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Processing and inspection of high-pressure microfluidics systems: A review.
Biomicrofluidics
January 2025
State Key Laboratory of Power Grid Environmental Protection, Wuhan, Hubei 430074, China.
In the field of microfluidics, high-pressure microfluidics technology, which utilizes high driving pressure for microfluidic analysis, is an evolving technology. This technology combines microfluidics and pressurization, where the flow of fluid is controlled by means of high-pressure-driven devices greater than 10 MPa. This paper first reviews the existing high-pressure microfluidics systems and describes their components and applications.
View Article and Find Full Text PDFThe TRIPOD-LLM reporting guideline for studies using large language models.
Nat Med
January 2025
Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
Large language models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present transparent reporting of a multivariable model for individual prognosis or diagnosis (TRIPOD)-LLM, an extension of the TRIPOD + artificial intelligence statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion.
View Article and Find Full Text PDFA decade of advances in human gut microbiome-derived biotherapeutics.
Nat Microbiol
January 2025
Sitala Bio, Cambridge, UK.
Microbiome science has evolved rapidly in the past decade, with high-profile publications suggesting that the gut microbiome is a causal determinant of human health. This has led to the emergence of microbiome-focused biotechnology companies and pharmaceutical company investment in the research and development of gut-derived therapeutics. Despite the early promise of this field, the first generation of microbiome-derived therapeutics (faecal microbiota products) have only recently been approved for clinical use.
View Article and Find Full Text PDFUncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches.
Sci Rep
January 2025
Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi, 75660, Pakistan.
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it challenging to trust predictions, particularly in uncertain cases. This sort of uncertainty can be crucial in medical image analysis; diabetic retinopathy is an example where even slight errors without an indication of confidence can have adverse impacts.
View Article and Find Full Text PDFA Bibliometric Review of Software Tools in Plastic Surgery: How They Benefit Surgeons and Improve Practice from 2004 to 2024.
Aesthetic Plast Surg
January 2025
Department of Craniomaxillofacial Surgery, Plastic Surgery Hospital, CAMS&PUMC (Chinese Academy of Medical Sciences and Peking Union Medical College), Beijing, 100144, China.
Background: Bibliometric analyses of software applications in plastic surgery are relatively limited. This study aims to address this gap by summarizing current research trends and providing insights that may guide future developments in this field.
Methods: Data were retrieved from the Web of Science Core Collection.
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