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Cell-Instructive Biomaterials with Native-Like Biochemical Complexity.
Annu Rev Biomed Eng
January 2025
1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA; email:
Biochemical signals in native tissue microenvironments instruct cell behavior during many biological processes ranging from developmental morphogenesis and tissue regeneration to tumor metastasis and disease progression. The detection and characterization of these signals using spatial and highly resolved quantitative methods have revealed their existence as matricellular proteins in the matrisome, some of which are bound to the extracellular matrix while others are freely diffusing. Including these biochemical signals in engineered biomaterials can impart enhanced functionality and native-like complexity, ultimately benefiting efforts to understand, model, and treat various diseases.
View Article and Find Full Text PDFUser and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study.
JMIR Cancer
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.
Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.
View Article and Find Full Text PDFValue Propositions for Digital Shared Medication Plans to Boost Patient-Health Care Professional Partnerships: Co-Design Study.
J Particip Med
January 2025
Department of Ambulatory Care, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Background: Health authorities worldwide have invested in digital technologies to establish robust information exchange systems for improving the safety and efficiency of medication management. Nevertheless, inaccurate medication lists and information gaps are common, particularly during care transitions, leading to avoidable harm, inefficiencies, and increased costs. Besides fragmented health care processes, the inconsistent incorporation of patient-driven changes contributes to these problems.
View Article and Find Full Text PDFProbabilistic Approaches for Risk Assessment and Regulatory Criteria Development: Current Applications, Gaps, and Opportunities.
Integr Environ Assess Manag
January 2025
Institute of Environmental Toxicology, Western Washington University, Bellingham, Washington, USA.
Traditional ecological and human health risk assessment often relies on deterministic frameworks that preclude the presence of variability or uncertainty among input parameters characterizing exposure, effects, and risk. To promote increased realism and generate more robust risk management decisions, probabilistic risk assessment (PRA) has been introduced as a foundational grouping of techniques that seeks to broadly characterize variability among its components. While multiple methods exist (e.
View Article and Find Full Text PDFMultidimensional scaling improves distance-based clustering for microbiome data.
Bioinformatics
January 2025
Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, WI 53726, United States.
Motivation: Clustering patients into subgroups based on their microbial compositions can greatly enhance our understanding of the role of microbes in human health and disease etiology. Distance-based clustering methods, such as partitioning around medoids (PAM), are popular due to their computational efficiency and absence of distributional assumptions. However, the performance of these methods can be suboptimal when true cluster memberships are driven by differences in the abundance of only a few microbes, a situation known as the sparse signal scenario.
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