Machine-Learning Based Automatic and Real-time Detection of Mouse Scratching Behaviors

Scratching is a main behavioral response accompanied by acute and chronic itch conditions, and has been quantified as an objective correlate to assess itch in studies using laboratory animals. Scratching has been counted mostly by human annotators, which is a time-consuming and laborious process. It has been attempted to develop automated scoring methods using various strategies, but they often require specialized equipment, costly software, or implantation of device which may disturb animal behaviors. To complement limitations of those methods, we have adapted machine learning-based strategy to develop a novel automated and real-time method detecting mouse scratching from experimental movies captured using monochrome cameras such as a webcam. Scratching is identified by characteristic changes in pixels, body position, and body size by frame as well as the size of body. To build a training model, a novel two-step J48 decision tree-inducing algorithm along with a C4.5 post-pruning algorithm was applied to three 30-min video recordings in which a mouse exhibits scratching following an intradermal injection of a pruritogen, and the resultant frames were then used for the next round of training. The trained method exhibited, on average, a sensitivity and specificity of 95.19% and 92.96%, respectively, in a performance test with five new recordings. This result suggests that it can be used as a non-invasive, automated and objective tool to measure mouse scratching from video recordings captured in general experimental settings, permitting rapid and accurate analysis of scratching for preclinical studies and high throughput drug screening.

Draft Genome of Toxocara canis, a Pathogen Responsible for Visceral Larva Migrans

This study aimed at constructing a draft genome of the adult female worm Toxocara canis using next-generation sequencing (NGS) and de novo assembly, as well as to find new genes after annotation using functional genomics tools. Using an NGS machine, we produced DNA read data of T. canis. The de novo assembly of the read data was performed using SOAPdenovo. RNA read data were assembled using Trinity. Structural annotation, homology search, functional annotation, classification of protein domains, and KEGG pathway analysis were carried out. Besides them, recently developed tools such as MAKER, PASA, Evidence Modeler, and Blast2GO were used. The scaffold DNA was obtained, the N50 was 108,950 bp, and the overall length was 341,776,187 bp. The N50 of the transcriptome was 940 bp, and its length was 53,046,952 bp. The GC content of the entire genome was 39.3%. The total number of genes was 20,178, and the total number of protein sequences was 22,358. Of the 22,358 protein sequences, 4,992 were newly observed in T. canis. Following proteins previously unknown were found: E3 ubiquitin-protein ligase cbl-b and antigen T-cell receptor, zeta chain for T-cell and B-cell regulation; endoprotease bli-4 for cuticle metabolism; mucin 12Ea and polymorphic mucin variant C6/1/40r2.1 for mucin production; tropomodulin-family protein and ryanodine receptor calcium release channels for muscle movement. We were able to find new hypothetical polypeptides sequences unique to T. canis, and the findings of this study are capable of serving as a basis for extending our biological understanding of T. canis.

Celiac Disease in a Predisposed Subject (HLA-DQ2.5) with Coexisting Graves' Disease

Celiac disease is an intestinal autoimmune disorder, triggered by ingestion of a gluten-containing diet in genetically susceptible individuals. The genetic predisposition is related to human leukocyte antigen (HLA) class II genes, especially HLA-DQ2-positive patients. The prevalence of celiac disease has been estimated to be ~1% in Europe and the USA, but it is rarer and/or underdiagnosed in Asia. We report a case of celiac disease in a predisposed patient, with a HLA-DQ2 heterodimer, and Graves' disease that was treated successfully with a gluten-free diet. A 47-year-old woman complained of persistent chronic diarrhea and weight loss over a 9 month period. Results of all serological tests and stool exams were negative. However, the patient was found to carry the HLA DQ2 heterodimer. Symptoms improved after a gluten-free diet was initiated. The patient has been followed and has suffered no recurrence of symptoms while on the gluten-free diet. An overall diagnosis of celiac disease was made in a genetically predisposed patient (HLA-DQ2 heterodimer) with Graves' disease.