AIMC Topic: Antioxidants
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Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018.
Lipids in health and disease
Nov 26, 2024
BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors...
Exploring the cytotoxic and antioxidant properties of lanthanide-doped ZnO nanoparticles: a study with machine learning interpretation.
Journal of nanobiotechnology
Nov 10, 2024
BACKGROUND: Lanthanide-based nanomaterials offer a promising alternative for cancer therapy because of their selectivity and effectiveness, which can be modified and predicted by leveraging the improved accuracy and enhanced decision-making of machin...
The Bioprotective Effects of Marigold Tea Polyphenols on Obesity and Oxidative Stress Biomarkers in High-Fat-Sugar Diet-Fed Rats.
Cardiovascular therapeutics
Oct 4, 2024
The research is aimed at exploring the potential of marigold petal tea (MPT), rich in polyphenol contents, against oxidative stress and obesity in a rat model following a high-fat-sugar diet (HFSD). The MPT was prepared through the customary method...
Phenolic content discrimination in Thai holy basil using hyperspectral data analysis and machine learning techniques.
PloS one
Oct 2, 2024
Hyperspectral imaging has emerged as a powerful tool for the non-destructive assessment of plant properties, including the quantification of phytochemical contents. Traditional methods for antioxidant analysis in holy basil (Ocimum tenuiflorum L.) ar...
A machine learning-guided modeling approach to the kinetics of α-tocopherol and myricetin synergism in bulk oil oxidation.
Food chemistry
Sep 27, 2024
The shelf-life and quality of food products depend heavily on antioxidants, which protect lipids from free radical degradation. α-Tocopherol and myricetin, two potent antioxidants, synergistically enhance the prevention of oxidative rancidity in bulk...
Machine learning and multiple linear regression models can predict ascorbic acid and polyphenol contents, and antioxidant activity in strawberries.
Journal of the science of food and agriculture
Sep 18, 2024
BACKGROUND: Strawberry is a rich source of antioxidants, including ascorbic acid (ASA) and polyphenols, which have numerous health benefits. Antioxidant content and activity are often determined manually using laboratory equipment, which is destructi...
Analysis of sediment re-formation factors after ginseng beverage clarification based on XGBoost machine learning algorithm.
Food chemistry
Sep 17, 2024
The aim of this study was to explore the sediment re-formation factors of ginseng beverages subjected to four clarification ways (11 subgroups) including the ethanol precipitation, enzymatic treatment, clarifier clarification, and Hollow Fiber Column...
Rapid determination of total phenolic content and antioxidant capacity of maple syrup using Raman spectroscopy and deep learning.
Food chemistry
Sep 16, 2024
Total phenolic content (TPC) and antioxidant capacity of maple syrup were determined using Raman spectroscopy and deep learning. TPC was determined by Folin-Ciocalteu assay, while the antioxidant capacity was measured by 2,2-diphenyl-1picrylhydrazyl ...
RSM and ANN-Based Optimized Ultrasound-Assisted Extraction of Functional Components from Olive Fruit (cv Arbequina): Assessment of Antioxidant Attributes and GC-MS Metabolites Profiling.
Chemistry & biodiversity
Aug 30, 2024
The current study devises an optimized ethanolic extraction for efficient recovery of high-value components from Pakistani olives (cv. Arbequina) using response surface methodology (RSM) and artificial neural networking (ANN). Four factors such as ti...
Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR.
Food chemistry
Aug 2, 2024
Pigmented rice contains beneficial phenolic antioxidants but analysing them across germplasm collections is laborious and time-consuming. Here we utilised rapid surface Fourier transform infrared (FTIR) spectroscopy and machine learning algorithms (M...
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