AIMC Topic: Animals

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Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification.

Molecular & cellular proteomics : MCP
Tandem mass spectrometry (MS/MS)-based phosphoproteomics is a powerful technology for global phosphorylation analysis. However, applying four computational pipelines to a typical mass spectrometry (MS)-based phosphoproteomic dataset from a human canc...

ColGen: An end-to-end deep learning model to predict thermal stability of de novo collagen sequences.

Journal of the mechanical behavior of biomedical materials
Collagen is the most abundant structural protein in humans, with dozens of sequence variants accounting for over 30% of the protein in an animal body. The fibrillar and hierarchical arrangements of collagen are critical in providing mechanical proper...

Automated Processing and Phenotype Extraction of Ovine Medical Images Using a Combined Generative Adversarial Network and Computer Vision Pipeline.

Sensors (Basel, Switzerland)
The speed and accuracy of phenotype detection from medical images are some of the most important qualities needed for any informed and timely response such as early detection of cancer or detection of desirable phenotypes for animal breeding. To impr...

The pilot study of group robot intervention on pediatric inpatients and their caregivers, using 'new aibo'.

European journal of pediatrics
The study on robot-assisted therapy in a pediatric field has not been applied sufficiently in clinical settings. The purpose of this pilot study is to explore the potential therapeutic effects of a group robot intervention (GRI), using dog-like socia...

Graphene oxide enhanced the endocrine disrupting effects of bisphenol A in adult male zebrafish: Integrated deep learning and metabolomics studies.

The Science of the total environment
In our previous studies, it was found that graphene oxide (GO) reduced the endocrine disruption of bisphenol A (BPA) in zebrafish embryo and larvae, but through different mechanisms. In this study, adult male zebrafish were selected to further unders...

A deep learning model for burn depth classification using ultrasound imaging.

Journal of the mechanical behavior of biomedical materials
Identification of burn depth with sufficient accuracy is a challenging problem. This paper presents a deep convolutional neural network to classify burn depth based on altered tissue morphology of burned skin manifested as texture patterns in the ult...

The creation of phenomena in interactive biorobotics.

Biological cybernetics
In so-called interactive biorobotics, robotic models of living systems interact with animals in controlled experimental settings. By observing how the focal animal reacts to the stimuli delivered by the robot, one tests hypotheses concerning the dete...

A systematic review of sutureless vascular anastomosis technologies.

Seminars in vascular surgery
Vascular anastomoses typically involve a handsewn technique requiring significant surgical training, expertise, and time. The aim of our systematic review was to identify and describe sutureless vascular anastomosis techniques. We performed a systema...

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram.

Nature methods
Charting an organs' biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehe...

Applying deep learning to quantify empty lacunae in histologic sections of osteonecrosis of the femoral head.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Osteonecrosis of the femoral head (ONFH) is a disease in which inadequate blood supply to the subchondral bone causes the death of cells in the bone marrow. Decalcified histology and assessment of the percentage of empty lacunae are used to quantify ...