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.

Prediction of the 3D cancer genome from whole-genome sequencing using InfoHiC.

The 3D genome prediction in cancer is crucial for uncovering the impact of structural variations (SVs) on tumorigenesis, especially when they are present in noncoding regions. We present InfoHiC, a systemic framework for predicting the 3D cancer genome directly from whole-genome sequencing (WGS). InfoHiC utilizes contig-specific copy number encoding on the SV contig assembly, and performs a contig-to-total Hi-C conversion for the cancer Hi-C prediction from multiple SV contigs. We showed that InfoHiC can predict 3D genome folding from all types of SVs using breast cancer cell line data. We applied it to WGS data of patients with breast cancer and pediatric patients with medulloblastoma, and identified neo topologically associating domains. For breast cancer, we discovered super-enhancer hijacking events associated with oncogenic overexpression and poor survival outcomes. For medulloblastoma, we found SVs in noncoding regions that caused super-enhancer hijacking events of medulloblastoma driver genes (GFI1, GFI1B, and PRDM6). In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC , uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets.

Crossfeat: a transformer-based cross-feature learning model for predicting drug side effect frequency.

BACKGROUND: Safe drug treatment requires an understanding of the potential side effects. Identifying the frequency of drug side effects can reduce the risks associated with drug use. However, existing computational methods for predicting drug side effect frequencies heavily depend on known drug side effect frequency information. Consequently, these methods face challenges when predicting the side effect frequencies of new drugs. Although a few methods can predict the side effect frequencies of new drugs, they exhibit unreliable performance owing to the exclusion of drug-side effect relationships. RESULTS: This study proposed CrossFeat, a model based on convolutional neural network-transformer architecture with cross-feature learning that can predict the occurrence and frequency of drug side effects for new drugs, even in the absence of information regarding drug-side effect relationships. CrossFeat facilitates the concurrent learning of drugs and side effect information within its transformer architecture. This simultaneous exchange of information enables drugs to learn about their associated side effects, while side effects concurrently acquire information about the respective drugs. Such bidirectional learning allows for the comprehensive integration of drug and side effect knowledge. Our five-fold cross-validation experiments demonstrated that CrossFeat outperforms existing studies in predicting side effect frequencies for new drugs without prior knowledge. CONCLUSIONS: Our model offers a promising approach for predicting the drug side effect frequencies, particularly for new drugs where prior information is limited. CrossFeat's superior performance in cross-validation experiments, along with evidence from case studies and ablation experiments, highlights its effectiveness.

The dopamine analogue CA140 alleviates AD pathology, neuroinflammation, and rescues synaptic/cognitive functions by modulating DRD1 signaling or directly binding to Abeta.

BACKGROUND: We recently reported that the dopamine (DA) analogue CA140 modulates neuroinflammatory responses in lipopolysaccharide-injected wild-type (WT) mice and in 3-month-old 5xFAD mice, a model of Alzheimer's disease (AD). However, the effects of CA140 on Aß/tau pathology and synaptic/cognitive function and its molecular mechanisms of action are unknown. METHODS: To investigate the effects of CA140 on cognitive and synaptic function and AD pathology, 3-month-old WT mice or 8-month-old (aged) 5xFAD mice were injected with vehicle (10% DMSO) or CA140 (30 mg/kg, i.p.) daily for 10, 14, or 17 days. Behavioral tests, ELISA, electrophysiology, RNA sequencing, real-time PCR, Golgi staining, immunofluorescence staining, and western blotting were conducted. RESULTS: In aged 5xFAD mice, a model of AD pathology, CA140 treatment significantly reduced Aß/tau fibrillation, Aß plaque number, tau hyperphosphorylation, and neuroinflammation by inhibiting NLRP3 activation. In addition, CA140 treatment downregulated the expression of cxcl10, a marker of AD-associated reactive astrocytes (RAs), and c1qa, a marker of the interaction of RAs with disease-associated microglia (DAMs) in 5xFAD mice. CA140 treatment also suppressed the mRNA levels of s100ß and cxcl10, markers of AD-associated RAs, in primary astrocytes from 5xFAD mice. In primary microglial cells from 5xFAD mice, CA140 treatment increased the mRNA levels of markers of homeostatic microglia (cx3cr1 and p2ry12) and decreased the mRNA levels of a marker of proliferative region-associated microglia (gpnmb) and a marker of lipid-droplet-accumulating microglia (cln3). Importantly, CA140 treatment rescued scopolamine (SCO)-mediated deficits in long-term memory, dendritic spine number, and LTP impairment. In aged 5xFAD mice, these effects of CA140 treatment on cognitive/synaptic function and AD pathology were regulated by dopamine D1 receptor (DRD1)/Elk1 signaling. In primary hippocampal neurons and WT mice, CA140 treatment promoted long-term memory and dendritic spine formation via effects on DRD1/CaMKIIα and/or ERK signaling. CONCLUSIONS: Our results indicate that CA140 improves neuronal/synaptic/cognitive function and ameliorates Aß/tau pathology and neuroinflammation by modulating DRD1 signaling in primary hippocampal neurons, primary astrocytes/microglia, WT mice, and aged 5xFAD mice.

Molecular epidemiology and virulence factors of group B Streptococcus in South Korea according to the invasiveness.

BACKGROUND: Group B Streptococcus (GBS) causes invasive infections in newborns and elderly individuals, but is a noninvasive commensal bacterium in most immunocompetent people. Recently, the incidence of invasive GBS infections has increased worldwide, and there is growing interest in the molecular genetic characteristics of invasive GBS strains. Vaccines against GBS are expected in the near future. Here, we aimed to analyze the molecular epidemiology of GBS according to the invasiveness in South Korea. METHODS: We analyzed GBS isolates collected and stored in two hospitals in South Korea between January 2015 and December 2020. The invasiveness of these isolates was determined via a retrospective review of clinical episodes. Totally, 120 GBS isolates from 55 children and 65 adults were analyzed. Serotype and sequence type (ST) were determined using multiplex polymerase chain reaction (PCR) and multilocus sequence typing, respectively. Fourteen virulence factor-encoding genes of GBS were analyzed using multiplex PCR. RESULTS: Forty one (34.2%) were invasive infection-related GBS isolates (iGBS). The most frequently detected serotype was III (39/120, 32.5%), and it accounted for a high proportion of iGBS (21/41, 51.2%). The most frequent ST was ST19 (18/120, 15.0%), followed by ST2 (17/120, 14.2%). Serotype III/ST17 was predominant in iGBS (12/41, 29.3%), and all 17 ST2 strains were noninvasive. The distribution of most of the investigated virulence factors was not significantly related to invasiveness; noteworthily, most of the serotype III/ST17 iGBS carried pilus island (PI) 2b (10/12, 83.3%), and the prevalence of fbsB was significantly low compared with noninvasive GBS isolates (P = 0.004). Characteristically, the combination of bca(+)-cspA(+)-pavA(+)-fbsB(-)-rib(+)-bac(-) was predominant in iGBS (24.4%, 10/41). CONCLUSIONS: Serotype III/ST17 GBS carrying PI-2b was frequently detected in iGBS. There was no significant association between invasiveness and the pattern of virulence factors; however, a specific combination of virulence factors was predominant in iGBS.

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.

Establishing a Framework for Evaluating the Effectiveness of Vaccines Targeting National Vaccination Programs.

BACKGROUND: The increasing number of vaccines and the complexity of immunization programs, along with continuous changes in the epidemiology of infectious diseases, necessitate a systematic approach to vaccine effectiveness (VE) evaluation. This study presents a preliminary survey to establish a VE evaluation framework in Korea, focusing on the National Immunization Program. METHODS: Experts' opinions were collected through a two-round online survey targeting key stakeholders. The first round consisted of two multiple-choice questions and two open-ended questions. The second round was a quantitative survey with 17 questionnaires based on five domains derived by analyzing the results of the first-round survey. RESULTS: The results emphasize the necessity and urgency of a government-led VE evaluation system and the establishment of a multidisciplinary evaluation organization. Key considerations include personnel, budget, data integration, legal standards, and surveillance system enhancements. CONCLUSION: These findings provide valuable insights for policymakers, emphasizing the need for collaboration, financial support, and robust data management in developing evidence-based vaccination policies.

MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification.

MOTIVATION: Accurate diagnostic classification and biological interpretation are important in biology and medicine, which are data-rich sciences. Thus, integration of different data types is necessary for the high predictive accuracy of clinical phenotypes, and more comprehensive analyses for predicting the prognosis of complex diseases are required. RESULTS: Here, we propose a novel multi-task attention learning algorithm for multi-omics data, termed MOMA, which captures important biological processes for high diagnostic performance and interpretability. MOMA vectorizes features and modules using a geometric approach and focuses on important modules in multi-omics data via an attention mechanism. Experiments using public data on Alzheimer's disease and cancer with various classification tasks demonstrated the superior performance of this approach. The utility of MOMA was also verified using a comparison experiment with an attention mechanism that was turned on or off and biological analysis. AVAILABILITY AND IMPLEMENTATION: The source codes are available at https://github.com/dmcb-gist/MOMA. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Characterization of Kikuchi-Fujimoto Disease in Children and Risk Factors Associated with Its Course.

OBJECTIVE: To outline the characteristics of Kikuchi-Fujimoto disease (KFD) in children and analyze factors associated with severe and recurring courses. METHODS: Electronic medical records of children histopathologically diagnosed with KFD at Seoul National University Bundang Hospital from March 2015 to April 2021 were retrospectively reviewed. RESULTS: A total of 114 cases (62 males) were identified. The mean patient age was 12.0 ± 3.5 years. Most patients came to medical attention with cervical lymph node enlargement (97.4%) and fever (85%); 62% had a high-grade fever (≥39°C). Prolonged fever (≥14 days) was seen in 44.3% and was associated with a high-grade fever (P = .004). Splenomegaly, oral ulcer, or rash was present in 10.5%, 9.6%, and 15.8%, respectively. Laboratory findings showed leukopenia, anemia, and thrombocytopenia in 74.1%, 49%, and 24%, respectively. Sixty percent of cases had a self-limited course. Antibiotics were initially prescribed in 20%. A corticosteroid was prescribed in 40% of patients and was associated with oral ulcer (P = .045) and anemia (P = .025). Twelve patients (10.5%) had a recurrence with a median interval of 19 months. No risk factor for recurrence was identified in multivariable analysis. Clinical characteristics of KFD were similar between our current and previous studies. However, antibiotics use decreased (P < .001); nonsteroidal anti-inflammatory drugs use increased (P < .001), and, although statistically not significant, corticosteroid treatment also increased. CONCLUSIONS: Over a span of 18 years, the clinical characteristics of KFD did not change. Patients presenting with high-grade fever, oral ulcer, or anemia may benefit from corticosteroid intervention. All patients should be monitored for recurrence.

Inhibition of CDK4/6 regulates AD pathology, neuroinflammation and cognitive function through DYRK1A/STAT3 signaling.

Repurposing approved drugs is an emerging therapeutic development strategy for Alzheimer's disease (AD). The CDK4/6 inhibitor abemaciclib mesylate is an FDA-approved drug for breast cancer treatment. However, whether abemaciclib mesylate affects Aß/tau pathology, neuroinflammation, and Aß/LPS-mediated cognitive impairment is unknown. In this study, we investigated the effects of abemaciclib mesylate on cognitive function and Aß/tau pathology and found that abemaciclib mesylate improved spatial and recognition memory by regulating the dendritic spine number and neuroinflammatory responses in 5xFAD mice, an Aß-overexpressing model of AD. Abemaciclib mesylate also inhibited Aß accumulation by enhancing the activity and protein levels of the Aß-degrading enzyme neprilysin and the α-secretase ADAM17 and decreasing the protein level of the γ-secretase PS-1 in young and aged 5xFAD mice. Importantly, abemaciclib mesylate suppressed tau phosphorylation in 5xFAD mice and tau-overexpressing PS19 mice by reducing DYRK1A and/or p-GSK3ß levels. In wild-type (WT) mice injected with lipopolysaccharide (LPS), abemaciclib mesylate rescued spatial and recognition memory and restored dendritic spine number. In addition, abemaciclib mesylate downregulated LPS-induced microglial/astrocytic activation and proinflammatory cytokine levels in WT mice. In BV2 microglial cells and primary astrocytes, abemaciclib mesylate suppressed LPS-mediated proinflammatory cytokine levels by downregulating AKT/STAT3 signaling. Taken together, our results support repurposing the anticancer drug, CDK4/6 inhibitor abemaciclib mesylate as a multitarget therapeutic for AD pathologies.

Development of diagnostic tests for pathogen identification and detection of antimicrobial resistance on WHO global priority pathogens using modular real-time nucleic acid amplification test.

BACKGROUND: Concerns regarding antimicrobial resistance (AMR) have resulted in the World Health Organization (WHO) designating so-called global priority pathogens (GPPs). However, little discussion has focused on the diagnosis of GPPs. To enable the simultaneous identification of pathogens and AMR, we developed a modular real-time nucleic acid amplification test (MRT-NAAT). METHODS: Sequence-specific primers for each modular unit for MRT-NAAT pathogen identification and AMR sets were designed. The composition of the reaction mixture and the real-time PCR program were unified irrespective of primer type so to give MRT-NAAT modularity. Standard strains and clinical isolates were used to evaluate the performance of MRT-NAAT by real-time PCR and melting curve analysis. Probit analysis for the MRT-NAAT pathogen identification set was used to assess the limit of detection (LoD). RESULTS: The MRT-NAAT pathogen identification set was made up of 15 modular units 109-199 bp in product size and with a Tms of 75.5-87.5 °C. The LoD was < 15.548 fg/µL, and nine modular units successfully detected the target pathogens. The MRT-NAAT AMR set included 24 modular units 65-785 bp in product size with a Tms of 75.5-87.5 °C; it showed high performance for detecting GPP target genes and variants. CONCLUSIONS: MRT-NAAT enables pathogen identification and AMR gene detection and is time-effective. By unifying the reaction settings of each modular unit, the modularity where combinations of primers can be used according to need could be achieved. This would greatly help in reflecting the researcher's need and the AMR status of a certain region while successfully detecting pathogens and AMR genes.

Detecting amyloid-ß positivity using regions of interest from structural magnetic resonance imaging.

BACKGROUND AND PURPOSE: Alzheimer disease (AD) is the most common type of dementia. Amyloid-ß (Aß) positivity is the main diagnostic marker for AD. Aß positron emission tomography and cerebrospinal fluid are widely used in the clinical diagnosis of AD. However, these methods only assess the concentrations of Aß, and the accessibility of these methods is thus relatively limited compared with structural magnetic resonance imaging (sMRI). METHODS: We investigated whether regions of interest (ROIs) in sMRIs can be used to predict Aß positivity for samples with normal cognition (NC), mild cognitive impairment (MCI), and dementia. We obtained 846 Aß negative (Aß-) and 865 Aß positive (Aß+) samples from the Alzheimer's Disease Neuroimaging Initiative database. To predict which samples are Aß+, we built five machine learning models using ROIs and apolipoprotein E (APOE) genotypes as features. To test the performance of the machine learning models, we constructed a new cohort containing 97 Aß- and 81 Aß+ samples. RESULTS: The best performing machine learning model combining ROIs and APOE had an accuracy of 0.798, indicating that it can help predict Aß+. Furthermore, we searched ROIs that could aid our prediction and discovered that an average left entorhinal cortical region (L-ERC) thickness is an important feature. We also noted significant differences in L-ERC thickness between the Aß- and Aß+ samples even in the same diagnosis of NC, MCI, and dementia. CONCLUSIONS: Our findings indicate that ROIs from sMRIs along with APOE can be used as an initial screening tool in the early diagnosis of AD.

Acoustic Analysis of Speech for Screening for Suicide Risk: Machine Learning Classifiers for Between- and Within-Person Evaluation of Suicidality.

BACKGROUND: Assessing a patient's suicide risk is challenging for health professionals because it depends on voluntary disclosure by the patient and often has limited resources. The application of novel machine learning approaches to determine suicide risk has clinical utility. OBJECTIVE: This study aimed to investigate cross-sectional and longitudinal approaches to assess suicidality based on acoustic voice features of psychiatric patients using artificial intelligence. METHODS: We collected 348 voice recordings during clinical interviews of 104 patients diagnosed with mood disorders at baseline and 2, 4, 8, and 12 months after recruitment. Suicidality was assessed using the Beck Scale for Suicidal Ideation and suicidal behavior using the Columbia Suicide Severity Rating Scale. The acoustic features of the voice, including temporal, formal, and spectral features, were extracted from the recordings. A between-person classification model that examines the vocal characteristics of individuals cross sectionally to detect individuals at high risk for suicide and a within-person classification model that detects considerable worsening of suicidality based on changes in acoustic features within an individual were developed and compared. Internal validation was performed using 10-fold cross validation of audio data from baseline to 2-month and external validation was performed using data from 2 to 4 months. RESULTS: A combined set of 12 acoustic features and 3 demographic variables (age, sex, and past suicide attempts) were included in the single-layer artificial neural network for the between-person classification model. Furthermore, 13 acoustic features were included in the extreme gradient boosting machine learning algorithm for the within-person model. The between-person classifier was able to detect high suicidality with 69% accuracy (sensitivity 74%, specificity 62%, area under the receiver operating characteristic curve 0.62), whereas the within-person model was able to predict worsening suicidality over 2 months with 79% accuracy (sensitivity 68%, specificity 84%, area under receiver operating characteristic curve 0.67). The second model showed 62% accuracy in predicting increased suicidality in external sets. CONCLUSIONS: Within-person analysis using changes in acoustic features within an individual is a promising approach to detect increased suicidality. Automated analysis of voice can be used to support the real-time assessment of suicide risk in primary care or telemedicine.

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.

Risk Factors for Sudden Death Within 2 Days After Diagnosis of COVID-19 in Korea.

BACKGROUND: We aimed to analyze the risk factors for sudden death after diagnosis of coronavirus disease 2019 (COVID-19) in South Korea and to provide evidence for informing prevention and control interventions for patients at risk of sudden death. METHODS: We included 30,302 COVID-19 related deaths registered in the patient management information system (Central Disease Control Headquarters) between January 1, 2021, and December 15, 2022. We collected their epidemiological data recorded by the reporting city, province, or country. We performed multivariate logistic regression analysis to identify risk factors for sudden death after diagnosis of COVID-19. RESULTS: Among the 30,302 deaths, there were 7,258 (24.0%) and 23,044 (76.0%) sudden and non-sudden deaths, respectively. Sudden death means a person who died within 2 days of diagnosis and who did not receive inpatient treatment. Underlying condition, vaccination status, and place of death were significantly associated with the survival period in all age groups. Moreover, region, sex, and prescription were significantly associated with the survival period only in certain age groups. However, reinfection was not significantly associated with the survival period in any age group. CONCLUSION: To our knowledge, this is the first study on the risk factors for sudden death after a diagnosis of COVID-19, which included age, underlying condition, vaccination status, and place of death. Additionally, individuals aged < 60 years without an underlying condition were at high risk for sudden death. However, this group has relatively low interest in health, as can be seen from the high non-vaccination rate (16.1% of the general population vs. 61.6% of the corresponding group). Therefore, there is a possibility for the presence of an uncontrolled underlying disease in this population. In addition, many sudden deaths occurred due to delayed hospital visits to continue economic activities even after the onset of COVID-19 symptoms (7 days overall vs. 10 days average for the group). In conclusion, 'continued interest in health' is a key factor in avoiding sudden death in the economically active group (under 60 years of age).

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.

Pediatric Deaths Associated With Coronavirus Disease 2019 (COVID-19) in Korea.

As of September 3, 2022, 5,388,338 coronavirus disease 2019 (COVID-19) cases and 46 deaths (3 in 2021 and 43 in 2022) were reported in children ≤ 18 years in Korea. Cumulative confirmed cases accounted for 67.3% of the population aged ≤ 18 years and case fatality rate was 0.85/100,000. Among 46 fatal cases, 58.7% were male and median age was 7 years. Underlying diseases were present in 47.8%; neurologic diseases (63.6%) and malignancy (13.6%) most common. Only four had history of COVID-19 immunization. COVID-19 associated deaths occurred at median 2 days from diagnosis (range: -1 to 21). Among COVID-19 deaths, 41.3% occurred before admission; 2 before hospital arrival and 17 in the emergency department. Among children whose cause was documented, myocarditis, respiratory and multiorgan failure were most common. COVID-19 associated death was seen early after diagnosis in children and public health policies to provide access to medical care for children with COVID-19 are essential during the pandemic.

Twenty-Five Year Trend Change in the Etiology of Pediatric Invasive Bacterial Infections in Korea, 1996-2020.

BACKGROUND: The coronavirus disease-2019 (COVID-19) pandemic has contributed to the change in the epidemiology of many infectious diseases. This study aimed to establish the pre-pandemic epidemiology of pediatric invasive bacterial infection (IBI). METHODS: A retrospective multicenter-based surveillance for pediatric IBIs has been maintained from 1996 to 2020 in Korea. IBIs caused by eight bacteria (Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus pyogenes, Listeria monocytogenes, and Salmonella species) in immunocompetent children > 3 months of age were collected at 29 centers. The annual trend in the proportion of IBIs by each pathogen was analyzed. RESULTS: A total of 2,195 episodes were identified during the 25-year period between 1996 and 2020. S. pneumoniae (42.4%), S. aureus (22.1%), and Salmonella species (21.0%) were common in children 3 to 59 months of age. In children ≥ 5 years of age, S. aureus (58.1%), followed by Salmonella species (14.8%) and S. pneumoniae (12.2%) were common. Excluding the year 2020, there was a trend toward a decrease in the relative proportions of S. pneumoniae (rs = -0.430, P = 0.036), H. influenzae (rs = -0.922, P < 0.001), while trend toward an increase in the relative proportion of S. aureus (rs = 0.850, P < 0.001), S. agalactiae (rs = 0.615, P = 0.001), and S. pyogenes (rs = 0.554, P = 0.005). CONCLUSION: In the proportion of IBIs over a 24-year period between 1996 and 2019, we observed a decreasing trend for S. pneumoniae and H. influenzae and an increasing trend for S. aureus, S. agalactiae, and S. pyogenes in children > 3 months of age. These findings can be used as the baseline data to navigate the trend in the epidemiology of pediatric IBI in the post COVID-19 era.

A Study on Optimization of Noise Reduction of Powered Vehicle Seat Movement Using Brushless Direct-Current Motor.

In this paper, an optimal design model was developed to reduce noise and secure the torque performance of a brushless direct-current motor used in the seat of an autonomous vehicle. An acoustic model using finite elements was developed and verified through the noise test of the brushless direct-current motor. In order to reduce noise in the brushless direct-current motor and obtain a reliable optimization geometry of noiseless seat motion, parametric analysis was performed through the design of experiments and Monte Carlo statistical analysis. The slot depth, stator tooth width, slot opening, radial depth, and undercut angle of the brushless direct-current motor were selected as design parameters for design parameter analysis. Then, a non-linear prediction model was used to determine the optimal slot depth and stator tooth width to maintain the drive torque and minimize the sound pressure level at 23.26 dB or lower. The Monte Carlo statistical method was used to minimize the deviation of the sound pressure level caused by the production deviation of the design parameters. The result is that the SPL was 23.00-23.50 dB with a confidence level of approximately 99.76% when the level of production quality control was set at 3σ.

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.