Results 211 to 220 of about 3,443,781 (274)

Combinatorial Synthesis of Next Generation Water‐Soluble Quaternized N‐Halamine Oligomers with Long‐Lasting Antiviral Properties

open access: yesAdvanced Functional Materials, EarlyView.
A combinatorial library of dual‐functional antiviral oligomers incorporating N‐halamine and quaternary ammonium functionalities is developed for long‐lasting antiviral activity. The lead materials exhibit rapid and durable antiviral activity against SARS‐CoV‐2 variants and influenza H1N1, with 4 to 5 log reduction in viral copies at 5 mg mL−1 ...
Eid Nassar‐Marjiya   +14 more
wiley   +1 more source

A practical evaluation of statistical methods for the analysis of patient reported outcomes in an observational pharmaceutical study. [PDF]

open access: yesPLoS One
Williams LR   +6 more
europepmc   +1 more source

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

open access: yesAdvanced 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   +7 more
wiley   +1 more source

Inactivating SARS‐CoV‐2 Virus with MOF‐Composites as Smart Face Masks

open access: yesAdvanced Functional Materials, EarlyView.
In situ preparation and functionalization of MOF@Cotton fabrics as smart face masks for the immobilization of proteins and inactivation viruses, such as SARS‐CoV‐2. Abstract The significant impact of the SARS‐CoV‐2 (COVID‐19) pandemic outbreak on people's lives has highlighted the urgent need for effective personal protective equipment.
Romy Ettlinger   +9 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced 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   +7 more
wiley   +1 more source

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