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Current status of fluid biomarkers for early Alzheimer's disease and FDA regulation implications.
J Neurol Sci
December 2024
Department of Bionanotechnology, Bionano Research Institute, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si 13120, Gyeonggi-do, Republic of Korea. Electronic address:
Many changes can now be seen in the development and use of tests, especially those incorporating fluid biomarkers, to diagnose Alzheimer's disease (AD), a devastating disease caused by the progressive but rapid degeneration of cortical tissue. Some biomarkers we already know have a significant association with AD, such as amyloid beta (Aβ) and tau, as well as the ratio of concentrations of other Aβ isoforms. In addition, several novel biomarkers are emerging that can also be used as diagnostic fluid biomarkers for AD, but many studies are still needed before we can consider them reliable.
View Article and Find Full Text PDFAn improved TEAD dominant-negative protein inhibitor to study Hippo YAP1/TAZ-dependent transcription.
bioRxiv
October 2024
Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States.
Hippo signaling is one of the top pathways altered in human cancer, and intensive focus has been devoted to developing therapies targeting Hippo-dependent transcription mediated by YAP1 and TAZ interaction with TEAD proteins. However, a significant challenge in evaluating the efficacy of these approaches is the lack of models that can precisely characterize the consequences of TEAD inhibition. To address this gap, our laboratory developed a strategy that utilizes a fluorescently traceable, dominant-negative protein named TEADi.
View Article and Find Full Text PDFThe US FDA's New Rule for Regulating Laboratory-Developed Tests.
JAMA Health Forum
October 2024
Harvard Law School, Cambridge, Massachusetts.
Regulatory Aspects of Artificial Intelligence and Machine Learning.
Mod Pathol
December 2024
Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Computational Pathology and Artificial Intelligence Center of Excellence, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania. Electronic address:
In the realm of health care, numerous generative and nongenerative artificial intelligence and machine learning (AI-ML) tools have been developed and deployed. Simultaneously, manufacturers of medical devices are leveraging AI-ML. However, the adoption of AI in health care raises several concerns, including safety, security, ethical biases, accountability, trust, economic impact, and environmental effects.
View Article and Find Full Text PDFIVDCheckR - simplifying documentation for laboratory developed tests according to IVDR requirements by introducing a new digital tool.
Clin Chem Lab Med
August 2024
Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg, Oldenburg, Germany.
Objectives: A recent challenge for clinical laboratories is the lack of clear guidelines for handling significant modifications of CE-marked assays. The modifications may involve, for example, extending measurement intervals, changing dilution procedures or using non-validated sample materials. The challenge arises due to the amended Regulation (EU) 2017/746 on diagnostic medical devices (IVDR), which is now poised for implementation, despite the extended transition periods.
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