Mediating effect of resilience and fear of COVID-19 on the relationship between social support and post-traumatic stress disorder among campus-quarantined nursing students: a cross-sectional study.

BACKGROUND: The emergency of Omicron variants, spreading in China and worldwide, has sparked a new wave of the coronavirus disease 2019 (COVID-19) pandemic. The high infectivity and persistence of the pandemic may trigger some degrees of post-traumatic stress disorder (PTSD) for nursing students experiencing indirect trauma exposure to the epidemic, which hinders the role transition from students to qualified nurses and exacerbates the health workforce shortage. Thus, it's well worth an exploration to understand PTSD and its underlying mechanism. Specifically, PTSD, social support, resilience, and fear of COVID-19 were selected after widely literature review. This study aimed to investigate the relationship between social support and PTSD among nursing students during COVID-19, to address the mediating role of resilience and fear of COVID-19 between social support and PTSD, and to provide practical guidance for nursing students' psychological intervention. METHODS: From April 26 to April 30, 2022, 966 nursing students from Wannan Medical College were selected by the multistage sampling method to fill the Primary Care PTSD Screen for the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), Brief Resilience Scale, Fear of COVID-19 Scale, and Oslo 3 Items Social Support Scale. Data were analyzed by descriptive statistics, spearman's correlation analysis, regression analysis, and path analysis. RESULTS: 15.42% of nursing students had PTSD. There were significant correlations between social support, resilience, fear of COVID-19, and PTSD (r =-0.291 ~ 0.353, P <0.001). Social support had a direct negative effect on PTSD (ß =-0.216; 95% confidence interval, CI: -0.309~-0.117), accounting for 72.48% of the total effect. Analysis of mediating effects revealed that social support influenced PTSD through three indirect pathways: the mediated effect of resilience was statistically significant (ß =-0.053; 95% CI: -0.077~-0.031), accounting for 17.79% of the total effect; the mediated effect of fear of COVID-19 was statistically significant (ß =-0.016; 95% CI: -0.031~-0.003), accounting for 5.37% of the total effect; the chain mediating effect of resilience and fear of COVID-19 was statistically significant (ß =-0.013; 95% CI: -0.022~-0.006), accounting for 4.36% of the total effect. CONCLUSION: The social support of nursing students not only directly affects PTSD, but also indirectly affects PTSD through the separate and chain mediating effect of resilience and fear of COVID-19. The compound strategies targeted at boosting perceived social support, fostering resilience, and controlling fear of COVID-19 are warranted for reducing PTSD.

COVID-19 and Male Reproduction: A Thorny Problem.

With the global epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the increasing number of infections, little is known about how SARS-CoV-2 affects the male reproductive system during infection or after recovery. Based on the existing research data, we reviewed the effects of SARS-CoV-2 on the male reproductive system and discussed its possible mechanism of action. SARS-CoV-2 enters host cells through the angiotensin-converting enzyme 2 (ACE2)/transmembrane serine protease 2 (TMPRSS2) pathway, and males are more susceptible than females. After infection, immunopathological damage is noticed in the testicles, and the semen index is significantly reduced. Second, abnormalities of serum follicle-stimulating hormone (FSH), luteinizing hormone (LH), and testosterone (T) levels were also observed, suggesting that there may be dysfunction of the hypothalamic-pituitary-gonadal (HPG) axis. Even after recovery, the effect of SARS-CoV-2 on the male reproductive system can last for at least a period. There are still many unresolved questions about the effect of SARS-CoV-2 infection on the male reproductive tract. Other receptors involved during the invasion of human cells by SARS-CoV-2 remain to be identified. Will the mutation of SARS-CoV-2 increase the diversity of receptors? How does SARS-CoV-2 affect the HPG axis? The long-term effects of SARS-CoV-2 on the male reproductive system remain to be evaluated. SARS-CoV-2 infection can affect male reproductive function. Standard treatment strategies should be developed in time to protect the fertility of infected patients. For recovered patients with fertility requirements, fertility assessments should be performed and professional fertility guidance should be provided at the same time.

Rapid detection of SARS-CoV-2: The gradual boom of lateral flow immunoassay.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is still in an epidemic situation, which poses a serious threat to the safety of people and property. Rapid diagnosis and isolation of infected individuals are one of the important methods to control virus transmission. Existing lateral flow immunoassay techniques have the advantages of rapid, sensitive, and easy operation, and some new options have emerged with the continuous development of nanotechnology. Such as lateral flow immunoassay test strips based on colorimetric-fluorescent dual-mode and gold nanoparticles, Surface Enhanced Raman Scattering, etc., these technologies have played an important role in the rapid diagnosis of COVID-19. In this paper, we summarize the current research progress of lateral flow immunoassay in the field of Severe Acute Respiratory Syndrome Coronavirus 2 infection diagnosis, analyze the performance of Severe Acute Respiratory Syndrome Coronavirus 2 lateral flow immunoassay products, review the advantages and limitations of different detection methods and markers, and then explore the competitive CRISPR-based nucleic acid chromatography detection method. This method combines the advantages of gene editing and lateral flow immunoassay and can achieve rapid and highly sensitive lateral flow immunoassay detection of target nucleic acids, which is expected to be the most representative method for community and clinical point-of-care testing. We hope that researchers will be inspired by this review and strive to solve the problems in the design of highly sensitive targets, the selection of detection methods, and the enhancement of CRISPR technology, to truly achieve rapid, sensitive, convenient, and specific detection of novel coronaviruses, thus promoting the development of novel coronavirus diagnosis and contributing our modest contribution to the world's fight against epidemics.

Proteomic analysis and identification reveal the anti-inflammatory mechanism of clofazimine on lipopolysaccharide-induced acute lung injury in mice.

BACKGROUND AND OBJECTIVE: Acute lung injury (ALI)/ acute respiratory distress syndrome (ARDS) was increasingly recognized as one of the most severe acute hyperimmune response of coronavirus disease 2019 (COVID-19). Clofazimine (CFZ) has attracted attention due to its anti-inflammatory property in immune diseases as well as infectious diseases. However, the role and potential molecular mechanism of CFZ in anti-inflammatory responses remain unclear. METHODS: We analyze the protein expression profiles of CFZ and LPS from Raw264.7 macrophages using quantitative proteomics. Next, the protective effect of CFZ on LPS-induced inflammatory model is assessed, and its underlying mechanism is validated by molecular biology analysis. RESULTS: LC-MS/MS-based shotgun proteomics analysis identified 4746 (LPS) and 4766 (CFZ) proteins with quantitative information. The key proteins and their critical signal transduction pathways including TLR4/NF-κB/HIF-1α signaling was highlighted, which was involved in multiple inflammatory processes. A further analysis of molecular biology revealed that CFZ could significantly inhibit the proliferation of Raw264.7 macrophages, decrease the levels of TNF-α and IL-1ß, alleviate lung histological changes and pulmonary edema, improve the survival rate, and down-regulate TLR4/NF-κB/HIF-1α signaling in LPS model. CONCLUSION: This study can provide significant insight into the proteomics-guided pharmacological mechanism study of CFZ and suggest potential therapeutic strategies for infectious disease.

Application of piecewise fractional differential equation to COVID-19 infection dynamics.

We proposed a new mathematical model to study the COVID-19 infection in piecewise fractional differential equations. The model was initially designed using the classical differential equations and later we extend it to the fractional case. We consider the infected cases generated at health care and formulate the model first in integer order. We extend the model into Caputo fractional differential equation and study its background mathematical results. We show that the fractional model is locally asymptotically stable when R 0 < 1 at the disease-free case. For R 0 ≤ 1 , we show the global asymptotical stability of the model. We consider the infected cases in Saudi Arabia and determine the parameters of the model. We show that for the real cases, the basic reproduction is R 0 ≈ 1 . 7372 . We further extend the Caputo model into piecewise stochastic fractional differential equations and discuss the procedure for its numerical simulation. Numerical simulations for the Caputo case and piecewise models are shown in detail.

Assessing the potential impact of COVID-19 Omicron variant: Insight through a fractional piecewise model.

We consider a new mathematical model for the COVID-19 disease with Omicron variant mutation. We formulate in details the modeling of the problem with omicron variant in classical differential equations. We use the definition of the Atangana-Baleanu derivative and obtain the extended fractional version of the omicron model. We study mathematical results for the fractional model and show the local asymptotical stability of the model for infection-free case if R 0 < 1 . We show the global asymptotically stable of the model for the disease free case when R 0 ≤ 1 . We show the existence and uniqueness of solution of the fractional model. We further extend the fractional order model into piecewise differential equation system and give a numerical algorithm for their numerical simulation. We consider the real cases of COVID-19 in South Africa of the third wave March 2021-Sep 2021 and estimate the model parameters and get R 0 ≈ 1 . 4004 . The real parameters values are used to show the graphical results for the fractional and piecewise model.

Modeling the dynamics of coronavirus with super-spreader class: A fractal-fractional approach.

Super-spreaders of the novel coronavirus disease (or COVID-19) are those with greater potential for disease transmission to infect other people. Understanding and isolating the super-spreaders are important for controlling the COVID-19 incidence as well as future infectious disease outbreaks. Many scientific evidences can be found in the literature on reporting and impact of super-spreaders and super-spreading events on the COVID-19 dynamics. This paper deals with the formulation and simulation of a new epidemic model addressing the dynamics of COVID-19 with the presence of super-spreader individuals. In the first step, we formulate the model using classical integer order nonlinear differential system composed of six equations. The individuals responsible for the disease transmission are further categorized into three sub-classes, i.e., the symptomatic, super-spreader and asymptomatic. The model is parameterized using the actual infected cases reported in the kingdom of Saudi Arabia in order to enhance the biological suitability of the study. Moreover, to analyze the impact of memory index, we extend the model to fractional case using the well-known Caputo-Fabrizio derivative. By making use of the Picard-Lindelöf theorem and fixed point approach, we establish the existence and uniqueness criteria for the fractional-order model. Furthermore, we applied the novel fractal-fractional operator in Caputo-Fabrizio sense to obtain a more generalized model. Finally, to simulate the models in both fractional and fractal-fractional cases, efficient iterative schemes are utilized in order to present the impact of the fractional and fractal orders coupled with the key parameters (including transmission rate due to super-spreaders) on the pandemic peaks.

Whether Urbanization Has Intensified the Spread of Infectious Diseases-Renewed Question by the COVID-19 Pandemic.

The outbreak of the COVID-19 epidemic has triggered adiscussion of the relationship between urbanization and the spread of infectious diseases. Namely, whether urbanization will exacerbate the spread of infectious diseases. Based on 31 provincial data from 2002 to 2018 in China, the impact of urbanization on the spread of infectious diseases from the dimensions of "population" and "land" is analyzed in this paper by using the GMM (generalized method of moments) model. The empirical study shows that the population increase brought by urbanization does not aggravate the spread of infectious diseases. On the contrary, urban education, employment and entrepreneurship, housing, medical and health care, and other basic public services brought by population urbanization can help reduce the risk of the spread of infectious diseases. The increasing density of buildings caused by land urbanization increases the risk of the spread of infectious diseases. Moreover, the impact of urbanization on the spread of infectious diseases has regional heterogeneity. Therefore, the prevention and control of disease play a crucial role.

Protective Effect of Remdesivir Against Pulmonary Fibrosis in Mice.

Pulmonary fibrosis is a known sequela of severe or persistent lung damage. Existing clinical, imaging and autopsy studies have shown that the lungs exhibit a pathological pulmonary fibrosis phenotype after infection with coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pulmonary fibrosis may be one of the most serious sequelae associated with coronavirus disease 2019 (COVID-19). In this study, we aimed to examine the preventative effects of the antiviral drug remdesivir on pulmonary fibrosis. We used a mouse model of bleomycin-induced pulmonary fibrosis to evaluate the effects of remdesivir on pulmonary fibrosis in vivo and further explored the potential pharmacological mechanisms of remdesivir in lung fibroblasts and alveolar epithelial cells in vitro. The preventive remdesivir treatment was started on the day of bleomycin installation, and the results showed that remdesivir significantly alleviated bleomycin-induced collagen deposition and improved pulmonary function. In vitro experiments showed that remdesivir dose-dependently suppressed TGF-ß1-induced lung fibroblast activation and improved TGF-ß1-induced alveolar epithelial to mesenchymal transition. Our results indicate that remdesivir can preventatively alleviate the severity of pulmonary fibrosis and provide some reference for the prevention of pulmonary fibrosis in patients with COVID-19.

A vigorous study of fractional order COVID-19 model via ABC derivatives.

The newly arose irresistible sickness known as the Covid illness (COVID-19), is a highly infectious viral disease. This disease caused millions of tainted cases internationally and still represent a disturbing circumstance for the human lives. As of late, numerous mathematical compartmental models have been considered to even more likely comprehend the Covid illness. The greater part of these models depends on integer-order derivatives which cannot catch the fading memory and crossover behavior found in many biological phenomena. Along these lines, the Covid illness in this paper is studied by investigating the elements of COVID-19 contamination utilizing the non-integer Atangana-Baleanu-Caputo derivative. Using the fixed-point approach, the existence and uniqueness of the integral of the fractional model for COVID is further deliberated. Along with Ulam-Hyers stability analysis, for the given model, all basic properties are studied. Furthermore, numerical simulations are performed using Newton polynomial and Adams Bashforth approaches for determining the impact of parameters change on the dynamical behavior of the systems.

A dynamical study of SARS-COV-2: A study of third wave.

The coronavirus still an epidemic in most countries of the world and put the people in danger with so many infected cases and death. Considering the third wave of corona virus infection and to determine the peak of the infection curve, we suggest a new mathematical model with reported cases from March 06, 2021, till April 30, 2021. The model provides an accurate fitting to the suggested data, and the basic reproduction number calculated to be R0=1.2044 . We study the stability of the model and show that the model is locally as well as globally asymptotically stable when R0<1 , for the disease free case. The parameters that are sensitive to the basic reproduction number, their effect on the model variables are shown graphically. We can observe that the suggested parameters can decrease efficiently the infection cases of the third wave in Pakistan. Further, our model suggests that the infection peak is to be May 06, 2021. The present results determine that the model can be useful in order to predict other countries data.

Myricetin Inhibits SARS-CoV-2 Viral Replication by Targeting Mpro and Ameliorates Pulmonary Inflammation.

The coronavirus disease 2019 (COVID-19) has spread widely around the world and has seriously affected the human health of tens of millions of people. In view of lacking anti-virus drugs target to SARS-CoV-2, there is an urgent need to develop effective new drugs. In this study, we reported our discovery of SARS-CoV-2 Mpro inhibitors. We selected 15 natural compounds, including 7 flavonoids, 3 coumarins, 2 terpenoids, one henolic, one aldehyde and one steroid compound for molecular docking and enzymatic screening. Myricetin were identified to have potent inhibit activity with IC50 3.684 ± 0.076 µM in the enzyme assay. The binding pose of Myricetin with SARS-CoV-2 Mpro was identified using molecular docking method. In the binding pocket of SARS-CoV-2 Mpro, the chromone ring of Myricetin interacts with His41 through π-π stacking, and the 3'-, 4'- and 7-hydroxyl of Myricetin interact with Phe140, Glu166and Asp187 through hydrogen bonds. Significantly, our results showed that Myricetin has potent effect on bleomycin-induced pulmonary inflammation by inhibiting the infiltration of inflammatory cells and the secretion of inflammatory cytokines IL-6, IL-1α, TNF-α and IFN-γ. Overall, Myricetin may be a potential drug for anti-virus and symptomatic treatment of COVID-19.

Early risk factors for extrapulmonary organ injury in adult COVID-19 patients.

BACKGROUND: The novel 2019 coronavirus (COVID-19) has caused a global pandemic, and often leads to extrapulmonary organ injury. However, the risk factors for extrapulmonary organ injury are still unclear. We aim to explore the risk factors for extrapulmonary organ injury and the association between extrapulmonary organ injury and the prognosis in COVID-19 patients. METHODS: We implemented a single-center, retrospective, observational study, in which a total of 349 confirmed COVID-19 patients admitted to Tongji Hospital from January 25, 2020, to February 25, 2020, were enrolled. We collected demographic, clinical, laboratory, and treatment data from electronic medical records. Potential risk factors for extrapulmonary organ injury of COVID-19 patients were analyzed by a multivariable binary logistic model, and multivariable Cox proportional hazards regression model was used for survival analysis in the patients with extrapulmonary organ injury. RESULTS: The average age of the included patients was 61.73±14.64 years. In the final logistic model, variables including aged 60 or older [odds ratio (OR) 1.826, 95% confidence interval (CI): 1.060-3.142], acute respiratory distress syndrome (ARDS) (OR 2.748, 95% CI: 1.051-7.185), lymphocytes count lower than 1.1×109/L (OR 0.478, 95% CI: 0.240-0.949), level of interleukin-6 (IL-6) greater than 7 pg/mL (OR 1.664, 95% CI: 1.005-2.751) and D-Dimer greater than 0.5 µg/mL (OR 2.190, 95% CI: 1.176-4.084) were significantly associated with the extrapulmonary organ injury. Kaplan-Meier curve and log-rank test showed that the probabilities of survival for patients with extrapulmonary organ injury were significantly lower than those without extrapulmonary organ injury. Multivariate Cox proportional hazards model showed that only myocardial injury (P=0.000, HR: 5.068, 95% CI: 2.728-9.417) and circulatory system injury (P=0.000, HR: 4.076, 95% CI: 2.216-7.498) were the independent factors associated with COVID-19 patients' poor prognosis. CONCLUSIONS: Older age, lymphocytopenia, high level of D-Dimer and IL-6, and the severity of lung injury were the high-risk factors of extrapulmonary organ injury in COVID-19 patients. Myocardial and circulatory system injury were the most important risk factors related to poor outcomes of COVID-19 patients. It may help clinicians to identify extrapulmonary organ injury early and initiate appropriate treatment.

Initial CT imaging characters of an imported family cluster of COVID-19.

The objective of this report is to better understand the initial CT imaging spectrum and the relationship between clinical characteristics and initial CT imaging features of an imported family cluster cases involving 7 laboratory-confirmed COVID-19 patients. We find that initial CT findings of 4 patients were positive within one week after the onset of symptoms and 1 patient was negative before the onset of symptoms. Two asymptomatic patients had typical CT abnormalities. The initial CT imaging manifestations are mainly peripheral or subpleural ground-glass opacities and ground-glass with consolidation. Our report is of potential guiding value for the initial CT screening of imported familial cluster cases since the imported cases have an identified time of infection.