Can AI make people happy? The effect of AI-based chatbot on smile and speech in Parkinson's disease.

INTRODUCTION: Approaches for objectively measuring facial expressions and speech may enhance clinical and research evaluation in telemedicine, which is widely employed for Parkinson's disease (PD). This study aimed to assess the feasibility and efficacy of using an artificial intelligence-based chatbot to improve smile and speech in PD. Further, we explored the potential predictive value of objective face and speech parameters for motor symptoms, cognition, and mood. METHODS: In this open-label randomized study, we collected a series of face and conversational speech samples from 20 participants with PD in weekly teleconsultation sessions for 5 months. We investigated the effect of daily chatbot conversations on smile and speech features, then we investigated whether smile and speech features could predict motor, cognitive, and mood status. RESULTS: A repeated-measures analysis of variance revealed that the chatbot conversations had a significant interaction effect on the mean and standard deviation of the smile index during smile sections (both P = .02), maximum duration of the initial rise of the smile index (P = .04), and frequency of filler words (P = .04), but no significant interaction effects were observed for clinical measurements including motor, cognition, depression, and quality of life. Explorative analysis using statistical and machine-learning models revealed that the smile indices and several speech features were associated with motor symptoms, cognition, and mood in PD. CONCLUSION: An artificial intelligence-based chatbot may positively affect smile and speech in PD. Smile and speech features may capture the motor, cognitive, and mental status of patients with PD.

Current Status of Telemedicine for Parkinson's Disease in Japan: A Single-Center Cross-Sectional Questionnaire Survey.

OBJECTIVE: Using telemedicine is a way to improve the accessibility of specialists for patients with Parkinson's disease (PD); however, it is not widely used in Japan. We investigated the efficacy of telemedicine in PD by using a single-center cross-sectional questionnaire survey. METHODS: We sent a questionnaire to patients who agreed to participate from among 52 patients with PD who had used telemedicine services at Juntendo University Hospital from October 2017 to November 2018. Caregivers were asked to respond to one question separately. RESULTS: A total of 38 patients responded to the questionnaire. Most patients were satisfied with the telemedicine consultation (7.8 ± 1.9), reporting that it was effective in reducing their travel burden. Twenty-one patients attended a telemedicine consultation with their caregivers, and their satisfaction was high (8.4 ± 1.8). CONCLUSION: In a specific cohort in Japan, patients with PD and their caregivers were mostly satisfied with the telemedicine service.

Possible Antipruritic Mechanism of Cyclosporine A in Atopic Dermatitis.

Cyclosporine A is an immunosuppressive agent that suppresses pruritus and is currently used in the treatment of patients with severe atopic dermatitis. The aim of this study was to elucidate the antipruritic mechanism of cyclosporine A using a mouse model of atopic dermatitis. Intraperitoneal injection of cyclosporine A (5 mg/kg) significantly reduced epidermal nerve density, number of scratching bouts, dermatitis scores, and transepidermal water loss, as well as decreasing the numbers of inflammatory cells in the dermis and decreasing epidermal thickness. Intraperitoneal injection of cyclosporine A dose-dependently inhibited increased itch-related receptor gene expression, such as interleukin-31 receptor A and neurokinin-1 receptor, in the dorsal root ganglion of atopic dermatitis model mice. Thus, the antipruritic efficacy of cyclosporine A may involve reduced epidermal nerve density and expression levels of itch-related receptor genes in the dorsal root ganglion, as well as improvement in acanthosis and reduction in cutaneous inflammatory cell number.