ABSTRACT
Nosocomial coronavirus disease 2019 (COVID-19) outbreaks have been reported despite widespread quarantine methods to prevent COVID-19 in society and hospitals. Our study was performed to investigate the clinical outcome and prognosis of a nosocomial outbreak of COVID-19. We retrospectively analyzed the medical records of patients diagnosed with nosocomial COVID-19 of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) at a university teaching hospital between 1 November 2021 and 31 April 2022. Nosocomial COVID-19 was defined as a positive SARS-CoV-2 polymerase chain reaction (PCR) test result 4 or more days after admission in asymptomatic patients who had a negative SARS-CoV-2 PCR test on admission. In this study, 167 patients were diagnosed with nosocomial COVID-19 (1.14%) among a total of 14,667 patients admitted to hospital during the study period. A total of 153 patients (91.6%) survived, but 14 patients (8.4%) died. The median time between admission and COVID-19 diagnosis was 11 days, and the median duration of hospital stay was 24 days. After adjusting for other factors, no vaccination (adjusted HR = 5.944, 95% CI = 1.626-21.733, p = 0.007) and chronic kidney disease (adjusted HR = 6.963, 95% CI = 1.182-41.014, p = 0.032) were found to increase mortality risk. Despite strict quarantine, a significant number of nosocomial COVID-19 cases with a relatively high mortality rate were reported. As unvaccinated status or chronic kidney disease were associated with poor outcomes of nosocomial COVID-19, more active preventive strategies and treatments for patients with these risk factors are needed.
ABSTRACT
Due to the COVID-19 pandemic and industrialized food systems, people's eating behavior has become seriously restricted. Especially, university students have started to overly depend on processed foods and carnivorous diets, and it places a huge burden on society by inducing the deterioration of health and environmental sustainability. Therefore, this study was undertaken to examine the effects of university students' perceived food literacy on ecological eating behavior towards sustainability. A total of 395 university students in South Korea participated in this research. First, students' food literacy components, which are reading labels and budgeting, healthy snack styles, healthy food stockpiling and resilience and resistance, exert positive influences on ecological eating behavior;second, the other two components, which are food preparation skills and social and conscious eating, have no positive impact on ecological eating behavior. Finally, the influences of food literacy on ecological behavior are significantly moderated by gender differences. This suggests that strengthening university students' food literacy through education is necessary to promote ecological eating behaviors and advance the development of sustainable society.
ABSTRACT
The importance of protein engineering in the research and development of biopharmaceuticals and biomaterials has increased. Machine learning in computer-aided protein engineering can markedly reduce the experimental effort in identifying optimal sequences that satisfy the desired properties from a large number of possible protein sequences. To develop general protein descriptors for computer-aided protein engineering tasks, we devised new protein descriptors, one sequence-based descriptor (PCgrades), and three structure-based descriptors (PCspairs, 3D-SPIEs_5.4 Å, and 3D-SPIEs_8Å). While the PCgrades and PCspairs include general and statistical information in physicochemical properties in single and pairwise amino acids respectively, the 3D-SPIEs include specific and quantum-mechanical information with parameterized quantum mechanical calculations (FMO2-DFTB3/D/PCM). To evaluate the protein descriptors, we made prediction models with the new descriptors and previously developed descriptors for diverse protein datasets including protein expression and binding affinity change in SARS-CoV-2 spike glycoprotein. As a result, the newly devised descriptors showed a good performance in diverse datasets, in which the PCspairs showed the best performance ( R 2 = 0.783 for protein expression and R 2 = 0.711 for binding affinity). As a result, the newly devised descriptors showed a good performance in diverse datasets, in which the PCspairs showed the best performance. Similar approaches with those descriptors would be promising and useful if the prediction models are trained with sufficient quantitative experimental data from high-throughput assays for industrial enzymes or protein drugs.
ABSTRACT
BACKGROUND: We would evaluate the epidemiology, clinical aspects, and prognostic factors of patients of all ages admitted with human corona virus (HCoV). METHODS: This study was retrospectively performed at five university teaching hospitals between 1st January 2018 and 31th March 2020. Routine molecular testing using for multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) methods was conducted on the respiratory viruses. We assessed the demographics, laboratory findings, and treatment of patients infected with coronavirus. RESULTS: There were 807 coronavirus-infected patients from 24,311 patients with respiratory virus PCR test admitted to five hospitals over 27 months. All-cause mortality rates of patients admitted for seasonal HCoV disease were 3.1% in all patients and 10.8% in patients aged ≥18 years. The Cox proportional hazard regression analysis was performed in patients aged ≥18 years. After adjusting for other clinical variables, general weakness symptoms [hazard ratio (HR), 2.651; 95% confidence interval (CI), 1.147-6.125, P=0.023], National Early Warning Score (NEWS) ≥2 (HR, 5.485; 95% CI, 1.261-23.858, P=0.023), and coronavirus subtype OC43 (HR, 2.500; 95% CI, 1.060-5.897, P=0.036) were significantly associated with death from coronavirus. CONCLUSIONS: Coronavirus infection can reveal a higher mortality rate in patients of ≥18 than those of <18 years, thus, adult patients require more careful treatment. Furthermore, in adult patients, the factors associated with death from coronavirus include general weakness symptoms, NEWS higher than 2, and OC43 subtype.
ABSTRACT
BACKGROUND: The COVID-19 pandemic is predicted to significantly affect patients with lung cancer, owing to its rapid progression and high mortality. Studies on lung cancer diagnosis and treatment during an epidemic are lacking. We analyzed the impact of COVID-19 on lung cancer diagnosis in Korea, where lung cancer incidence continues to rise. METHODS: The number of newly diagnosed lung cancer cases in three university-affiliated hospitals during the pandemic and their clinical features were compared with lung cancer cases diagnosed during the same period in the past 3 years. The effectiveness of measures taken by the study hospitals to prevent nosocomial transmission was reviewed. RESULTS: A total of 612 patients were diagnosed with lung cancer from February through June, 2017-2020. During the pandemic, the number of patients who sought consultation at the division of pulmonology of study hospitals dropped by 16% from the previous year. Responding to the pandemic, the involved hospitals created physically isolated triage areas for patients with acute respiratory infection symptoms. Wide-range screening and preventive measures were implemented, thus minimizing the delay in lung cancer diagnosis. No patient acquired COVID-19 due to hospital exposure. The proportion of patients with stage III-IV non-small-cell lung cancer (NSCLC) significantly increased (2020: 74.7% vs. 2017: 57.9%, 2018: 66.7%, 2019: 62.7%, p = 0.011). The number of lung cancers diagnosed during this period and the previous year remained the same. CONCLUSIONS: The proportion of patients with advanced NSCLC increased during the COVID-19 pandemic.