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.

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.

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.

Family-based genome-wide association analysis of novelty seeking in a Korean schizophrenic population: A pilot study.

Schizophrenia (SPR) is the most devastating mental illness that causes severe deterioration in social and occupational functioning, but, the etiology remains unknown. The objective of this study is to explore the genetic underpinnings of novelty seeking behavior in schizophrenic family within the Korean population. By conducting a family-based genome-wide association study, we aim to identify potential genetic markers and variations associated with novelty seeking traits in the context of SPR. We have recruited 27 probands (with SPR) with their parents and siblings whenever possible. DNA was extracted from blood sampling of 58 individuals in 27 families and analyzed in an Illumina core exome single nucleotide polymorphism (SNP) array. A family-based association test (qFAM) was used to derive SNP association values across all chromosomes. Although none of the final 800,000 SNPs reached the genome-wide significant threshold of 8.45 × 10-7, the most significant 4 SNPs were within the 10-5 to 10-7. This study identifies genetic associations between novelty seeking behavior and SPR within families. RAPGEF5 emerges as a significant gene, along with other neuropsychiatric-related genes. Noteworthy genes like DRD4 and COMT did not show associations, possibly due to the focus on schizophrenic family. While shedding light on this complex relationship, larger studies are needed for robust conclusions and deeper mechanistic insights.

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.

Prediction of suicidal ideation in children and adolescents using machine learning and deep learning algorithm: A case study in South Korea where suicide is the leading cause of death.

BACKGROUND: Korea has the highest suicide rate among Organisation for Economic Co-operation and Development (OECD) countries. Consequently, central and local governments and private organizations in Korea cooperate in promoting various suicide prevention projects to actively respond to suicide problems. Machine learning has been used to predict suicidal ideation in the fields of health and medicine but not from a social science perspective. OBJECTIVE: Since suicidal ideation is a major predictor of suicide attempts, being able to anticipate and mitigate it helps prevent suicide. Therefore, this study presents a data-based analysis method for predicting suicidal thoughts quickly and effectively and suggests countermeasures against the causes of suicidal thoughts. PARTICIPANTS AND METHODS: To predict early signs of suicidal ideation in children and adolescents, big data collected for approximately 4 years (from 2017 to 2020) from the Korea Youth Policy Institute (NYPI) were used. To accurately predict suicidal ideation, supervised ma- chine learning classification algorithms such as logistic regression, random forest, XGBoost, multilayer perceptron (MLP), and convolutional neural network (CNN) were used. RESULTS: Using CNN, suicidal ideation was predicted with an accuracy of approximately 90 %. The logistic regression results showed that sadness and depression increased suicidal thoughts by more than 25 times, and anxiety, loneliness, and experience of abusive language increased suicidal thoughts by more than three times. CONCLUSIONS: Machine learning and deep learning approaches have the potential to predict and respond to suicidal thoughts in children, adolescents, and the general population, as well as help respond to the suicide crisis by preemptively identifying the cause.

A comparison of the perceived importance and performance of midwives' roles between midwives and nurses in Korea: a cross-sectional study.

PURPOSE: This study aimed to identify the perceptions, importance, and performance of midwives' roles among midwives and nurses in Korea. METHODS: A descriptive correlational design was employed. Data were collected from 164 nurses and 79 midwives from April 1 to June 25, 2021. Midwives enrolled in the Korean Midwifery Association and nurses and midwives from two hospitals each Daegu and Gyeonggi Province in Korea were invited to participate. The independent t-test, chi-square test, the Welch-Aspin test, and Pearson correlation coefficient were used for analysis. RESULTS: The midwives' role perception score (3.47±1.46) was lower than that of nurses (3.95±0.85), and the midwives' role performance score (2.98±0.83) was also lower than that of nurses (3.34±0.89). Significant differences were observed between midwives and nurses in their perception and performance of roles related to prenatal management, childbirth management, management of psychological changes, postpartum management, and newborn care. Higher role perception and performance among midwives were linked to the management of psychological changes and women's health, indicating potential areas for future development. CONCLUSION: The study results suggest directions for developing new roles for midwives. It is necessary to find a way to expand the field of midwives in public health by benchmarking the roles of midwives in various countries.

Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine.

The clinical characteristics and prognoses of acromegaly vary among patients. Assessment of current and novel predictors can lead to multilevel categorization of patients, allowing integration into new clinical guidelines and a reduction in the increased morbidity and mortality associated with acromegaly. Despite advances in the diagnosis and treatment of acromegaly, its pathophysiology remains unclear. Recent advancements in multiomics technologies, including genomics, transcriptomics, proteomics, metabolomics, and radiomics, have offered new opportunities to unravel the complex pathophysiology of acromegaly. This review comprehensively explores the emerging role of multiomics approaches in elucidating the molecular landscape of acromegaly. We discuss the potential implications of multiomics data integration in the development of novel diagnostic tools, identification of therapeutic targets, and the prospects of precision medicine in acromegaly management. By integrating diverse omics datasets, these approaches can provide valuable insights into disease mechanisms, facilitate the identification of diagnostic biomarkers, and identify potential therapeutic targets for precision medicine in the management of acromegaly.

Changes of Locomotor Activity by Dopamine D2, D3 Agonist Quinpirole in Mice Using Home-cage Monitoring System.

Objective: : As dopamine is closely linked to locomotor activities, animal studies on locomotor activities using dopaminergic agents were widely done. However, most of animal studies were performed for a short period that there is a lack of longitudinal study on the effects of dopaminergic agents on locomotor activities. This study aimed to examine the longterm effect of a dopamine D2, D3 agonist quinpirole on locomotor activities in mice using a home-cage monitoring system. Methods: : The locomotor activities of Institute Cancer Research mice were measured by infrared motion detectors in home-cages under the 12-hour dark and 12-hour light condition for three days after the quinpirole injection. Quinpirole was injected at a concentration of 0.5 mg/kg intraperitoneally in the beginning of the dark phase. The locomotor activities before and after the quinpirole administration were compared by the Wilcoxon signed-rank test and one-way repeated measures ANOVA. Results: : After the quinpirole administration, the 24-hour total locomotor activity did not change (p = 0.169), but activities were significantly increased in the 12-hour dark phase sum (p = 0.013) and decreased in the 12-hour light phase sum (p = 0.009). Significant increases in the activities were observed in the dark-light difference (p = 0.005) and dark-light ratio (p = 0.005) as well. Conclusion: : This study suggests that quinpirole injection entrains the circadian rest-activity rhythm of locomotor activities. Therefore, quinpirole can be a drug that mediates locomotor activity as a dopamine agonist as well as a modulator of the circadian rhythms.