Purpose: Renal tumors account for approximately 7% of all childhood cancers. These include Wilms tumor (WT), clear cell sarcoma of the kidney (CCSK), malignant rhabdoid tumor of the kidney (MRTK), renal cell carcinoma (RCC), congenital mesoblastic nephroma (CMN) and other rare tumors. We investigated the epidemiology of pediatric renal tumors in Korea. Materials and Methods: From January 2001 to December 2015, data of pediatric patients (0–18 years) newly-diagnosed with renal tumors at 26 hospitals were retrospectively analyzed. Results: Among 439 patients (male, 240), the most common tumor was WT (n=342, 77.9%), followed by RCC (n=36, 8.2%), CCSK (n=24, 5.5%), MRTK (n=16, 3.6%), CMN (n=12, 2.7%), and others (n=9, 2.1%). Median age at diagnosis was 27.1 months (range 0-225.5) and median follow-up duration was 88.5 months (range 0-211.6). Overall, 32 patients died, of whom 17, 11, 1, and 3 died of relapse, progressive disease, second malignant neoplasm, and treatment-related mortality. Five-year overall survival and event free survival were 97.2% and 84.8% in WT, 90.6% and 82.1% in RCC, 81.1% and 63.6% in CCSK, 60.3% and 56.2% in MRTK, and 100% and 91.7% in CMN, respectively (p < 0.001). Conclusion The pediatric renal tumor types in Korea are similar to those previously reported in other countries. WT accounted for a large proportion and survival was excellent. Non-Wilms renal tumors included a variety of tumors and showed inferior outcome, especially MRTK. Further efforts are necessary to optimize the treatment and analyze the genetic characteristics of pediatric renal tumors in Korea.

Kidney organoids derived from human pluripotent stem cells (hPSCs) contain multilineage nephrogenic progenitor cells and can recapitulate the development of the kidney. Kidney organoids derived from hPSCs have the potential to be applied in regenerative medicine as well as renal disease modeling, drug screening, and nephrotoxicity testing. Despite biotechnological advances, individual differences in morphological and growth characteristics among kidney organoids need to be addressed before clinical and commercial application. In this study, we hypothesized that an automated noninvasive method based on deep learning of bright-field images of kidney organoids can predict their differentiation status. Methods: Bright-field images of kidney organoids were collected on day 18 after differentiation. To train convolutional neural networks (CNNs), we utilized a transfer learning approach. CNNs were trained to predict the differentiation of kidney organoids on bright-field images based on the messenger RNA expression of renal tubular epithelial cells as well as podocytes. Results: The best prediction model was DenseNet121 with a total Pearson correlation coefficient score of 0.783 on a test dataset. W classified the kidney organoids into two categories: organoids with above-average gene expression (Positive) and those with below-average gene expression (Negative). Comparing the best-performing CNN with human-based classifiers, the CNN algorithm had a receiver operating characteristic-area under the curve (AUC) score of 0.85, while the experts had an AUC score of 0.48. Conclusion: These results confirmed our original hypothesis and demonstrated that our artificial intelligence algorithm can successfully recognize the differentiation status of kidney organoids.

Background: Since the global coronavirus disease 2019 (COVID-19) pandemic, nonpharmacological interventions (NPIs) such as extensive and comprehensive hand hygiene, mask-wearing, and social distancing have been implemented globally. This study aimed to investigate changes in respiratory viruses other than severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that occurred following the implementation of these NPIs. Methods: From January 2018 to December 2021, influenza-like illness patient specimens and specimens from the Korea Influenza and Respiratory Viruses Surveillance System were analyzed at the Incheon Metropolitan City Institute of Public Health and Environment.Oropharyngeal or nasopharyngeal swab samples from respiratory infection patients were transferred in a virus transport medium at 4°C. After RNA or DNA extraction, respiratory virus-specific genes for human influenza virus (IFV), adenovirus (ADV), parainfluenza virus (PIV), respiratory syncytial virus (RSV), human rhinovirus (hRV), human coronavirus, human bocavirus, and human metapneumovirus were detected by individual real-time reverse transcription polymerase chain reaction. Results: A total 3,334 samples were collected. After NPI was implemented, the detection of respiratory viruses other than SARS-CoV-2 decreased overall. The yearly detection rate of respiratory viruses was decreased from 69.5% (399/574) in 2018 and 73.3% (505/689) in 2019 to 19.8% (206/1,043) in 2020 and 34.9% (365/1,028) in 2021. The epidemic was more prominent in respiratory viruses such as IFV and RSV, which were considered dominant viruses, especially those with viral envelopes. Among viruses that were not considered dominant, hRV showed no clear change before and after NPI, while PIV showed a rapid increase compared to the existing dominant viruses between October–December 2021, after the increase in the number of gatherings started at the end of September and the “Relaxing COVID19 and mitigation policy,” which was implemented on November 1. Conclusion NPI seems to have influenced the isolation and transmission of respiratory viruses in South Korea. In the future, additional studies focusing on the isolation and transmission patterns of respiratory viruses following NPI are needed.

Background: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.

We report a 61-year-old woman with clinical course for Alzheimer’s disease (AD) dementia and discordant amyloid-β positron-emission tomography (PET) and cerebrospinal fluid biomarkers. Brain magnetic resonance imaging revealed remarkable atrophy in the hippocampus. However, repeated delayed 18F-flutemetamol brain amyloid PET images with 1 year-interval revealed no amyloid deposition, whereas her CSF revealed low Aβ42, high total tau and p-tau181. This discordant amyloid-β PET and CSF biomarkers in this early-onset AD dementia might be associated with her low resilience or mixed pathology.

We report a 61-year-old woman with clinical course for Alzheimer’s disease (AD) dementia and discordant amyloid-β positron-emission tomography (PET) and cerebrospinal fluid biomarkers. Brain magnetic resonance imaging revealed remarkable atrophy in the hippocampus. However, repeated delayed 18F-flutemetamol brain amyloid PET images with 1 year-interval revealed no amyloid deposition, whereas her CSF revealed low Aβ42, high total tau and p-tau181. This discordant amyloid-β PET and CSF biomarkers in this early-onset AD dementia might be associated with her low resilience or mixed pathology.

Background/Aims: Tacrolimus has been used as an immunosuppressive agent in organ transplantation. Despite the therapeutic benefits, tacrolimus’s use is limited due to its nephrotoxicity. To reduce tacrolimus nephrotoxicity, effective humanized experimental models may be helpful. Here, we modeled tacrolimus nephrotoxicity using kidney organoids derived from human inducible pluripotent stem cells (iPSCs) in vitro. Methods: Kidney organoids were differentiated from the CMC11 iPSC cell line, re-seeded in 96-well plates, and treated with tacrolimus at doses of 0, 30, or 60 μM for 24 hours. This in vitro model was compared to a mouse model of tacrolimus nephrotoxicity and the associated mechanisms were investigated. Results: The size of the kidney organoids and cell viability decreased in dose-dependent manners after treatment with tacrolimus. The number of tubular cells decreased with a loss of polarity, similar to the effects seen in mouse tacrolimus nephrotoxicity. Ultrastructural analysis showed numerous vacuoles in the proximal tubular cells of the kidney organoids treated with tacrolimus. Tacrolimus treatment induced oxidative stress and mitochondrial dysfunction, and autophagic activity was enhanced in the kidney organoids. Rapamycin, an autophagy inducer, accelerated cell death in the kidney organoid model of tacrolimus nephrotoxicity, which was attenuated by treatment with 3-methyladenine, an autophagy inhibitor. These findings indicate that the augmentation of autophagy by rapamycin treatment accelerated tacrolimus nephrotoxicity. Conclusions Our data suggest that human kidney organoids are an effective in vitro model of tacrolimus nephrotoxicity and that autophagy plays a critical role in tacrolimus nephrotoxicity.

While recently extending that research, however, the authors discovered that 236 members of the general population were mistakenly to be duplicated by the investigating agency (Word Research) and 1,241 were reported rather than 1,005. The authors present corrections and discuss the relevant data. The authors wish to apologize to the publisher and readers of Journal of Korean Medical Science for these errors.

A granular cell tumor (GCT) is a relatively rare benign tumor that has been seldom reported since Abrikossoff first described it as a granular cell myoblastoma in 1926. While GCTs can occur anywhere in the human body, they are very rarely observed in the gastrointestinal tract and are especially rare in the large intestine. Most GCTs are small and asymptomatic and are often found by endoscopy, upper gastrointestinal series, and autopsy. We report two cases in which a submucosal tumor in the cecum was accidentally discovered by colonoscopy and was subsequently removed by colon polypectomy and endoscopic mucosal resection. Immunohistochemical analysis of the samples confirmed both cases as GCT. The literature review and reports of other growths in the gastrointestinal tracts support the necessity for proper identification of GCTs within the body to differentiate them from more malignant tumors.

A granular cell tumor (GCT) is a relatively rare benign tumor that has been seldom reported since Abrikossoff first described it as a granular cell myoblastoma in 1926. While GCTs can occur anywhere in the human body, they are very rarely observed in the gastrointestinal tract and are especially rare in the large intestine. Most GCTs are small and asymptomatic and are often found by endoscopy, upper gastrointestinal series, and autopsy. We report two cases in which a submucosal tumor in the cecum was accidentally discovered by colonoscopy and was subsequently removed by colon polypectomy and endoscopic mucosal resection. Immunohistochemical analysis of the samples confirmed both cases as GCT. The literature review and reports of other growths in the gastrointestinal tracts support the necessity for proper identification of GCTs within the body to differentiate them from more malignant tumors.