AIMC Topic: Caffeine
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Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control.
Scientific reports
Mar 3, 2025
Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the...
Harnessing artificial neural networks to model caffeine degradation by High-Yield biodiesel algae Desmodesmus pannonicus.
Bioresource technology
Dec 10, 2024
In this study, Desmodesmus pannonicus IITISM-DIX2, outperforming Chlorella sorokiniana IITISM-DIX3 in caffeine degradation, was used to develop an artificial neural network (ANN) model for predicting caffeine removal efficiency under varying pH, phot...
Modeling and predicting caffeine contamination in surface waters using artificial intelligence and standard statistical methods.
Environmental monitoring and assessment
Dec 5, 2024
Caffeine, considered an emerging contaminant, serves as an indicator of anthropic influence on water resources. This research employs various modeling techniques, including Artificial Neural Networks (ANN), Random Forest (RF), and more, along with hy...
A novel open-access artificial-intelligence-driven platform for CNS drug discovery utilizing adult zebrafish.
Journal of neuroscience methods
Aug 24, 2024
BACKGROUND: Although zebrafish are increasingly utilized in biomedicine for CNS disease modelling and drug discovery, this generates big data necessitating objective, precise and reproducible analyses. The artificial intelligence (AI) applications ha...
Metabolomics Unveils Disrupted Pathways in Parkinson's Disease: Toward Biomarker-Based Diagnosis.
ACS chemical neuroscience
Aug 23, 2024
Parkinson's disease (PD) is a neurodegenerative disorder characterized by diverse symptoms, where accurate diagnosis remains challenging. Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biomarker-based...
Unveiling the potential of machine learning in cost-effective degradation of pharmaceutically active compounds: A stirred photo-reactor study.
Chemosphere
May 5, 2024
In this study, neural networks and support vector regression (SVR) were employed to predict the degradation over three pharmaceutically active compounds (PhACs): Ibuprofen (IBP), diclofenac (DCF), and caffeine (CAF) within a stirred reactor featuring...
Improved artificial intelligence discrimination of minor histological populations by supplementing with color-adjusted images.
Scientific reports
Nov 4, 2023
Despite the dedicated research of artificial intelligence (AI) for pathological images, the construction of AI applicable to histopathological tissue subtypes, is limited by insufficient dataset collection owing to disease infrequency. Here, we prese...
Overcoming the impact of physiologic tremors in ophthalmology.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Jul 5, 2022
PURPOSE: Ophthalmic surgery involves the manipulation of micron-level sized structures such as the internal limiting membrane where tactile sensation is practically absent. All humans have physiologic tremors that are of low amplitude and not discern...
Impact of microwave-assisted extraction on roasted coffee carbohydrates, caffeine, chlorogenic acids and coloured compounds.
Food research international (Ottawa, Ont.)
Dec 2, 2019
Microwave-assisted extraction (MAE) allows to quickly achieve soluble compounds from solid matrices due to the promotion of temperatures higher than the solvent (atmospheric) boiling point, once a closed-vessel system is used for operating at high pr...
Application of artificial neural networks for Process Analytical Technology-based dissolution testing.
International journal of pharmaceutics
Jun 25, 2019
This work proposes the application of artificial neural networks (ANN) to non-destructively predict the in vitro dissolution of pharmaceutical tablets from Process Analytical Technology (PAT) data. An extended release tablet formulation was studied, ...
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