AIMC Topic: Animals

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Attention module incorporated transfer learning empowered deep learning-based models for classification of phenotypically similar tropical cattle breeds (Bos indicus).

Tropical animal health and production
Accurate breed identification in dairy cattle is essential for optimizing herd management and improving genetic standards. A smart method for correctly identifying phenotypically similar breeds can empower farmers to enhance herd productivity. A conv...

Machine Learning-Driven SERS Nanoendoscopy and Optophysiology.

Annual review of analytical chemistry (Palo Alto, Calif.)
A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic ef...

Rapid total sialic acid monitoring during cell culture process using a machine learning model based soft sensor.

Biotechnology progress
Total sialic acid content (TSA) in biotherapeutic proteins is often a critical quality attribute as it impacts the drug efficacy. Traditional wet chemical assays to quantify TSA in biotherapeutic proteins during cell culture typically takes several h...

The implementation of robotic dogs in automatic detection and surveillance of red imported fire ant nests.

Pest management science
BACKGROUND: The Red Imported Fire Ant (RIFA), scientifically known as Solenopsis invicta, is a destructive invasive species causing considerable harm to ecosystems and generating substantial economic costs globally. Traditional methods for RIFA nests...

A deep-learning-based threshold-free method for automated analysis of rodent behavior in the forced swim test and tail suspension test.

Journal of neuroscience methods
BACKGROUND: The forced swim test (FST) and tail suspension test (TST) are widely used to assess depressive-like behaviors in animals. Immobility time is used as an important parameter in both FST and TST. Traditional methods for analyzing FST and TST...

A DNA robotic switch with regulated autonomous display of cytotoxic ligand nanopatterns.

Nature nanotechnology
The clustering of death receptors (DRs) at the membrane leads to apoptosis. With the goal of treating tumours, multivalent molecular tools that initiate this mechanism have been developed. However, DRs are also ubiquitously expressed in healthy tissu...

Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning.

Parasites & vectors
BACKGROUND: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understanding of their behaviour to devise effective disease control strategies. In this article we show that machine learning can provide a performance assessme...

Bioinformatics and machine learning to support nanomaterial grouping.

Nanotoxicology
Nanomaterials (NMs) offer plenty of novel functionalities. Moreover, their physicochemical properties can be fine-tuned to meet the needs of specific applications, leading to virtually unlimited numbers of NM variants. Hence, efficient hazard and ris...

Artificial Intelligence-Powered Molecular Docking and Steered Molecular Dynamics for Accurate scFv Selection of Anti-CD30 Chimeric Antigen Receptors.

International journal of molecular sciences
Chimeric antigen receptor (CAR) T cells represent a revolutionary immunotherapy that allows specific tumor recognition by a unique single-chain fragment variable (scFv) derived from monoclonal antibodies (mAbs). scFv selection is consequently a funda...