Deep Learning for Face Detection and Pain Assessment in Japanese macaques (Macaca fuscata).

Facial expressions have increasingly been used to assess emotional states in mammals. The recognition of pain in research animals is essential for their well-being and leads to more reliable research outcomes. Automating this process could contribute to early pain diagnosis and treatment. Artificial neural networks have become a popular option for image classification tasks in recent years due to the development of deep learning. In this study, we investigated the ability of a deep learning model to detect pain in Japanese macaques based on their facial expression. Thirty to 60 min of video footage from Japanese macaques undergoing laparotomy was used in the study. Macaques were recorded undisturbed in their cages before surgery (No Pain) and one day after the surgery before scheduled analgesia (Pain). Videos were processed for facial detection and image extraction with the algorithms RetinaFace (adding a bounding box around the face for image extraction) or Mask R-CNN (contouring the face for extraction). ResNet50 used 75% of the images to train systems; the other 25% were used for testing. Test accuracy varied from 48 to 54% after box extraction. The low accuracy of classification after box extraction was likely due to the incorporation of features that were not relevant for pain (for example, background, illumination, skin color, or objects in the enclosure). However, using contour extraction, preprocessing the images, and fine-tuning, the network resulted in 64% appropriate generalization. These results suggest that Mask R-CNN can be used for facial feature extractions and that the performance of the classifying model is relatively accurate for nonannotated single-frame images.

Seasonal variation of energy expenditure in Japanese macaques (Macaca fuscata).

Animals living in seasonal environments must adapt to a wide variation of temperature changes which requires flexible adjustments of time budget and metabolic processes for efficient thermoregulation. The Japanese macaque (Macaca fuscata) is one of only a handful of nonhuman primate species that experience seasonal climates over a wide temperature range. We used behavior observations, accelerometer sensors and the doubly-labelled water (DLW) method to measure activity and total daily energy expenditure (TDEE) of M. fuscata housed in captivity but exposed to natural seasonal variations at day lengths ranging from 10 to 12 h and temperature ranging from 0° to 32°C. Although overall activity was significantly lower in winter compared to summer and autumn, we found no effect of temperature on day-time activity. However nocturnal inactivity and mean length of sleeping bouts significantly increased along a gradient of decreasing temperatures from summer through winter, suggesting the importance of adaptive behavioral thermoregulation in this species. Energy expenditure that was unaccounted for by Basal Metabolic Rate (BMR) and physical activity i.e. expended through diet-induced thermogenesis or thermoregulation was between 14% and 32%. This residual energy expenditure differed between summer/autumn and winter and was relatively consistent across individuals (approximately 5-8% higher in winter). The percentage of body fat and residual energy expenditure were negatively correlated, supporting that fat storage was higher when less energy was required for thermoregulation. Our results suggest that physiological mechanisms like behavioral and autonomic thermoregulation enable M. fuscata to adapt to wide fluctuations in environmental conditions which provide insights into the evolutionary adaptations of nonhuman primates in seasonal climate.

A novel therapeutic approach for thrombocytopenia by minibody agonist of the thrombopoietin receptor.

Antibodies have brought valuable therapeutics in the clinical treatment of various diseases without serious adverse effects through their intrinsic features such as specific binding to the target antigen with high affinity, clinical safety as serum proteins, and long half-life. Agonist antibodies, furthermore, could be expected to maximize the value of therapeutic antibodies. Indeed, several IgG/IgM antibodies have been reported to induce cellular growth/differentiation and apoptosis. These agonist antibodies, however, should be further improved to exert more potent biologic activities and appropriate serum half-life depending upon the disease indications. Here, we report that IgG antibodies against the thrombopoietin receptor (Mpl), which have an absence or very weak agonist activity, can be engineered to be agonist minibodies, which include diabody or sc(Fv)2 as potent as natural ligand. Through this technological development, minibodies have been successfully constructed to bind and activate 2 types of dysfunctional mutant Mpls that cause congenital amegakaryocytic thrombocytopenia (CAMT). This drastic conversion of biologic activities by designing minibodies can be widely applicable to generate agonist minibodies for clinical application, which will constitute a new paradigm in antibody-based therapeutics.