Results 211 to 220 of about 1,016,426 (283)

A Spatially Resolved View on the Aging Substantia nigra: An Exploratory Proteomic Study

open access: yesAdvanced Biology, EarlyView.
Although aging is the most important risk factor for several neurodegenerative diseases, the molecular effects of physiological aging are still understudied. By applying spatially‐resolved proteomic analyses of the human substantia nigra pars compacta, alterations in vesicular trafficking and mitochondrial proteins are observed, as well as reduced ...
Britta Eggers   +10 more
wiley   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani   +2 more
wiley   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

open access: yesAdvanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

BME Annual Report 2006-2007 [PDF]

open access: yes, 2007
Department of Biomedical Engineering, Florida International University
core  

DNA hydrogels and their derivatives in biomedical engineering applications. [PDF]

open access: yesJ Nanobiotechnology
Wu R   +8 more
europepmc   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

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