AIMC Topic: Animals

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Function of a multimodal signal: A multiple hypothesis test using a robot frog.

The Journal of animal ecology
Multimodal communication may evolve because different signals may convey information about the signaller (content-based selection), increase efficacy of signal processing or transmission through the environment (efficacy-based selection), or modify t...

Detecting Animal Contacts-A Deep Learning-Based Pig Detection and Tracking Approach for the Quantification of Social Contacts.

Sensors (Basel, Switzerland)
The identification of social interactions is of fundamental importance for animal behavioral studies, addressing numerous problems like investigating the influence of social hierarchical structures or the drivers of agonistic behavioral disorders. Ho...

Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning.

Nature biomedical engineering
Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with gliob...

Detecting fine and elaborate movements with piezo sensors provides non-invasive access to overlooked behavioral components.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Behavioral phenotyping devices have been successfully used to build ethograms, but many aspects of behavior remain out of reach of available phenotyping systems. We now report on a novel device, which consists in an open-field platform resting on hig...

Three-Dimensional Visualization of the Podocyte Actin Network Using Integrated Membrane Extraction, Electron Microscopy, and Machine Learning.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Actin stress fibers are abundant in cultured cells, but little is known about them . In podocytes, much evidence suggests that mechanobiologic mechanisms underlie podocyte shape and adhesion in health and in injury, with structural change...

Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides are promising tools to fight against ever-growing antibiotic resistance. However, despite many advantages, their toxicity to mammalian cells is a critical obstacle in clinical application and needs to be addressed.

Ultrasound deep learning for monitoring of flow-vessel dynamics in murine carotid artery.

Ultrasonics
Several arterial diseases are closely related with mechanical properties of the blood vessel and interactions of flow-vessel dynamics such as mean flow velocity, wall shear stress (WSS) and vascular strain. However, there is an opportunity to improve...

Neural network features distinguish chemosensory stimuli in Caenorhabditis elegans.

PLoS computational biology
Nervous systems extract and process information from the environment to alter animal behavior and physiology. Despite progress in understanding how different stimuli are represented by changes in neuronal activity, less is known about how they affect...

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning.

Histochemistry and cell biology
Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tis...

An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila.

Genome biology
BACKGROUND: Enhancers are non-coding regions of the genome that control the activity of target genes. Recent efforts to identify active enhancers experimentally and in silico have proven effective. While these tools can predict the locations of enhan...