Complement component 3 glomerulonephritis (C3GN) is a rare kidney disease characterized by complement dysregulation that results in prominent complement component 3 (C3) deposition in the kidneys. The clinical course of C3GN varies from mild hematuria to progressive chronic kidney disease. In most patients, C3GN is driven by acquired factors, namely, autoantibodies that target C3 or C5 convertases. Genetic variations in complement-related genes are less frequent. We report the case of a 9-yearold Korean boy who presented with microscopic hematuria and a persistently low C3 level and had biopsy findings of C3GN, with the presence of a C3 gene mutation: a frameshift mutation associated with C3 deficiency. However, the patient did not exhibit any other symptoms of complement deficiency. Direct DNA sequencing of his family members revealed the same genetic mutation in his father and older brother. This case report is significant because there are very few such reports worldwide concerning gene mutations related to C3 deficiency to be discovered in patients with C3GN. Explaining C3GN pathogenesis is challenging; therefore, additional research is required in the future.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019.In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virusinfected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Cytomegalovirus (CMV) is the most important opportunistic viral pathogen in solid organ transplant (SOT) recipients.The Korean guideline for the prevention of CMV infection in SOT recipients was developed jointly by the Korean Society for Infectious Diseases and the Korean Society of Transplantation. CMV serostatus of both donors and recipients should be screened before transplantation to best assess the risk of CMV infection after SOT. Seronegative recipients receiving organs from seropositive donors face the highest risk, followed by seropositive recipients. Either antiviral prophylaxis or preemptive therapy can be used to prevent CMV infection. While both strategies have been demonstrated to prevent CMV infection post-transplant, each has its own advantages and disadvantages. CMV serostatus, transplant organ, other risk factors, and practical issues should be considered for the selection of preventive measures. There is no universal viral load threshold to guide treatment in preemptive therapy. Each institution should define and validate its own threshold.Valganciclovir is the favored agent for both prophylaxis and preemptive therapy. The evaluation of CMV-specific cellmediated immunity and the monitoring of viral load kinetics are gaining interest, but there was insufficient evidence to issue recommendations. Specific considerations on pediatric transplant recipients are included.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Background: We aimed to analyze the effects of an antimicrobial stewardship program (ASP) on the proportion of antimicrobial-resistant pathogens in bacteremia, antimicrobial use, and mortality in pediatric patients. Methods: A retrospective single-center study was performed on pediatric inpatients under 19 years old who received systemic antimicrobial treatment from 2001 to 2019. A pediatric infectious disease attending physician started ASP in January 2008. The study period was divided into the pre-intervention (2001–2008) and the post-intervention (2009–2019) periods. The amount of antimicrobial use was defined as days of therapy per 1,000 patientdays, and the differences were compared using delta slope (= changes in slopes) between the two study periods by an interrupted time-series analysis. The proportion of resistant pathogens and the 30-day overall mortality rate were analyzed by the χ2 . Results: The proportion of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae bacteremia increased from 17% (39 of 235) in the pre-intervention period to 35% (189 of 533) in the post-intervention period (P < 0.001). The total amount of antimicrobial use significantly decreased after the introduction of ASP (delta slope value = −16.5; 95% confidence interval [CI], −30.6 to −2.3; P = 0.049). The 30-day overall mortality rate in patients with bacteremia did not increase, being 10% (55 of 564) in the pre-intervention and 10% (94 of 941) in the post-intervention period (P = 0.881). Conclusion The introduction of ASP for pediatric patients reduced the delta slope of the total antimicrobial use without increasing the mortality rate despite an increased incidence of ESBL-producing gram-negative bacteremia.