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Perinatal exposure to valproic acid is commonly used for autism spectrum disorder (ASD) animal model development. The inhibition of histone deacetylases by VPA has been proposed to induce epigenetic changes during neurodevelopment, but the specific alterations in genetic expression underlying ASD-like behavioral changes remain unclear. We used qPCR-based gene expression and epigenetics tools and Western blotting in the hippocampi of neonatal valproic acid-exposed animals at 4 weeks of age and conducted the social interaction test to detect behavioral changes. Significant alterations in gene expression were observed in males, particularly concerning mRNA expression of Foxo3 , which was significantly associated with behavioral changes. Moreover, notable differences were observed in H3K27ac chromatin immunoprecipitation, quantitative PCR (ChIP-qPCR), and methylation-sensitive restriction enzyme-based qPCR targeting the Foxo3 gene promoter region. These findings provide evidence that epigenetically regulated hippocampal Foxo3 expression may influence social interaction-related behavioral changes. Furthermore, identifying sex-specific gene expression and epigenetic changes in this model may elucidate the sex disparity observed in autism spectrum disorder prevalence.

Background: Previous physiology-driven pain studies focused on examining the presence or intensity of physical pain. However, people experience various types of pain, including social pain, which induces negative mood; emotional distress; and neural activities associated with physical pain. In particular, comparison of autonomic nervous system (ANS) responses between social and physical pain in healthy adults has not been well demonstrated., Methods: We explored the ANS responses induced by two types of pain-social pain, associated with a loss of social ties; and physical pain, caused by a pressure cuff-based on multimodal physiological signals. Seventy-three healthy individuals (46 women; mean age = 20.67 ± 3.27 years) participated. Behavioral responses were assessed to determine their sensitivity to pain stimuli. Electrocardiogram, electrodermal activity, photoplethysmogram, respiration, and finger temperature (FT) were measured, and 12 features were extracted from these signals., Results: Social pain induced increased heart rate (HR) and skin conductance (SC) and decreased blood volume pulse (BVP), pulse transit time (PTT), respiration rate (RR), and FT, suggesting a heterogeneous pattern of sympathetic-parasympathetic coactivation. Moreover, physical pain induced increased heart rate variability (HRV) and SC, decreased BVP and PTT, and resulted in no change in FT, indicating sympathetic-adrenal-medullary activation and peripheral vasoconstriction., Conclusion: These results suggest that changes in HR, HRV indices, RR, and FT can serve as markers for differentiating physiological responses to social and physical pain stimuli., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jang, Eum, Yoon, Sohn and Byun.)

The current study aimed to investigate the possibility of rapid and accurate diagnoses of Panic disorder (PD) and Major depressive disorder (MDD) using machine learning. The support vector machine method was applied to 2-channel EEG signals from the frontal lobes (Fp1 and Fp2) of 149 participants to classify PD and MDD patients from healthy individuals using non-linear measures as features. We found significantly lower correlation dimension and Lempel-Ziv complexity in PD patients and MDD patients in the left hemisphere compared to healthy subjects at rest. Most importantly, we obtained a 90% accuracy in classifying MDD patients vs. healthy individuals, a 68% accuracy in classifying PD patients vs. controls, and a 59% classification accuracy between PD and MDD patients. In addition to demonstrating classification performance in a simplified setting, the observed differences in EEG complexity between subject groups suggest altered cortical processing present in the frontal lobes of PD patients that can be captured through non-linear measures. Overall, this study suggests that machine learning and non-linear measures using only 2-channel frontal EEGs are useful for aiding the rapid diagnosis of panic disorder and major depressive disorder., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships influencing this work., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Valproic acid (VPA), an anticonvulsant and mood stabilizer, may affect Notch signaling and mitochondrial function. In a previous study, acute VPA exposure induced increased expression of FOXO3, a transcription factor that shares common targets with pro-neuronal ASCL1. In this study, intraperitoneal acute VPA (400 mg/kg) administration in 4-week-old mice increased and decreased FOXO3 and ASCL1 expression, respectively, in the hippocampus, associated with sex-based differences. Treatment of Foxo3 siRNA increased the mRNA expression levels of Ascl1, Ngn2, Hes6, and Notch1 in PC12 cells. Furthermore, VPA exposure induced significant expression changes of mitochondria-related genes, including COX4 and SIRT1, in hippocampal tissues, associated with sex-based differences. This study suggests that acute VPA exposure differently affects proneural gene expression via FOXO3 induction in the hippocampus based on sex., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Valproic acid (VPA) is a known drug for treating epilepsy and mood disorders; however, it is not recommended for pregnant women because of its possible teratogenicity. VPA affects neurotransmission and gene expression through epigenetic mechanisms by acting as a histone deacetylase inhibitor and has been used to establish animal models of autism spectrum disorder (ASD). However, studies on the long-term effects of early exposure to VPA on glucocorticoid and neurosteroid synthesis in the brain are lacking. Therefore, this study aimed to investigate the long-term changes in metabolic alterations and gene expression regulation according to sex, using metabolic steroid profiling data from cerebral cortex samples of rats four weeks after VPA exposure (400 mg/kg). In neonatal VPA-exposed models, estradiol levels decreased, and cytochrome P450 19A1 gene ( Cyp19a1 ) expression was reduced in the prepubertal male cortex. Progesterone and allopregnanolone levels decreased, and 3β-hydroxysteroid dehydrogenase 1 gene ( Hsd3b1 ) expression was also downregulated in the prepubertal female cortex. Furthermore, cortisol levels increased, and mRNA expression of the nuclear receptor subfamily 3 group C member 1 gene ( Nr3c1 ) was downregulated in the cortices of both sexes. Unlike the neonatal VPA-exposed models, although a decrease in progestin and estradiol levels was observed in females and males, respectively, no differences were observed in cortisol levels in the cortex tissues of 8-week-old adult rats administered VPA for four weeks. These results indicate that early environmental chemical exposure induces long-term neurosteroid metabolic effects in the brain, with differences according to sex.

Background: Automatic diagnosis of depression based on speech can complement mental health treatment methods in the future. Previous studies have reported that acoustic properties can be used to identify depression. However, few studies have attempted a large-scale differential diagnosis of patients with depressive disorders using acoustic characteristics of non-English speakers., Objective: This study proposes a framework for automatic depression detection using large-scale acoustic characteristics based on the Korean language., Methods: We recruited 153 patients who met the criteria for major depressive disorder and 165 healthy controls without current or past mental illness. Participants' voices were recorded on a smartphone while performing the task of reading predefined text-based sentences. Three approaches were evaluated and compared to detect depression using data sets with text-dependent read speech tasks: conventional machine learning models based on acoustic features, a proposed model that trains and classifies log-Mel spectrograms by applying a deep convolutional neural network (CNN) with a relatively small number of parameters, and models that train and classify log-Mel spectrograms by applying well-known pretrained networks., Results: The acoustic characteristics of the predefined text-based sentence reading automatically detected depression using the proposed CNN model. The highest accuracy achieved with the proposed CNN on the speech data was 78.14%. Our results show that the deep-learned acoustic characteristics lead to better performance than those obtained using the conventional approach and pretrained models., Conclusions: Checking the mood of patients with major depressive disorder and detecting the consistency of objective descriptions are very important research topics. This study suggests that the analysis of speech data recorded while reading text-dependent sentences could help predict depression status automatically by capturing the characteristics of depression. Our method is smartphone based, is easily accessible, and can contribute to the automatic identification of depressive states., (©Ah Young Kim, Eun Hye Jang, Seung-Hwan Lee, Kwang-Yeon Choi, Jeon Gue Park, Hyun-Chool Shin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 25.01.2023.)

Objective: In this study, we investigated sex- and region-specific effects of acute trimethyltin (TMT) exposure on mitochondrial biogenesis., Methods: We treated TMT to primary neuronal cultures and 4-week-old male and female mice. We measured the mitochondrial DNA copy numbers using the quantitative polymerase chain reaction method. We also measured mitochondrial biogenesis related genes (sirtuin-1, estrogen-related receptor alpha, cytochrome C oxidase subunit IV) by western blotting., Results: The mitochondrial DNA copy number increased in the primary hippocampal neuron; however, it decreased in the primary cortical neuron. The mitochondrial copy number increased in the hippocampus and decreased in the cortex in the TMT treated female mice, though the mitochondrial copy number increased in both cortex and hippocampus in the TMT treated male mice. TMT treatment increased sirtuin-1 expression in the male hippocampus but did not in the female brain. In the female brain, estrogen-related receptor alpha expression decreased in the cortex though there is no significant change in the male brain. The protein level of mitochondrial protein, cytochrome C oxidase subunit IV, increased in both cortex and hippocampus after TMT injection in male mice brain, but not in female mice brain., Conclusion: Our data suggest that acute TMT exposure induces distinct sex-specific metabolic characteristics in the brain before significant sexual maturation.

Alteration in stress response seems to affect the development of psychiatric disorders. In this study, we aimed to investigate whether baseline peripheral biomarkers could predict the reduction of stress response among patients with major depressive disorder (MDD) and panic disorder (PD). Patients with MDD ( n = 41) and PD ( n = 52) and healthy controls (HC, n = 59) were selected and regularly followed up with five visits for 12 weeks. The severity of stress at every visit was assessed using the Stress Response Inventory (SRI), and peripheral biomarkers were measured by blood tests at baseline and 2, 4, 8, and 12 weeks. Interleukin (IL)-6, IL-10, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, C-reactive protein (CRP), adiponectin, and leptin levels were analyzed using enzyme-linked immunosorbent assays. Reduction of stress response was defined as the difference in SRI score between baseline and 12 weeks divided by the baseline score. SRI scores were significantly ( p < 0.0001) higher in patients with MDD and PD than in HC at every visit after adjusting for variables. In multivariable linear regression, adiponectin levels at baseline were significantly associated with reduction of stress response in patients with PD. When adiponectin increased 1 mg/l, stress response decreased 0.781 points (β = -0.781, S.E. = 0.220, p = 0.001). Among the subscales of SRI, somatization had a moderate negative correlation with adiponectin levels ( r = -0.469). There was no significant association between baseline peripheral biomarkers and reduction of stress response in patients with MDD. Our study showed an inverse association between baseline adiponectin levels and stress response changes in patients with PD, but not in patients with MDD. Thus, differentiated approaches for assessing and treating stress responses of patients with PD and MDD might be helpful. Larger and longitudinal studies are necessary to establish the role and mechanism of action of adiponectin in regulating stress responses in PD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Park, Jang, Kim, Kim, Kim, Byun, Yu and Jeon.)

Valproic acid (VPA) is an antiepileptic drug found to induce mitochondrial dysfunction and autophagy in cancer cell lines. We treated the SH-SY5Y cell line with various concentrations of VPA (1, 5, and 10 mM). The treatment decreased cell viability, ATP production, and mitochondrial membrane potential and increased reactive oxygen species production. In addition, the mitochondrial DNA copy number increased after VPA treatment in a dose-dependent manner. Western blotting showed that the levels of mitochondrial biogenesis-related proteins (PGC-1α, TFAM, and COX4) increased, though estrogen-related receptor expression decreased after VPA treatment. Further, VPA treatment increased the total and acetylated FOXO3a protein levels. Although SIRT1 expression was decreased, SIRT3 expression was increased, which regulated FOXO3 acetylation in the mitochondria. Furthermore, VPA treatment induced autophagy via increased LC3-II levels and decreased p62 expression and mTOR phosphorylation. We suggest that VPA treatment induces mitochondrial biogenesis and autophagy via changes in FOXO3a expression and posttranslational modification in the SH-SY5Y cell line.

Trimethyltin (TMT) is an irreversible neurotoxicant. Because prenatal TMT exposure has been reported to induce behavioral changes, this study was conducted to observe gender differences and epigenetic changes using a mouse model. In behavioral testing of offspring at 5 weeks of age, the total times spent in the center, corner, or border zones in the male prenatal TMT-exposed mice were less than those of control unexposed mice in the open-field test. Female TMT-exposed mice scored lower on total numbers of arm entries and percentages of alternations than controls in the Y-maze test with lower body weight. We found that only TMT-exposed males had fewer copies of mtDNA in the hippocampus and prefrontal cortex region than controls. Additional epigenetic changes, including increased 5-methyl cytosine/5-hydroxymethyl cytosine levels in the male TMT hippocampus, were observed. After methylation binding domain (MBD) sequencing, multiple signaling pathways related to metabolism and neurodevelopment, including FoxO signaling, were identified by pathway analysis for differentially methylated regions (DMRs). Increased FOXO3 and decreased ASCL1 expression were also observed in male TMT hippocampi. This study suggests that sex differences and epigenetics should be more carefully considered in prenatal toxicology studies.

Background/aim: In this study, we investigated sex-specific effects of acute exposure to trimethyltin, a known neurotoxicant on metabolic steroids., Materials and Methods: We administered intraperitoneally 2.3 mg/kg trimethyltin to 4-week-old male mice and measured the levels of metabolic steroids 24 h after treatment. We also measured mRNA and protein levels of cytochrome P450 1B1 using real-time polymerase chain reaction and western blotting., Results: Cortisol levels in the cortex increased in both sexes following acute trimethyltin exposure. The estradiol levels decreased, and the 4-hydroxyestradiol levels increased only in females. We also observed increased cytochrome P450 1B1 mRNA and protein levels only in the female cortex., Conclusion: Acute trimethyltin exposure induces distinct sex-specific metabolic changes in the brain before significant sexual maturation., (Copyright© 2021, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Previous studies have investigated the role of inflammatory markers in suicidality of patients with major depressive disorder (MDD) or panic disorder (PD). However, few studies have investigated associations between serum inflammatory cytokine levels and suicidality. We hypothesized that MDD and PD status might be significantly associated with serum inflammatory cytokines and that we could predict levels of improvement in suicide ideation intensity using serum inflammatory biomarkers in patients with MDD and PD. For this study, 41 patients with MDD, 52 patients with PD, and 59 healthy control (HC) subjects were enrolled. Psychological measurements and serum inflammatory markers such as interleukin (IL) -6, -10, interferon (IFN)-γ, tumor necrosis factor (TNF)-α, and C reactive protein (CRP) were examined. A total of five visits were completed during 12 weeks. After controlling for confounding factors, log-transformed IL-6 (ln&#95;IL-6) at baseline (MDD: 0.297 ± 0.626; PD: 0.342 ± 0.723; HC: -0.121 ± 0.858; p = 0.007, >0.0017, 0.05/30) and mean ln&#95;IL-6 (MDD: 0.395 ± 0.550, PD: 0.249 ± 0.544, HC: -0.139 ± 0.622, p = 0.002, >0.0017, 0.05/30) levels were trends towards significantly higher in patients with MDD and PD than in HC. In MDD patients, a higher level of basal ln&#95;TNF-α was a significant predictor of ΔSSI (changes in SSI scores between baseline and week 12) even after controlling for changes of depression symptoms and baseline SSI scores (standardized β = 0.541, p = 0.002 < 0.0028, 0.05/18). In conclusion, we could predict ΔSSI using baseline inflammatory biomarkers for patients with MDD., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Emotions are experienced differently by individuals, and thus, it is important to account for individuals' experienced emotions to understand their physiological responses to emotional stimuli. The present study investigated the physiological responses to a fear-inducing stimulus and examined whether these responses can predict experienced fear. A total of 230 participants were presented with neutral and fear-inducing film clips, after which they self-rated their experienced emotions. Physiological measures (skin conductance level and response: SCL, SCR, heart rate: HR, pulse transit time: PTT, fingertip temperature: FT, and respiratory rate: RR) were recorded during the stimuli presentation. We examined the correlations between the physiological measures and the participants' experienced emotional intensity, and performed a multiple linear regression to predict fear intensity based on the physiological responses. Of the participants, 92.5% experienced the fear emotion, and the average intensity was 5.95 on a 7-point Likert scale. Compared to the neutral condition, the SCL, SCR, HR, and RR increased significantly during the fear-inducing stimulus presentation whereas FT and PTT decreased significantly. Fear intensity correlated positively with SCR and HR and negatively with SCL, FT, PTT, and RR. The multiple linear regression demonstrated that fear intensity was predicted by a combination of SCL, SCR, HR, FT, and RR. Our findings indicate that the physiological responses to experiencing fear are associated with cholinergic, sympathetic, and α-adrenergic vascular activation as well as myocardial β-sympathetic excitation, and support the use of multimodal physiological signals for quantifying emotions., (Copyright: © 2020 University of Economics and Human Sciences in Warsaw.)

We report on the synthesis and characterization of highly monodisperse amorphous silica nanoparticles (ASNs) and mesoporous silica nanoparticles (MSNs) with particle sizes of 15-60 nm. We demonstrate adsorption of Cr(VI) ions on amino-functionalized ASNs (NH 2 -ASNs) and MSNs (NH 2 -MSNs) and their removal from aqueous environments and show the specific surface area (SSA) of NH 2 -MSNs is four times as larger as that of NH 2 -ASNs and that more than 70% of the total SSA of NH 2 -MSNs is due to the presence of nanopores. Analyses of Cr(VI) adsorption kinetics on NH 2 -ASNs and NH 2 -MSNs exhibited relatively rapid adsorption behavior following pseudo-second order kinetics as determined by nonlinear fitting. NH 2 -ASNs and NH 2 -MSNs exhibited significantly higher Cr(VI) adsorption capacities of 34.0 and 42.2 mg·g -1 and removal efficiencies of 61.9 and 76.8% than those of unfunctionalized ASNs and MSNs, respectively. The Langmuir model resulted in best fits to the adsorption isotherms of NH 2 -ASNs and NH 2 -MSNs. The adsorption of Cr(VI) on NH 2 -ASNs and NH 2 -MSNs was an endothermic and spontaneous process according to the thermodynamic analyses of temperature-dependent adsorption isotherms. The removal efficiencies of NH 2 -ASNs and NH 2 -MSNs exhibited a moderate reduction of less than 25% of the maximum values after five regeneration cycles. Furthermore, NH 2 -MSNs were also found to reduce adsorbed Cr(VI) into less harmful Cr(III).

Purpose: The purpose of this study was to evaluate the effects of an education program for mothers of late-preterm infants on parenting confidence, breastfeeding rate, and infants' growth and readmission rate., Methods: The participants were 53 mothers of late-preterm infants (26 in the experimental group and 27 in the control group). The experimental group was administered the late-preterm care education program while the control group received standard care. The program consisted of two sessions during hospitalization after birth, one session at the time of discharge, and telephone and social networking service consultations at weekly intervals for the month following discharge. The collected data were analyzed using the t-test, χ 2 test, and repeated-measures analysis of variance., Results: Parenting confidence and the breastfeeding rate were significantly higher in the experimental group than in the control group. However, there was no significant difference in the late-preterm infants' growth and readmission rates between the experimental and control groups., Conclusion: A care education program for mothers of late-preterm infants can be a useful nursing intervention in clinical practice., Competing Interests: No existing or potential conflict of interest relevant to this article was reported., (Copyright © 2020 Korean Academy of Child Health Nursing. All rights reserved.)

Studies in animal models have shown that the short-chain fatty acid, propionic acid (PPA), interferes with mitochondrial metabolism leading to mitochondrial dysfunction and behavioral abnormalities. The aim of this study was to investigate the effects of PPA on mitochondrial function and gene expression in neuronal cells. SH-SY5Y cells and normal human neural progenitor (NHNP) cells were exposed to 1, 5 mM PPA for 4 or 24 h and we found that the mitochondrial potential measured in SH-SY5Y cells decreased in a dose-dependent manner after PPA treatment. Electron microscopy analysis revealed that the size of the mitochondria was significantly reduced following PPA treatment. A dose-dependent increase in the mitochondrial DNA copy number was observed in the PPA-treated cells. The expression of the mitochondrial biogenesis-related proteins PGC-1α, TFAM, SIRT3, and COX4 was significantly increased after PPA treatment. Transcriptome analysis revealed that mRNA expression in the notch signaling-related genes ASCL1 and LFNG changed after PPA treatment and the positive correlated protein expression changes were also observed. These results revealed that PPA treatment may affect neurodevelopment by altering mitochondrial function and notch signaling-related gene expression., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: A link between brain-derived neurotrophic factor (BDNF) expression and the mood regulatory effect of leptin has been suggested in the pathophysiology of major depressive disorder (MDD). We investigated treatment response and pre-treatment leptin and BDNF in patients with MDD and with panic disorder (PD)., Methods: We recruited 41 patients with MDD, 52 patients with PD, and 59 matched healthy controls. All subjects completed five visits (at baseline, 2, 4, 8, and 12 weeks), and both MDD and PD patients were treated with standard pharmacotherapy for 12 weeks. Plasma BDNF (pBDNF) and blood leptin levels were obtained along with a 17-item Hamilton Depression Scale rating (HDRS-17) score at every visit., Results: The ratio of pre-treatment pBDNF to leptin was significantly lower in patients with MDD and PD compared to healthy controls (p = 0.024), but was not associated with severity of depressive or anxiety symptoms. Pre-treatment pBDNF:leptin ratio was significantly higher in treatment responders than in non-responders (p = 0.012) in MDD but not in PD. This difference was larger in MDD patients with appetite loss (p = 0.034). In multivariate analysis, pre-treatment pBDNF:leptin ratio was significantly associated with treatment responsiveness (Adjusted Odds Ration [AOR] = 2.50, 95% CI 1.02-6.14) in MDD., Limitation: small sample size; limited information on detailed pharmacological effects., Conclusions: A relatively higher ratio of pre-treatment pBDNF to leptin was associated with greater treatment response in MDD but not in PD. Further research should focus on exploration of a link between BDNF and leptin underlying neuronal plasticity in depression., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Although emotion-specific autonomic responses based on the discrete theory of emotion have been widely studied, studies on the reliability of physiological responses to emotional stimuli are limited. In this study, we aimed to assess the reliability of physiological changes induced by the six basic emotions (happiness, sadness, anger, fear, disgust, and surprise) that were measured during 10 weekly repeated experiments., Methods: Twelve college students participated, and in each experiment, physiological signals were collected before and while participants were watching emotion-provoking film clips. Additionally, the participants self-evaluated the emotions that they experienced during the film presentation at the end of each emotional stimulus. To avoid adaptation of participants to identical stimuli during repeated measurements, we used 10 different film clips for each emotion, and thus a total of 60 film clips over 10 weeks were used. Physiological features, such as skin conductance level (SCL), fingertip temperature (FT), heart rate (HR), and blood volume pulse (BVP), were extracted from the physiological signals. Two reliability indices, Cronbach's alpha and intraclass correlation coefficient, were calculated from the physiological features to assess internal consistency and interrater reliability, respectively., Results: We found that SCL, HR, and BVP measured during the emotion-provoking phase over the 10 weekly sessions were more reliable than those assessed at baseline. Furthermore, SCL, HR, and BVP from the emotion-provoking phase exhibited excellent internal consistency and interrater reliability., Conclusions: Our findings suggest that these features can be used as reliable physiological indices in emotion studies. The results also support the significance of physiological signals as meaningful indicators for emotion recognition in HCI (human computer interface) area.

Objective: Peripheral biomarkers have been studied to predict treatment response of panic symptoms. We hypothesized that depressive disorder (MDD) vs. panic disorder (PD) would exhibit different peripheral biomarkers, and their correlation with severity of panic attacks (PA) would also differ., Methods: Forty-one MDD patients, 52 PD patients, and 59 healthy controls were followed for 12 weeks. We measured peripheral biomarkers along with the Panic Disorder Severity Scale (PDSS) at each visit-pre-treatment, 2, 4, 8, and 12 weeks on a regular schedule. Peripheral biomarkers including serum cytokines, plasma and serum brain-derived neurotrophic factor (BDNF), leptin, adiponectin, and C-reactive protein (CRP) were quantified using enzyme-linked immunosorbent assay (ELISA)., Results: Patients with MDD and PD demonstrated significantly higher levels of pre-treatment IL-6 compared to controls, but no differences were seen in plasma and serum BDNF, leptin, adiponectin, and CRP. Pre-treatment leptin showed a significant clinical correlation with reduction of panic symptoms in MDD patients at visit 5 (p=0.011), whereas pre-treatment IL-6 showed a negative correlation with panic symptom reduction in PD patients (p=0.022). An improvement in three panic-related items was observed to be positively correlated with pre-treatment leptin in MDD patients: distress during PA, anticipatory anxiety, and occupational interference., Conclusion: Higher pre-treatment leptin was associated with better response to treatment regarding panic symptoms in patients with MDD, while higher IL-6 was associated with worse response regarding panic symptoms in PD patients. Different predictive peripheral biomarkers observed in MDD and PD suggest the need for establishing individualized predictive biomarkers, even in cases of similar symptoms observed in different disorders., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Major depressive disorder (MDD) is one of the leading causes of disability; however, current MDD diagnosis methods lack an objective assessment of depressive symptoms. Here, a machine learning approach to separate MDD patients from healthy controls was developed based on linear and nonlinear heart rate variability (HRV), which reflects the autonomic cardiovascular regulation., Methods: HRV data were collected from 37 MDD patients and 41 healthy controls during five 5-min experimental phases: the baseline, a mental stress task, stress recovery, a relaxation task, and relaxation task recovery. The experimental protocol was designed to assess the autonomic responses to stress and recovery. Twenty HRV indices were extracted from each phase, and a total of 100 features were used for classification using a support vector machine (SVM). SVM-recursive feature elimination (RFE) and statistical filter were employed to perform feature selection., Results: We achieved 74.4% accuracy, 73% sensitivity, and 75.6% specificity with two optimal features selected by SVM-RFE, which were extracted from the stress task recovery and mental stress phases. Classification performance worsened when individual phases were used separately as input data, compared to when all phases were included. The SVM-RFE using nonlinear and Poincaré plot HRV features performed better than that using the linear indices and matched the best performance achieved by using all features., Conclusions: We demonstrated the machine learning-based diagnosis of MDD using HRV analysis. Monitoring the changes in linear and nonlinear HRV features for various autonomic nervous system states can facilitate the more objective identification of MDD patients., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Depressive symptoms are related to abnormalities in the autonomic nervous system (ANS), and physiological signals that can be used to measure and evaluate such abnormalities have previously been used as indicators for diagnosing mental disorder, such as major depressive disorder (MDD). In this study, we investigate the feasibility of developing an objective measure of depressive symptoms that is based on examining physiological abnormalities in individuals when they are experiencing mental stress. To perform this, we recruited 30 patients with MDD and 31 healthy controls. Then, skin conductance (SC) was measured during five 5-min experimental phases, comprising baseline, mental stress, recovery from the stress, relaxation, and recovery from the relaxation, respectively. For each phase, the mean amplitude of the skin conductance level (MSCL), standard deviations of the SCL (SDSCL), slope of the SCL (SSCL), mean amplitude of the non-specific skin conductance responses (MSCR), number of non-specific skin conductance responses (NSCR), and power spectral density (PSD) were evaluated from the SC signals, producing 30 parameters overall (six features for each phase). These features were used as input data for a support vector machine (SVM) algorithm designed to distinguish MDD patients from healthy controls based on their physiological responses. Statistical tests showed that the main effect of task was significant in all SC features, and the main effect of group was significant in MSCL, SDSCL, SSCL, and PSD. In addition, the proposed algorithm achieved 70% accuracy, 70% sensitivity, 71% specificity, 70% positive predictive value, 71% negative predictive value in classifying MDD patients and healthy controls. These results demonstrated that it is possible to extract meaningful features that reflect changes in ANS responses to various stimuli. Using these features, detection of MDD was feasible, suggesting that SC analysis has great potential for future diagnostics and prediction of depression based on objective interpretation of depressive states., Competing Interests: The authors have declared that no competing interests exist.

Background: Heart Rate Variability (HRV) parameters have been used to evaluate the autonomic nervous system. We hypothesized that patients with major depressive disorder (MDD) and panic disorder (PD) showed different HRV profiles compared to healthy controls. We also hypothesized that we could predict the responder groups in the MDD and PD patients, using differences in HRV indices between the stress and rest phases., Methods: 28 MDD patients and 29 PD patients were followed for 12 weeks, and we also followed 39 healthy control subjects. We measured HRV parameters at the rest, stress, and recovery phases., Results: Patients with MDD and PD demonstrated lower pNN50 than controls during the stress (F = 7.49, p = 0.001), and recovery phases (F = 9.43, p = 0.0001). Patients with MDD and PD also showed higher LF/HF ratio than controls during the stress phase (F = 6.15, p = 0.002). Responders in the PD group presented a lower level of LF/HF ratio during the stress phase compared to non-responders (F = 10.14, p = 0.002), while responders in the MDD group showed a lower level of heart rate during all three phases, compared to non-responders. Additionally, we could predict treatment response in patients with MDD using ΔLF/HF ratio (OR: 1.33, 95% CI = 1.07-1.65, p = 0.011) and ΔpNN50 (OR: 1.49, 95% CI 1.09-1.77, p = 0.014)., Conclusion: The changes of HRV parameters of pNN50 and LF/HF ratio between the stress and recovery phase may be clinical markers of predictors of treatment responsiveness in MDD and PD patients., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: The current method to evaluate major depressive disorder (MDD) relies on subjective clinical interviews and self-questionnaires., Objective: Autonomic imbalance in MDD patients is characterized using entropy measures of heart rate variability (HRV). A machine learning approach for screening depression based on the entropy is demonstrated., Methods: The participants experience five experimental phases: baseline (BASE), stress task (MAT), stress task recovery (REC1), relaxation task (RLX), and relaxation task recovery (REC2). The four entropy indices, approximate entropy, sample entropy, fuzzy entropy, and Shannon entropy, are extracted for each phase, and a total of 20 features are used. A support vector machine classifier and recursive feature elimination are employed for classification., Results: The entropy features are lower in the MDD group; however, the disease does not have a significant effect. Experimental tasks significantly affect the features. The entropy did not recover during REC1. The differences in the entropy features between the two groups increased after MAT and showed the largest gap in REC2. We achieved 70% accuracy, 64% sensitivity, and 76% specificity with three optimal features during RLX and REC2., Conclusion: Monitoring of HRV complexity changes when a subject experiences autonomic arousal and recovery can potentially facilitate objective depression recognition.

Major depressive disorder (MDD) is a common psychiatric disorder and the leading cause of disability worldwide. However, current methods used to diagnose depression mainly rely on clinical interviews and self-reported scales of depressive symptoms, which lack objectivity and efficiency. To address this challenge, we present a machine learning approach to screen for MDD using electrodermal activity (EDA). Participants included 30 patients with MDD and 37 healthy controls. Their EDA was measured during five experimental phases consisted of baseline, mental arithmetic task, recovery from the stress task, relaxation task, and recovery from the relaxation task, which elicited multiple alterations in autonomic activity. Selected EDA features were extracted from each phase, and differential EDA features between two distinct phases were evaluated. By using these features as input data and performing feature selection with SVM-RFE, 74% accuracy, 74% sensitivity, and 71% specificity could be achieved by our decision tree classifier. The most relevant features selected by SVM-RFE included differential EDA features and features from the stress and relaxation tasks. These findings suggest that automatic detection of depression based on EDA features is feasible and that monitoring changes in physiological signal when a subject is experiencing autonomic arousal and recovery may enhance discrimination power.

This study proposes a simple method of fabricating flexible electronic devices using a metal template for passive alignment between chip components and an interconnect layer, which enabled efficient alignment with high accuracy. An electrocardiogram (ECG) sensor was fabricated using 20 µm thick polyimide (PI) film as a flexible substrate to demonstrate the feasibility of the proposed method. The interconnect layer was fabricated by a two-step photolithography process and evaporation. After applying solder paste, the metal template was placed on top of the interconnect layer. The metal template had rectangular holes at the same position as the chip components on the interconnect layer. Rectangular hole sizes were designed to account for alignment tolerance of the chips. Passive alignment was performed by simply inserting the components in the holes of the template, which resulted in accurate alignment with positional tolerance of less than 10 µm based on the structural design, suggesting that our method can efficiently perform chip mounting with precision. Furthermore, a fabricated flexible ECG sensor was easily attachable to the curved skin surface and able to measure ECG signals from a human subject. These results suggest that the proposed method can be used to fabricate epidermal sensors, which are mounted on the skin to measure various physiological signals.

CD38 is an enzyme that catalyzes the formation of cyclic ADP ribose and nicotinic acid adenine dinucleotide phosphate, both of which are involved in the mobilization of Ca(2+) from intracellular stores. Recently, CD38 has been shown to regulate oxytocin release from hypothalamic neurons. Importantly, CD38 mutations are associated with autism spectrum disorders (ASD) and CD38 knockout (CD38(-/-)) mice display ASD-like behavioral phenotypes including deficient parental behavior and poor social recognition memory. Although ASD and learning deficits commonly co-occur, the role of CD38 in learning and memory has not been investigated. We report that CD38(-/-) mice show deficits in various learning and memory tasks such as the Morris water maze, contextual fear conditioning, and the object recognition test. However, either long-term potentiation or long-term depression is not impaired in the hippocampus of CD38(-/-) mice. Our results provide convincing evidence that CD38(-/-) mice show deficits in various learning and memory tasks including spatial and non-spatial memory tasks. Our data demonstrate that CD38 is critical for regulating hippocampus-dependent learning and memory without modulating synaptic plasticity.

Background/aims: A limited number of studies addressed MRI-based neurodegenerative changes in subjective memory impairment (SMI). We investigated changes in white matter (WM) microstructures as well as gray matter (GM) macrostructures in subjects with SMI of high and low risk for progression., Methods: A modeling scale (score range, 0-6) developed for prediction of SMI progression was used to divide SMI subjects (n = 46) into two groups: a high risk of progression (score ≥3; n = 19) and a low risk of progression (score ≤2; n = 27). Cross-sectional comparisons were performed using a region-of-interest-based diffusion tensor imaging (DTI) analysis, cortical thickness analysis, and hippocampal volumetry., Results: The high-risk group had more microstructural disruption shown by lower fractional anisotropy in the hippocampus, parahippocampal gyrus, supramarginal gyrus, and parts of frontotemporal lobes. On the other hand, GM macrostructural changes did not differ between the groups and were not associated with modeling scale scores., Conclusion: SMI subjects with a high risk of progression had more WM microstructural disruption than those with a low risk, and the changes were not explained by GM atrophy. Our findings suggest that the degree of microstructural alterations in SMI may be distinctive according to the risk factors and may precede GM atrophy., (© 2016 S. Karger AG, Basel.)

Background: The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals., Methods: Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions., Results: The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7% is obtained by using DFA., Conclusions: This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.

Objective: As the fiberoptic gastroscopy using midazolam is being in widespread use, the exact nature of midazolam on memory should be clarified. We intended to examine whether midazolam causes selective anterograde amnesia and what impact it has on other aspects of memory and general cognitive function., Methods: We recruited healthy subjects undergoing fiberoptic gastroscopy under conscious sedation. At baseline, history taking for retrograde amnesia and the Korean version of the Montreal Cognitive Assessment were performed. A man's name and address were given immediately after intravenous midazolam administration. After gastroscopy, the subjects were asked to recall those items. By the time they had fully recovered consciousness, the same test was repeated along with the Korean version of the Montreal Cognitive Assessment and a test for retrograde amnesia., Results: A total of 30 subjects were enrolled in this study. Subjects with high-dose midazolam showed lower scores in the immediate and delayed recall of "a man's name and address" compared with those with low-dose midazolam. The midazolam dose was inversely correlated with the delayed recall scores of "a man's name and address." On full recovery of consciousness, the subjects did not exhibit any of anterograde or retrograde amnesia., Conclusions: These findings suggest that midazolam causes transient selective anterograde amnesia in a dose-dependent manner.

Mild cognitive impairment (MCI) describes a transitional state in progression from normal aging to dementia, especially Alzheimer's disease (AD). Currently, there is no effective pharmacological treatment that offers a long-term beneficial effect to delay the progression to dementia. There is growing evidence that supports an important role of non-pharmacological cognitive interventions. Therefore, it is warranted to clarify the distinct forms of cognitive interventions and their effects based on previous clinical trials. We aimed to provide a review of clinical trials of non-pharmacological cognitive interventions for MCI and to address the characteristics of the study patients, cognitive intervention programs and short-term / long-term benefits of the interventions. A total of 32 articles were identified according to the inclusion criteria. The results showed positive effects for both objective and subjective outcome variables, and these effects persisted from 1 month up to 5 years. Although many of the positive effects were related to improvement in trained tasks, alterations in neuroimaging and the transfer effects shown by some studies are encouraging. Future research in this area requires a larger sample size with a wider spectrum of MCI, more instructive outcome measures and a longer follow up duration.

Background: The genetic factors that determine the heterogeneity of cognitive impairment in Alzheimer's disease (AD) patients have been rarely reported. We aimed to investigate the association between top hits of genome-wide association studies (GWAS) and specific cognitive domains in AD patients., Methods: We investigated 86 single nucleotide polymorphisms (SNPs) selected from 12 genes (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, LRAT, MS4A6A, PCDH11X, and PICALM) based on results of the recent GWAS and genotyped in 211 AD cases. We also analyzed results of comprehensive neuropsychological evaluations in all cases. We performed multiple regression analyses., Results: There were four significant associations between genotypes and phenotypes of AD patients: CR1 SNP rs11803956 correlated with Mini-Mental State Examination (MMSE) score (β=1.718, Pcorrected=0.002); ABCA7 SNP rs3752232 correlated with Rey Complex Figure Test (RCFT) copy score (β=-6.861, Pcorrected=0.013); APOE SNP rs2075650 correlated with the percentile of RCFT copy score (β=14.005, Pcorrected=0.021) and the percentile of total score in phonemic fluency (β=11.052, Pcorrected=0.035)., Conclusion: Our results suggest that CR1, ABCA7, and APOE correlate with specific aspects of cognitive impairments in AD patients., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Although Parkinson's disease is a neurodegenerative disease primarily involving basal ganglia and midbrain, the deficit of white matter is also involved during the disease progression. As the diffusion tensor imaging method is sensitive to the microstructural changes, we investigated the microstructural alterations in white matter and deep gray matter in patients with Parkinson's disease. Brain images of 64 patients and sex- and age-matched 64 healthy controls were obtained from a 3T MRI scanner. Tract-based spatial statistics were used to compare the mean diffusivity of the white matter tract between the groups. Voxel-based analysis was used to compare the mean diffusivity of the subcortical gray matter between the groups. There were white matter deficits in the corticofugal tract, cingulum, uncinate fasciculus, crus of fornix or stria terminalis, corpus callosum, external capsule, superior longitudinal fasciculus, posterior thalamic radiation including optic radiation, and the tracts adjacent to the precuneus and supramarginal gyrus, as indicated by higher mean diffusivity in Parkinson's disease patients than in controls. There were also deficits in the left putamen, pallidum, thalamus, and caudate as indicated by higher mean diffusivity in Parkinson's disease patients than in controls. Using diffusion tensor imaging and multi-methods of image analysis, we successfully characterized and visualized brain white matter and deep gray matter areas with microstructural deficits in Parkinson's disease patients., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

We report an enhancement in light emission efficiency of Si nanocrystal (NC) light-emitting diodes (LEDs) by employing 5.5 periods of SiCN/SiC superlattices (SLs). SiCN and SiC layers in SiCN/SiC SLs were designed by considering the optical bandgap to induce the uniform electron sheet parallel to the SL planes. The electrical property of Si NC LED with SiCN/SiC SLs was improved. In addition, light output power and wall-plug efficiency of the Si NC LED with SiCN/SiC SLs were also enhanced by 50% and 40%, respectively. This was attributed to both the formation of two-dimensional electron gas, i.e., uniform electron sheet parallel to the SiCN/SiC SL planes due to the conduction band offset between the SiCN layer and SiC layer, and an enhanced electron transport into the Si NCs due to a lower tunneling barrier height. We show here that the use of the SiCN/SiC SL structure can be very useful in realizing a highly efficient Si NC LED.

Multiple system atrophy (MSA) is a sporadic, adult-onset disease characterized by progressive degeneration of nervous systems including cerebellar, pyramidal, extrapyramidal, and autonomic system. Although a few recent studies reported that cognitive impairments could occur in patients with MSA, prominent dementia with progressive decline is not a typical clinical manifestation of MSA. In particular, dementia with MSA-cerebellar type is very rare. We have experienced a patient with 2-year history of severe cognitive impairment, who was finally diagnosed as MSA-cerebellar type.

Background: The coexistence of myasthenia gravis (MG) and Lambert-Eaton myasthenic syndrome (LEMS) is very rare and remains controversial., Case Report: A 48-year-old woman initially presented with noticeable right ptosis and intermittent diplopia. She then developed fluctuating proximal limb weakness and difficulty in swallowing. The serum titer of anti-acetylcholine-receptor antibody was elevated and the edrophonium (Tensilon) test was positive. However, repetitive nerve stimulation revealed abnormalities typical of LEMS. The patient exhibited a good response to treatment with anticholinesterase inhibitors and steroids, and long-term evaluation disclosed that she presented with the clinical, electrophysiological, and immunological characteristics of both diseases., Conclusions: The reported clinical and electrophysiological features suggest that this patient was a very rare case of combined MG and LEMS.

The increasing occurrence of antibiotic-resistant pathogens is of growing concern, and must be counteracted by alternative antimicrobial treatments. Bacteriophages represent the natural enemies of bacteria. However, the strong immune response following application of phages and rapid clearance from the blood stream are hurdles which need to be overcome. Towards our goal to render phages less immunogenic and prolong blood circulation time, we have chemically modified intact bacteriophages by conjugation of the non-immunogenic polymer monomethoxy-polyethylene glycol (mPEG) to virus proteins. As a proof of concept, we have used two different polyvalent and strictly virulent phages of the Myoviridae, representing typical candidates for therapeutical approaches: Felix-O1 (infects Salmonella) and A511 (infects Listeria). Loss of phage infectivity after PEGylation was found to be proportional to the degree of modification, and could be conveniently controlled by adjusting the PEG concentration. When injected into naïve mice, PEGylated phages showed a strong increase in circulation half-life, whereas challenge of immunized mice did not reveal a significant difference. Our results suggest that the prolonged half-life is due to decreased susceptibility to innate immunity as well as avoidance of cellular defence mechanisms. PEGylated viruses elicited significantly reduced levels of T-helper type 1-associated cytokine release (IFN-γ and IL-6), in both naïve and immunized mice. This is the first study demonstrating that PEGylation can increases survival of infective phage by delaying immune responses, and indicates that this approach can increase efficacy of bacteriophage therapy., (© 2008 The Authors.)

This study aimed to investigate whether inhalation of the air with 30% oxygen compared with normal air enhances cognitive functioning through increased activation in the brain. The verbal and visuospatial tasks were performed while brain images were scanned. The results showed that there were improvements in performance and also increased activation in several brain areas under the condition of 30% oxygen. These results suggest that a higher concentration of the inhaled oxygen increases the saturation of the blood oxygen in the brain, and facilitates cognitive performance.