Results 211 to 220 of about 1,725,137 (297)

Highly Sensitive Electrochemical Biosensor Based on Hairy Particles with Controllable High Enzyme Loading and Activity

Advanced Functional Materials, EarlyView.
For the first time, a highly sensitive electrochemical biosensor based on SiO2‐based hairy particles with a grafted PDMAEMA polymer brush containing a quantifiable and large amount of immobilized Laccase is reported. The fabricated biosensor exhibits a sensitivity of 0.14 A·m⁻¹, a limit of detection (LOD) of 0.1 µm, and a detection range of 0.3–750 µm,
Pavel Milkin, Anila Antony, Hongtao Cai, Antonia Debevc, Ceyda Topal, Anne Linhardt, Alla Synytska, Leonid Ionov   +7 more
wiley   +1 more source

Modulating Electrochemical CO2 Reduction Pathways via Interfacial Electric Field

Advanced Functional Materials, EarlyView.
Engineering interfacial electric fields in Cu/ITO electrodes enables precise control of CO2 reduction pathways. Charge transfer from Cu to ITO generates positively charged Cu species that steer selectivity from ethylene toward methane. This work demonstrates how interfacial electric‐field modulation can direct reaction intermediates and transform ...
Mahdi Salehi, Zhengyuan Gao, Sai Phani Kumar Vangala, Amirhossein Farzi, Hamed Heidarpour, Morgan McKee, Nikolay Kornienko, Ali Seifitokaldani   +7 more
wiley   +1 more source

ecg2o: a seamless extension of g2o for equality-constrained factor graph optimization. [PDF]

Front Robot AI
Abdelkarim A, Görges D, Voos H.
europepmc   +1 more source

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

Advanced Functional Materials, EarlyView.
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker, Thierry Roland, Damien Favier, Antoine Egele, Michael Heymann, Cosima Stubenrauch   +5 more
wiley   +1 more source

Morphometric features enhance phenotype discrimination in frontotemporal lobar degeneration. [PDF]

Brain Commun
Stocks JK, Heywood AA, Popuri K, Beg MF, Rosen HJ, Wang L.   +5 more
europepmc   +1 more source

Implementation of Drug‐Induced Rhabdomyolysis and Acute Kidney Injury in Microphysiological System

Advanced Functional Materials, EarlyView.
A modular Muscle–Kidney proximal tubule‐on‐a‐chip integrates 3D skeletal muscle and renal proximal tubule tissues to model drug‐induced rhabdomyolysis and acute kidney injury. The coculture system enables dynamic tissue interaction, functional contraction monitoring, and quantification of nephrotoxicity, revealing drug side effect‐induced metabolic ...
Jaesang Kim, Zhuo Feng Lee, Gi‐Dong Sim, Sejoong Kim, Jessie S. Jeon   +4 more
wiley   +1 more source

Modeling physics data with the generalized Marshall-Olkin Kumaraswamy distribution. [PDF]

PLoS One
Gündüz S, Ozkan E, Karakaya K.
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Evaluation of the Effect of Food and Formulation on the Pharmacokinetics of the SHP2 Inhibitor Migoprotafib Within a Phase I Study in Cancer Patients. [PDF]

Clin Transl Sci
Suchomel J, Bowman CM, Chiang PC, Dhawan M, Eng-Wong J, Hauser P, Johnson R, Muliadi AR, Pisupati S, Ramakrishnan V, Wagner L, Mandlekar SV.   +11 more
europepmc   +1 more source