Aim Previous reports showed associations between oxytocin induced labor and mental disorders in offspring. However, those reports are restricted in epidemiological analyses and its mechanism remains unclear. In this study, we hypothesized that induced labor directly causes brain damage in newborns and results in the development of mental disorders. Therefore we aimed to investigate this hypothesis with animal model. Methods The animal model of induced labor was established by subcutaneous oxytocin administration to term‐pregnant C57BL/6J mice. We investigated the neonatal brain damage with evaluating immediate early gene expression (c‐Fos, c‐Jun and JunB) by quantitative polymerase reaction and TdT‐mediated dUTP nick end labeling staining. To investigate the injured brain cell types, we performed double‐immunostaining with TdT‐mediated dUTP nick end labeling staining and each brain component specific protein, such as Oligo2, NeuN, GFAP and Iba1. Results Brain damage during induced labor led to cell death in specific brain regions, which are implicated in mental disorders, in only male offspring at P0. Furthermore, oligodendrocyte precursors were selectively vulnerable compared to the other cell types. This oligodendrocyte‐specific impairment during the perinatal period led to an increased numbers of Olig2‐positive cells at P5. Expression levels of oxytocin and Oxtr in the fetal brain were not affected by the oxytocin administered to mothers during induced labor. Conclusion Oligodendrocyte cell death in specific brain regions, which was unrelated to the oxytocin itself, was caused by induced labor in only male offspring. This may be an underlying mechanism explaining the human epidemiological data suggesting an association between induced labor and mental disorders.

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Purpose Sleep is an essential factor for athletes, and it is important to intervene in sleep to manage it. We need a device that can evaluate sleep easily and constantly. Consumer wearable devices can be useful tools for athletes. In order to use consumer wearable devices in clinical research, it is essential to conduct a validation study. Thus, we conducted a validation study to assess the Fitbit Alta HR TM (FBA)- a consumer wearable device with an accelerometer and a heart rate monitor to detect sleep stages and quality against electroencephalographic (EEG) studies in athletes. Patients and Methods Forty college athletes participated in the study. EEG was applied to participants simultaneously while wearing FBA. Results Regarding sleep parameters, there was a strong correlation between the total sleep time (TST)-EEG and the TST-Fitbit (r = 0.83; p < 0.001). Regarding the sleep stages, there was a modest correlation between the N3 sleep-EEG and the N3 sleep-Fitbit (r = 0.68; p < 0.001). In addition, there was a strong correlation between the percentage of N3 sleep in between sleep onset and initial rapid eye movement sleep-EEG and those on Fitbit (r = 0.73; p < 0.001). Conclusion These results demonstrate that FBA facilitates sleep monitoring and exhibits acceptable agreement with EEG. Therefore, FBA is a useful tool in athletes’ sleep management.

Sleep is involved in many physiological processes and is essential for both physical and mental health. Obesity and sleep deprivation due to sleep disorders are major public health issues. Their incidence is increasing, and they have a wide range of adverse health-related consequences, including life-threatening cardiovascular disease. The impact of sleep on obesity and body composition is well-known, and many studies have shown an association between insufficient or excessive sleep duration and obesity, body fat percentage, and weight gain. However, there is growing evidence of the effects of body composition on sleep and sleep disorders (particularly sleep disordered breathing) through anatomical and physiological mechanisms (nocturnal fluid shift, core body temperature, or diet). Although some research has been conducted on the bidirectional effects of sleep-disordered breathing and body composition, the specific effects of obesity and body composition on sleep and the underlying mechanisms that explain these effects remain unclear. Therefore, this review summarizes the findings on the effects of body composition on sleep and draws conclusions and proposals for future research in this field.