Results 101 to 110 of about 43,338 (227)

A review of dominant lactic acid bacteria strains and inoculation fermentation for fermented mustard plant. [PDF]

Front Microbiol
Zhou Y, Cai A, Mo Z, Diao N, Huang J, Long B, Shang S, Hu W, Feng K, Sarengaowa.   +9 more
europepmc   +1 more source

Evaluation of Dried Plasma Spot‐Based Quantification of Glial Fibrillary Acidic Protein as a Disease‐Associated Biomarker in Neuromyelitis Optica Spectrum Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the diagnostic accuracy of glial fibrillary acidic protein (GFAP) measured in dried plasma spots versus conventional plasma‐ and serum‐GFAP testing for assessment of disease severity in aquaporin‐4 immunoglobulin G–positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD).
Felix Wohlrab, Evelyn Alvarez, Roua Hamdi, Bingqing Zhang, Hayeun Ji, Niyati Jhaveri, Patrick Schindler, Pedro Sanchez, Pia S. Sperber, Tanja Schmitz‐Hübsch, Frederike C. Oertel, Nisa Vorasoot, Najib Kissani, Falko Böhringer, Jens Kuhle, Anne‐Katrin Pröbstel, Xiao‐Jun Ma, Péter Körtvelyessy, Patrick Waters, Friedemann Paul   +19 more
wiley   +1 more source

Single-Particle Characterization Reveals Heterogeneous Extracellular Vesicle Fusion with Liposomes. [PDF]

Small Methods
Mizenko RR, Arun V, Meshkanian D, Lowe NM, Mohabbat H, Wang A, Carney RP.   +6 more
europepmc   +1 more source

Mechanochemical Synthesis and Characterization of Nanostructured ErB4 and NdB4 Rare‐Earth Tetraborides

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
ErB4 and NdB4 nanostructured powders are produced by mechanochemical synthesis. 5 h mechanical alloying and 4 M HCl acid leaching are used in the production. ErB4 and NdB4 powders exhibit maximum magnetization of 0.4726 emu g−1 accompanied with an antiferromagnetic‐to‐paramagnetic phase transition at about TN = 18 K and 0.132 emu g−1 with a maximum at ...
Burçak Boztemur, Faruk Kaya, Bora Derin, Mustafa Lütfi Öveçoğlu, Ju Li, Duygu Ağaoğulları   +5 more
wiley   +1 more source

In-Solution Characterization of Extracellular Vesicles: A New Approach to Evaluating Antibody Binding and Surface Interactions. [PDF]

J Extracell Vesicles
Kakavoulia MA, Spies P, Kutzner TJ, Tertel T, Franzmeier S, Andaloussi SE, Giebel B, Kaltner H, Meinel D, Görgens A, Ludwig AK.   +10 more
europepmc   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Buffering effects of supporting electrolytes on pH profiles in electrochemical cells. [PDF]

Sci Rep
Janotta B, Schalenbach M, Turiaux M, Tempel H, Eichel RA.   +4 more
europepmc   +1 more source

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

Advanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +1 more source

Preliminary evaluation of a lemongrass-based nanoparticle gel for antibacterial control of <i>Enterococcus faecalis</i>: an <i>in vitro</i> study. [PDF]

Biomater Investig Dent
Leite LRR, da Costa MO, de Souza Wanderley Á, Neiva GS, Duarte CAL, Sette-de-Souza PH, Barbosa-Ribeiro M.   +6 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source