AIMC Topic: Antioxidants
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Prediction of p-phenylenediamine antioxidant concentrations in human urine using machine learning models.
Journal of hazardous materials
Jan 10, 2025
p-phenylenediamine antioxidants (PPDs) are extensively used in rubber manufacturing for their potent antioxidative properties, but PPDs and 2-anilino-5-[(4-methylpentan-2yl)amino]cyclohexa-2,5-diene-1,4-dione (6PPDQ) pose potential environmental and ...
Machine learning assisted multi-signal nanozyme sensor array for the antioxidant phenolic compounds intelligent recognition.
Food chemistry
Jan 7, 2025
Identifying antioxidant phenolic compounds (APs) in food plays a crucial role in understanding their biological functions and associated health benefits. Here, a bifunctional Cu-1,3,5-benzenetricarboxylic acid (Cu-BTC) nanozyme was successfully prepa...
High-Accuracy Identification and Structure-Activity Analysis of Antioxidant Peptides via Deep Learning and Quantum Chemistry.
Journal of chemical information and modeling
Jan 7, 2025
Antioxidant peptides (AOPs) hold great promise for mitigating oxidative-stress-related diseases, but their discovery is hindered by inefficient and time-consuming traditional methods. To address this, we developed an innovative framework combining ma...
X-ray irradiation as a potential postharvest treatment for maintaining the quality of lily (Lilium davidii var. unicolor) bulbs and predicting shelf life using an artificial neural network.
Food research international (Ottawa, Ont.)
Dec 31, 2024
This study aimed to investigate the impact of X-ray irradiation pretreatment at varying doses (0.5, 1.0, 1.5, 2.0 kGy) on the preservation quality of lily bulbs and to elucidate its potential regulatory mechanisms. The findings revealed that X-ray ir...
A hybrid artificial neural network and multi-objective genetic algorithm approach to optimize extraction conditions of Mentha longifolia and biological activities.
Scientific reports
Dec 28, 2024
In this work, artificial neural network coupled with multi-objective genetic algorithm (ANN-NSGA-II) has been used to develop a model and optimize the conditions for the extracting of the Mentha longifolia (L.) L. plant. Input parameters were extract...
MOF-Based Biomimetic Enzyme Microrobots for Efficient Detection of Total Antioxidant Capacity of Fruits and Vegetables.
Small (Weinheim an der Bergstrasse, Germany)
Dec 26, 2024
Green and efficient total antioxidant capacity (TAC) detection is significant for healthy diet and disease prevention. This work first proposed the concept of TAC colorimetric detection based on microrobots. A novel metal-organic framework (MOF)-base...
Deep eutectic solvent-based green extraction of Strychnos potatorum seed phenolics: Process optimization via response surface methodology and artificial neural network.
Talanta
Dec 20, 2024
The current research focused on extraction optimization of bioactive compounds from Strychnos potatorum seeds (SPs) using an eco-friendly glycerol-sodium acetate based deep eutectic solvent (DES). The optimization was accomplished using response surf...
Preparation, characterization, and protective effects of carbon dots against oxidative damage induced by LPS in IPEC-J2 cells.
Frontiers in cellular and infection microbiology
Dec 18, 2024
This study aimed to prepare carbon dots (GF-CDs) and examine their efficacy in mitigating oxidative stress and apoptosis in intestinal porcine epithelial cells from the jejunum (IPEC-J2 cells) induced by lipopolysaccharide (LPS). The GF-CDs were syn...
Cytotoxicity, Antiadipogenic, Low-Density Lipoprotein Oxidation Inhibitory Activities, and Acute Toxicity Study of Hydroethanolic Leaf and Bark Extracts.
TheScientificWorldJournal
Dec 17, 2024
Obesity is increasingly taking an important stage as a cause of death worldwide, and interventions with a good cost-effectiveness ratio are needed. is one of these natural products with health benefits. Objective. The present study evaluated the cy...
Machine learning and SHAP value interpretation for predicting comorbidity of cardiovascular disease and cancer with dietary antioxidants.
Redox biology
Dec 16, 2024
OBJECTIVE: To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction.
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