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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 PDFUV-Resistant Nanostructured Anti-reflective Film for Achieving Efficiency Enhancement of Perovskite Solar Cells and Potential of Fabricating Large-Scale Cu(In, Ga)Se Solar Cells.
ACS Appl Mater Interfaces
January 2025
Guangxi Key Laboratory of Optical and Electronic Material and Devices, School of Materials Science and Engineering, Guilin University of Technology, 12 Jiangan Road, Guilin, Guangxi 541004, China.
Sticker-type transparent antireflective film (STAF) is applied to perovskite solar cells (PSCs) to reduce the reflection and improve the light-trapping ability of PSCs. However, the development of STAF is hindered by many factors, such as expensive materials, low actual service life, unsatisfactory antireflective effect, and a lack of research on stability. This work proposes an ultraviolet (UV)-resistant enhanced sticker-type nanostructure acrylic resin antireflective film (SNAAF), which is applied to the incident surface of PSCs.
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 PDFPredicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.
Ann Rheum Dis
January 2025
Department of Surgery, University of Cambridge, Cambridge, UK.
Objectives: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we created an automated machine learning (autoML) tool predicting the rapid progression of knee OA over a 2-year period.
Methods: We developed autoML models integrating clinical, biochemical, X-ray and MRI data. Using two data sets within the OA Initiative-the Foundation for the National Institutes of Health OA Biomarker Consortium for training and hold-out validation, and the Pivotal Osteoarthritis Initiative MRI Analyses study for external validation-we employed two distinct definitions of clinical outcomes: Multiclass (categorising OA progression into pain and/or radiographic) and binary.
A Comprehensive Evaluation of the Neuropharmacological Potential of Methanolic Leaf Extract of Acanthus ebracteatus (Vahl.) Using Experimental and In Silico Approaches.
Chem Biodivers
January 2025
Department of Pharmaceutical Sciences, College of Health Sciences and Pharmacy, Chicago State University, Chicago, Illinois, USA.
This study was undertaken to assess the antioxidant and neuropharmacological potentials of the methanol leaf extract of Acanthus ebracteatus (MAEL) through experimental and in silico methods. The phytochemical screening (PS) and GC-MS (gas chromatography-mass spectrometry) identified 28 phytochemicals with different classes in nature in MAEL. The MAEL revealed better antioxidant activity through various in vitro antioxidant assays.
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