by leveraging prior knowledge, and the registration accuracy and computational efficiency have been greatly improved. Models based on Transformers have achieved better performance than convolutional neural network methods (ConvNet) in image registration.
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