Antibacterial Efficacy Comparison of Electrolytic and Reductive Silver Nanoparticles Against Propionibacterium acnes

Antibiotics, Journal Year: 2025, Volume and Issue: 14(1), P. 86 - 86

Published: Jan. 14, 2025

Background: The aim of this study was to develop an electrolysis system produce silver nanoparticles free from toxic gases, as the most common reduction and techniques nitrogen dioxide (NO2) a byproduct, which is harmful human health. new used two identical plate electrodes, replacing carbon rods, water electrolyte instead nitrate (AgNO3) solution since AgNO3 source NO2. Methods: electrolytic (ESNs) produced by were characterized compared with reductive (RSNs). Using UV-Visible spectrophotometry, absorption peaks found at 425 nm (ESN) 437 (RSN). dynamic light scattering, particle diameters measured 40.3 39.9 for ESNs concentrations 10 ppm 30 ppm, respectively, 74.0 74.6 RSNs respectively. Antibacterial activity against Propionibacterium acnes (P. acnes) assessed using Kirby-Bauer method. Results: It that efficacy relatively lower than 5% chloramphenicol because it in different concentration units (ESNs %). calibration curve, comparable 0.005% ESN. also P. developed strong resistance showed no ESNs. Conclusions: This finding underlines tremendous potential future antibiotic raw material.

Language: Английский

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AI-Enabled Compact and Efficient Dynamic Light Scattering System for Precise Microparticle Sizing

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 1900 - 1900

Published: Feb. 12, 2025

A cost-effective and efficient AI-DLS framework integrating dynamic light scattering (DLS) with artificial intelligence (AI) enables precise microparticle size characterization. compact DLS system was developed using a helium–neon laser, high-frequency photodetectors, optimized optical components, achieving significant miniaturization—4.5% volume, 16.7% weight, 25% cost of conventional systems. Advanced signal processing, such as Kalman filtering, improved data quality, while deep learning models (deep neural network (DNN), one-dimensional convolutional (1D-CNN), 2D-CNN Gramian angular field transformations) enhanced prediction accuracy. The model achieved exceptional results, mean absolute error 10 nm 99% matched the stability accuracy traditional instruments, reducing test time by 80%. This scalable, low-cost solution overcomes limitations, offering broad accessibility for scientific industrial

Language: Английский

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An optimally designed virtual impactor integrated with a quartz crystal microbalance sensor for submicron particulate matter classification and detection

Review of Scientific Instruments, Journal Year: 2025, Volume and Issue: 96(2)

Published: Feb. 1, 2025

Long-term exposure to particulate matter, especially submicron matter (PM1), poses significant health risks by inducing oxidative stress and inflammation. This paper reports an optimally designed virtual impactor (VI) integrated with a quartz crystal microbalance (QCM) sensor for the classification detection of PM1 particles. Computational fluid dynamics simulations were employed optimize included angles outlet size VI’s flow channels, minimizing eddy formation reducing airflow impact on sidewalls thereby enhancing durability VI. The VI was fabricated using 3D printing, its optimization effectiveness validated assessing particle wall loss. performance system examined classifying SiO2 particles ranging from 0.2 2 µm detecting QCM sensor. Results showed that after classification, majority in major channels PM1. frequency shift linear correlation mass deposited surface. Moreover, system’s found be comparable commercial instruments.

Language: Английский

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Advancing liposome and extracellular vesicle characterization through deep learning-enhanced optical trapping and nanoparticle tracking

Microchemical Journal, Journal Year: 2025, Volume and Issue: unknown, P. 113057 - 113057

Published: Feb. 1, 2025

Language: Английский

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In vitro and in vivo Attenuation of Salmonella resistance using a novel synthesized chloramphenicol magnesium Nano-complex

Microbial Pathogenesis, Journal Year: 2025, Volume and Issue: unknown, P. 107511 - 107511

Published: March 1, 2025

Language: Английский

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