Exploring intra-diagnosis heterogeneity and inter-diagnosis commonality in genetic architectures of bipolar disorders: association of polygenic risks of major psychiatric illnesses and lifetime phenotype dimensions.

BACKGROUND: Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses. METHODS: Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed. RESULTS: Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028). CONCLUSION: This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry.

Integrated proteomic and genomic analysis to identify predictive biomarkers for valproate response in bipolar disorder: a 6-month follow-up study.

BACKGROUND: Several genetic studies have been undertaken to elucidate the intricate interplay between genetics and drug responses in bipolar disorder (BD). However, there has been notably limited research on biomarkers specifically linked to valproate, with only a few studies investigating integrated proteomic and genomic factors in response to valproate treatment. Therefore, this study aimed to identify biological markers for the therapeutic response to valproate treatment in BD. Patients with BD in remission were assessed only at baseline, whereas those experiencing acute mood episodes were evaluated at three points (baseline, 8 ± 2 weeks, and 6 ± 1 months). The response to valproate treatment was measured using the Alda scale, with individuals scoring an Alda A score ≥ 5 categorized into the acute-valproate responder (acute-VPAR) group. We analyzed 158 peptides (92 proteins) from peripheral blood samples using multiple reaction monitoring mass spectrometry, and proteomic result-guided candidate gene association analyses, with 1,627 single nucleotide variants (SNVs), were performed using the Korean chip. RESULTS: The markers of 37 peptides (27 protein) showed temporal upregulation, indicating possible association with response to valproate treatment. A total of 58 SNVs in 22 genes and 37 SNVs in 16 genes showed nominally significant associations with the Alda A continuous score and the acute-VPAR group, respectively. No SNVs reached the genome-wide significance threshold; however, three SNVs (rs115788299, rs11563197, and rs117669164) in the secreted phosphoprotein 2 gene reached a gene-based false discovery rate-corrected significance threshold with response to valproate treatment. Significant markers were associated with the pathophysiological processes of bipolar disorders, including the immune response, acute phase reaction, and coagulation cascade. These results suggest that valproate effectively suppresses mechanisms associated with disease progression. CONCLUSIONS: The markers identified in this study could be valuable indicators of the underlying mechanisms associated with response to valproate treatment.

Understanding and comparing risk factors and subtypes in South Korean adult and adolescent women's suicidal ideation or suicide attempt using survey and social media data.

Objective: This study aimed to investigate the similarities and differences in risk factors for suicide among adult and adolescent women in South Korea and identify subtypes of suicidal ideation or suicide attempt in each group. Methods: Multifaceted data were collected and analyzed by linking survey and social media data. Interpretable machine learning models were constructed to predict suicide risk and major risk factors were extracted by investigating their feature importance. Additionally, subtypes of suicidal adult and adolescent women were identified and explained using risk factors. Results: The risk factors for adult women were primarily related to mental disorders, while those for adolescent women were primarily related to interpersonal experiences and needs. Two subtypes of suicidal adult women were one with high psychiatric symptoms and mental disorders of them and/or their families and the other with excessive social media use and high online victimization. Two subtypes of suicidal adolescent women were one with high psychiatric symptoms, high ACEs, and high social connectedness, and the other with frequent social media use, high online sexual victimization, and high social assurance. Conclusions: These findings enable a stratified and targeted understanding of suicide in women and help develop customized suicide prevention plans in South Korea.

Artificial Synapse Based on a δ-FAPbI3/Atomic-Layer-Deposited SnO2 Bilayer Memristor.

Halide perovskite-based resistive switching memory (memristor) has potential in an artificial synapse. However, an abrupt switch behavior observed for a formamidinium lead triiodide (FAPbI3)-based memristor is undesirable for an artificial synapse. Here, we report on the δ-FAPbI3/atomic-layer-deposited (ALD)-SnO2 bilayer memristor for gradual analogue resistive switching. In comparison to a single-layer δ-FAPbI3 memristor, the heterojunction δ-FAPbI3/ALD-SnO2 bilayer effectively reduces the current level in the high-resistance state. The analog resistive switching characteristics of δ-FAPbI3/ALD-SnO2 demonstrate exceptional linearity and potentiation/depression performance, resembling an artificial synapse for neuromorphic computing. The nonlinearity of long-term potentiation and long-term depression is notably decreased from 12.26 to 0.60 and from -8.79 to -3.47, respectively. Moreover, the δ-FAPbI3/ALD-SnO2 bilayer achieves a recognition rate of ≤94.04% based on the modified National Institute of Standards and Technology database (MNIST), establishing its potential in an efficient artificial synapse.

High-Performance Ferroelectric Thin Film Transistors with Large Memory Window Using Epitaxial Yttrium-Doped Hafnium Zirconium Gate Oxide.

Preventing ferroelectric materials from losing their ferroelectricity over a low thickness of several nanometers is crucial in developing multifunctional nanoelectronics. Epitaxially grown 5 at. % yttrium-doped Hf0.5Zr0.5O2 (YHZO) thin films exhibit an atomically smooth surface, an ability to maintain ferroelectricity even at a thickness of 10 nm, and excellent insulating properties, making them suitable for use as gate oxides in ferroelectric thin film transistors (FeTFTs). Through the epitaxial growth of a YHZO/La0.67Sr0.33MnO3 (LSMO)/SrTiO3 (STO) heterostructure, YHZO effectively retains its ferroelectricity and orthorhombic single phase, leading to enhancing electron mobility (∼19.74 cm2 V-1 s-1) and memory window (3.7 V) in the amorphous InGaZnO4 (a-IGZO)/YHZO/LSMO/STO FeTFTs. These FeTFTs demonstrate a consistent memory function with remarkable endurance (∼106 cycles) and retention (∼104 s). Furthermore, they sustain a constant memory window even under ±6 V bias stress for 104 s and exhibit excellent stability even under ±6 V/1 ms pulse cycling for 107 cycles. For comparison, a transistor with the same structure was fabricated using epitaxial nonferroelectric LaAlO3 (LAO) and epitaxial undoped Hf0.5Zr0.5O2 (HZO) as alternatives to YHZO. This study presents a novel approach to exploit the potential of YHZO in FeTFTs, contributing to the development of next-generation logic-in-memory.

Identifying predictive factors for mood recurrence in early-onset major mood disorders: A 4-year, multicenter, prospective cohort study.

We investigate the predictive factors of the mood recurrence in patients with early-onset major mood disorders from a prospective observational cohort study from July 2015 to December 2019. A total of 495 patients were classified into three groups according to recurrence during the cohort observation period: recurrence group with (hypo)manic or mixed features (MMR), recurrence group with only depressive features (ODR), and no recurrence group (NR). As a result, the baseline diagnosis of bipolar disorder type 1 (BDI) and bipolar disorder type 2 (BDII), along with a familial history of BD, are strong predictors of the MMR. The discrepancies in wake-up times between weekdays and weekends, along with disrupted circadian rhythms, are identified as a notable predictor of ODR. Our findings confirm that we need to be aware of different predictors for each form of mood recurrences in patients with early-onset mood disorders. In clinical practice, we expect that information obtained from the initial assessment of patients with mood disorders, such as mood disorder type, family history of BD, regularity of wake-up time, and disruption of circadian rhythms, can help predict the risk of recurrence for each patient, allowing for early detection and timely intervention.

Transdiagnostic clustering and network analysis for questionnaire-based symptom profiling and drug recommendation in the UK Biobank and a Korean cohort.

Clinical decision support systems (CDSSs) play a critical role in enhancing the efficiency of mental health care delivery and promoting patient engagement. Transdiagnostic approaches that utilize raw psychological and biological data enable personalized patient profiling and treatment. This study introduces a CDSS incorporating symptom profiling and drug recommendation for mental health care. Among the UK Biobank cohort, we analyzed 157,348 participants for symptom profiling and 14,358 participants with a drug prescription history for drug recommendation. Among the 1307 patients in the Samsung Medical Center cohort, 842 were eligible for analysis. Symptom profiling utilized demographic and questionnaire data, employing conventional clustering and community detection methods. Identified clusters were explored using diagnostic mapping, feature importance, and scoring. For drug recommendation, we employed cluster- and network-based approaches. The analysis identified nine clusters using k-means clustering and ten clusters with the Louvain method. Clusters were annotated for distinct features related to depression, anxiety, psychosis, drug addiction, and self-harm. For drug recommendation, drug prescription probabilities were retrieved for each cluster. A recommended list of drugs, including antidepressants, antipsychotics, mood stabilizers, and sedative-hypnotics, was provided to individual patients. This CDSS holds promise for efficient personalized mental health care and requires further validation and refinement with larger datasets, serving as a valuable tool for mental healthcare providers.

Halide Perovskites-Based Diffusive Memristors for Artificial Mechano-Nociceptive System.

Numerous efforts for emulating organ systems comprised of multiple functional units have driven substantial advancements in bio-realistic electronics and systems. The resistance change behavior observed in diffusive memristors shares similarities with the potential change in biological neurons. Here, the diffusive threshold switching phenomenon in Ag-incorporated organometallic halide perovskites is utilized to demonstrate the functions of afferent neurons. Halide perovskites-based diffusive memristors show a low threshold voltage of ≈0.2 V with little variation, attributed to the facile migration of Ag ions uniformly dispersed within the halide matrix. Based on the reversible and reliable volatile threshold switching, the memristors successfully demonstrate fundamental nociceptive functions including threshold firing, relaxation, and sensitization. Furthermore, to replicate the biological mechano-nociceptive phenomenon at a system level, an artificial mechano-nociceptive system is built by integrating a diffusive memristor with a force-sensing resistor. The presented system is capable of detecting and discerning the detrimental impact caused by a heavy steel ball, effectively exhibiting the corresponding sensitization response. By further extending the single nociceptive system into a 5 × 5 array, successful stereoscopic nociception of uneven impulses is achieved in the artificial skin system through array-scale sensitization. These results represent significant progress in the field of bio-inspired electronics and systems.

Intelligence-Dependent Differential Effects of Media Exposure on Executive Function Changes in Children: A Population-Based Cohort Study With a Longitudinal Design.

BACKGROUND: Excessive media use is known to be associated with executive dysfunction in children, but it's unclear whether this exposure can lead to long-term changes of executive function. This study aimed to investigate the association between media exposure and longitudinal changes in executive function within a population-based study, while considering the potential influence of intelligence. METHODS: This study used data from 1,209 participants in the Panel Korea Study for Children. The children's media exposure was measured at ages 7 and 8, and executive function was evaluated annually from ages 7 to 10 using the Executive Function Difficulty Screening Questionnaire. Participants were grouped by media exposure level (low, medium, or high), and longitudinal changes in executive function were analyzed using linear mixed effects models. Subgroup analysis was conducted to investigate how executive function changes varied based on intelligence within each media exposure group. RESULTS: Children with high media exposure (n = 97) had severer executive function difficulties than those with low (n = 141) or medium (n = 971) exposure in all waves. The high exposure group demonstrated persistent higher executive function difficulties up to age 10 after controlling for child gender, intelligence, parental education level and maternal depression. Children with intelligence quotient (IQ) ≤ 100 in the medium to high media exposure group had significantly more severe executive function difficulties than those with IQ > 100. CONCLUSION: This study provided evidence of a longitudinal negative association between media exposure and executive function. The findings suggest that excessive media exposure may lead to long-term changes in executive function in children and highlight the importance of implementing targeted interventions and educational strategies to mitigate the potential negative effects of excessive media use, particularly for children with lower cognitive abilities.

Network structure of symptomatology of adult attention-deficit hyperactivity disorder in patients with mood disorders.

Patients with mood disorders commonly manifest comorbid psychiatric disorders, including attention-deficit/hyperactivity disorder (ADHD). However, few studies have evaluated ADHD symptoms in this population. The current study aimed to explore the network structure of ADHD symptomology and identify central symptoms in patients with mood disorders. The Korean version of the Adult ADHD Self-Report Scale was used to assess the overall ADHD symptoms in 1,086 individuals diagnosed with mood disorders (major depressive disorder [n = 373], bipolar I disorder [n = 314], and bipolar II disorder [n = 399]). We used exploratory graph analysis to detect the number of communities, and the network structure was analyzed using regularized partial correlation models. We identified the central ADHD symptom using centrality indices. Network comparison tests were conducted with different subgroups of patients with mood disorders, including three mood diagnosis groups, between the patients who met the diagnostic criteria for ADHD [ADHD-suspected, n = 259] in their self-report and the others [ADHD-non-suspected, n = 827], and groups with high [n = 503] versus low [n = 252] levels of depressive state. The network analysis detected four communities: disorganization, agitation/restlessness, hyperactivity/impulsivity, and inattention. The centrality indices indicated that "feeling restless" was the core ADHD symptom. The result was replicated in the subgroup analyses within our clinically diverse population of mood disorders, encompassing three presentations: Patients with suspected ADHD, patients without suspected ADHD, and patients with a high depressive state. Our findings reveal that "feeling restless" is the central ADHD symptom. The treatment intervention for "feeling restless" may thus play a pivotal role in tackling ADHD symptoms in adult patients with mood disorders.

Unveiling the inhibition mechanism of Clostridioides difficile by Bifidobacterium longum via multiomics approach.

Antibiotic-induced gut microbiota disruption constitutes a major risk factor for Clostridioides difficile infection (CDI). Further, antibiotic therapy, which is the standard treatment option for CDI, exacerbates gut microbiota imbalance, thereby causing high recurrent CDI incidence. Consequently, probiotic-based CDI treatment has emerged as a long-term management and preventive option. However, the mechanisms underlying the therapeutic effects of probiotics for CDI remain uninvestigated, thereby creating a knowledge gap that needs to be addressed. To fill this gap, we used a multiomics approach to holistically investigate the mechanisms underlying the therapeutic effects of probiotics for CDI at a molecular level. We first screened Bifidobacterium longum owing to its inhibitory effect on C. difficile growth, then observed the physiological changes associated with the inhibition of C. difficile growth and toxin production via a multiomics approach. Regarding the mechanism underlying C. difficile growth inhibition, we detected a decrease in intracellular adenosine triphosphate (ATP) synthesis due to B. longum-produced lactate and a subsequent decrease in (deoxy)ribonucleoside triphosphate synthesis. Via the differential regulation of proteins involved in translation and protein quality control, we identified B. longum-induced proteinaceous stress. Finally, we found that B. longum suppressed the toxin production of C. difficile by replenishing proline consumed by it. Overall, the findings of the present study expand our understanding of the mechanisms by which probiotics inhibit C. difficile growth and contribute to the development of live biotherapeutic products based on molecular mechanisms for treating CDI.

Multiomics analysis reveals the biological effects of live Roseburia intestinalis as a high-butyrate-producing bacterium in human intestinal epithelial cells.

Butyrate-producing bacteria play a key role in human health, and recent studies have triggered interest in their development as next-generation probiotics. However, there remains limited knowledge not only on the identification of high-butyrate-producing bacteria in the human gut but also in the metabolic capacities for prebiotic carbohydrates and their interaction with the host. Herein, it was discovered that Roseburia intestinalis produces higher levels of butyrate and digests a wider variety of prebiotic polysaccharide structures compared with other human major butyrate-producing bacteria (Eubacterium rectale, Faecalibacterium prausnitzii, and Roseburia hominis). Moreover, R. intestinalis extracts upregulated the mRNA expression of tight junction proteins (TJP1, OCLN, and CLDN3) in human intestinal epithelial cells more than other butyrate-producing bacteria. R. intestinalis was cultured with human intestinal epithelial cells in the mimetic intestinal host-microbe interaction coculture system to explore the health-promoting effects using multiomics approaches. Consequently, it was discovered that live R. intestinalis only enhances purine metabolism and the oxidative pathway, increasing adenosine triphosphate levels in human intestinal epithelial cells, but that heat-killed bacteria had no effect. Therefore, this study proposes that R. intestinalis has potentially high value as a next-generation probiotic to promote host intestinal health.

Two-Terminal Lithium-Mediated Artificial Synapses with Enhanced Weight Modulation for Feasible Hardware Neural Networks.

Recently, artificial synapses involving an electrochemical reaction of Li-ion have been attributed to have remarkable synaptic properties. Three-terminal synaptic transistors utilizing Li-ion intercalation exhibits reliable synaptic characteristics by exploiting the advantage of non-distributed weight updates owing to stable ion migrations. However, the three-terminal configurations with large and complex structures impede the crossbar array implementation required for hardware neuromorphic systems. Meanwhile, achieving adequate synaptic performances through effective Li-ion intercalation in vertical two-terminal synaptic devices for array integration remains challenging. Here, two-terminal Au/LixCoO2/Pt artificial synapses are proposed with the potential for practical implementation of hardware neural networks. The Au/LixCoO2/Pt devices demonstrated extraordinary neuromorphic behaviors based on a progressive dearth of Li in LixCoO2 films. The intercalation and deintercalation of Li-ion inside the films are precisely controlled over the weight control spike, resulting in improved weight control functionality. Various types of synaptic plasticity were imitated and assessed in terms of key factors such as nonlinearity, symmetricity, and dynamic range. Notably, the LixCoO2-based neuromorphic system outperformed three-terminal synaptic transistors in simulations of convolutional neural networks and multilayer perceptrons due to the high linearity and low programming error. These impressive performances suggest the vertical two-terminal Au/LixCoO2/Pt artificial synapses as promising candidates for hardware neural networks.

The Core Symptoms of Adolescents Online and Offline Gambling in South Korea Using Network Analysis.

OBJECTIVE: Adolescent gambling is rapidly increasing recently. However, little is known about the core feature of adolescent gambling that should be the treatment target for adolescents. Thus, the objective of this study was to determine the core symptom of adolescent gambling using network analysis with large-scale data targeting community indwelling adolescents. METHODS: We used dataset of the 2018 national survey on youth gambling problems collected by the Korea Center on Gambling Problems to explore symptom networks of gambling in adolescents. Of 17,520 respondents in the dataset of the 2018 national survey on youth gambling problems collected by the Korea Center on Gambling Problems, 5,619 adolescents with experience of gambling were included in the analysis. We computed an association network, a graphical least absolute shrinkage and selection operator, and a directed acyclic graph to model symptom interactions. RESULTS: In each network of online, offline, and all gambling, stealing money or other valuable things in order to gamble or pay off gambling debts was the most centrally situated and skipping practice followed by dropping out of activities. Especially strong connections emerged between stealing money or other valuable things in order to gamble or pay off gambling debts and academic performance degradation due to gambling. Feeling bad due to gamble and skipping hanging out with friends who do not gamble emerged as a highly central node that might be distinctive to adolescents with online gambling. CONCLUSION: These findings demonstrate central features of adolescent gambling. Different associations among specific network nodes suggest the existence of distinctive psychopathological constructs between online and offline gambling.

Prediction of impending mood episode recurrence using real-time digital phenotypes in major depression and bipolar disorders in South Korea: a prospective nationwide cohort study.

BACKGROUND: Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones. METHODS: The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy. RESULTS: Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively. CONCLUSIONS: We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.

Increased metabolic variability in Korean patients with new onset bipolar disorder: a nationwide cohort study.

Introduction: The aim of this study was to determine associations between changes of metabolic parameters and the development of BD using nationally representative data. Methods: We used health examination data provided by the South Korean National Health Insurance System (NHIS) (n = 8,326,953). The variability of each metabolic parameter including weight circumference, blood pressure, fasting blood glucose, high-density lipoprotein cholesterol, and triglyceride levels was caculated using variability independent of mean (VIM) indices. The presence of metabolic syndrome was associated with new onset BD. Each metabolic parameter with high variability was associated with a higher risk of new onset BD compared to those with low variability after adjusting for age, sex, smoking, alcohol drinking, regular exercise, income status, baseline diabetes, hypertension, and dyslipidemia. Results: As the number of highly variable metabolic parameters increased, the risk for new onset depression also increased even after covariates adjustment. The associations between new onset BD and metabolic variability were greater in populations with age > 50 years. In addition, these associations remained significant after adjusting for the presence of depression prior to diagnoses of BD. Discussion: Our results suggest possibility of metabolic variability as an independent environmental risk factor for BD even after adjusting for the presence of metabolic syndrome.

Heterogeneous early illness courses of Korean patients with bipolar disorders: replication of the staging model.

BACKGROUND: Clinical staging of bipolar disorder (BD) requires application of real-world data, as the next step in hypothesis. This study used the staging model to analyze the long-term course of BD in Korean patients based on clinical features and treatment responses to map the progression of bipolar illness from its early phase after the onset of illness. METHODS: A total of 136 patients diagnosed with BD-I (n = 62) or BD-II (n = 74) were recruited. Their progressive stages were retrospectively evaluated. A multi-state model was used to calculate the probability of progression to each stage. Hazard ratios of covariates expected to influence different courses of BD were calculated. Using the Alda score, long-term responses to mood stabilizers depending on the current stage were compared. RESULTS: Several sub-populations showed varied courses during the first five years after the onset of illness, with 41.5% remaining in stage 2 and 53% progressing to higher stages with shortened time for transition. Profiles of patients with BD-I and BD-II were different, suggesting biologically distinct groups. Comorbid psychiatric disorders, such as obsessive-compulsive disorder (OCD) and bulimia nervosa (BN) were associated with a recurrent course (stage 3a or 3b) or a malignant course (stage 3c or 4). Early age of onset, shorter duration of illness, older age at the start of medication, and poor response to lithium affected the illness progression. CONCLUSION: We were able to apply the stage model based on episode recurrence patterns in early illness courses of Korean patients with BD. The stage progression pattern differed from the early phase in BD-I and BD-II patients. Psychotic comorbidity, age at onset, age at starting psychiatric treatment showed associations with the illness progression.

Efficacy and safety of daily home-based transcranial direct current stimulation as adjunct treatment for bipolar depressive episodes: Double-blind sham-controlled randomized clinical trial.

Background: Although transcranial direct current stimulation (tDCS) is known to be a promising therapeutic modality for unipolar depression, the efficacy and safety of tDCS for bipolar depressive episodes (BD) are still unknown and clinical trials of home-based tDCS treatment are scarce. As a result, we set out to investigate the efficacy and safety of home-based tDCS for the treatment BD. Methods: Participants (n = 64), diagnosed as bipolar disorder as per the diagnostic and statistical manual of mental disorders (DSM-5), were randomly assigned to receive tDCS. Hamilton Depression Rating Scale (HDRS-17) scores were measured at the baseline, week 2, 4, and 6, and home-based tDCS (for 30 min with 2 mA) was self-administered daily. Results: Of the 64 patients (15.6% bipolar disorder I, 84.4% bipolar disorder II), 41 patients completed the entire assessment. In the intention-to-treat analysis, time-group interaction for the HDRS-17 [F (3, 146.36) = 2.060; p = 0.108] and adverse effect differences between two groups were not statistically significant, except the pain score, which was higher in the active group than the sham group (week 0-2: p < 0.01, week 2-4: p < 0.05, and week 4-6: p < 0.01). Conclusion: Even though we found no evidence for the efficacy of home-based tDCS for patients with BD, this tool was found to be a safe and tolerable treatment modality for BD. Clinical trial registration: [https://clinicaltrials.gov/show/NCT03974815], identifier [NCT03974815].

Investigation of metabolic crosstalk between host and pathogenic Clostridioides difficile via multiomics approaches.

Clostridioides difficile is a gram-positive anaerobic bacterium that causes antibiotic-associated infections in the gut. C. difficile infection develops in the intestine of a host with an imbalance of the intestinal microbiota and, in severe cases, can lead to toxic megacolon, intestinal perforation, and even death. Despite its severity and importance, however, the lack of a model to understand host-pathogen interactions and the lack of research results on host cell effects and response mechanisms under C. difficile infection remain limited. Here, we developed an in vitro anaerobic-aerobic C. difficile infection model that enables direct interaction between human gut epithelial cells and C. difficile through the Mimetic Intestinal Host-Microbe Interaction Coculture System. Additionally, an integrative multiomics approach was applied to investigate the biological changes and response mechanisms of host cells caused by C. difficile in the early stage of infection. The C. difficile infection model was validated through the induction of disaggregation of the actin filaments and disruption of the intestinal epithelial barrier as the toxin-mediated phenotypes following infection progression. In addition, an upregulation of stress-induced chaperones and an increase in the ubiquitin proteasomal pathway were identified in response to protein stress that occurred in the early stage of infection, and downregulation of proteins contained in the electron transfer chain and ATP synthase was observed. It has been demonstrated that host cell energy metabolism is inhibited through the glycolysis of Caco-2 cells and the reduction of metabolites belonging to the TCA cycle. Taken together, our C. difficile infection model suggests a new biological response pathway in the host cell induced by C. difficile during the early stage of infection at the molecular level under anaerobic-aerobic conditions. Therefore, this study has the potential to be applied to the development of future therapeutics through basic metabolic studies of C. difficile infection.

Changes in working status after cancer diagnosis and socio-demographic, clinical, work-related, and psychological factors associated with it.

BACKGROUND: While many studies investigated changes in working status in cancer survivors, most studies have been performed in survivors of breast cancer and few studies evaluated factors associated with changes in the working status of cancer survivors comprehensively. We aimed to evaluate the changes in the working status of cancer survivors after diagnosis and socio-demographic, clinical, work-related and psychological factors associated with it. METHODS: We conducted a cross-sectional survey of adult patients with cancer who were working at the time of diagnosis. A trained interviewer inquired about participants' current working status, including leave of absence, discontinuing, continuing, and changing work. Sociodemographic, clinical, work-related and psychological factors were measured. Multinomial logistic regression was used to identify factors associated with changes in the working status. RESULTS: Among the 730 patients, 29%, 18% and 6% were currently on a discontinued working, leave of absence and had changed jobs, respectively. Patients who discontinued working after cancer diagnosis were more likely to be female, have ≥ $3,000 of monthly family income, not be the principal wage earners for their families and be blue-collar workers. In clinical characteristics, advanced-stage cancer and experienced cancer recurrence was associated with leave of absence and discontinued working. In work-related and psychological factors, stress due to insufficient job control (relative risk ratio [RRR] = 2.26), interpersonal conflict (RRR = 1.86), job insecurity (RRR = 2.63), organizational system (RRR = 3.49), and lack of reward (RRR = 11.76), and less meaning to work were more likely to discontinue working after a cancer diagnosis. CONCLUSION: Occupational health care professionals and other stakeholders need to openly communicate with patients with cancer about potential barriers during the return-to-work trajectory.