Non‐covalent protein–protein interactions mediated by SH3, PDZ, or GBD domains enable the self‐assembly of stable and biocatalytically active hydrogel materials. These soft materials can be processed into monodisperse foams that, once dried, exhibit enhanced mechanical stability and activity and are easily integrated into microstructured flow ...
Julian S. Hertel +5 more
wiley +1 more source
Influencing factors of oil-bearing capacity in tight sandstones based on pore structure characterization: a case study of the Fuyu reservoir in the Xinmiao oilfield, Southern Songliao Basin. [PDF]
Wang H +11 more
europepmc +1 more source
Multicolor optoelectronic synapses are realized by vertically integrating solution‐processed MoS2 thin‐film and SWCNT. The electronically disconnected but interactive MoS2 enables photon‐modulated remote doping, producing a bi‐directional photoresponse.
Jihyun Kim +8 more
wiley +1 more source
Frequency and Outcomes of Distal Radioulnar Joint Dislocation Associated With Distal Radius Fractures in the Elderly. [PDF]
Ishimatsu M +5 more
europepmc +1 more source
Application of multiplanar ligamentotaxis to external fixation of distal radius fractures.
Agee Jm
openalex +1 more source
Epidemiology, Risk Factor, and Economic Analysis of Peripheral Nerve Injury Following Distal Radius Fractures [PDF]
Michael Miskiewicz +5 more
openalex +1 more source
Device Integration Technology for Practical Flexible Electronics Systems
Flexible device integration technologies are essential for realizing practical flexible electronic systems. In this review paper, wiring and bonding techniques critical for the industrial‐scale manufacturing of wearable devices are emphasized based on flexible electronics.
Masahito Takakuwa +5 more
wiley +1 more source
Growth Plate Injury Leading to Madelung-Type Deformity After ESIN in Children: A Case Report and a Narrative Review of the Literature. [PDF]
Cosentino A, Odorizzi G, Berger W.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source

