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Photoplethysmography (PPG) is easy to measure and provides important parameters related to heart rate and arrhythmia. However, automated PPG methods have not been developed because of their susceptibility to motion artifacts and differences in waveform characteristics among individuals. With increasing use of telemedicine, there is growing interest in application of deep neural network (DNN) technology for efficient analysis of vast amounts of PPG data. This study is about an algorithm for measuring a patient's PPG and comparing it with their own data stored previously and with the average data of several groups. Six deep neural networks were used to normalize the PPG waveform according to the heart rate by removing uninformative regions from the PPG, distinguishing between heartbeat and reflection pulses, dividing the heartbeat waveform into 10 segments and averaging the values according to each segments. PPG data were measured using telemedicine in both groups. Group 1 consisted of healthy people aged 25 to 35 years, and Group 2 consisted of patients between 60 and 75 years of age taking antihypertensive medications. The proposed algorithm could accurately determine which group the subject belonged with the newly measured PPG data (AUC = 0.998). On the other hand, errors were frequently observed in identification of individuals (AUC = 0.819).

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social communication deficits and repetitive/restricted behaviors. Although gene-environment interactions may explain the heterogeneous etiology of ASD, it is still largely unknown how the gene-environment interaction affects behavioral symptoms and pathophysiology in ASD. To address these questions, we used Cntnap2 knockout mice (genetic factor, G) exposed to valproic acid during embryonic development (environmental factor, E) as a gene-environment interaction (G × E) model. Paradoxically, the social deficits observed in the respective G and E models were improved in the G × E model; however, the high seizure susceptibility was more severe in the G × E -model than in the G and E models. Repetitive self-grooming and hyperactivity did not differ among the three models. The amplitudes of miniature excitatory postsynaptic currents in layer 2/3 pyramidal neurons of the medial prefrontal cortex were aberrant and similar in the G × E model when compared to the control group. Our findings suggest that the interaction of two risk factors does not always aggravate ASD symptoms but can also alleviate them, which may be key to understanding individual differences in behavioral phenotypes and symptom intensity.

Social support can relieve stress-induced behavioural outcomes, although its underlying molecular mechanisms are not fully understood. Here, we evaluated whether social interactions can prevent the restraint stress (RS)-induced cognitive impairments in male adolescent mice by utilizing molecular, cellular, and behavioural approaches. Acute RS in adolescent ICR mice impaired the working memory in the Y-maze test and memory consolidation and retrieval in the novel-object-recognition test (NORT). In addition, RS increased the extracellular signal-regulated kinases 1/2 phosphorylation (p-ERK1/2) in the prefrontal cortex (PFC) and corticosterone levels in the plasma. Interestingly, these outcomes were normalized by the presence of a conspecific animal (social support) during RS. RS also significantly upregulated the expression levels of known stress-relevant genes such as Egr1, Crh, and Crhr1, which were normalized by social support. Systemic injection of SL327 (an inhibitor of MEK1/2 that also blocks its downstream signal ERK1/2) prior to RS rescued the working memory impairments and the increased p-ERK1/2 while normalizing the expression of Egr1. Our results suggest that social support can alleviate the RS-induced cognitive impairments partly by modulating ERK1/2 phosphorylation and gene transcription in the PFC, and provide novel insights into the molecular mechanisms of the stress-buffering effects of social support.