AIMC Topic: Glycolipids
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Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.
Nature communications
Jun 18, 2025
Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed...
Diagnostic and prognostic perspectives of Fabry disease via fiber evanescent wave spectroscopy advanced by machine learning.
Biosensors & bioelectronics
Jan 7, 2025
Fabry disease (FD) is a rare disorder resulting from a genetic mutation characterized by the accumulation of sphingolipids in various cells throughout the human body, leading to progressive and irreversible organ damage, particularly in males. Geneti...
Lipid discovery enabled by sequence statistics and machine learning.
eLife
Dec 10, 2024
Bacterial membranes are complex and dynamic, arising from an array of evolutionary pressures. One enzyme that alters membrane compositions through covalent lipid modification is MprF. We recently identified that MprF synthesizes lysyl-phosphatidylgl...
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...
On the Evaluation of Rhamnolipid Biosurfactant Adsorption Performance on Amberlite XAD-2 Using Machine Learning Techniques.
BioMed research international
Apr 26, 2021
Biosurfactants are a series of organic compounds that are composed of two parts, hydrophobic and hydrophilic, and since they have properties such as less toxicity and biodegradation, they are widely used in the food industry. Important applications i...
Kinetic modeling and quasi-economic analysis of fermentative glycolipopeptide biosurfactant production in a medium co-optimized by statistical and neural network approaches.
Preparative biochemistry & biotechnology
Apr 21, 2021
This study presents the kinetics of production of a glycolipopeptide biosurfactant in a medium previously co-optimized by response surface and neural network methods to gain some insight into its volumetric and specific productivities for possible sc...
Pathogen Identification Direct From Polymicrobial Specimens Using Membrane Glycolipids.
Scientific reports
Oct 26, 2018
With the increased prevalence of multidrug-resistant Gram-negative bacteria, the use of colistin and other last-line antimicrobials is being revisited clinically. As a result, there has been an emergence of colistin-resistant bacterial species, inclu...
The antibacterial activity of rhamnolipid biosurfactant is pH dependent.
Food research international (Ottawa, Ont.)
Sep 6, 2018
Rhamnolipid (RL) biosurfactants have been studied as agents to control the growth of food pathogens however, to be successful applied as antimicrobial agent in food, is important to determine the effect of environmental conditions on RL activity. Onc...
Machine Learning-Based Glycolipid Metabolism Gene Signature Predicts Prognosis and Immune Landscape in Oesophageal Squamous Cell Carcinoma.
Journal of cellular and molecular medicine
Mar 1, 2025
Using machine learning approaches, we developed and validated a novel prognostic model for oesophageal squamous cell carcinoma (ESCC) based on glycolipid metabolism-related genes. Through integrated analysis of TCGA and GEO datasets, we established a...
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