AIMC Topic: Animals

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Multi-omics and random forest reveal lipid metabolism disruption and biomarkers in grass carp (Ctenopharyngodon idellus) exposed to 2-methylisoborneol.

Environmental research
The lipophilic nature of 2-methylisoborneol (2-MIB), a prevalent off-flavor compound in aquatic systems, raises concerns about its bioaccumulation potential and metabolic interference in fish. Most studies have focused on removing this compound from ...

CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy.

eLife
Understanding the complex three-dimensional structure of cells is crucial across many disciplines in biology and especially in neuroscience. Here, we introduce a set of models including a 3D transformer (SwinUNetR) and a novel 3D self-supervised lear...

High-entropy nanozyme biosensors: Machine learning-assisted design and stimulus-responsive applications.

Colloids and surfaces. B, Biointerfaces
High-entropy nanozymes (HENs) have emerged as a revolutionary class of bio-inspired catalysts that integrate multi-enzyme mimetic activities with environmental responsiveness, creating transformative opportunities for next-generation biosensing techn...

Establishing identifiable characteristic fingerprints of mulberry leaves: Integrating chemical composition and bioactivity through machine learning.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves (Morus alba L.) are used in traditional Chinese medicine to clear the lungs and dispel wind-heat. Despite their common use, chemical reference substance rely solely on rutin, which may not reflect their...

Cold receptor TRPM8 as a target for migraine-associated pain and affective comorbidities.

The journal of headache and pain
BACKGROUND: Genetic variations in the Trpm8 gene that encodes the cold receptor TRPM8 have been linked to protection against polygenic migraine, a disabling condition primarily affecting women. Noteworthy, TRPM8 has been recently found in brain areas...

Uncovering injury-specific proteomic signatures and neurodegenerative risks in single and repetitive traumatic brain injury.

Signal transduction and targeted therapy
Traumatic brain injury (TBI) is a major public health concern associated with an increased risk of neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), and chronic traumatic encephalopathy, yet the underlying molec...

Use of Artificial Neural Networks (ANNs) to assess xenobiotics in a river catchment using macroinvertebrates as bioindicators.

Aquatic toxicology (Amsterdam, Netherlands)
The Danube flows through various European regions, exposing its aquatic ecosystem to multiple stressors, including dams, canalization, and agricultural activities. Fertilizers, manures, pesticides, animal husbandry activities, irrigation practices, d...

Identification of natural food-derived emulsifiers using QSAR and machine learning: Application in dairy emulsions.

Food chemistry
Emulsifiers maintain the stability of emulsions, and milk protein-formed emulsions are unstable. Hence, efficient ways to screen food-derived compounds need to be identified. This study combined molecular descriptors with machine learning algorithms ...

Triclosan exposure potentiates ischemic stroke risk: Multi-omics integration and molecular docking unveil neurotoxic mechanisms.

Ecotoxicology and environmental safety
This study applied network toxicology and multimodal biological approaches integrated with machine learning to systematically identify four TCS-IS-related genes, providing a comprehensive understanding of the pathophysiological relationship between t...

Transcriptomic analysis reveals novel targets in benign schwannoma using machine learning.

Neuroscience
BACKGROUND & OBJECTIVE: This study aimed to identify key immune-related biomarkers of benign schwannoma through machine learning-assisted transcriptomic and single-cell analyses, and to construct a predictive model for disease evaluation.