Objectives: Severe mental illness has become one of the leading concerns for the cost of health services. This study analyzed the demographic characteristics and compared the patterns of medical health service use according to the diagnosis of severe mental illness, including schizophrenia spectrum disease, bipolar disease, and major depressive disorder. Methods: The data from the National Health Insurance Corporation were analyzed, selecting subjects diagnosed at least once for severe mental illness between 2014 and 2019. Severe mental illness included the following: schizophrenia, schizotypal, and delusional disorders (F20– 29); manic episodes and bipolar affective disorder (F30–31); and moderate depressive episodes with psychotic features and recurrent depressive disorder (F32.3–F33). The demographic factors and patterns of medical services, such as outpatient, hospitalization, and re-admission differences, were compared according to the diagnostic categories. Results: This study included 842459 patients, with 39.6% people in F20–F29, 33.7% in F32.3– F33, and 26.8% in the F30–F31 category. There were significant differences in gender, age, insurance type, Charlson Comorbidity Index score, and economic level according to the diagnostic categories. The engagement of medical health services also showed significant differences among the diagnostic categories. F32.3–F33 showed higher engagement of outpatients than the out-groups, while F20–F29 showed a higher admission rate. The hospitalization duration was significantly longer in F20–F29, and the re-admission rate after discharge within one year was significantly higher in the same group. Conclusion This paper reviewed the differences in medical care utilization among severe mental illness. The result emphasizes the need for a mental health care system broadening to the community, facilitating psychosocial intervention, and case management.

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.

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.