AIMC Topic: Animals

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Learning machine approach reveals microbial signatures of diet and sex in dog.

PloS one
The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already inve...

DeepCINAC: A Deep-Learning-Based Python Toolbox for Inferring Calcium Imaging Neuronal Activity Based on Movie Visualization.

eNeuro
Two-photon calcium imaging is now widely used to infer neuronal dynamics from changes in fluorescence of an indicator. However, state-of-the-art computational tools are not optimized for the reliable detection of fluorescence transients from highly s...

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography.

Journal of visualized experiments : JoVE
Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translation...

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.

Journal of visualized experiments : JoVE
Machine learning (ML) algorithms permit the integration of different features into a model to perform classification or regression tasks with an accuracy exceeding its constituents. This protocol describes the development of an ML algorithm to predic...

Capsule robot for gut microbiota sampling using shape memory alloy spring.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Human gut microbiota can provide lifelong health information and even influence mood and behaviour. We currently lack the tools to obtain a microbial sample, directly from the small intestine, without contamination.

Improved Antibiotic Detection in Raw Milk Using Machine Learning Tools over the Absorption Spectra of a Problem-Specific Nanobiosensor.

Sensors (Basel, Switzerland)
In this article we present the development of a biosensor system that integrates nanotechnology, optomechanics and a spectral detection algorithm for sensitive quantification of antibiotic residues in raw milk of cow. Firstly, nanobiosensors were des...

Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units.

Sensors (Basel, Switzerland)
Disaster robotics is a growing field that is concerned with the design and development of robots for disaster response and disaster recovery. These robots assist first responders by performing tasks that are impractical or impossible for humans. Unfo...

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

PloS one
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to r...

Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.

Laboratory investigation; a journal of technical methods and pathology
As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)popula...

Zebrafish exhibit associative learning for an aversive robotic stimulus.

Lab animal
Zebrafish have quickly emerged as a species of choice in preclinical research, holding promise to advance the field of behavioral pharmacology through high-throughput experiments. Besides biological and heuristic considerations, zebrafish also consti...