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Phenols

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Antimicrobial Activity of Tea and Agarwood Leaf Extracts Against Multidrug-Resistant Microbes.

BioMed research international
Emerging multidrug-resistant (MDR) strains are the main challenges to the progression of new drug discovery. To diminish infectious disease-causing pathogens, new antibiotics are required while the drying pipeline of potent antibiotics is adding to t...

Phenolic content discrimination in Thai holy basil using hyperspectral data analysis and machine learning techniques.

PloS one
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...

Effects of environmental phenols on eGFR: machine learning modeling methods applied to cross-sectional studies.

Frontiers in public health
PURPOSE: Limited investigation is available on the correlation between environmental phenols' exposure and estimated glomerular filtration rate (eGFR). Our target is established a robust and explainable machine learning (ML) model that associates env...

Artificial intelligence-based data extraction for next generation risk assessment: Is fine-tuning of a large language model worth the effort?

Toxicology
To underpin scientific evaluations of chemical risks, agencies such as the European Food Safety Authority (EFSA) heavily rely on the outcome of systematic reviews, which currently require extensive manual effort. One specific challenge constitutes th...

Machine learning approach for high-throughput phenolic antioxidant screening in black Rice germplasm collection based on surface FTIR.

Food chemistry
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...

Machine Learning-Based Nanozyme Sensor Array as an Electronic Tongue for the Discrimination of Endogenous Phenolic Compounds in Food.

Analytical chemistry
The detection of endogenous phenolic compounds (EPs) in food is of great significance in elucidating their bioactivity and health effects. Here, a novel bifunctional vanillic acid-Cu (VA-Cu) nanozyme with peroxidase-like and laccase-like activities w...

Rapid determination of total phenolic content and antioxidant capacity of maple syrup using Raman spectroscopy and deep learning.

Food chemistry
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 ...

Unveiling the role of artificial intelligence in tetracycline antibiotics removal using UV/sulfite/phenol advanced reduction process.

Journal of environmental management
UV/sulfite-based advanced reduction processes (ARP) have attracted increasing attention due to their high capability for removing a wide range of pollutants. Therefore, developing UV/sulfite ARP systems with assisted Artificial Intelligence (AI) mode...

Deep eutectic solvent-based green extraction of Strychnos potatorum seed phenolics: Process optimization via response surface methodology and artificial neural network.

Talanta
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...

A hybrid artificial neural network and multi-objective genetic algorithm approach to optimize extraction conditions of Mentha longifolia and biological activities.

Scientific reports
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...