AIMC Topic: Antioxidants

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Predictive modeling approach using machine learning-integrated design of experiments in quality by design for optimizing resveratrol-loaded polymeric nanoparticle formulation.

International journal of pharmaceutics
This study aimed to explore the potential of a Machine learning (ML)-integrated Quality by design (QbD) process to formulate resveratrol (RES)-loaded polymeric nanoparticles (RES-PNPs) for potential use in transdermal drug delivery. The RES-PNPs were...

Pred5AOP: an efficient screening of food-derived antioxidant peptides based on deep learning, molecular docking, and experimental validation.

Food chemistry
Antioxidant peptides derived from dietary proteins positively impact human health due to their high activity and safety. In this study, a database of 76,343 peptides was constructed via in silico hydrolysis of 29 dietary proteins. A novel antioxidant...

Color Dynamics, Pigments and Antioxidant Capacity in Pouteria sapota Puree During Frozen Storage: A Correlation Study Using CIELAB Color Space and Machine Learning Models.

Plant foods for human nutrition (Dordrecht, Netherlands)
The accurate prediction of bioactive compounds and antioxidant activity in food matrices is critical for optimizing nutritional quality and industrial applications. This study compares the performance of multiple linear regression (MLR) and artificia...

Modelling key ecological factors influencing the distribution and content of silymarin antioxidant in Silybum marianum L.

PloS one
The increasing demand for natural medicine has increased the significance of Silybum marianum as a valuable medicinal plant. It is used to restore liver cells; reduce blood cholesterol; prevent prostate, skin, and breast cancer; and protect cervical ...

Optimization of biological activities of Agaricus species: an artificial intelligence-assisted approach.

Scientific reports
This study aims to determine the optimum extraction conditions that maximize the biological activities of Agaricus campestris and Agaricus bisporus species. In the study, a total of 64 extraction experiments were carried out at different temperatures...

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 ...

Machine learning-based assessment of sustainable extraction methodologies tackling the biotechnological exploitation of Arnica montana extracts.

Food chemistry
Heat-assisted (HAE), ultrasound-assisted (UAE), microwave-assisted (MAE), and pressurized liquid extraction (PLE) represent diverse techniques with distinct physical principles that influence the efficiency and selectivity of bioactive compound recov...

Protective effects of minocycline on dermal fibroblast cells from oxidant and apoptotic effects of HO: A comprehensive analysis with Raman spectroscopy and data-driven approach.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Minocycline (Mino) is an antibiotic with neuroprotective, anti-inflammatory, and antioxidant properties. This study investigated the protective effects of Mino against hydrogen peroxide (HO)-induced oxidative damage in dermal fibroblast cells and ana...

Machine learning optimization of microwave-assisted extraction of phenolics and tannins from pomegranate peel.

Scientific reports
The peel of pomegranate (Punica granatum) is rich in bioactive compounds, specifically phenolic compounds and tannin compounds. However, there is still a lot of difficulty dealing with the extraction of these substances due to the limitations of trad...

Ecofriendly Extraction of Polyphenols from Leaves Coupled with Response Surface Methodology and Artificial Neural Network-Genetic Algorithm.

Molecules (Basel, Switzerland)
This study aimed to optimize a novel deep eutectic solvents (DESs)-assisted extraction process for polyphenols in the leaves of (AGPL) with response surface methodology (RSM) and a genetic algorithm-artificial neural network (GA-ANN). Under the infl...