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.
Animals ; Animals, Laboratory ; Behavior, Animal ; Body Size ; Complement System Proteins ; Decision Trees ; Drug Evaluation, Preclinical ; Humans ; Injections, Intradermal ; Machine Learning ; Methods ; Mice ; Motion Pictures as Topic ; Pruritus ; Research Design ; Sensitivity and Specificity ; Video Recording

We report a case of bilateral femur fracture which may have resulted in part from long-term administration of antipsychotic agents. A 43-year-old female patient with pain in both thighs visited our clinic. We conducted Xray and magnetic resonance imaging (MRI) examinations which revealed bilateral femur fractures. The right proximal femur had a complete fracture, and the left proximal femur had an incomplete fracture, both of which were in the subtrochanteric area. The patient was treated by intramedullary nailing in the right femur. Laboratory analysis showed hyperprolactinemia and hypogonadism. Bone mineral density analysis showed osteoporosis. Antipsychotic drug-induced hyperprolactinemia is a well-known phenomenon. Despite concerns about hyperprolactinemia induced osteoporotic fracture in patients treated with only prolactin-elevating medications, the issue has not been extensively studied. If hyperprolactinemia patients suffer from uncontrolled pain, we recommend MRI examination as surgeons should be aware of the possibility of osteoporotic fracture induced by hyperprolactinemia.

Purpose: The purpose of this study was to analyze the motion of the shoulder joint dynamically through a depth sensor-based motion analysis system for the normal group and patients group with shoulder disease and to report the results along with a review of the relevant literature. Materials and Methods: Seventy subjects participated in the study and were categorized as follows: 30 subjects in the normal group and 40 subjects in the group of patients with shoulder disease. The patients with shoulder disease were subdivided into the following four disease groups: adhesive capsulitis, impingement syndrome, rotator cuff tear, and cuff tear arthropathy. Repeating abduction and adduction three times, the angle over time was measured using a depth sensor-based motion analysis system. The maximum abduction angle (θmax ), the maximum abduction angular velocity (ωmax ), the maximum adduction angular velocity (ωmin ) , and the abduction/adduction time ratio (tabd / tadd ) were calculated. The above parameters in the 30 subjects in the normal group and 40 subjects in the patients group were compared. In addition, the 30 subjects in the normal group and each subgroup (10 patients each) according to the four disease groups, giving a total of five groups, were compared. Results: Compared to the normal group, the maximum abduction angle (θmax ), the maximum abduction angular velocity (ωmax ), and the maximum adduction angular velocity (ωmin ) were lower, and abduction/adduction time ratio (tabd /tadd ) was higher in the patients with shoulder disease. A comparison of the subdivided disease groups revealed a lower maximum abduction angle (θmax ) and the maximum abduction angular velocity (ωmax ) in the adhesive capsulitis and cuff tear arthropathy groups than the normal group. In addition, the abduction/adduction time ratio (tabd /tadd ) was higher in the adhesive capsulitis group, rotator cuff tear group, and cuff tear arthropathy group than in the normal group. Conclusion Through an evaluation of the shoulder joint using the depth sensor-based motion analysis system, it was possible to measure the range of motion, and the dynamic motion parameter, such as angular velocity. These results show that accurate evaluations of the function of the shoulder joint and an in-depth understanding of shoulder diseases are possible.

This paper reports the use of a traction device for the treatment of neglected proximal interphalangeal fracture dislocations. A 44-year-old man with a fracture dislocation of a right ring finger proximal interphalangeal joint was admitted 17 days after the injury. Closed reduction and external fixation were performed using a dynamic traction device and C-arm under a brachial plexus block. Passive range of motion exercise was started after two weeks postoperatively and active range of motion exercise was started after three weeks. The traction device was removed after five weeks. No infection occurred during the traction period. No subluxation or displacement was observed on the X-ray taken two months postoperatively. The active range of motion of the proximal interphalangeal joint was 90°. The patient was satisfied with the functional result of the treatment with the traction device. The dynamic traction device is an effective treatment for neglected fracture dislocations of the proximal interphalangeal joint of a finger.
Adult ; Brachial Plexus Block ; Dislocations ; External Fixators ; Fingers ; Humans ; Joints ; Range of Motion, Articular ; Traction