Spliceosome component TCERG1 regulates the aggressiveness of somatotroph adenoma.

PURPOSE: We aimed to identify differentially expressed spliceosome components in growth hormone (GH)-secreting pituitary tumors and investigate their roles in pathogenesis. METHODS: We performed transcriptome analysis of 20 somatotroph adenomas and 6 normal pituitary tissues to select dysregulated spliceosome components. Clinical characteristics were analyzed based on gene expression in 64 patients with acromegaly. Proliferation, invasion, and hormonal activity of GH secreting pituitary adenoma cells were investigated. RESULTS: TCERG1 expression was significantly higher in somatotroph adenomas than in normal pituitaries (log2 fold change 0.59, adjusted P = 0.0002*). Genotype-phenotype analysis revealed that patients with higher TCERG1 expression had lower surgical remission rates than those with lower expression (63.64% vs. 95.45%, P = 0.009*). TCERG1 expression was significantly higher in groups with cavernous sinus (CS) invasion or Ki67 index over 3 (all P>0.05*). TCERG1 overexpression led to a 29.60% increase in proliferation (P<0.001*) and a 249.47% increase in invasion after 48 h in GH3 cells (P = 0.026*). Conversely, TCERG1 silencing significantly decreased cell proliferation (25.76% at 72 h, P<0.001*) and invasion (96.87% at 48 h, P = 0.029*). E-cadherin was decreased, but vimentin was increased in both TCERG1 overexpressed GH3 cells and somatotroph adenomas. And TCERG1 silence reversed the expression of the genes (CDH2, SNAI1, ZEB2, and VIM) in GH3 cells. CONCLUSIONS: Spliceosome machinery provide novel insights into the pathogenesis of GH-secreting pituitary tumor and highlight the potential role of TCERG1 as a biomarker for tumor aggressiveness.

A Bioinformatics Investigation of Hub Genes Involved in Treg Migration and Its Synergistic Effects, Using Immune Checkpoint Inhibitors for Immunotherapies.

This study aimed to identify hub genes involved in regulatory T cell (Treg) function and migration, offering insights into potential therapeutic targets for cancer immunotherapy. We performed a comprehensive bioinformatics analysis using three gene expression microarray datasets from the GEO database. Differentially expressed genes (DEGs) were identified to pathway enrichment analysis to explore their functional roles and potential pathways. A protein-protein interaction network was constructed to identify hub genes critical for Treg activity. We further evaluated the co-expression of these hub genes with immune checkpoint proteins (PD-1, PD-L1, CTLA4) and assessed their prognostic significance. Through this comprehensive analysis, we identified CCR8 as a key player in Treg migration and explored its potential synergistic effects with ICIs. Our findings suggest that CCR8-targeted therapies could enhance cancer immunotherapy outcomes, with breast invasive carcinoma (BRCA) emerging as a promising indication for combination therapy. This study highlights the potential of CCR8 as a biomarker and therapeutic target, contributing to the development of targeted cancer treatment strategies.

Association between visceral obesity and tumor recurrence in hepatocellular carcinoma recipients undergoing liver transplantation.

BACKGROUND: Excessive visceral obesity in recipients of living donor liver transplantation (LDLT) is associated with mortality, and a recent study reported the correlation between visceral adiposity of male LDLT recipients and hepatocellular carcinoma (HCC) recurrence. However, there is no study on the relationship between the donor's visceral adiposity and surgical outcomes in LDLT recipients. We investigated the association of the visceral-to-subcutaneous fat area ratio (VSR) in donors and recipients with HCC recurrence and mortality in LDLT. METHODS: We analyzed 1386 sets of donors and recipients who underwent LDLT between January 2008 and January 2018. The maximal chi-square method was used to determine the optimal cutoff values for VSR for predicting overall HCC recurrence and mortality. Cox regression analyses were performed to evaluate the association of donor VSR and recipient VSR with overall HCC recurrence and mortality in recipients. RESULTS: The cutoff values of VSR was determined as 0.73 in males and 0.31 in females. High donor VSR was significantly associated with overall HCC recurrence (adjusted hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.06-1.93, p = 0.019) and mortality (HR: 1.35, 95% CI: 1.03-1.76, p = 0.030). High recipient VSR was significantly associated with overall HCC recurrence (HR: 1.40, 95% CI: 1.04-1.88, p = 0.027) and mortality (HR: 1.50, 95% CI: 1.14-1.96, p = 0.003). CONCLUSIONS: Both recipient VSR and donor VSR were significant risk factors for HCC recurrence and mortality in LDLT recipients. Preoperative donor VSR and recipient VSR may be strong predictors of the surgical outcomes of LDLT recipients with HCC.

Association of sex-specific donor skeletal muscle index with surgical outcomes in living donor liver transplantation recipients.

BACKGROUND: A recent study reported a correlation between the muscle mass of male donors and graft failure in living donor liver transplantation (LDLT) recipients. We investigated the association of sex-specific donor skeletal muscle index (SMI) with mortality and graft failure in LDLT recipients. METHODS: We retrospectively analysed 2750 sets of donors and recipients between January 2008 and January 2018. The recipient outcomes were analysed by dividing the data according to donor sex. Cox regression analyses were performed to evaluate the association between donor SMI by sex and 1-year mortality and graft failure in recipients. RESULTS: In the male donor group, robust donor (increased SMI) was significantly associated with higher risks for mortality (hazard ratio [HR]: 1.03, 95% confidence interval [CI]: 1.00-1.06, p = .023) and graft failure (HR: 1.04, 95% CI: 1.01-1.06, p = .007) at 1 year. In the female donor group, the robust donor was significantly associated with lower risks for mortality (HR: 0.92, 95% CI: 0.87-0.97, p = .003) and graft failure (HR: 0.95, 95% CI: 0.90-1.00, p = .032) at 1 year. CONCLUSIONS: Donor SMI was associated with surgical outcomes in recipients. Robust male and female donors were a significant negative and protective factor for grafts respectively.

Associations of sarcopenia with graft failure and mortality in patients undergoing living donor liver transplantation.

Recent studies have reported that sarcopenia influences morbidity and mortality in surgical patients. However, few studies have investigated the associations of sarcopenia with short-term and long-term graft failure in recipients after living donor liver transplantation (LDLT). In this study, we investigated the associations between sarcopenia and graft failure/mortality in patients undergoing LDLT. We retrospectively examined 2816 recipients who underwent LDLT between January 2008 and January 2018. Cox regression analysis was performed to evaluate the associations between sarcopenia and graft failure/mortality in recipients at 60 days, 180 days, and 1 year and overall. Sarcopenia in the recipient was significantly associated with 60-day graft failure (adjusted hazard ratio [HR], 1.98; 95% confidence interval [CI], 1.09-3.61; p = 0.03), 180-day graft failure (HR, 1.85; 95% CI, 1.19-2.88; p = 0.01), 1-year graft failure (HR, 1.45; 95% CI, 1.01-2.17; p = 0.05), and overall graft failure (HR, 1.42; 95% CI, 1.08-1.87; p = 0.01). In addition, recipient sarcopenia was associated with 180-day mortality (HR, 1.88; 95% CI, 1.17-3.01; p = 0.01), 1-year mortality (HR, 1.53; 95% CI, 1.01-2.29; p = 0.04), and overall mortality (HR, 1.43; 95% CI, 1.08-1.90; p = 0.01). Preoperative sarcopenia was associated with high rates of graft failure and mortality in LDLT recipients. Therefore, preoperative sarcopenia may be a strong predictor of the surgical prognosis in LDLT recipients.

Role of Melatonin in the Management of Sleep and Circadian Disorders in the Context of Psychiatric Illness.

PURPOSE OF REVIEW: We present a review of research on the role of melatonin in the management of sleep and circadian disorders, stressing current overall view of the knowledge across psychiatric disorders. RECENT FINDINGS: Dysregulation of sleep and circadian rhythms has been established in several psychiatric and neurocognitive disorders for long. Recent research confirms this finding consistently across disorders. The secretion of melatonin in schizophrenia and neurocognitive disorders is reduced due to a smaller volume and enlarged calcification of the pineal gland. On the other hand, melatonin dysregulation in bipolar disorder may be more dynamic and caused by light-sensitive melatonin suppression and delayed melatonin secretion. In both cases, exogenous melatonin seems indicated to correct the dysfunction. However, a very limited number of well-designed trials with melatonin to correct sleep and circadian rhythms exist in psychiatric disorders, and the evidence for efficacy is robust only in autism, attention deficit hyperactivity disorder (ADHD), and neurocognitive disorders. This topic has mainly not been of interest for recent work and well-designed trials with objective circadian parameters are few. Overall, recent studies in psychiatric disorders reported that melatonin can be effective in improving sleep parameters such as sleep onset latency, sleep efficiency, and sleep quality. Recent meta-analysis suggests that optimal dosage and dosing time might be important to maximize the efficacy of melatonin. The knowledge base is sufficient to propose well-designed, larger trials with circadian parameters as inclusion and outcome criteria. Based on the partly fragmentary information, we propose testing efficacy in disorders with neurocognitive etiopathology with later and higher dosing, and affective and anxiety disorders with lower and earlier dosing of melatonin. Melatonin is promising for the correction of sleep and circadian abnormalities in psychiatric disorders. However, research results on its effect are still few and need to be accumulated. For effective use of melatonin, it is necessary to consider the appropriate dosage and administration time, depending on the individual abnormality of sleep and circadian rhythms.

Safe use of right lobe living donor livers with moderate steatosis in adult-to-adult living donor liver transplantation: a retrospective study.

Hepatic steatosis (HS) beyond a certain degree can jeopardize living donor (LD) safety, particularly in right lobe (RL) donors, making it a major obstacle for donor pool expansion in adult-to-adult living donor liver transplantation (ALDLT). From July 2004 to June 2016, 58 LDs donated their RLs despite having moderate HS (30%-50% steatosis) determined by intraoperative biopsy at a single center. We performed greedy matching to compare the outcomes of the donors and recipients of this group with those of LDs with no HS. The mean left lobe (LL) HS value in the 58 cases was 20.9 ± 12.4%, which was significantly lower than the mean RL HS value (38.8 ± 6.7%, P < 0.001). The mean ratio of the remnant LL to the total liver volume was 37.8 ± 2.2. No differences were observed in the postoperative liver function and donor and recipient morbidity and mortality rates. The liver regeneration rates in recipients and donors at 1 month, 6 months, and 1 year postoperatively did not differ significantly. The patient and graft survival rates of the recipients showed no differences. The use of well-selected RL grafts with moderate steatosis does not impair graft function, recipient outcomes, or donor safety.

The Impact of the COVID-19 Pandemic on the Unpredictable Dynamics of the Cryptocurrency Market.

The global economy is under great shock again in 2020 due to the COVID-19 pandemic; it has not been long since the global financial crisis in 2008. Therefore, we investigate the evolution of the complexity of the cryptocurrency market and analyze the characteristics from the past bull market in 2017 to the present the COVID-19 pandemic. To confirm the evolutionary complexity of the cryptocurrency market, three general complexity analyses based on nonlinear measures were used: approximate entropy (ApEn), sample entropy (SampEn), and Lempel-Ziv complexity (LZ). We analyzed the market complexity/unpredictability for 43 cryptocurrency prices that have been trading until recently. In addition, three non-parametric tests suitable for non-normal distribution comparison were used to cross-check quantitatively. Finally, using the sliding time window analysis, we observed the change in the complexity of the cryptocurrency market according to events such as the COVID-19 pandemic and vaccination. This study is the first to confirm the complexity/unpredictability of the cryptocurrency market from the bull market to the COVID-19 pandemic outbreak. We find that ApEn, SampEn, and LZ complexity metrics of all markets could not generalize the COVID-19 effect of the complexity due to different patterns. However, market unpredictability is increasing by the ongoing health crisis.

Temporal Changes in In Vivo Glutamate Signal during Demyelination and Remyelination in the Corpus Callosum: A Glutamate-Weighted Chemical Exchange Saturation Transfer Imaging Study.

BACKGROUND: Glutamate-weighted chemical exchange saturation transfer (GluCEST) is a useful imaging tool that can be used to detect changes in glutamate levels in vivo and could also be helpful in the diagnosis of brain myelin changes. We investigated glutamate level changes in the cerebral white matter of a rat model of cuprizone-administered demyelination and remyelination using GluCEST. METHOD: We used a 7 T pre-clinical magnetic resonance imaging (MRI) system. The rats were divided into the normal control (CTRL), cuprizone-administered demyelination (CPZDM), and remyelination (CPZRM) groups. GluCEST data were analyzed using the conventional magnetization transfer ratio asymmetry in the corpus callosum. Immunohistochemistry and transmission electron microscopy analyses were also performed to investigate the myelinated axon changes in each group. RESULTS: The quantified GluCEST signals differed significantly between the CPZDM and CTRL groups (-7.25 ± 1.42% vs. -2.84 ± 1.30%; p = 0.001). The increased GluCEST signals in the CPZDM group decreased after remyelination (-6.52 ± 1.95% in CPZRM) to levels that did not differ significantly from those in the CTRL group (p = 0.734). CONCLUSION: The apparent temporal signal changes in GluCEST imaging during demyelination and remyelination demonstrated the potential usefulness of GluCEST imaging as a tool to monitor the myelination process.

The Effect of Pressure Injury Training for Nurses: A Systematic Review and Meta-analysis.

OBJECTIVE: To conduct a meta-analysis of the literature on training programs that aimed to improve nurses' pressure injury management skills. METHODS: Literature searches were conducted using Ovid-MEDLINE, Cochrane Library, CINAHL, and Korean databases. The search terms used were: (nurse* AND ((pressure OR decubitus) AND (ulcer* OR injur*)) OR bed sore OR bedsore OR decubitus) AND (program* OR training)). Random-effects models were used to calculate the standardized mean difference and odds ratios, with 95% confidence intervals (CIs) to analyze the effects. MAIN RESULTS: Initial searches yielded 1,067 studies. Of these, 23 met the selection criteria. Nurses' knowledge (standard mean difference, 1.23; 95% CI, 0.50-1.96; P < .001), visual discrimination ability (standard mean difference, 1.13; 95% CI, 0.88-1.38; P < .001), and clinical judgment (odds ratio, 1.52; 95% CI, 1.46-1.57; P < .001) improved after the programs. CONCLUSIONS: Pressure injury training programs can improve nurses' competency. The results from this study indicate that such programs may help improve nurses' knowledge, visual discrimination ability, and clinical judgment and can be considered continuing education programs. However, large-scale studies are needed to confirm this conclusion.

Explainable prediction of problematic smartphone use among South Korea's children and adolescents using a Machine learning approach.

BACKGROUND: Korea is known for its technological prowess, has the highest smartphone ownership rate in the world at 95%, and the smallest gap in smartphone ownership between generations. Since the onset of the COVID-19 pandemic, problematic smartphone use is becoming more prevalent among Korean children and adolescent owing to limited school attendance and outdoor activities, resulting in increased reliance on smartphones. 40.1% of adolescents are classified as high-risk, with only the adolescent group showing a persistent rise year after year. OBJECTIVE: The study purpose is to present data-driven analysis results for predicting and preventing smartphone addiction in Korea, where problematic smartphone use is severe. PARTICIPANTS AND METHODS: To predict the risk of problematic smartphone use in Korean children and adolescents at an early stage, we used data collected from the Smartphone Overdependence Survey conducted by the National Information Society Agency between 2017 and 2021. Eight representative machine and deep learning algorithms were used to predict groups at high risk for smartphone addiction: Logistic Regression, Random Forest, Gradient Boosting Machine (GBM), extreme Gradient Boosting (XGBoost), Light GBM, Categorical Boosting, Multilayer Perceptron, and Convolutional Neural Network. RESULTS: The XGBoost ensemble algorithm predicted 87.60% of participants at risk of future problematic smartphone usebased on precision. Our results showed that prolonged use of games, webtoons/web novels, and e-books, which have not been found in previous studies, further increased the risk of problematic smartphone use. CONCLUSIONS: Artificial intelligence algorithms have potential predictive and explanatory capabilities for identifying early signs of problematic smartphone use in adolescents and young children. We recommend that a variety of healthy, beneficial, and face-to-face activities be offered as alternatives to smartphones for leisure and play culture.

Psychometric Properties of the Patient Health Questionnaire-9 in Patients With Breast Cancer.

OBJECTIVE: Due to the high frequency of depressive symptoms associated with breast cancer, it is crucial to screen for depression in breast cancer patients. While numerous screening tools are available for depression in this population, there is a need for a brief and convenient tool to enhance clinical use. This study aims to investigate the psychometric properties of the Patient Health Questionnaire-9 (PHQ-9) in patients with breast cancer. METHODS: Patients with breast cancer (n=327) who visited the Breast Cancer Clinic were included in this study. The reliability of the PHQ-9 was analyzed by Cronbach's α, and the construct validity of the PHQ-9 was explored by factor analysis. The concurrent validity of the PHQ-9 was evaluated by Pearson correlation analysis with the Hospital Anxiety and Depression Scale (HADS) and Perceived Stress Scale (PSS). RESULTS: The values of Cronbach's α ranged from 0.800 to 0.879 was acceptable. The exploratory factor analysis revealed that the one-factor model and two-factor model of the PHQ-9 explained 46% and 57% of the variance, respectively. The PHQ-9 were significantly correlated with those of HADS (r=0.702, p<0.001) and PSS (r=0.466, p<0.001). Consequently, the PHQ-9 demonstrated acceptable reliability and validity in breast cancer patients. CONCLUSION: The findings of this study indicate that the PHQ-9 exhibits acceptable reliability and validity in patients with breast cancer. The convenience of this brief self-report questionnaire suggests its potential as a reliable and valid tool for assessing depression in breast cancer clinics.

Solubility, complexation and thermodynamics of the Tc(IV)-isosaccharinic acid system: Trends in the M(IV) series.

Isosaccharinic acid (HISA, or ISA in its deprotonated form) is the main degradation product of cellulose under alkaline conditions. It can form strong complexes with radionuclides and other toxic metal ions, eventually enhancing their mobility in the context of nuclear waste repositories and other environmental systems. 99Tc is a redox-sensitive, long-lived fission product produced in high yield in nuclear reactors. The solubility of 99Tc(IV) was investigated in 0.5 M NaCl‒NaISA‒NaOH solutions with 6 ≤ pHm ≤ 12.5 and 10-6 M ≤ [ISA] ≤ 0.2 M. Complete chemical and thermodynamic models were derived on the basis of solubility data, (pe + pHm) measurements, redox speciation, and solid phase characterization. These models include the previously unreported aqueous complexes TcO(OH)(ISA)2‒ and TcO(OH)2(ISA)22-. In spite of the small size and high polarizability of the Tc4+ metal ion, the Tc(IV)-ISA complexes described in this work are significantly weaker than other ISA complexes formed with larger M4+ metal ions, i.e., Zr, Pu and U. This unexpected behavior can be possibly explained by the strong hydrolysis of Tc(IV) and corresponding stabilization of the TcO2+ moiety, which does not occur for other M(IV) systems. Thermodynamic data derived in this work can be implemented in geochemical calculations of relevance in the context of nuclear waste disposal and other environmental applications.

Elucidating Clinical Queries for Tailored Therapy in Patients with Prolactinoma.

Prolactinomas are the most prevalent type of pituitary neuroendocrine adenomas, primarily affecting women of reproductive age. Unlike other pituitary tumors, the first-line management has traditionally been pharmacological rather than surgical. This preference is due to the effectiveness of dopamine agonists (DAs), which typically reduce tumor size and normalize prolactin levels in most patients. However, this does not imply that there is no room for improvement; the duration of treatment and medication side effects often lead to compliance issues among patients. Recent advances in surgical techniques and molecular biology have paved the way for the development of precision medicine, allowing for more flexible and personalized treatment strategies for prolactinomas. This review aims to enhance clinical decision-making and patient care for endocrinologists by focusing on several key factors: predictive markers of DA sensitivity, clinical characteristics and suitability for transsphenoidal adenomectomy as a potential first-line treatment, factors determining the successful withdrawal of DAs after prolonged use, safety concerns during pre/post-pregnancy and breastfeeding, and determinants of tumor aggressiveness. Through tailored therapy-a patient-focused, multidisciplinary approach- we aim to improve the management of prolactinoma patients.

Exploration of a Machine Learning Model Using Self-rating Questionnaires for Detecting Depression in Patients with Breast Cancer.

Objective: Given the long-term and severe distress experienced during breast cancer treatment, detecting depression among breast cancer patients is clinically crucial. This study aimed to explore a machine-learning model using self-report questionnaires to screen for depression in patients with breast cancer. Methods: A total of 327 patients who visited the breast cancer clinic were included in this study. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9), Beck Depression Inventory (BDI), and Hospital Anxiety and Depression Scale (HADS). The depression was evaluated according to the Diagnostic and Statistical Manual of Mental Disorders 5th edition. The prediction model's performance based on supervised machine learning was conducted using MATLAB2022. Results: The BDI showed an area under the curve (AUC) of 0.785 when using the logistic regression (LR) classifier. The HADS and PHQ-9 showed an AUC of 0.784 and 0.756 when using the linear discriminant analysis, respectively. The combinations of BDI and HADS showed an AUC of 0.812 when using the LR. The combinations of PHQ-9, BDI, and HADS showed an AUC of 0.807 when using LR. Conclusion: The combination model with BDI and HADS in breast cancer patients might be better than the method using a single scale. In future studies, it is necessary to explore strategies that can improve the performance of the model by integrating the method using questionnaires and other methods.

Differential gene expression and pathway analysis in growth hormone-secreting pituitary tumors according to granulation pattern.

This study investigated differential gene expression between granulation patterns in growth hormone (GH)-secreting pituitary tumors, aiming to elucidate novel transcriptomes that explain clinical variances in patients with acromegaly. Transcriptome analysis was conducted on 6 normal pituitary tissues and 15 GH-secreting pituitary tumors, including 9 densely granulated somatotroph tumors (DGSTs) and 6 sparsely granulated somatotroph tumors (SGSTs). We identified 3111 differentially expressed genes (DEGs) in tumors compared to normal pituitaries, with 1117 DEGs unique to a specific granulation within tumors. SGST showed enrichment of neuronal development and acute inflammatory response pathways, along with a significant enhancement of JAK-STAT, phosphatidylinositol 3-kinase, and MAPK signaling. The results suggest that granulation-specific gene expression may underpin diverse clinical presentations in acromegaly, highlighting the potential for further investigation into these transcriptomic variations and their roles in disease pathology, particularly the involvement of genes linked to neuronal development, inflammatory response, and JAK-STAT signaling in SGST.

Simultaneous Utilization of Mood Disorder Questionnaire and Bipolar Spectrum Diagnostic Scale for Machine Learning-Based Classification of Patients With Bipolar Disorders and Depressive Disorders.

OBJECTIVE: Bipolar and depressive disorders are distinct disorders with clearly different clinical courses, however, distinguishing between them often presents clinical challenges. This study investigates the utility of self-report questionnaires, the Mood Disorder Questionnaire (MDQ) and Bipolar Spectrum Diagnostic Scale (BSDS), with machine learning-based multivariate analysis, to classify patients with bipolar and depressive disorders. METHODS: A total of 189 patients with bipolar disorders and depressive disorders were included in the study, and all participants completed both the MDQ and BSDS questionnaires. Machine-learning classifiers, including support vector machine (SVM) and linear discriminant analysis (LDA), were exploited for multivariate analysis. Classification performance was assessed through cross-validation. RESULTS: Both MDQ and BSDS demonstrated significant differences in each item and total scores between the two groups. Machine learning-based multivariate analysis, including SVM, achieved excellent discrimination levels with area under the ROC curve (AUC) values exceeding 0.8 for each questionnaire individually. In particular, the combination of MDQ and BSDS further improved classification performance, yielding an AUC of 0.8762. CONCLUSION: This study suggests the application of machine learning to MDQ and BSDS can assist in distinguishing between bipolar and depressive disorders. The potential of combining high-dimensional psychiatric data with machine learning-based multivariate analysis as an effective approach to psychiatric disorders.

Development of a Mature B Lymphocyte Probe through Gating-Oriented Live-Cell Distinction (GOLD) and Selective Imaging of Topical Spleen.

B lymphocytes play a pivotal role in the adaptive immune system by facilitating antibody production. Young B cell progenitors originate in the bone marrow and migrate to the spleen for antigen-dependent maturation, leading to the development of diverse B cell subtypes. Thus, tracking B cell trajectories through cell type distinction is essential for an appropriate checkpoint assessment. Despite its significance, monitoring specific B cell subclasses in live states has been hindered by a lack of suitable molecular tools. In this study, we introduce CDoB as the first mature B cell-selective probe, enabling real-time discrimination of three classified stages in B-cell development: progenitor, transitional, and mature B cells, through a single analysis using CyTOF. The selective mechanism of CDoB, elucidated as gating-oriented live-cell distinction (GOLD), targets SLC25A16, identified through systematic screening of SLC-CRISPRa and CRISPRi libraries. CDoB selectively brightens mature B cells in the mitochondrial area using SLC25A16 as the main gate, and the staining intensity correlates positively with the expression level of SLC25A16 along the B cell maturation continuum. In spleen tissues, CDoB demonstrates selective marking in mature B cell areas in live tissue status, representing the first performance achieved by a small-molecule fluorescent probe.

The Dropout Rates and Associated Factors in Patients with Mood Disorders in Long-term Naturalistic Treatment.

Objective: Although maintenance treatment for mood disorders is important, the treatment discontinuation rate is reported to be high. This study aimed to investigate the dropout rates and associated factors in mood disorders. Methods: The patients in a mood disorder clinic (n = 535) were examined. Demographic and clinical factors, scores of psychometric scales, time to dropout from initial treatment in patients with bipolar disorder (BP) (n = 288) and depressive disorder (DD) (n = 143) were evaluated based on database of the mood disorder clinic. Results: Among the studied patients with BP and DD, 50% showed dropout in 4.05 and 2.17 years, respectively. The mean survival times were 8.90 years in bipolar disorder I (BP-I), 5.19 years in bipolar II disorder, 3.22 years in bipolar disorder not otherwise specified, 4.24 years in major depressive disorder, and 4.03 years in other depressive disorders. In the multivariate Cox proportional hazards regression model in the BP group, diagnosis BP-I was found to be significantly related to the decrease in dropout rate (hazard ratio [HR] = 0.22, p = 0.001); however, increased past suicide attempt number was significantly related to the increase in dropout rate (HR = 1.13, p = 0.017). In the DD group, none of anxiety disorders as comorbidity, increased scores of openness, and extraversion personality were related to the increase in dropout rate. Conclusion: Patients with BP, especially BP-I, showed a lower dropout rate as compared to patients with other mood disorders.

Subjective Experience on Virtual Reality-Assisted Mental Health Promotion Program.

OBJECTIVE: Mental health promotion programs using virtual reality (VR) technology have been developed in various forms. This study aimed to investigate the subjective experience of a VR-assisted mental health promotion program for the community population, which was provided in the form of VR experience on a bus to increase accessibility. METHODS: Ninety-six people participated in this study. The relationship between the subjective experience and mental health states such as depression, anxiety, perceived stress, and quality of life was explored. The subjective experience on depression and stress before and after VR program treatment was compared using the Wilcoxon signed-rank test. The satisfaction with the VR-assisted mental health promotion program was examined after using the VR program. RESULTS: The VR-assisted mental health promotion program on a bus significantly improved subjective symptoms such as depression (p=0.036) and perceived stress (p=0.010) among all the participants. Among the high-risk group, this VR program significantly relieved subjective depressive feeling score (p=0.033), and subjective stressful feeling score (p=0.035). In contrast, there were no significant changes in subjective depressive feelings (p=0.182) and subjective stressful feelings (p=0.058) among the healthy group. Seventy-two percent of the participants reported a high level of satisfaction, scoring 80 points or more. CONCLUSION: The findings of this study suggest that the VR-assisted mental health promotion program may effectively improve the subjective depressive and stressful feelings. The use of VR programs on buses to increase of accessibility for the community could be a useful approach for promoting mental health among the population.