AIMC Topic: Animals

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Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.

PloS one
OBJECTIVE: In this work, we explore and develop a method that uses Raman spectroscopy to measure and differentiate radiation induced toxicity in murine lungs with the goal of setting the foundation for a predictive disease model.

Next generation insect taxonomic classification by comparing different deep learning algorithms.

PloS one
Insect taxonomy lies at the heart of many aspects of ecology, and identification tasks are challenging due to the enormous inter- and intraspecies variation of insects. Conventional methods used to study insect taxonomy are often tedious, time-consum...

The feasibility of robot-assisted radical cystectomy: an experimental study.

World journal of urology
PURPOSE: To investigate the feasibility of the avatera system for performing robot-assisted radical cystectomy (RARC) followed by intracorporeal reconstruction of ileal neobladder.

3D Soma Detection in Large-Scale Whole Brain Images via a Two-Stage Neural Network.

IEEE transactions on medical imaging
3D soma detection in whole brain images is a critical step for neuron reconstruction. However, existing soma detection methods are not suitable for whole mouse brain images with large amounts of data and complex structure. In this paper, we propose a...

Bio-Inspired Transparent Soft Jellyfish Robot.

Soft robotics
Jellyfish are among the widely distributed nature creatures that can effectively control the fluidic flow around their transparent soft body, thus achieving movements in the water and camouflage in the surrounding environments. Till now, it remains a...

Noninvasive Tracking of Every Individual in Unmarked Mouse Groups Using Multi-Camera Fusion and Deep Learning.

Neuroscience bulletin
Accurate and efficient methods for identifying and tracking each animal in a group are needed to study complex behaviors and social interactions. Traditional tracking methods (e.g., marking each animal with dye or surgically implanting microchips) ca...

Deconstructing body axis morphogenesis in zebrafish embryos using robot-assisted tissue micromanipulation.

Nature communications
Classic microsurgical techniques, such as those used in the early 1900s by Mangold and Spemann, have been instrumental in advancing our understanding of embryonic development. However, these techniques are highly specialized, leading to issues of int...

Deep learning-based ensemble modeling of Vibrio parahaemolyticus concentration in marine environment.

Environmental monitoring and assessment
Vibrio parahaemolyticus (V.p) is a marine pathogenic bacterium that poses a high risk to human health and shellfish industry, yet an effective regional-scale nowcasting model for managing the risk remains lacking. This study presents the first region...

Automated quantification and statistical assessment of proliferating cardiomyocyte rates in embryonic hearts.

American journal of physiology. Heart and circulatory physiology
The use of digital image analysis and count regression models contributes to the reproducibility and rigor of histological studies in cardiovascular research. The use of formalized computer-based quantification strategies of histological images essen...

AbAgIntPre: A deep learning method for predicting antibody-antigen interactions based on sequence information.

Frontiers in immunology
INTRODUCTION: Antibody-mediated immunity is an essential part of the immune system in vertebrates. The ability to specifically bind to antigens allows antibodies to be widely used in the therapy of cancers and other critical diseases. A key step in a...