Identification of 3 key genes as novel diagnostic and therapeutic targets for OA and COVID-19.

Background: Corona Virus Disease 2019 (COVID-19) and Osteoarthritis (OA) are diseases that seriously affect the physical and mental health and life quality of patients, particularly elderly patients. However, the association between COVID-19 and osteoarthritis at the genetic level has not been investigated. This study is intended to analyze the pathogenesis shared by OA and COVID-19 and to identify drugs that could be used to treat SARS-CoV-2-infected OA patients. Methods: The four datasets of OA and COVID-19 (GSE114007, GSE55235, GSE147507, and GSE17111) used for the analysis in this paper were obtained from the GEO database. Common genes of OA and COVID-19 were identified through Weighted Gene Co-Expression Network Analysis (WGCNA) and differential gene expression analysis. The least absolute shrinkage and selection operator (LASSO) algorithm was used to screen key genes, which were analyzed for expression patterns by single-cell analysis. Finally, drug prediction and molecular docking were carried out using the Drug Signatures Database (DSigDB) and AutoDockTools. Results: Firstly, WGCNA identified a total of 26 genes common between OA and COVID-19, and functional analysis of the common genes revealed the common pathological processes and molecular changes between OA and COVID-19 are mainly related to immune dysfunction. In addition, we screened 3 key genes, DDIT3, MAFF, and PNRC1, and uncovered that key genes are possibly involved in the pathogenesis of OA and COVID-19 through high expression in neutrophils. Finally, we established a regulatory network of common genes between OA and COVID-19, and the free energy of binding estimation was used to identify suitable medicines for the treatment of OA patients infected with SARS-CoV-2. Conclusion: In the present study, we succeeded in identifying 3 key genes, DDIT3, MAFF, and PNRC1, which are possibly involved in the development of both OA and COVID-19 and have high diagnostic value for OA and COVID-19. In addition, niclosamide, ciclopirox, and ticlopidine were found to be potentially useful for the treatment of OA patients infected with SARS-CoV-2.

Emerging Role of Neutrophil Extracellular Traps in Gastrointestinal Tumors: A Narrative Review.

Neutrophil extracellular traps (NETs) are extracellular fibrous networks consisting of depolymerized chromatin DNA skeletons with a variety of antimicrobial proteins. They are secreted by activated neutrophils and play key roles in host defense and immune responses. Gastrointestinal (GI) malignancies are globally known for their high mortality and morbidity. Increasing research suggests that NETs contribute to the progression and metastasis of digestive tract tumors, among them gastric, colon, liver, and pancreatic cancers. This article explores the formation of NETs and reviews the role that NETs play in the gastrointestinal oncologic microenvironment, tumor proliferation and metastasis, tumor-related thrombosis, and surgical stress. At the same time, we analyze the qualitative and quantitative detection methods of NETs in recent years and found that NETs are specific markers of coronavirus disease 2019 (COVID-19). Then, we explore the possibility of NET inhibitors for the treatment of digestive tract tumor diseases to provide a new, efficient, and safe solution for the future therapy of gastrointestinal tumors.

Modeling the Impact of Nonpharmaceutical Interventions on COVID-19 Transmission in K-12 Schools.

Background. The novel coronavirus SARS-CoV-2 spread across the world causing many waves of COVID-19. Children were at high risk of being exposed to the disease because they were not eligible for vaccination during the first 20 mo of the pandemic in the United States. While children 5 y and older are now eligible to receive a COVID-19 vaccine in the United States, vaccination rates remain low despite most schools returning to in-person instruction. Nonpharmaceutical interventions (NPIs) are important for controlling the spread of COVID-19 in K-12 schools. US school districts used varied and layered mitigation strategies during the pandemic. The goal of this article is to analyze the impact of different NPIs on COVID-19 transmission within K-12 schools. Methods. We developed a deterministic stratified SEIR model that captures the role of social contacts between cohorts in disease transmission to estimate COVID-19 incidence under different NPIs including masks, random screening, contact reduction, school closures, and test-to-stay. We designed contact matrices to simulate the contact patterns between students and teachers within schools. We estimated the proportion of susceptible infected associated with each intervention over 1 semester under the Omicron variant. Results. We find that masks and reducing contacts can greatly reduce new infections among students. Weekly screening tests also have a positive impact on disease mitigation. While self-quarantining symptomatic infections and school closures are effective measures for decreasing semester-end infections, they increase absenteeism. Conclusion. The model provides a useful tool for evaluating the impact of a variety of NPIs on disease transmission in K-12 schools. While the model is tested under Omicron variant parameters in US K-12 schools, it can be adapted to study other populations under different disease settings. Highlights: A stratified SEIR model was developed that captures the role of social contacts in K-12 schools to estimate COVID-19 transmission under different nonpharmaceutical interventions.While masks, random screening, contact reduction, school closures, and test-to-stay are all beneficial interventions, masks and contact reduction resulted in the greatest reduction in new infections among students from the tested scenarios.Layered interventions provide more benefits than implementing interventions independently.

Social work self-care education informed during the pandemic: Experience, reflection, and suggestion

During the coronavirus pandemic, self-care practice was more than ever underscored for social work students as they have encountered increasing stress in their personal life, schoolwork, and professional practice. These stressors have been interweaved with social problems, further increasing the pressure on them. For social work educators, this situation highlights the necessity of developing students? self-care competency. This brief note reflects upon the challenges we face in integrating self-care components in social policy courses since the outbreak of the pandemic and suggests that social work self-care education can be broadened in terms of purpose, scope, and content in the future.

Nanoparticle encapsulation of non-genotoxic p53 activator Inauhzin-C for improved therapeutic efficacy.

The tumor suppressor protein p53 remains in a wild type but inactive form in ~50% of all human cancers. Thus, activating it becomes an attractive approach for targeted cancer therapies. In this regard, our lab has previously discovered a small molecule, Inauhzin (INZ), as a potent p53 activator with no genotoxicity. Method: To improve its efficacy and bioavailability, here we employed nanoparticle encapsulation, making INZ-C, an analog of INZ, to nanoparticle-encapsulated INZ-C (n-INZ-C). Results: This approach significantly improved p53 activation and inhibition of lung and colorectal cancer cell growth by n-INZ-C in vitro and in vivo while it displayed a minimal effect on normal human Wi38 and mouse MEF cells. The improved activity was further corroborated with the enhanced cellular uptake observed in cancer cells and minimal cellular uptake observed in normal cells. In vivo pharmacokinetic evaluation of these nanoparticles showed that the nanoparticle encapsulation prolongates the half-life of INZ-C from 2.5 h to 5 h in mice. Conclusions: These results demonstrate that we have established a nanoparticle system that could enhance the bioavailability and efficacy of INZ-C as a potential anti-cancer therapeutic.

The Impacts of Perceived Risks on Information Search and Risk Reduction Strategies: A Study of the Hotel Industry during the COVID-19 Pandemic

This study examined the impacts of perceived risks on information search and risk reduction strategies as well as the relative importance of each risk reduction strategy. Multiple regression analysis was applied to analyze the sample of South Korean hotel customers and to test the hypotheses of the study. It was found that when hotel customers faced the same kind of risk, they adopted different information search strategies to reduce various risks during the COVID-19 pandemic. Moreover, ‘following hotel employee’s advice’ was perceived to be the most important information search strategy to reduce risks. This is the first study to compare the differences of perceived risk and information search strategies under the COVID-19 pandemic and normal conditions to help hotels to develop more effective strategies to recover from the pandemic. The results of the study should be interpreted with care since it was based on Korean hotel customers. The influence of cultural differences in perceived risk and information search strategy should be addressed in future studies. The study contributes to the tourism and hospitality information search and risk reduction strategy-related literature and recommends avenues for further research in the field.

Early vs. Late Onset Cardiac Injury and Mortality in Hospitalized COVID-19 Patients in Wuhan.

Background: Increasing evidence points to cardiac injury (CI) as a common coronavirus disease 2019 (COVID-19) related complication. The characteristics of early CI (occurred within 72 h of admission) and late CI (occurred after 72 h of admission) and its association with mortality in COVID-19 patients is unknown. Methods: This retrospective study analyzed patients confirmed with COVID-19 in Union Hospital (Wuhan, China) from Jan 29th to Mar 15th, 2020. Clinical outcomes (discharge, or death) were monitored to April 15, 2020, the latest date of follow-up. Demographic, clinical, laboratory, as well as treatment and prognosis were collected and analyzed in patients with early, late CI and without CI. Results: A total of 196 COVID-19 patients were included for analysis. The median age was 65 years [interquartile range (IQR) 56-73 years], and 112 (57.1%) were male. Of the 196 COVID-19 patients, 49 (25.0%) patients had early and 20 (10.2%) patients had late CI, 56.6% developed Acute-Respiratory-Distress-Syndrome (ARDS) and 43 (21.9%) patients died. Patients with any CI were more likely to have developed ARDS (87.0 vs. 40.2%) and had a higher in-hospital mortality than those without (52.2 vs. 5.5%, P < 0.001). Among CI subtypes, a significantly higher risk of in-hospital death was found in patients with early CI with recurrence [19/49 patients, adjusted odds ratio (OR) = 7.184, 95% CI 1.472-35.071] and patients with late CI (adjusted OR = 5.019, 95% CI 1.125-22.388) compared to patients with early CI but no recurrence. Conclusions: CI can occur early on or late after, the initial 72 h of admission and is associated with ARDS and an increased risk of in-hospital mortality. Both late CI and recurrent CI after the initial episode were associated with worse outcomes than patients with early CI alone. This study highlights the importance of early examination and periodical monitoring of cardiac biomarkers, especially for patients with early CI or at risk of clinical deterioration.

Prognostic Value of Right Ventricular Ejection Fraction Assessed by 3D Echocardiography in COVID-19 Patients.

Background: RVEF (right ventricular ejection fraction) measured by three-dimensional echocardiography (3DE) has been used in evaluating right ventricular (RV) function and can provide useful prognostic information in other various cardiovascular diseases. However, the prognostic value of 3D-RVEF in coronavirus disease 2019 (COVID-19) remains unknown. We aimed to investigate whether 3D-RVEF can predict the mortality of COVID-19 patients. Methods: A cohort of 128 COVID-19-confirmed patients who had undergone echocardiography were studied. Thirty-one healthy volunteers were also enrolled as controls. COVID-19 patients were divided into three subgroups (general, severe, and critical) according to COVID-19 severity-of-illness. Conventional RV structure and function parameters, RV free wall longitudinal strain (FWLS) and 3D-RVEF were acquired. RVFWLS was measured by two-dimensional speckle tracking echocardiography. RVEF was acquired by 3DE. Results: Compared with controls, 2D-RVFWLS and 3D-RVEF were both significantly decreased in COVID-19 patients (-27.2 ± 4.4% vs. -22.9 ± 4.8%, P < 0.001; 53.7 ± 4.5% vs. 48.5 ± 5.8%, P < 0.001). Critical patients were more likely to have a higher incidence of acute cardiac injury and acute respiratory distress syndrome (ARDS), and worse prognosis than general and severe patients. The critical patients exhibited larger right-heart chambers, worse RV fractional area change (RVFAC), 2D-RVFWLS, and 3D-RVEF and higher proportion of pulmonary hypertension than general and severe patients. Eighteen patients died during a median follow-up of 91 days. The multivariate Cox regression analysis revealed the acute cardiac injury, ARDS, RVFAC, RVFWLS, and 3D-RVEF were independent predictors of death. 3D-RVEF (chi-square to improve 18.3; P < 0.001), RVFAC (chi-square to improve 4.5; P = 0.034) and 2D-RVFWLS (chi-square to improve 5.1; P = 0.024) all provided additional prognostic value of higher mortality over clinical risk factors. Moreover, the incremental predictive value of 3D-RVEF was significantly (P < 0.05) higher than RVFAC and RVFWLS. Conclusion: 3D-RVEF was the most robust independent predictor of mortality in COVID-19 patients and provided a higher predictive value over conventional RV function parameters and RVFWLS, which may be helpful to identify COVID-19 patients at a higher risk of death.