The characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders.

BACKGROUND: Recent studies have indicated that clinical high risk for psychosis (CHR-P) is highly specific for psychotic disorders other than pluripotential to various serious mental illnesses. However, not all CHR-P develop psychotic disorder only, and psychosis can occur in non-psychotic disorders as well. Our prospective cohort study aims to investigate the characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders. METHODS: The SPRIM study is a prospective naturalistic cohort program that focuses on the early detection of those at risk of developing serious mental illness, including psychosis (CHR-P), bipolar (CHR-B), and depressive disorder (CHR-D), as well as undifferentiated risk participants (UCHR). Our study has a longitudinal design with a baseline assessment and eight follow-up evaluations at 6, 12, 18, 24, 30, 36, 42, and 48 months to determine whether participants have transitioned to psychosis or mood disorders. RESULTS: The SPRIM sample consisted of 90 CHR participants. The total cumulative incidence rate of transition was 53.3% (95% CI 32.5-77.2). CHR-P, CHR-B, CHR-D, and UCHR had cumulative incidence rates of 13.7% (95% CI 3.4-46.4), 52.4% (95% CI 28.1-81.1), 66.7% (95% CI 24.6-98.6) and 54.3% (95% CI 20.5-93.1), respectively. The cumulative incidence of psychosis, bipolar, and depressive disorder among all participants was 3.3% (95% CI 0.8-11.5), 45.7% (95% CI 24.4-73.6), and 11.2% (95% CI 3.1-36.2), respectively. CONCLUSIONS: Our study suggests that the concept of pluripotent high-risk for a diverse range of psychiatric disorders is an integrative approach to examining transdiagnostic interactions between illnesses with a high transition rate and minimizing stigma.

Development of Prediction Model for Intensive Care Unit Admission Based on Heart Rate Variability: A Case-Control Matched Analysis.

This study aimed to develop a predictive model for intensive care unit (ICU) admission by using heart rate variability (HRV) data. This retrospective case-control study used two datasets (emergency department [ED] patients admitted to the ICU, and patients in the operating room without ICU admission) from a single academic tertiary hospital. HRV metrics were measured every 5 min using R-peak-to-R-peak (R-R) intervals. We developed a generalized linear mixed model to predict ICU admission and assessed the area under the receiver operating characteristic curve (AUC). Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated from the coefficients. We analyzed 610 (ICU: 122; non-ICU: 488) patients, and the factors influencing the odds of ICU admission included a history of diabetes mellitus (OR [95% CI]: 3.33 [1.71-6.48]); a higher heart rate (OR [95% CI]: 3.40 [2.97-3.90] per 10-unit increase); a higher root mean square of successive R-R interval differences (RMSSD; OR [95% CI]: 1.36 [1.22-1.51] per 10-unit increase); and a lower standard deviation of R-R intervals (SDRR; OR [95% CI], 0.68 [0.60-0.78] per 10-unit increase). The final model achieved an AUC of 0.947 (95% CI: 0.906-0.987). The developed model effectively predicted ICU admission among a mixed population from the ED and operating room.

Efficacy of Learning Disorder Treatment for Reading or Mathematics Disorders: An Open Study.

Objectives: This study aimed to identify the effectiveness of treatment programs for children with reading (RD) or mathematics disorders (MD). Structured treatment programs were developed to improve phonological awareness and number sense among children and adolescents with RD or MD, respectively, and the effectiveness of the learning disorder treatment programs were evaluated. Methods: We used standardized, objective diagnostic, and evaluation tools not only to recruit participants with RD, MD, or comorbid attention deficit and hyperactivity disorder, but also to assess the effectiveness of the treatments regarding both improved core neurocognitive deficits of RD or MD and academic achievement. Forty children with RD or MD received one-on-one treatments from therapists. Results: In the RD group, treatment effects were observed in all subtests. In the word and paragraph reading tests, the accuracy rates and fluency improved. The results of the phonological working memory test, word-sound correspondence test, and rapid automatic naming tests also improved. In the MD group, the accuracy rate and fluency on the arithmetic test improved. An increase in the accuracy rate in the size and distance comparison tests and a decrease in the error rate in the estimation test were also observed. However, there were no improvements in reaction time in these subtests. Conclusion: Learning disorder treatment programs that focus on improving phonological awareness or number sense in children with RD or MD improved achievement, phonological awareness, and number sense.

L-DOPA regulates neuroinflammation and Aß pathology through NEP and ADAM17 in a mouse model of AD.

Dopamine plays important roles in cognitive function and inflammation and therefore is involved in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease (AD). Drugs that increase or maintain dopamine levels in the brain could be a therapeutic strategy for AD. However, the effects of dopamine and its precursor levodopa (L-DOPA) on Aß/tau pathology in vivo and the underlying molecular mechanisms have not been studied in detail. Here, we investigated whether L-DOPA treatment alters neuroinflammation, Aß pathology, and tau phosphorylation in 5xFAD mice, a model of AD. We found that L-DOPA administration significantly reduced microgliosis and astrogliosis in 5xFAD mice. In addition, L-DOPA treatment significantly decreased Aß plaque number by upregulating NEP and ADAM17 levels in 5xFAD mice. However, L-DOPA-treated 5xFAD mice did not exhibit changes in tau hyperphosphorylation or tau kinase levels. These data suggest that L-DOPA alleviates neuroinflammatory responses and Aß pathology but not tau pathology in this mouse model of AD.

Individual-specific postural discomfort prediction using decision tree models.

The objective of the current study was to explore the utilization of the decision tree (DT) algorithm to model posture-discomfort relationships at the individual level. The DT algorithm has the advantage that it makes no assumptions about the distribution of data, is robust in representing non-linear data with noise, and produces white-box models that are interpretable. Individual-level modelling is essential for examining individual-specific postural discomfort perception processes and understanding the inter-individual variability. It also has practical applications, including the development of individual-specific digital human models and more precise and informative population accommodation analysis. Individual-specific DT models were generated using postural discomfort rating data for various seated upper body postures to predict discomfort based on postural and task variables. The individual-specific DT models accurately predicted postural discomfort and revealed large inter-individual variability in the modelling results. DT modelling is expected to greatly facilitate investigating the human discomfort perception process.

Developing theragnostics for Alzheimer's disease: Insights from cancer treatment.

The prevalence of Alzheimer's disease (AD) and its associated economic and societal burdens are on the rise, but there are no curative treatments for AD. Interestingly, this neurodegenerative disease shares several biological and pathophysiological features with cancer, including cell-cycle dysregulation, angiogenesis, mitochondrial dysfunction, protein misfolding, and DNA damage. However, the genetic factors contributing to the overlap in biological processes between cancer and AD have not been actively studied. In this review, we discuss the shared biological features of cancer and AD, the molecular targets of anticancer drugs, and therapeutic approaches. First, we outline the common biological features of cancer and AD. Second, we describe several anticancer drugs, their molecular targets, and their effects on AD pathology. Finally, we discuss how protein-protein interactions (PPIs), receptor inhibition, immunotherapy, and gene therapy can be exploited for the cure and management of both cancer and AD. Collectively, this review provides insights for the development of AD theragnostics based on cancer drugs and molecular targets.

PANCDR: precise medicine prediction using an adversarial network for cancer drug response.

Pharmacogenomics aims to provide personalized therapy to patients based on their genetic variability. However, accurate prediction of cancer drug response (CDR) is challenging due to genetic heterogeneity. Since clinical data are limited, most studies predicting drug response use preclinical data to train models. However, such models might not be generalizable to external clinical data due to differences between the preclinical and clinical datasets. In this study, a Precision Medicine Prediction using an Adversarial Network for Cancer Drug Response (PANCDR) model is proposed. PANCDR consists of two sub-models, an adversarial model and a CDR prediction model. The adversarial model reduces the gap between the preclinical and clinical datasets, while the CDR prediction model extracts features and predicts responses. PANCDR was trained using both preclinical data and unlabeled clinical data. Subsequently, it was tested on external clinical data, including The Cancer Genome Atlas and brain tumor patients. PANCDR outperformed other machine learning models in predicting external test data. Our results demonstrate the robustness of PANCDR and its potential in precision medicine by recommending patient-specific drug candidates. The PANCDR codes and data are available at https://github.com/DMCB-GIST/PANCDR.

Effect of information provision on parental intention toward COVID-19 vaccination for children: a nationwide survey experiment.

The reluctance of parents to vaccinate their children against COVID-19 was prevalent particularly when uncertainty over vaccination outcomes prevailed. We conducted a nationwide randomized online survey experiment to assess the effect of information provision on parental intention for COVID-19 vaccination before the government started vaccination for children in South Korea. Parents of elementary school children were provided with either no information (Control), information on vaccine profile (vaccine informed group; VI), or COVID-19 (disease informed group; DI). Among 359,110 participants, parental intention for vaccination of children was significantly higher in both VI and DI groups compared with the Control group. In terms of effect size, information on COVID-19 vaccine increased likelihood to vaccinate by 1620 per 100,000 parents and reduced vaccine hesitancy by 1340 per 100,000 parents. Consistently with the positive effect on vaccination intention, both VI and DI interventions increased participants' perceptions on vaccination benefits being higher than its risks and vaccination risks being lower than health risks of COVID-19 infection, and self-reported trust in COVID-19 information. Our results lend strong support to the claim that the provision of targeted, tailored information on COVID-19 vaccine and infection increases parental intention to vaccinate children and reduces vaccine hesitancy.

Staphylococcus argenteus bacteremia in the Republic of Korea.

In 2015, Staphylococcus argenteus and Staphylococcus schweitzeri were proposed as new species, distinct from Staphylococcus aureus and collectively referred to as the S. aureus complex. However, no clinical reports of these new species exist in Korea. Upon the application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for all bloodstream isolates since September 2022, S. argenteus was identified in one patient. Therefore, we aimed to search for new species among the archives of the S. aureus bacteremia cohort and describe their clinical and microbiological characteristics. Among the 691 archived S. aureus isolates between 2012 and 2018, one was identified as S. argenteus via MALDI-TOF MS. Both S. argenteus isolates (one in 2022) were obtained from patients with extensive pneumonia accompanied by bacteremia and both cases had fatal outcomes. They harbored multiple virulence genes (clfA, clfB, fnbpA, sdrC, sdrD, sdrE, bbp, cna, see, seg, sei, blaZ, fnbpB, and map) but did not harbor mecA and pvl. No matched sequence type (ST) was found in either isolate, and both S. argenteus isolates were closely related to ST1594, ST1593, ST1793, and ST1303, which belonged to S. argenteus. S. argenteus accounted for <1% of the S. aureus complex but had clinical characteristics similar to S. aureus. Therefore, clinicians should be aware of these factors to avoid misidentifying these strains as coagulase-negative staphylococci, and appropriate reporting is required to minimize confusion.IMPORTANCEStaphylococcus argenteus, a member of Staphylococcus aureus complex, has been reported as an important pathogen that causes clinically invasive infections in humans similar to S. aureus. Clinical isolates of S. argenteus have been reported across the world, showing a large geographical difference in prevalence and genomic profile. However, there have been no clinical reports regarding this new species in Korea. This is the first report to investigate the clinical and genetic characteristics of S. argenteus identified in patients with bacteremia, and the proportion of S. argenteus bacteremia among S. aureus bacteremia cohort in Korea.

Changes in the intrinsic severity of severe acute respiratory syndrome coronavirus 2 according to the emerging variant: a nationwide study from February 2020 to June 2022, including comparison with vaccinated populations.

BACKGROUND: As the population acquires immunity through vaccination and natural infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), understanding the intrinsic severity of coronavirus disease (COVID-19) is becoming challenging. We aimed to evaluate the intrinsic severity regarding circulating variants of SARS-CoV-2 and to compare this between vaccinated and unvaccinated individuals. METHODS: With unvaccinated and initially infected confirmed cases of COVID-19, we estimated the case severity rate (CSR); case fatality rate (CFR); and mortality rate (MR), including severe/critical cases and deaths, stratified by age and compared by vaccination status according to the period regarding the variants of COVID-19 and vaccination. The overall rate was directly standardized with age. RESULTS: The age-standardized CSRs (aCSRs) of the unvaccinated group were 2.12%, 5.51%, and 0.94% in the pre-delta, delta, and omicron period, respectively, and the age-standardized CFRs (aCFRs) were 0.60%, 2.49%, and 0.63% in each period, respectively. The complete vaccination group had lower severity than the unvaccinated group over the entire period showing under 1% for the aCSR and 0.5% for the aCFR. The age-standardized MR of the unvaccinated group was 448 per million people per month people in the omicron period, which was 11 times higher than that of the vaccinated group. In terms of age groups, the CSR and CFR sharply increased with age from the 60 s and showed lower risk reduction in the 80 s when the period changed to the omicron period. CONCLUSIONS: The intrinsic severity of COVID-19 was the highest in the delta period, with over 5% for the aCSR, whereas the completely vaccinated group maintained below 1%. This implies that when the population is vaccinated, the impact of COVID-19 will be limited, even if a new mutation appears. Moreover, considering the decreasing intrinsic severity, the response to COVID-19 should prioritize older individuals at a higher risk of severe disease.

Integrated drug response prediction models pinpoint repurposed drugs with effectiveness against rhabdomyosarcoma.

Targeted therapies for inhibiting the growth of cancer cells or inducing apoptosis are urgently needed for effective rhabdomyosarcoma (RMS) treatment. However, identifying cancer-targeting compounds with few side effects, among the many potential compounds, is expensive and time-consuming. A computational approach to reduce the number of potential candidate drugs can facilitate the discovery of attractive lead compounds. To address this and obtain reliable predictions of novel cell-line-specific drugs, we apply prediction models that have the potential to improve drug discovery approaches for RMS treatment. The results of two prediction models were ensemble and validated via in vitro experiments. The computational models were trained using data extracted from the Genomics of Drug Sensitivity in Cancer database and tested on two RMS cell lines to select potential RMS drug candidates. Among 235 candidate drugs, 22 were selected following the result of the computational approach, and three candidate drugs were identified (NSC207895, vorinostat, and belinostat) that showed selective effectiveness in RMS cell lines in vitro via the induction of apoptosis. Our in vitro experiments have demonstrated that our proposed methods can effectively identify and repurpose drugs for treating RMS.

Risk Factors for Severe and Critical Coronavirus Disease 2019 in Children.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is generally mild in children; however, severe or critical cases may occur. In this nationwide study, we analyzed clinical manifestations in children diagnosed with severe acute respiratory syndrome coronavirus 2 to identify high-risk groups for severe or critical disease and compared the clinical features between the Delta- and Omicron-dominant periods. METHODS: Data were retrieved from the National Health Insurance Service (NHIS) database and merged with the Korea Disease Control and Prevention Agency-COVID-19-NHIS cohort, which includes information on COVID-19 cases and vaccination records. We included individuals <20 years old diagnosed with COVID-19 during both periods (Delta: July 25, 2021-January 15, 2022; Omicron: January 16, 2022-March 31, 2022). RESULTS: Proportion of severe or critical cases was higher during the Delta period than during the Omicron period. The Omicron period saw increased hospitalization for pneumonia and croup and increased likelihood of hospitalization for neurological manifestations. The risk of severe COVID-19 depended on age group (Delta: highest for 12-19 years; Omicron: 0-4 years). This risk was high in children with multiple complex chronic conditions during both periods and with obesity or asthma during the Delta but not during the Omicron period. Two-dose COVID-19 vaccination provided strong protection against severe disease in the Delta period (adjusted odds ratio: 0.20), with reduced effectiveness in the Omicron period (adjusted odds ratio: 0.91). However, it significantly reduced the risk of critical illness (adjusted odds ratio: 0.14). CONCLUSIONS: These findings can facilitate identification of children at high risk of severe or critical COVID-19, who may require intensive medical support, and development of vaccination policies.

Proteomic profiling in the progression of psychosis: Analysis of clinical high-risk, first episode psychosis, and healthy controls.

BACKGROUND AND HYPOTHESIS: Recent evidence has highlighted the benefits of early detection and treatment for better clinical outcomes in patients with psychosis. Biological markers of the disease have become a focal point of research. This study aimed to identify protein markers detectable in the early stages of psychosis and indicators of progression by comparing them with those of healthy controls (HC) and first episode psychosis (FEP). STUDY DESIGN: The participants comprised 28 patients in the clinical high-risk (CHR) group, 49 patients with FEP, and 61 HCs aged 15-35 years. Blood samples were collected and analyzed using multiple reaction monitoring-mass spectrometry to measure the expression of 158 peptide targets. Data were adjusted for age, sex, and use of psychotropic drugs. STUDY RESULTS: A total of 18 peptides (17 proteins) differed significantly among the groups. The protein PRDX2 was higher in the FEP group than in the CHR and HC groups and showed increased expression according to disease progression. The levels of six proteins were significantly higher in the FEP group than in the CHR group. Nine proteins differed significantly in the CHR group compared to the other groups. Sixteen proteins were significantly correlated with symptom severity. These proteins are primarily related to the coagulation cascade, inflammatory response, brain structure, and synaptic plasticity. CONCLUSIONS: Our findings suggested that peripheral protein markers reflect disease progression in patients with psychosis. Further longitudinal research is needed to confirm these findings and to identify the specific roles of these markers in the pathogenesis of schizophrenia.

Molecular data representation based on gene embeddings for cancer drug response prediction.

Cancer drug response prediction is a crucial task in precision medicine, but existing models have limitations in effectively representing molecular profiles of cancer cells. Specifically, when these models represent molecular omics data such as gene expression, they employ a one-hot encoding-based approach, where a fixed gene set is selected for all samples and omics data values are assigned to specific positions in a vector. However, this approach restricts the utilization of embedding-vector-based methods, such as attention-based models, and limits the flexibility of gene selection. To address these issues, our study proposes gene embedding-based fully connected neural networks (GEN) that utilizes gene embedding vectors as input data for cancer drug response prediction. The GEN allows for the use of embedding-vector-based architectures and different gene sets for each sample, providing enhanced flexibility. To validate the efficacy of GEN, we conducted experiments on three cancer drug response datasets. Our results demonstrate that GEN outperforms other recently developed methods in cancer drug prediction tasks and offers improved gene representation capabilities. All source codes are available at https://github.com/DMCB-GIST/GEN/ .

Information amount, accuracy, and relevance of generative artificial intelligence platforms' answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study

PURPOSE: This study assessed the performance of 6 generative artificial intelligence (AI) platforms on the learning objectives of medical arthropodology in a parasitology class in Korea. We examined the AI platforms' performance by querying in Korean and English to determine their information amount, accuracy, and relevance in prompts in both languages. METHODS: From December 15 to 17, 2023, 6 generative AI platforms­Bard, Bing, Claude, Clova X, GPT-4, and Wrtn­were tested on 7 medical arthropodology learning objectives in English and Korean. Clova X and Wrtn are platforms from Korean companies. Responses were evaluated using specific criteria for the English and Korean queries. RESULTS: Bard had abundant information but was fourth in accuracy and relevance. GPT-4, with high information content, ranked first in accuracy and relevance. Clova X was 4th in amount but 2nd in accuracy and relevance. Bing provided less information, with moderate accuracy and relevance. Wrtn's answers were short, with average accuracy and relevance. Claude AI had reasonable information, but lower accuracy and relevance. The responses in English were superior in all aspects. Clova X was notably optimized for Korean, leading in relevance. CONCLUSION: In a study of 6 generative AI platforms applied to medical arthropodology, GPT-4 excelled overall, while Clova X, a Korea-based AI product, achieved 100% relevance in Korean queries, the highest among its peers. Utilizing these AI platforms in classrooms improved the authors' self-efficacy and interest in the subject, offering a positive experience of interacting with generative AI platforms to question and receive information.

Etiology and Clinical Characteristics of Community-Acquired Pneumonia in Korean Children During the Pre-COVID-19 Period, 2015-2020.

BACKGROUND: There have been many epidemiologic studies on community-acquired pneumonia (CAP) among children, most of which had substantial limitations. This study investigated the etiologic distribution and clinical characteristics of CAP in Korean children for 5 years before the coronavirus disease 2019 (COVID-19) pandemic. METHODS: A retrospective analysis of children hospitalized for CAP at 4 referral hospitals during 2015-2020 was performed. Cases in which bronchiolitis was suspected or pulmonary infiltration was not evident on chest radiography (CXR) were excluded. Viruses and atypical bacteria were defined as detected when positive in the polymerase chain reaction test performed for respiratory specimens. Serologic testing result for Mycoplasma pneumoniae was incorporated with strict interpretation. Pyogenic bacteria were included only when cultured in blood, pleural fluid, or bronchoalveolar lavage, but those cultured in endotracheal aspirate or sputum when the case was clinically evident bacterial pneumonia were also included. RESULTS: A total of 2,864 cases of suspected pneumonia were selected by diagnosis code and CXR findings. Medical chart and CXR review excluded nosocomial pneumonia and cases without evident infiltration, resulting in 517 (18.1%) CAP cases among 489 children. Regarding clinical symptoms, high fever was present in 59.4% and dyspnea in 19.9% of cases. Respiratory support was required for 29.2% of patients, including mechanical ventilation for 3.9%. Pathogens were detected in 49.9% of cases, with viruses in 32.3%, atypical bacteria in 17.8%, and pyogenic bacteria in 2.3% of cases. As single pathogens, M. pneumoniae (16.8%) and respiratory syncytial virus (RSV, 13.7%) were the most common. Parenteral ß-lactam and macrolide antibiotics were administered in 81.6% and 50.7% of cases, respectively. A total of 12 (2.3%) cases resulted in poor outcomes, including 3 deaths. CONCLUSION: M. pneumoniae and RSV were the most commonly detected pathogens of pediatric CAP, which was selected by strict clinical and radiologic criteria. It is necessary to carefully decide whether to use parenteral antibiotics based on the epidemiology and clinical features of CAP in children.

Joint triplet loss with semi-hard constraint for data augmentation and disease prediction using gene expression data.

The accurate prediction of patients with complex diseases, such as Alzheimer's disease (AD), as well as disease stages, including early- and late-stage cancer, is challenging owing to substantial variability among patients and limited availability of clinical data. Deep metric learning has emerged as a promising approach for addressing these challenges by improving data representation. In this study, we propose a joint triplet loss model with a semi-hard constraint (JTSC) to represent data in a small number of samples. JTSC strictly selects semi-hard samples by switching anchors and positive samples during the learning process in triplet embedding and combines a triplet loss function with an angular loss function. Our results indicate that JTSC significantly improves the number of appropriately represented samples during training when applied to the gene expression data of AD and to cancer stage prediction tasks. Furthermore, we demonstrate that using an embedding vector from JTSC as an input to the classifiers for AD and cancer stage prediction significantly improves classification performance by extracting more accurate features. In conclusion, we show that feature embedding through JTSC can aid in classification when there are a small number of samples compared to a larger number of features.

The association between insulin resistance and depressive symptoms - A national representative cross-sectional study.

OBJECTIVE: Increasing evidence suggests a positive association between insulin resistance (IR) and depression. However, whether sex-or body mass index-specific differences exist remains controversial, and only few studies have analyzed specific symptom domains. Thus, the present study aimed to analyze the association between IR and depressive symptom domains and to clarify the effects of sex and body mass index. METHODS: The study sample comprised 4007 participants, aged 19-79, from the Korea National Health and Nutrition Examination Study 2020. Participants completed health interviews and examinations, providing data on circulating insulin and glucose levels, the Patient Health Questionnaire-9 (PHQ-9), and related covariates. IR was calculated using the homeostasis model assessment of insulin resistance. Associations between IR and PHQ-9 were analyzed using negative binomial regression with adjustments for the complex survey design. RESULTS: The association between log-transformed IR and PHQ-9 total scores was statistically significant (incidence rate ratio [IRR] = 1.17, 95% confidence interval [CI] = 1.07-1.29, p = 0.001). Only body mass index specific differences were statistically significant, as the association was only significant in those without obesity (IRR = 1.21, 95% CI = 1.06-1.38, p = 0.005). IR was associated with cognitive/affective (IRR = 1.23, 95% CI = 1.08-1.41, p = 0.002) and somatic (IRR = 1.14, 95% CI = 1.04-1.25, p = 0.005) depressive symptom domains. Sensitivity analyses revealed similar results. CONCLUSIONS: IR was positively associated with cognitive/affective and somatic depressive symptoms in non-obese individuals.

VDUP1 Deficiency Promotes the Severity of DSS-Induced Colitis in Mice by Inducing Macrophage Infiltration.

The loss of vitamin D3 upregulated protein 1 (VDUP1) has been implicated in the pathogenesis of various inflammation-related diseases. Notably, reduced expression of VDUP1 has been observed in clinical specimens of ulcerative colitis (UC). However, the role of VDUP1 deficiency in colitis remains unclear. In this study, we investigated the role of VDUP1 in dextran sulfate sodium (DSS)-induced experimental colitis in mice. VDUP1-deficient mice were more susceptible to DSS-induced colitis than their wild-type (WT) littermates after 2% DSS administration. VDUP1-deficient mice exhibited an increased disease activity index (DAI) and histological scores, as well as significant colonic goblet cell loss and an increase in apoptotic cells. These changes were accompanied by a significant decrease in MUC2 mRNA expression and a marked increase in proinflammatory cytokines and chemokines within damaged tissues. Furthermore, phosphorylated NF-κB p65 expression was significantly upregulated in damaged tissues in the context of VDUP1 deficiency. VDUP1 deficiency also led to significant infiltration of macrophages into the site of ulceration. An in vitro chemotaxis assay confirmed that VDUP1 deficiency enhanced bone marrow-derived macrophage (BMDM) chemotaxis induced by CCL2. Overall, this study highlights VDUP1 as a regulator of UC pathogenesis and a potential target for the future development of therapeutic strategies.

Contact Investigations With a Single Tuberculin Skin Test on Infants Exposed to Tuberculosis in a Postpartum Care Center During the Neonatal Period.

BACKGROUND: Tuberculosis (TB) exposure in congregate settings related to neonates is a serious medical and social issue. TB exposure happens during the neonatal period, but contact investigations for exposed infants are usually conducted after the neonatal period. Generally, recommendations for screening and managing close contact are different for neonates and children. Thus, there are challenges in contact investigations. We aimed to report contact investigations with a single tuberculin skin test (TST) on infants exposed to infectious TB in a postpartum care center. METHODS: The index case was a healthcare worker with active pulmonary TB: sputum acid-fast bacilli smear negative, culture positive, and no cavitary lesion. All exposed infants underwent medical examinations and chest X-ray. After TB disease was ruled out, contacts received window period prophylaxis with isoniazid (INH) until three months after the last exposure. TST was performed only once after completing the prophylaxis. RESULTS: A total of 288 infants were selected as high-priority contacts. At the initial contact investigation, the age of infants ranged from 8 to 114 days. None of these exposed infants had TB disease. The prevalence of latent TB infection (LTBI) was 25.3% (73/288; 95% confidence interval [CI], 20.7-30.7). There were no serious adverse events related to the window period prophylaxis or LTBI treatment with INH. During the 1-year follow-up period, no infants progressed to overt TB disease. The size of TST induration in infants vaccinated with percutaneous Bacillus Calmette-Guérin (BCG) vaccine was significantly larger than that of infants vaccinated with intradermal BCG vaccine (median, 8 mm vs. 5 mm; P = 0.002). In multiple logistic regression analysis, independent factors associated with TST positivity (≥ 10 mm induration) were male (adjusted odds ratio [aOR], 2.98; 95% CI, 1.6-5.64), percutaneous BCG vaccination (aOR, 3.30; 95% CI, 1.75-6.48), TST reading between 60 and 72 hours after injecting purified protein derivative (aOR, 2.87; 95% CI, 1.53-5.49), and INH prophylaxis more than four weeks (aOR, 0.49; 95% CI, 0.25-0.94). CONCLUSION: A single TST at three months after the last TB exposure with INH prophylaxis could be used as a main protocol in contact investigations for infants exposed to infectious TB during the neonatal period in congregate settings in Korea.