Results 161 to 170 of about 63,888 (253)
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source
A rational architectural design of hierarchical, CNT‐interwoven hollow carbon microclusters unlocks and stabilizes a unique monoclinic Co3Se4‐mediated conversion–insertion pathway for potassium storage. This structural confinement effectively guides the reaction kinetics and accommodates severe mechanical strain.
Ho Rim Kim +8 more
wiley +1 more source
The hidden costs of imperfection: transcription errors in protein aggregation diseases. [PDF]
Sun Y, Vermulst M.
europepmc +1 more source
Nanomaterials offer dual applications in allergy management. For diagnosis, nanomaterials enhance analytical sensitivity and improve detection in specific IgE and functional assays such as the basophil activation test (BAT). For allergen‐specific immunotherapy, nanomaterials enable allergen masking and controlled release, and effectively modulate the ...
Madiha Habib +8 more
wiley +1 more source
The hidden costs of 'free' treatment: A cross-sectional study of patient-incurred costs for daily methadone maintenance treatment in Nairobi, Kenya. [PDF]
Masai TW +3 more
europepmc +1 more source
Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer
This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu +7 more
wiley +1 more source
Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao +4 more
wiley +1 more source
The hidden costs of PEG-rhG-CSF in autologous stem cell transplantation for newly diagnosed multiple myeloma. [PDF]
Wang R +5 more
europepmc +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Correcting the apparent priming effect resolves systematic biases in Asian rice fertilizer nitrogen accounting. Net soil retention drops below 7%, while 48% of fertilizer escapes, inflicting US$98.53 billion in annual reactive‐nitrogen damages. High‐resolution mapping uncovers N‐risk archetypes across 42% of the rice area, delivering a spatially ...
Xiuyun Liu +5 more
wiley +1 more source

