Coronavirus Disease 2019 Disease Research Articles

Advanced nanomedicines and immunotherapeutics to treat respiratory diseases especially COVID-19 induced thrombosis

Immunotherapy and associated immune regulation strategies gained huge attraction in order to be utilized for treatment and prevention of respiratory diseases. Engineering specifically nanomedicines can be used to regulate host immunity in lungs in the case of respiratory diseases including coronavirus disease 2019 (COVID-19) infection. COVID-19 causes pulmonary embolisms, thus new therapeutic options are required to target thrombosis, as conventional treatment options are either not effective due to the complexity of the immune-thrombosis pathophysiology. In this review, we discuss regulation of immune response in respiratory diseases especially COVID-19. We further discuss thrombosis and provide an overview of some antithrombotic nanoparticles, which can be used to develop nanomedicine against thrombo-inflammation induced by COVID-19 and other respiratory infectious diseases. We also elaborate the importance of immunomodulatory nanomedicines that can block pro-inflammatory signalling pathways, and thus can be recommended to treat respiratory infectious diseases.

Biomarkers can Predict COVID-19 Disease

Abstract:: Health professionals have been confronted with a series of challenges because of the ongoing pandemic of coronavirus disease 2019 (COVID-19). To save the greatest number of lives possible, it is essential to make a prompt diagnosis and admission to the hospital, as well as to stratify risks, make efficient use of intensive care services, choose appropriate treatments, monitor patients, and ensure a prompt discharge. Laboratory markers, also known as biomarkers, can provide additional information that is objective and has the potential to significantly influence various aspects of patient care. Clinical assessment is necessary, but laboratory markers can provide this information. The COVID-19 virus is not an infection that causes the respiratory system; rather, it is a multisystem disease that is caused by a diffuse system-wide process that involves a complex interplay of the immune, nervous, and endocrine systems in inflammatory and coagulative cascades. A wide variety of potential biomarkers have been uncovered because of a better understanding of the virus's effects on the body and how the body responds to them. Here, the pathophysiology and current data are examined in relation to various kinds of biomarkers, such as immunological and inflammation biomarkers, coagulation and hematological biomarkers, as well as cardiac, biochemical, and other biomarkers. This review provides a comprehensive analysis of the research on the association between biomarkers and clinical characteristics, viral load, treatment efficacy, and how this knowledge might most usefully contribute to patient care.

Public Preference for Financing Preventive Vaccines in Health Shocks: The Case of COVID-19 Vaccines in a Middle-Income Country.

To effectively manage health crises such as disease pandemics, health authorities require reliable information regarding people's preferences. This helps to ensure timely and targeted interventions and avoids increasing societal costs through developing evidence-based policies. This study investigates the Iranian people's preference for financing coronavirus disease 2019 (COVID-19) vaccines and the factors affecting this. A cross-sectional survey was performed during the third-wave peak of COVID-19 in Iran from 1 to 20 February 2021 utilizing various data collection methods. The public preference regarding imported and domestically produced vaccines, their willingness to fully or partially contribute to the financing of these vaccines, and their willingness to pay (WTP) for domestically produced vaccines using the contingent valuation method was assessed in different scenarios. The determinants of the probability of positive financing preferences were evaluated using an ordered probit regression model. Among the 2071 survey respondents, approximately 60% stated willingness to contribute to vaccine financing in the form of partial or full user fee payments. Forty percent of respondents are willing to be vaccinated if it is provided for free by the government. Interestingly, people's preference for financing the vaccine was not related to the type of vaccine. The regression analysis showed that income, having supplementary insurance, being male, perceived COVID-19 risk, education, and working in the health sector are significantly related to a higher probability of contribution to vaccine financing. Regardless of country of origin of COVID-19 vaccines, vaccination is very important for the Iranian people, and the majority of respondents in our study showed an inclination to contribute to vaccine funding, from partial to full user fees, to achieve higher protection against COVID-19 disease. Hence, ensuring timely access to vaccines during health crises such as pandemics is imperative, as it saves lives and reduces the economic burden of disease. This commitment from the health system can be supported by financial contributions from the general public. In this regard, considering public preferences is strongly advised to policymakers.

Profile and Outcomes of COVID-19 Infection in Pediatric Patients with and without Cancer: A Case–Control Study

Abstract Objectives Pediatric patients with cancer are considered a vulnerable population to the ill effects of coronavirus disease 2019 (COVID-19). We hereby studied the difference between clinical characteristics, lab parameters, and outcomes of COVID-19 among children suffering from cancer and those without cancer. We also analyzed risk factors for the occurrence of moderate-to-severe COVID-19 disease in pediatric cancer patients. Materials and Methods This retrospective case–control study was carried out using the medical record review method over 6 months in a tertiary-care center in India. All patients below 18 years of age, with reverse-transcriptase polymerase chain reaction (RTPCR) confirmed COVID-19, were screened for enrolment. Patients were split into two groups: Group A comprised of patients with cancer, while group B consisted of patients without any underlying comorbidity. Patients with other comorbidity except cancer and inadequately recorded case sheets were excluded. Details regarding demography, clinical features, investigations, treatment, and outcomes were recorded. Statistical Analysis Microsoft Excel and Statistical Package for the Social Sciences (SPSS) software, version 25 was used for data analysis. A p-value less than 0.05 was considered significant. Results Two-hundred-five pediatric inpatients with RTPCR-established COVID-19 infection were screened and final analyses were performed on 97 patients, of which 31 children were classified into group A and 66 into group B. Median age of enrolled children was 5 years with 58.8% males. The prevalence of cancer as a comorbidity in pediatric inpatients with COVID-19 was 15%. Fifty-five percent of cancer patients had hematological malignancies, while 45% had solid tumors. Fever (p = 0.001) and gastrointestinal manifestations (p = 0.0001) were significantly less common among pediatric cancer patients. Children with cancer had significantly more leukopenia (p = 0.003), neutropenia (p = 0.003), and lymphopenia (p = 0.005). The case fatality rate was higher in children with cancer (3.2%) as compared to noncancer patients (1.5%, p = 1.0). Few risk factors for moderate-to-severe COVID-19 among children with cancer included age less than 2 years (p = 0.06), undernutrition (p = 0.33), advanced stage of cancer (p = 0.49), and presence of coinfection (p = 0.35) Conclusion Cancer is a significant comorbidity among pediatric COVID-19 patients. While children with cancer have less severe COVID-19, their case fatality rate is higher than those without cancer. Younger age, undernutrition, advanced stage of cancer, and presence of coinfections may predispose to the development of moderate-to-severe COVID-19 among pediatric cancer patients.

Determinants of Disease Progression in Bangladeshi COVID-19 Patients: A Cross-sectional Survey

Background Coronavirus disease 2019 (COVID-19) shows a wide range of clinical manifestations, including asymptomatic presentation to severe pneumonia, acute respiratory distress syndrome, and respiratory failure. Although COVID-19 disease progression was studied elsewhere, it is largely unknown in Bangladesh. Methods We conducted this cross-sectional study in November 2020 to January 2021 on patients diagnosed with COVID-19 confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR). Pearson chi-square tests were used to assess the disease progressions across selected variables. A logistic regression model was used to assess the associated factors of COVID-19 infection for explanatory variables. All statistics were performed using the Stata software version 14.0 (Stata corporation, college station, Texas, USA). Results A total of 384 of respondents were involved in the survey. Of participants, most males (73%), unmarried (69%), aged 18 to 35 years during survey, and lived in urban community (73%). Overall, 41% of patients were in asymptotic condition, 44% were in mild condition, while 17% were moderate to severe conditions. Male patients and patients over 50 years had severe symptoms, accounting for 52% and 50%, respectively. Nearly half of business persons and office employees had severe symptoms. Almost all married patients (98%) had severe symptoms. The severity of symptoms was also higher for patients living in urban areas (79%), smoking (95%), and not physically active (52%). Patients with diabetes, asthma/COPD, and cancer were significantly associated with severe stage of COVID-19 (p≤0.05). Patient’s age, gender, smoking status, diabetics, working conditions significantly affect Covid-19 disease progression. Conclusion The study found that 7.03% of patients had severe, 9.11% had moderate and 40.36% had asymptomatic conditions. The heterogenic association between the disease progressions with age, sex, residence, marital status, smoking habits, diabetes, physical exercise, working conditions, sedentary lifestyles. Findings highlight the idea of using vulnerability ratings for each risk factor related to disease progression.

Long-term outcome of COVID-19 patients with acute kidney injury requiring kidney replacement therapy

BackgroundLimited data existed on the burden of coronavirus disease 2019 (COVID-19) renal complications and the outcomes of the most critical patients who required kidney replacement therapy (KRT) during intensive care unit (ICU) stay. We aimed to describe mortality and renal function at 90 days in patients admitted for COVID-19 and KRT.MethodsA retrospective cohort study of critically ill patients admitted for COVID-19 and requiring KRT from March 2020 to January 2022 was conducted in an Italian ICU from a tertiary care hospital. Primary outcome was mortality at 90 days and secondary outcome was kidney function at 90 days.ResultsA cohort of 45 patients was analyzed. Mortality was 60% during ICU stay and increased from 64% at the time of hospital discharge to 71% at 90 days. Among 90-day survivors, 31% required dialysis, 38% recovered incompletely, and 31% completely recovered renal function. The probability of being alive and dialysis-free at 3 months was 22%.ConclusionsCritically ill patients with COVID-19 disease requiring KRT during ICU stay had elevated mortality rate at 90 days, with low probability of being alive and dialysis-free at 3 months. However, a non-negligible number of patients completely recovered renal function.

Association between Usage of Prophylactic AYUSH Medicines and Disease Severity in COVID-19 Patients: A Retrospective Cohort Study.

Prior vaccination is often studied for its impact on individuals' post-infection prognosis. Ayurveda, Yoga, Unani, Siddha and Homeopathy (AYUSH) medicines, advised by the Government of India as prophylaxis during the first wave of the coronavirus disease 2019 (COVID-19) pandemic, were consumed by the masses in 2020. A study was therefore undertaken to observe any association between the prior usage of AYUSH prophylactic medicines and post-infection severity as reported by recovered COVID-19 individuals. This was a retrospective, multi-centre, cohort study conducted in 21 cities of India from 5th August to 30th November 2020. Data from recovered COVID-19 patients, of either sex or any age, captured information about AYUSH prophylactic medicines intake prior to infection, disease severity, symptomatology, duration of complaints, etc. The study participants were grouped into AYUSH intake and non-intake. Primary composite outcome was the disease clinical course. Secondary clinical outcomes were the rate of and time to clinical recovery. Data of 5,023 persons were analysed. Ayurveda or homeopathic prophylactic medicines were consumed by more than half of the study participants: that is, 56.85% (n = 1,556) and 56.81% (n = 1,555) respectively. The overall adjusted protective effect (PE) of AYUSH prophylactic intake against moderate/severe forms of COVID-19 disease was 56.7% (95% confidence interval [CI], 48.7 to 63.50; p < 0.001). Adjusted PE for homeopathy and Siddha was 52.9% (95% CI, 42.30 to 61.50; p < 0.001) and 59.8% (95% CI, 37.80 to 74.10; p < 0.001), respectively. A statistically significant association was found between AYUSH prophylactic medicine intake and clinical recovery more frequently by the 3rd day of illness (χ2 = 9.01; p = 0.002). Time to resolution of symptoms in the AYUSH intake group was on average 0.3 days earlier than in the non-intake group (p = 0.002). AYUSH prophylactics were associated with statistically significant levels of protection against COVID-19 disease severity. Amongst these, previous intake of homeopathy or Siddha medicines was associated with some protection against moderate/severe illness and with a somewhat quicker clinical recovery. Prospective studies with experimental research design are needed to validate the findings of this study. Clinical Trials Registry-India (CTRI/2020/08/027000).

Using the Lagrange Interpolation Polynomial Method to calculate the prevalence of coronavirus disease 2019 (COVID-19) in Turkey

The goal of this paper is to look into a numerical approximation for the spread of the coronavirus disease 2019 (COVID-19) in Turkey. From March 11th to November 30th, all data is examined one by one for this purpose. The Lagrange interpolation method does not require evenly spaced x values. On the other hand, it is usually preferable to look for the closest value in the table and then use the lowest-order interpolation that is consistent with the functional form of the data. Using this method, a function for monthly and general data on the number of COVID-19 disease deaths and cases infected with the disease is obtained. Matlab programming is used to obtain Lagrange interpolation polynomials. Simulations for month by month and general data are obtained using Lagrange interpolation polynomial. The rate of spread of disease and death numbers is obtained by taking the first derivative of this function. Monthly and general tables are constructed for this propagation rate data. Peak point of the disease and different change values ​​are determined from the information in these simulations. The rates of death and spread of the disease by months are compared. As a result of this comparison, it can be seen in which months the rate of spread of disease and death increases and decreases. Monthly increase and decrease values ​​can be seen from the Figure 3-Figure 6. For example, a relative decrease can be observed in April and May

Automated detection of COVID-19 and pneumonia diseases using data mining and transfer learning algorithms with focal loss from chest X-ray images

Pneumonia is a lung infection that produces severe inflammation, which can be caused by viruses, bacteria, or fungi. The global occurrence of pneumonia cases has been notably affected by the outbreak of Coronavirus Disease 2019 (COVID-19). Recent studies have demonstrated the capability of Deep Learning (DL) algorithms in detecting COVID-19 and pneumonia in medical images like X-rays. In this study, we employ four different Chest X-ray (CXR) datasets to evaluate four pre-trained Convolutional Neural Network (CNN) models: InceptionResNet V2, Inception V3, Xception, and MobileNet. These models were fine-tuned using either the Cross-Entropy (CE) loss function only for balanced datasets or separately using both the CE and Focal Loss (FL) functions for imbalanced datasets. For the first dataset, the InceptionResNet V2 model achieved the highest multi-classification accuracy of 88.63%. The superior model for the second and fourth datasets is Inception V3, with 94.35% and 97.67% multi-classification accuracy, respectively. For the third dataset, the best model is Xception, with a binary classification accuracy of 100.00%. Our results emphasize the significance of using the FL function in solving class imbalance problems in DL models. Additionally, it highlights the effectiveness of individual DL models in detecting different pneumonia infections using different CXR datasets.

Role of Inflammation in the Development of COVID-19 to Parkinson's Disease.

The coronavirus disease 2019 (COVID-19) can lead to neurological symptoms such as headaches, confusion, seizures, hearing loss, and loss of smell. The link between COVID-19 and Parkinson's disease (PD) is being investigated, but more research is needed for a definitive connection. Datasets GSE22491 and GSE164805 were selected to screen differentially expressed gene (DEG), and immune infiltration and gene set enrichment analysis (GSEA) of the DEG were performed. WGCNA analyzed the DEG and selected the intersection genes. Potential biological functions and signaling pathways were determined, and diagnostic genes were further screened using gene expression and receiver operating characteristic (ROC) curves. Screening and molecular docking of ibuprofen as a therapeutic target. The effectiveness of ibuprofen was verified by constructing a PD model in vitro, and constructing "COVID19-PD" signaling pathway, and exploring the role of angiotensin-converting enzyme 2 (ACE2) in PD. A total of 13 DEG were screened from the GSE36980 and GSE5281 datasets. Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the DEG were mainly associated with the hypoxia-inducible factor (HIF-1), epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance, etc. After analysis, it is found that ibuprofen alleviates PD symptoms by inhibiting the expression of nuclear factor kappa-B (NF-κB), interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-α (TNF-α). Based on signal pathway construction, the importance of ACE2 in COVID-19-induced PD has been identified. ACE2 is found to have widespread distribution in the brain. In the 1-methyl-4-phenyl-1,2,3,6-te-trahydropyridine (MPTP)-induced ACE2-null PD mice model, more severe motor and non-motor symptoms, increased NF-κB p65 and α-synuclein (α-syn) expression with significant aggregation, decreased tyrosine hydroxylase (TH), severe neuronal loss, and neurodegenerative disorders. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection increases the risk of PD through an inflammatory environment and downregulation of ACE2, providing evidence for the molecular mechanism and targeted therapy associated with COVID-19 and PD.

SARS-CoV-2 superinfection in CD14+ monocytes with latent human cytomegalovirus (HCMV) promotes inflammatory cascade

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), has posed significant challenges to global health. While much attention has been directed towards understanding the primary mechanisms of SARS-CoV-2 infection, emerging evidence suggests co-infections or superinfections with other viruses may contribute to increased morbidity and mortality, particularly in severe cases of COVID-19. Among viruses that have been reported in patients with SARS-CoV-2, seropositivity for Human cytomegalovirus (HCMV) is associated with increased COVID-19 risk and hospitalization. HCMV is a ubiquitous beta-herpesvirus with a seroprevalence of 60–90 % worldwide and one of the leading causes of mortality in immunocompromised individuals. The primary sites of latency for HCMV include CD14+ monocytes and CD34+ hematopoietic cells. In this study, we sought to investigate SARS-CoV-2 infection of CD14+ monocytes latently infected with HCMV. We demonstrate that CD14+ cells are susceptible and permissive to SARS-CoV-2 infection and detect subgenomic transcripts indicative of replication. To further investigate the molecular changes triggered by SARS-CoV-2 infection in HCMV-latent CD14+ monocytes, we conducted RNA sequencing coupled with bioinformatic differential gene analysis. The results revealed significant differences in cytokine-cytokine receptor interactions and inflammatory pathways in cells superinfected with replication-competent SARS-CoV-2 compared to the heat-inactivated and mock controls. Notably, there was a significant upregulation in transcripts associated with pro-inflammatory response factors and a decrease in anti-inflammatory factors. Taken together, these findings provide a basis for the heightened inflammatory response, offering potential avenues for targeted therapeutic interventions among HCMV-infected severe cases of COVID-19. SummaryCOVID-19 patients infected with secondary viruses have been associated with a higher prevalence of severe symptoms. Individuals seropositive for human cytomegalovirus (HCMV) infection are at an increased risk for severe COVID-19 disease and hospitalization. HCMV reactivation has been reported in severe COVID-19 cases with respiratory failure and could be the result of co-infection with SARS-CoV-2 and HCMV. In a cell culture model of superinfection, HCMV has previously been shown to increase infection of SARS-CoV-2 of epithelial cells by upregulating the human angiotensin-converting enzyme-2 (ACE2) receptor. In this study, we utilize CD14+ monocytes, a major cell type that harbors latent HCMV, to investigate co-infection of SARS-CoV-2 and HCMV. This study is a first step toward understanding the mechanism that may facilitate increased COVID-19 disease severity in patients infected with SARS-CoV-2 and HCMV.

Comparative analysis of various laboratory biomarkers based on the severity of COVID-19 in a tertiary care hospital in South India

COVID-19 (Corona Virus Disease 2019) was a life-changing pandemic with impact on social, environmental, health, and economic issues. Various inflammatory and hematological biomarkers studied individually or in combination in the literature have shown significant results with regard to COVID-19 pathology, severity, and prognosis. Yet the question of interest is how covid-19 inflammatory cascade impacts the interlink between the biomarkers during different stages. This study aims to retrospectively analyse ferritin, albumin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, direct bilirubin, blood urea nitrogen (BUN), creatinine, D-dimer, Lactate Dehydrogenase (LDH), C Reactive Protein (CRP) and Interleukin-6 (IL-6) levels between two groups based on COVID-19 severity. A retrospective cross-sectional study was conducted with laboratory data of COVID-19 patients admitted at Sri Ramachandra Medical College Hospital, India. The sample size was 104 [Group1: severe disease, n=52; Group-2: mild disease, n=52]. After normality testing, data were compared between the two groups followed by correlation analysis between the variables. A p&lt;0.05 was considered statistically significant. On comparison, Group 2 (severe COVID-19 disease) showed significant difference in the levels of all the biomarkers (p&lt;0.005) except Creatinine (p&lt;0.128) when compared with Group 1 (mild COVID-19 disease). Significant correlation was obtained between all biomarkers (p&lt;0.005) except creatinine. The correlation analysis primarily explains the inflammatory cascade involved in disease. Ferritin appears to have a standalone effect on disease severity, progression, organ dysfunction. This understanding can be used to provide better and more timely care.

Knowledge and preventive practices regarding COVID-19 disease among Ukrainian refugees in Poland.

Russia's invasion of Ukraine contributed one of the largest migration movements in the 21st century. Refugees may become a source of severe acute respiratory syndrome coronavirus 2 infections for the residents of host countries. The study aim was to assess knowledge and preventive practices regarding coronavirus disease 2019 (COVID-19) among Ukrainian refugees in Poland. The cross-sectional study was conducted between March and April 2022 among Ukrainian refugees registering consecutively in Zielona Góra, Poland. Knowledge and preventive practices were assessed by giving 1 point for each correct answer by anonymous, self-administered questionnaire. The response rate was 96%, 190 participated (mean age 37.8 ± 15.5 years; 57.9% females); 61.6% self-reported their socio-economic status (SES) as high, 38.9% reported high level of education. The mean COVID-19 knowledge score was 3.06 ± 1.95; 19.5% scored >50%. The knowledge level was higher among migrants with high SES (P = .003). The mean preventive practices score was 2.56 ± 1.38; 54.0% scored ≥ 60%. 40.5% declared social distancing, 62.6% followed coughing etiquette, 69.0% home isolate themselves during COVID-19. 57.9% always used masks in public space, however 74.2% wore masks with uncovered nose. Refugees with higher education, high SES and knowledge level had significantly greater preventive practices scores (P = .002; P = .02; P = .03, respectively). The knowledge and preventive practices level was insufficient. Educational campaigns oriented to raising knowledge and prevention behavior skills should be implemented, especially targeting high-risk groups to avoid spread of COVID-19.

Narrative Review Explaining the Role of HLA-A, -B, and -C Molecules in COVID-19 Disease in and around Africa.

The coronavirus disease 2019 (COVID-19) has left a devasting effect on various regions globally. Africa has exceptionally high rates of other infectious diseases, such as tuberculosis (TB), human immunodeficiency virus (HIV), and malaria, and was not impacted by COVID-19 to the extent of other continents Globally, COVID-19 has caused approximately 7 million deaths and 700 million infections thus far. COVID-19 disease severity and susceptibility vary among individuals and populations, which could be attributed to various factors, including the viral strain, host genetics, environment, lifespan, and co-existing conditions. Host genetics play a substantial part in COVID-19 disease severity among individuals. Human leukocyte antigen (HLA) was previously been shown to be very important across host immune responses against viruses. HLA has been a widely studied gene region for various disease associations that have been identified. HLA proteins present peptides to the cytotoxic lymphocytes, which causes an immune response to kill infected cells. The HLA molecule serves as the central region for infectious disease association; therefore, we expect HLA disease association with COVID-19. Therefore, in this narrative review, we look at the HLA gene region, particularly, HLA class I, to understand its role in COVID-19 disease.

Modelling the adverse impacts of urbanization on human health

Abstract Urbanization has been a growing trend for decades, but the Coronavirus disease 2019 (COVID-19) pandemic has accelerated this trend in several ways. In many countries, the pandemic has prompted significant investments in urban health infrastructure, including hospitals, clinics, and public health facilities. Also, there are many studies suggesting that COVID-19, urbanization, and chronic diseases are interconnected in several ways, and addressing one aspect requires a comprehensive approach that considers the interconnectedness of these factors. To date, there are no studies depicting COVID-19 as a cause of emerging chronic diseases within the urban population. To address this sensitive issue, we propose a mathematical model in which we divide the total human population into three compartments: susceptible, diseased, and recovered. We have obtained the equilibrium points of the model and the conditions for their local stabilities. A suitable Lyapunov function has been used to derive the condition for the global stability of the nontrivial equilibrium point. A detailed numerical simulation of the model has been carried out, which is followed by sensitivity analysis of the model system.

Exploring the mechanism of Corbrin capsules in the intervention of AKI-COVID-19 based on network pharmacology combined with GEO dataset

Aimof the study: This study used network pharmacology and the Gene Expression Omnibus (GEO) database to investigate the therapeutic effects of Corbrin capsules on acute kidney injury (AKI)-COVID-19 (coronavirus disease 2019). Materials and methodsThe active constituents and specific molecular targets of Corbrin capsules were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Swiss Target Prediction databases. The targets related to AKI and COVID-19 disease were obtained from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and GEO databases. A protein–protein interaction (PPI) network was constructed by utilizing Cytoscape. To enhance the analysis of pathways associated with the pathogenesis of AKI-COVID-19, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Furthermore, immune infiltration analysis was performed by using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Molecular docking was used to assess interactions between differentially expressed genes and active ingredients. Verification was performed by utilizing GEO databases and in vivo assays. ResultsThis study revealed an overlap of 18 significantly differentially expressed genes between the Corbrin capsules group and the AKI-COVID-19 target group. Analysis of the PPI network identified TP53, JAK2, PIK3CA, PTGS2, KEAP1, and MCL1 as the top six core protein targets with the highest degrees. The results obtained from GO and KEGG analyses demonstrated that the target genes were primarily enriched in the apoptosis and JAK-STAT signaling pathways. Moreover, the analysis of immune infiltration revealed a notable disparity in the percentage of quiescent memory CD4 + T cells. Western blot analyses provided compelling evidence suggesting that the dysregulation of 6 core protein targets could be effectively reversed by Corbrin capsules. ConclusionThis study revealed the key components, targets, and pathways involved in treating AKI-related COVID-19 using Corbrin capsules. This study also provided a new understanding of the molecular mechanisms underlying this treatment.

Post-vaccination SARS-CoV-2 IgG spike antibody responses among clinical and non-clinical healthcare workers at a tertiary facility in Kenya.

Following the coronavirus disease 19 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, vaccination became the main strategy against disease severity and even death. Healthcare workers were considered high-risk for infection and, thus, were prioritised for vaccination. A follow-up to a SARS-CoV-2 seroprevalence study among clinical and non-clinical HCWs at the Aga Khan University Hospital, Nairobi, we assessed how vaccination influenced SARS-CoV-2 anti-spike IgG antibody responses and kinetics. Blood samples were drawn at two points spanning 6 to 18 months post-vaccination, and SARS-CoV-2 spike antibody levels were determined by enzyme-linked immunosorbent assay. Almost all participants, 98% (961/981), received a second vaccine dose, and only 8.5% (83/981) received a third dose. SARS-CoV-2 spike IgG antibodies were detected in 100% (961/961) and 92.7% (707/762) of participants who received two vaccine doses, with the first and second post-vaccine test, respectively, and in 100% (83/83) and 91.4% (64/70) of those who received three vaccine doses at the first and second post-vaccine test, respectively. Seventy-six participants developed mild infections, not requiring hospitalisation even after receiving primary vaccination. Receiving three vaccine doses influenced the anti-spike S/Co at both the first (p<0.001) and second post-vaccination testing (p<0.001). Of those who tested SARS-CoV-2 positive, the anti-spike S/Co ratio was significantly higher than those who were seronegative at the first post-vaccine test (p = 0.001). Side effects were reported by almost half of those who received the first dose, 47.3% (464/981), 28.9% (278/961) and 25.3% (21/83) of those who received the second and third vaccine doses, respectively. Following the second dose of primary vaccination, all participants had detectable anti-spike antibodies. The observed mild breakthrough infections may have been due to emerging SARS-CoV-2 variants. Findings suggest that although protective antibodies are induced, vaccination protected against COVID-19 disease severity and not necessarily infection.

The role of C-reactive protein, procalcitonin, interleukin-6 and neutrophil / lymphocyte ratio as a laboratory biomarker in COVID-19

Biomarkers such as Interleukin-6 (IL-6), Procalcitonin (PCT), C-reactive protein (CRP) and Neutrophil-Lymphocyte Ratio (NLR) have a role in the pathogenesis of severe coronavirus disease 2019 (COVID-19). The aim of this study was to explore the differences between serum levels of such biomarkers in severe and non-severe COVID-19 cases and compare them with normal people and to evaluate the sociodemographic variables and chronic diseases effect on the severity of COVID-19. The study included 160 subjects, divided into two groups, a case group of 80 patients, and a control group of 80 normal persons. The case group was divided into two subgroups: 40 severe COVID-19 patients and 40 patients with non-severe disease. Blood IL-6 was assessed by an enzyme-linked immunosorbent assay (ELISA), PCT by an immunoassay, CRP by an immunoturbidimetric assay and NLR from CBC. The levels of IL-6, PCT, CRP, and NLR were significantly higher in the case group than in control group (p= 0.001, for all). However, there was no difference between these biomarkers level in the non-severe COVID-19 subgroup and the control group (p&gt;0.05 for all). The proportion of severe COVID-19 was significantly higher in patients aged &gt;50 years, and in patients with chronic diseases (p=0.046 and p=0.001, respectively). We also found a strong correlation between such biomarkers and old age, and chronic diseases with the disease severity. There was a significant difference in the level of the three biomarkers (IL-6, PCT, CRP, and NLR) between patients’ subgroups and the control group. In conclusion, since the levels of these biomarkers are correlated with the severity of the COVID-19 disease, and there was a difference in the levels between the groups with severe and non-severe symptoms, we suggest a role of these biomarkers in predicting the severity COVID-19 disease and its poor prognosis.

Temporal assessment of SARS-CoV-2 detection in wastewater and its epidemiological implications in COVID-19 case dynamics

This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase. However, significant lead times were observed during the Omicron wave, potentially attributed to testing capacity overload and subsequent case reporting delays or changes in shedding patterns. During the Post-Omicron wave (Febuary 23 to May 19, 2022), no lead time was discernible, whereas following the lifting of the COVID-19 state of emergency (May 30, 2022 to May 30, 2023), the correlation coefficient increased and demonstrated the potential of wastewater surveillance as an early warning system. Subsequently, we explored the virus shedding in wastewater through feces, operationalized as the ratio of SARS-CoV-2 concentrations to daily new COVID-19 cases. This ratio varied significantly across the Delta, Omicron, other variants and post-state-emergency phases, with the Kruskal-Wallis H test confirming a significant difference in medians across these stages (P < 0.0001). Despite its promise, wastewater surveillance of COVID-19 disease prevalence presents several challenges, including virus shedding variability, data interpretation complexity, the impact of environmental factors on viral degradation, and the lack of standardized testing procedures. Overall, our findings offer insights into the correlation between COVID-19 cases and wastewater viral concentrations, potential variation in SARS-CoV-2 shedding in wastewater across different pandemic phases, and underscore the promise and limitations of wastewater surveillance as an early warning system for disease prevalence trends.

A retrospective study of hematological and biochemical parameters in coronavirus disease 2019 (COVID-19) patients in Vietnam

The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus has had a serious impact on global public health. Currently, there are not many studies evaluating the impact of COVID-19 on changes in biochemical and hematological parameters of COVID-19 patients in Vietnam. This study aimed to investigate clinical characteris tics and changes in hematological and biochemical parameters in COVID-19 patients. This retrospective and cross-sectional study collected the medical records of 654 COVID-19 patients treated at Dong Nai General Hospital from August to December 2021. Medical information from COVID-19 patients was collected through handwritten medical records and HIS-FP software. The age of the study population was 56.69±15.97. Diabetes was the most common comorbidity and had a significant relationship with COVID-19 severity and mortality. For hematological tests, total white blood cell (WBC) and Percentage of neutrophils (%NEU) in non-survivors (12.87±6.45) signifi- cantly increased compared with survivors (9.08±4.48) (p&lt;0.001). Neutrophils (NEU), neutrophil/lymphocyte ratio (NLR), and platelet/lymphocyte ratio (PLR) increased in both non-survivors and survivors; lymphocytes (LYM) and percentage of lymphocyte (%LYM) decreased in both groups. For biological parameters, aspartate transaminase (AST) in non-survivors [55.9 (38.5–89.1)] significantly increased compared with survivors [36.55 (23.02–67.12)] (p&lt;0.001). Lactate dehy drogenase (LDH) activity, C-reactive protein (CRP), and D-dimer levels increased in both non-survivors and survivors. NEU, LYM, NLR, PLR, LDH, CRP, and D-dimer were related to the severity of COVID-19 disease.