AIMC Topic: Mycotoxins
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Exploring Hidden Dangers: Predicting Mycotoxin-like Toxicity and Mapping Toxicological Networks in Hepatocellular Carcinoma.
Journal of chemical information and modeling
May 20, 2025
Mycotoxins are potent triggers of hepatocellular carcinoma (HCC) due to their intricate interplay with cellular macromolecules and signaling pathways. This study integrates machine learning and biomolecular analyses to elucidate the mechanisms underl...
Machine Learning-Assisted Multiplexed Fluorescence-Labeled miRNAs Imaging Decoding for Combined Mycotoxins Toxicity Assessment.
Analytical chemistry
Apr 3, 2025
Mycotoxins, particularly deoxynivalenol (DON) and zearalenone (ZEN), are common food contaminants that frequently co-occur in grains, posing significant health risks. This study proposed a multiplexed detection platform for simultaneous quantificatio...
Structural Similarity, Activity, and Toxicity of Mycotoxins: Combining Insights from Unsupervised and Supervised Machine Learning Algorithms.
Journal of agricultural and food chemistry
Feb 27, 2025
A large number of mycotoxins and related fungal metabolites have not been assessed in terms of their toxicological impacts. Current methodologies often prioritize specific target families, neglecting the complexity and presence of co-occurring compou...
Dual-Mode Colorimetric/SERS Lateral Flow Immunoassay with Machine Learning-Driven Optimization for Ultrasensitive Mycotoxin Detection.
Analytical chemistry
Feb 14, 2025
Detecting and quantifying mycotoxins using LFIA are challenging due to the need for high sensitivity and accuracy. To address this, a dual-mode colorimetric-SERS LFIA was developed for detecting deoxynivalenol (DON). Rhodium nanocores provided strong...
Microfluidic Optical Aptasensor for Small Molecules Based on Analyte-Tuned Growth of Gold Nanoseeds and Machine Learning-Enhanced Spectrum Analysis: Rapid Detection of Mycotoxins.
ACS sensors
Nov 7, 2024
Natural toxins, mainly small molecules, are a category of chemical hazards in agri-food systems that pose threats to both public health and food security. Current standard methods for monitoring these toxins, predominantly based on liquid chromatogra...
Machine learning driven metal oxide-based portable sensor array for on-site detection and discrimination of mycotoxins in corn sample.
Food chemistry
Nov 1, 2024
Cereals, grains, and feedstuffs are prone to contamination by fungi during various stages from growth to storage. These fungi may produce harmful mycotoxins impacting food quality and safety. Thus, the development of quick and reliable methods for on...
Decoding wheat contamination through self-assembled whole-cell biosensor combined with linear and non-linear machine learning algorithms.
Biosensors & bioelectronics
Oct 21, 2024
The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on human beings and leads to tremendous economic loss. It is essential to develop a rapid and non-destructive method for contamination recognition parti...
Progress of machine learning-based biosensors for the monitoring of food safety: A review.
Biosensors & bioelectronics
Sep 12, 2024
Rapid urbanization and growing food demand caused people to be concerned about food safety. Biosensors have gained considerable attention for assessing food safety due to selectivity, and sensitivity but poor stability inherently limits their applica...
Sága, a Deep Learning Spectral Analysis Tool for Fungal Detection in Grains-A Case Study to Detect Fusarium in Winter Wheat.
Toxins
Aug 13, 2024
Fusarium head blight (FHB) is a plant disease caused by various species of the fungus. One of the major concerns associated with spp. is their ability to produce mycotoxins. Mycotoxin contamination in small grain cereals is a risk to human and anim...
Machine Learning Applied to the Detection of Mycotoxin in Food: A Systematic Review.
Toxins
Jun 12, 2024
Mycotoxins, toxic secondary metabolites produced by certain fungi, pose significant threats to global food safety and public health. These compounds can contaminate a variety of crops, leading to economic losses and health risks to both humans and an...
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