Results 201 to 210 of about 1,638,905 (280)
Machine Learning Guided Design of Nerve‐On‐A‐Chip Platforms with Promoted Neurite Outgrowth
Compared to labor‐intensive trial‐and‐error experimentation, a machine learning (ML)‐guided workflow, incorporating cell viability assays, data augmentation, ensemble modeling, and model interpretation, is developed to accelerate nerve‐on‐a‐chip optimization and uncover data‐driven design principles.
Tsai‐Chun Chung+8 more
wiley +1 more source
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto+8 more
wiley +1 more source
An integrated computational–experimental strategy accelerates the discovery of high‐performance PCFC cathodes. Computational screening using machine learning interatomic potentials and targeted experiments identifies optimal cobalt substitution in Ba0.95La0.05FeO3‐δ, reducing area‐specific resistance by 58% at 500 °C.
Abdullah Tahir+4 more
wiley +1 more source
This study investigates optoelectronic PUFs that improve on traditional optical and electrical PUFs. The absorber materials are randomly coated through spray coating, ligand exchange, and dynamic spin coating. Incident light generates wavelength‐dependent binary multikey and enhances security ternary keys, approaching near‐ideal inter‐ and intra ...
Hanseok Seo+6 more
wiley +1 more source
This review highlights emerging bioengineering strategies for treating neointimal hyperplasia in the peripheral vasculature, focusing on approaches that promote re‐endothelialization, modulate smooth muscle cell phenotype, reduce inflammation, mitigate oxidative stress, and optimize biomechanical compliance.
Nikita Wilson John+5 more
wiley +1 more source
This perspective provides an overview of the growing interest in utilizing various gasotransmitters—small gaseous signaling molecules namely nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2S)—for several therapeutic applications, with emphasis on the potential use of porous materials as carriers to provide safe and controlled local ...
Rosana V. Pinto+2 more
wiley +1 more source
This proof‐of‐concept study involves high‐throughput teratogenicity screening of compounds using XEn/EpiCs, a 3D stem cell‐based embryo model, within microwells. The term ‘morphotoxicity’ is introduced to complement traditional cytotoxicity assays through automated feature extraction and machine‐learning‐assisted classification of morphologies.
Vinidhra Shankar+4 more
wiley +1 more source
AIMSPec‐LoC is a novel lab‐on‐a‐chip platform integrating size‐based extracellular vesicle (EVs) separation with label‐free Raman spectroscopy and AI‐powered classification via SKiNET. This high‐throughput, portable system enables real‐time, multiplexed molecular fingerprinting of EVs from biofluids, offering transformative potential for early, non ...
Emma Buchan+3 more
wiley +1 more source
A comprehensive Malabar Spinach dataset for diseases classification. [PDF]
Rahman M, Mamun MA.
europepmc +1 more source
Nanomaterial‐Enhanced Biosensing: Mechanisms and Emerging Applications
Nanomaterial integration transforms biosensor capabilities through enhanced signal transduction, sensitivity, and selectivity. This review analyzes how nanoscale materials—from nanoparticles to nanosheets—leverage unique physicochemical properties to revolutionize electrochemical, optical, and electrical biosensing.
Younghak Cho+3 more
wiley +1 more source