Search

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.

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_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_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_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.

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 (NH2–ASNs) and MSNs (NH2–MSNs) and their removal from aqueous environments and show the specific surface area (SSA) of NH2–MSNs is four times as larger as that of NH2–ASNs and that more than 70% of the total SSA of NH2–MSNs is due to the presence of nanopores. Analyses of Cr(VI) adsorption kinetics on NH2–ASNs and NH2–MSNs exhibited relatively rapid adsorption behavior following pseudo-second order kinetics as determined by nonlinear fitting. NH2–ASNs and NH2–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 NH2–ASNs and NH2–MSNs. The adsorption of Cr(VI) on NH2–ASNs and NH2–MSNs was an endothermic and spontaneous process according to the thermodynamic analyses of temperature-dependent adsorption isotherms. The removal efficiencies of NH2–ASNs and NH2–MSNs exhibited a moderate reduction of less than 25% of the maximum values after five regeneration cycles. Furthermore, NH2–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, x2 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.

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.

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.

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.

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.

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.

In this study, we investigated sex- and region-specific effects of acute trimethyltin (TMT) exposure on mitochondrial biogenesis.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.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.Our data suggest that acute TMT exposure induces distinct sex-specific metabolic characteristics in the brain before significant sexual maturation.

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.

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. Keywords: Panic attack, Major depression disorder, Panic disorder, IL-6, Leptin

Herein, we developed a facile one-pot approach to prepare amphiphilic aggregation-induced emission (AIE)-active hyperbranched fluorescent nanoparticles with a core–shell structure. This was conducted via the addition reaction between tetraphenylethylene (TPE)-OH, isophorone diisocyanate, and hyperbranched polyglycidol (HPG) using a one-pot method. The resultant AIE-active hyperbranched polymer structure was characterized by 1H nuclear magnetic resonance and Fourier-transform infrared spectroscopy. The amphiphilic AIE-active polymer was prone to self-assemble in an aqueous solution to form core–shell type nanoparticles with a TPE core and hydroxyl groups on the core surface. The self-assembly of nanoparticles in the aqueous solution was characterized using dynamic light scattering, ultraviolet–visible spectroscopy, fluorescence spectroscopy, and transmission electron microscopy. Aggregation behavior of TPE-HPG polymer in water and diethyl ether was studied by dissipative particle dynamics simulation. Furthermore, these TPE-HPG nanoparticles exhibited a strong blue luminescence in the aqueous solution due to the aggregation of the AIE feature of TPE. These polymeric nanoparticles showed high water solubility, good photostability, and biological imaging properties. The cell viability assay and confocal microscopy imaging results suggested that the TPE-HPG fluorescent polymeric organic nanoparticles (FPNs) have low cytotoxicity and excellent biocompatibility. Thus, TPE-HPG FPNs are excellent candidates for biomedical applications.

In this study, we investigate the relationship between emotions and the physiological responses, with emotion recognition, using the proposed fuzzy information granulation-based neural network (FIGNN) for boredom, pain, and surprise emotions. For an analysis of the physiological responses, three emotions are induced through emotional stimuli, and the physiological signals are obtained from the evoked emotions. To recognize the emotions, we design an FIGNN recognizer and deal with the feature selection through an analysis of the physiological signals. The proposed method is accomplished in premise, consequence, and aggregation design phases. The premise phase takes information granulation using fuzzy c-means clustering, the consequence phase adopts a polynomial function, and the aggregation phase resorts to a general fuzzy inference. Experiments show that a suitable methodology and a substantial reduction of the feature space can be accomplished, and that the proposed FIGNN has a high recognition accuracy for the three emotions using physiological signals.

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.

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.