AIMC Topic: Oxidation-Reduction

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Analysis of interactions of particle-associated oxidative potential sources using multilayer perceptron neural networks: A case study in Shenyang, China.

Environmental pollution (Barking, Essex : 1987)
The oxidative potential (OP) of particulate matter (PM) is a possible indicator for assessing the oxidative-imbalance risk caused by PM exposure. The OP contributions of different PM sources exhibit nonlinear relationships, and the specific patterns ...

A neural network-shaped composite of α-MnO with N-doped graphene for electrocatalytic reduction of hydrogen peroxide in human urine samples.

The Analyst
A neural network-shaped composite fusing α-MnO and nitrogen-doped graphene (N@Gr/α-MnO) was synthesized a hydrothermal method. The resulting composite demonstrates enhanced electrocatalytic activity for hydrogen peroxide (HO) compared with each sing...

Modification and applications of glucose oxidase: optimization strategies and high-throughput screening technologies.

World journal of microbiology & biotechnology
Glucose oxidase (GOD), an oxidoreductase (EC 1.1.3.4), catalyzes the oxidation of β-D-glucose to gluconic acid using molecular oxygen as the electron acceptor, with concomitant generation of hydrogen peroxide. Owing to its versatile catalytic propert...

Effect of fatty acid composition on rosemary antioxidants in stabilizing woody edible oils: a kinetic and machine learning analysis of volatiles under accelerated oxidation.

Food chemistry
Prioritizing woody oil-bearing crops is essential to addressing edible oil supply-demand imbalances, yet oxidation remains a key challenge. Rosemary crude extract (RCE), an approved food-grade antioxidant, requires further evaluation for stabilizing ...

Decoding PM oxidative potential in Ningbo, China: Key chemicals, sources, and health risks via dual-assay and machine learning.

Journal of hazardous materials
PM oxidative potential (OP), a key driver of health risks, was investigated in Ningbo, China, using dual dithiothreitol (DTT) and ascorbic acid (AA) assays combined with machine learning (ML). This approach accounts for the complexity of interactions...

Exercise Therapy in Down Syndrome: A Systematic Review and Meta-Analysis Focused on Muscle Strength, Redox Balance, and Inflammatory Profile.

Medicine and science in sports and exercise
OBJECTIVE: This study systematically reviewed and meta-analyzed randomized and quasi-randomized controlled trials investigating the impact of exercise therapy on muscle strength, redox balance, and inflammatory profile in individuals with Down syndro...

Single-Component Double-Emissive Ratiometric Probe: Toward Machine Learning Driven Detection and Discrimination of Neurological Biomarkers.

Analytical chemistry
This study presents an attractive single-component ratiometric fluorescent sensor that utilizes the oxidation of BSA-protected Au nanoclusters (BSA-Au NCs) by -Bromosuccinimide (NBS) to detect catecholamine neurotransmitters and their metabolites, wh...

Evaluating degradation efficiency of pesticides by persulfate, Fenton, and ozonation oxidation processes with machine learning.

Environmental research
Quantifying organic properties is pivotal for enhancing the precision and interpretability of degradation predictive machine learning (ML) models. This study used Binary Morgan Fingerprints (B-MF) and Count-Based Morgan Fingerprints (C-MF) to quantif...

The environmental risk of heterogeneous oxidation is unneglectable: Time-resolved assessments beyond typical intermediate investigation.

Water research
The safety of advanced oxidation processes is paramount, surpassing treatment efficiency concerns. However, current research is limited to the qualitative toxicity investigations of targeted contaminants by-products, while the detoxification effects ...