Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia

Broadening sarbecovirus neutralization with bispecific antibodies combining distinct conserved targets on the receptor binding domain

Monoclonal neutralizing antibodies (mAbs) are considered an important prophylactic against SARS-CoV-2 infection in at-risk populations and a strategy to counteract future sarbecovirus-induced disease. However, most mAbs isolated so far neutralize only a few sarbecovirus strains. Therefore, there is a growing interest in bispecific antibodies (bsAbs) which can simultaneously target different spike epitopes and thereby increase neutralizing breadth and prevent viral escape. Here, we generate and characterize a panel of 30 novel broadly reactive bsAbs using an efficient controlled Fab-arm exchange protocol. We specifically combine some of the broadest mAbs described so far, which target conserved epitopes on the receptor binding domain (RBD). Several bsAbs show superior cross-binding and neutralization compared to the parental mAbs and cocktails against sarbecoviruses from diverse clades, including recent SARS-CoV-2 variants. BsAbs which include mAb COVA2-02 are among the most potent and broad combinations. As a result, we study the unknown epitope of COVA2-02 and show that this mAb targets a distinct conserved region at the base of the RBD, which could be of interest when designing next-generation bsAb constructs to contribute to a better pandemic preparedness.

Impact of a large-scale event on SARS-CoV-2 cases and hospitalizations in the Netherlands, carnival seasons 2022 and 2023

Objectives

The COVID-19 pandemic highlights the importance of understanding facilitators for disease transmission. Events such as Carnival, characterized by large gatherings and extensive social interactions, have the potential to become 'super spreading events' for respiratory infections. This paper aims to assess the impact of large gatherings on virus transmission, providing crucial insights for the development of effective public health strategies.

Study design

An ecological study was performed.

Methods

The age-standardized number of COVID-19 cases reported in 2022, stratified by age (under 60 and 60+ years) was compared countrywide for Dutch provinces where Carnival was celebrated versus those where it was not. Additionally, we compared standardized hospitalization rates in 2022 and 2023 for both areas.

Results

Countrywide, 2,278,431 COVID-19 cases were reported between 06-02-2022 and 10-04-2022. Daily incidence increased after Carnival, peaking at 803 per 100,000 inhabitants for under 60s in carnival provinces and 368 in non-carnival provinces. For individuals 60+ daily incidence peaked at 396 in carnival provinces and 247 in non-carnival provinces. Over the 10 weeks following the start of Carnival, the carnival provinces demonstrated a 15 % (2022) 17 % (2023) higher hospitalization rate compared to non-carnival provinces.

Conclusions

The peak in cases and hospitalizations in regions actively celebrating Carnival compared to the rest of the Netherlands qualifies Carnival as a 'super-spreading' event. Our findings underscore the elevated risk of respiratory infections associated with large gatherings, advocating guided policies, including transparent risk communication and healthcare preparedness.

Intelligent mobile robot for contagious disease treatments in hospitals

This paper provides a novel and applicable work that builds a real system for disinfecting the air and surfaces of the environment in a hospital room, with a non-contact measurement system for supporting contagious disease treatments in hospitals. The system is built on an intelligent mobile robot system that operates autonomously in a simulated real treatment room. The research team uses a new positioning algorithm. It is a combination of data from the Lidar sensor, encoder, and Extended Kalman filter. The program that applies segmentation and image feature extraction algorithms is developed to meet requirements of real-time environment mapping in the room. Control algorithms for moving and avoiding obstacles are also proposed. Next, techniques for collecting health data including patient identification, body temperature, and blood oxygen index via wireless sensor network are also mentioned in the article. Analysis and experimental results show qualified outcomes and promise. The main contribution of the paper can be listed as follows.•Design and build a new CEE-IMR, an intelligent mobile robot that can regconize patients, guide and lead them walking in hospitals, especially keep a safe distance avoiding contagious deseases.•A novel framework for controlling the robot is proposed. The robot can move flexible, avoid obstacles, etc. based on advanced control algorithms. A new control mechanism is also proposed.•Methods of collecting data and processing medical data to support either patients or doctors to improve the effecency in hospitals in contagious disease management.

The Challenges Experienced by ICU Nurses in Kuwait during the COVID-19 Pandemic

Background

The coronavirus (COVID-19) pandemic presented unprecedented challenges to healthcare systems worldwide, with intensive care unit (ICU) nurses at the forefront of patient care. To date, there is limited evidence into ICU nurses'experiences of the pandemic in Kuwait.

Research question/aims/objectives

To elucidate the challenges faced by ICU nurses in Kuwait during the pandemic, by considering two research questions: "What contributed to intensified pressure for the ICU nurses?" and "How were the nurses affected?".

Research design

This was a qualitative study which utilised semi-structured interviews. Interviews were conducted between January 2021 and June 2022 with ICU nurses who worked during the COVID-19 pandemic. The data were analysed using Charmaz's grounded theory methodology.

Participants and research context

25 nurses from three ICUs in Kuwait.

Ethical considerations

The study was approved by the University Ethics Committee and by the Ministry of Health in Kuwait.

Findings/Results

The analysis identified two themes (the factors contributing to intensified pressure in the ICU, and the impact on the nurses) and seven sub-themes. The pressure in the ICU intensified due to the rise in the number of patients, staff shortages, and the requirement to adhere to unrealistic new procedures for infection control. Restricted and cancelled leave, as well as impaired autonomy at work, impeded the nurses' ability to recover from stress. The heightened stress also contributed to a worsening in interpersonal relationships between the nurses and their colleagues. The nurses' care was compromised by these challenges, leading to moral distress and a range of mental health symptoms (e.g., stress, anxiety, emotional exhaustion).

Conclusions

The study accords with other research conducted during the pandemic in revealing a significant mental health toll among healthcare workers during the pandemic. The stressors were similar to those which have been reported in other studies, although there were also context-specific effects relating to the environment of the ICU and the Kuwaiti context.

Investigating the potential of natural compounds as novel inhibitors of SARS-CoV-2 RdRP using computational approaches

COVID-19 is a highly contagious disease caused by SARS-CoV-2. Currently, no vaccines or antiviral treatments are available to combat this deadly virus; however, precautions and some repurposed medicines are available to contain COVID-19. RNA-dependent RNA polymerase (RdRP) plays an important role in the replication or transcription of viral mechanisms. Approved antiviral drug such as Remdesivir has shown inhibitory activity against SARS-CoV-2 RdRP. The purpose of this study was to carry out a rational screening of natural products against SARS-CoV-2 RdRP, which may serve as a basis to develop a treatment option against COVID-19. For this purpose, a protein and structure conservation analysis of SARS-CoV-2 RdRP was performed to check mutations. A library of 15,000 phytochemicals was developed from literature review, ZINC database, PubChem and MPD3 database; and was used to performed molecular docking and molecular dynamics simulation (MD) analysis. The top-ranked compounds were subjected to pharmacokinetic and pharmacological studies. Among them, top 7 compounds (Spinasaponin A, Monotropane, Neohesperidoe, Posin, Docetaxel, Psychosaponin B2, Daphnodrine M, and Target Remedesvir) were noticed to interact with the active site residues. MD simulation in aqueous solution suggested conformational flexibility of loop regions in the complex to stabilize the docked inhibitors. Our study revealed that the studied compounds have potential to bind to the active site residues of SARS-CoV-2 RdRP. Although, this computational work is not experimentally determined but the structural information and selected compounds might help in the design of antiviral drugs targeting SAR-CoV-2 by inhibiting the activity of SARS-CoV-2 RdRP.

Dual-strain dynamics of COVID-19 variants in India: Modeling, analysis, and implications for pandemic control

This study introduces a detailed compartmental model developed to understand the complex dynamics of COVID-19 transmission, focusing on the Delta and Omicron variants in India. The model tracks disease progression through different population compartments, considering factors like vaccination, time-dependent transmission, economic burden and COVID-19 death rates, loss of vaccine-induced immunity, and the transition of asymptomatic cases to recovery. The model is validated against established epidemiological knowledge and real-world data, emphasizing dynamic parameterization and accurate representation of immunity dynamics. The basic reproduction number for both variants is calculated, and sensitivity analysis for various parameters is conducted. Time-dependent parameters are estimated using the discrete inverse method. The study also explores the economic burden, impact of different types of masks, vaccine efficacy, and vaccine-induced immunity through numerical analysis.

A conformable fractional finite difference method for modified mathematical modeling of SAR-CoV-2 (COVID-19) disease

In this research, the ongoing COVID-19 disease by considering the vaccination strategies into mathematical models is discussed. A modified and comprehensive mathematical model that captures the complex relationships between various population compartments, including susceptible (Sα), exposed (Eα), infected (Uα), quarantined (Qα), vaccinated (Vα), and recovered (Rα) individuals. Using conformable derivatives, a system of equations that precisely captures the complex interconnections inside the COVID-19 transmission. The basic reproduction number (R0), which is an essential indicator of disease transmission, is the subject of investigation calculating using the next-generation matrix approach. We also compute the R0 sensitivity indices, which offer important information about the relative influence of various factors on the overall dynamics. Local stability and global stability of R0 have been proved at a disease-free equilibrium point. By designing the finite difference approach of the conformable fractional derivative using the Taylor series. The present methodology provides us highly accurate convergence of the obtained solution. Present research fills research addresses the understanding gap between conceptual frameworks and real-world implementations, demonstrating the vaccination therapy's significant possibilities in the struggle against the COVID-19 pandemic.

The correlated factors of anxiety and depression among Chinese hospital staff during the COVID-19 local outbreak

Hospital staff in the COVID-19 local outbreak were facing different situations, their mental status and influencing factors were also different. The aim of this study is to investigate the anxiety and depression of hospital staff and its potential influence factors during the COVID-19 local outbreak. This was a cross-sectional survey based on a hospital with a local outbreak of COVID-19. We collected the demographic characteristics, COVID-19-related issues, self-rating anxiety scale (SAS), and self-rating depression scale (SDS) of participants through an anonymous questionnaire. Factors associated with anxiety and depression were explored through univariate and multivariate analyses. We also constructed nomograms and calibration curves to predict the probability of anxiety and depression. A total of 800 people completed the questionnaire. 239 (29.9%) of them were doctors, 249 (31.1%) of them were nurses and 312 (39.0%) of them were others. There were 173 (21.6%) cases had anxiety, including 36 (20.8%) doctors, 76 (43.9%) nurses and 61 (35.3%) from other occupations and 281 (35.1%) cases had depression, including 64 (22.8%) doctors, 101 (35.9%) nurses, and 116 (41.3%) from other occupations. Nurses had higher SAS and SDS score than doctors and others (F = 17.856, P < .001 and F = 14.376, P < .001). In addition, multivariate analysis found that occupation, education level, health condition, and reduced sleep were significant influences on anxiety and depression. At the same time, reduced income was also significantly associated with anxiety. During the local outbreak of COVID-19, hospital staff still had varying degrees anxiety and depression. Occupation, education level, health condition and reduced sleep were both significant influencing factors for anxiety and depression. The mental state of hospital staff, including nonmedical-related staff should still be taken seriously.

Solutions to SIR/SEIR epidemic models with exponential series: Numerical and non numerical approaches

This study revisits the mathematical SIR/SEIR epidemic models, aiming to introduce novel exponential-type series solutions. Beyond standard non-dimensionalization, we implement a successful rescaling technique that reduces the parameter count in classical epidemiology. Consequently, solutions for the SIR model are determined solely by the basic reproduction number and initial infected fractions. Similarly, the SEIR model requires only the transmission-to-recovery ratio and initial exposed fractions. We present both numerical and non numerical solutions, alongside elucidating the limitations on the existence of exponential-type series solutions. Our analysis reveals that these solutions are valid under two key conditions: endemic situations and early epidemic stages, where the basic reproduction number is close to one. We graphically illustrate the range of physical parameters guaranteeing the existence of non numerical exponential series solutions. However, for epidemic/pandemic outbreaks with significantly higher reproduction numbers, achieving complete convergence of the exponential series across the entire physical domain becomes impossible. In such cases, we divide the exponential series solution into two zones: from initial time to peak time and from peak time to the final epidemic time. For the first zone, where convergence is slow, we successfully employ Padé approximants to accelerate the convergence of the series. This accelerated solution is then smoothly joined to the second zone solution once the peak time is identified within the first region. The presented non numerical solutions are envisioned to serve as valuable benchmarks for testing and enhancing other numerical approaches used to solve epidemic models and their variants.

Microfluidic methods for the diagnosis of acute respiratory tract infections

Acute respiratory tract infections (ARTIs) are caused by sporadic or pandemic outbreaks of viral or bacterial pathogens, and continue to be a considerable socioeconomic burden for both developing and industrialized countries alike. Diagnostic methods and technologies serving as the cornerstone for disease management, epidemiological tracking, and public health interventions are evolving continuously to keep up with the demand for higher sensitivity, specificity and analytical throughput. Microfluidics is becoming a key technology in these developments as it allows for integrating, miniaturizing and automating bioanalytical assays at an unprecedented scale, reducing sample and reagent consumption and improving diagnostic performance in terms of sensitivity, throughput and response time. In this article, we describe relevant ARTIs-pneumonia, influenza, severe acute respiratory syndrome, and coronavirus disease 2019-along with their pathogenesis. We provide a summary of established methods for disease diagnosis, involving nucleic acid amplification techniques, antigen detection, serological testing as well as microbial culture. This is followed by a short introduction to microfluidics and how flow is governed at low volume and reduced scale using centrifugation, pneumatic pumping, electrowetting, capillary action, and propagation in porous media through wicking, for each of these principles impacts the design, functioning and performance of diagnostic tools in a particular way. We briefly cover commercial instruments that employ microfluidics for use in both laboratory and point-of-care settings. The main part of the article is dedicated to emerging methods deriving from the use of miniaturized, microfluidic systems for ARTI diagnosis. Finally, we share our thoughts on future perspectives and the challenges associated with validation, approval, and adaptation of microfluidic-based systems.

THE IMPACT OF THE COVID-19 PANDEMIC RESTRICTIVE MEASURES ON THE DIAGNOSIS OF ADENOMATOUS POLYPS AND COLORRECTAL ADENOCARCINOMA IN A POPULATION SUBMITTED TO COLONOSCOPY

BACKGROUND

•The impact of the COVID-19 pandemic on the diagnosis of adenomatous polyps and colorectal cancer.

BACKGROUND

•A cross-sectional study evaluating COL performed during the periods from 20 March to 31 October of 2019 and of 2020, which analyzed 10,232 colonoscopies.

BACKGROUND

•There was a 51,0% reduction in the number of COL performed in 2020 when compared to 2019. Of the altered exams, adenomatous polyps were diagnosed in 68.8% in 2019 and 78.3% in 2020. CRC was diagnosed in 0.9% in 2019 and 1.6% in 2020.

BACKGROUND

•The increase in adenomatous polyps and colorectal cancer diagnoses was observed, it was not enough to compensate for the reduction in the number of exams.

BACKGROUND

Colorectal cancer (CRC) is globally the third most common malignant neoplasm and the second leading cause of cancer-related death worldwide. The COVID-19 pandemic led to the suspension of routine screening tests by health services. A 35.5% drop in total cancer diagnoses in 2020 is estimated when compared to 2019.

OBJECTIVE

To evaluate the impact of the COVID-19 pandemic on the diagnosis of adenomatous polyps (AP) and CRC in a population undergoing colonoscopy (COL) in a clinic in Goiânia, Brazil.

METHODS

A cross-sectional study evaluating COL performed during the periods from 20 March to 31 October of 2019 and of 2020, was approved by the Research Ethics Committee (CAAE-45631421.0.0000.0037). We analyzed data related to identification, referral for medical examination, colonoscopic and histopathological findings.

RESULTS

We evaluated 10,232 (93.4%) COL, divided into two groups according to the year of performance. In 2019, 6,777 (66.2%) COL were performed and in 2020, 3,455 (33.8%), demonstrating a reduction of 51.0%. A total of 3,267 (31.9%) colonoscopies found polyps, 72.1% of which were AP (68.8% in 2019 and 78.3% in 2020, P<0.001). High-grade dysplasia was found in 5.0% of the AP (4.9% in 2019 and 5.8% in 2020, P<0.34). CRC was diagnosed in 121 (1.2%) (0.9% in 2019 and 1.6% in 2020, P<0.001).

CONCLUSION

The COVID-19 pandemic significantly reduced COL in 2020, mainly due to infection fears and restrictions. However, the detection rate of cancer and polyps per procedure increased, indicating more symptomatic patients sought medical attention. Despite this, the absolute number of tumors and adenomas found decreased, potentially causing diagnostic losses and fewer prevented colorectal cancer cases. Thus, adaptive strategies are vital for maintaining essential healthcare services during similar crises.

COVID-19-induced extracorporeal circulation coagulation during continuous renal replacement therapy: A cross-sectional study

After the control policies of the COVID-19 epidemic were lifted in China from December 5th, 2022, there was an increase in the demand for hemodialysis and continuous renal replacement therapy (CRRT) at our center, and patients experienced hypercoagulable blood states more frequently. This study aimed to investigate the effect of COVID-19 on extracorporeal coagulation during CRRT. All CRRT records were gathered from the Hemodialysis Center at our hospital from December 5th, 2022 to February 4th, 2023, and analyzed the incidence and risk factors associated with extracorporeal coagulation. COVID-19 substantially increased the likelihood of extracorporeal coagulation during CRRT. Venous pressure and transmembrane pressure were proportional to the severity of extracorporeal coagulation. Additionally, non-tunnel type conduit vascular access, and acute kidney injury had a positive correlation with the severity of coagulation. Blood tests demonstrated that COVID-19 altered 4 coagulation indices. Moreover, mitigation of coagulation can be achieved through increasing the dosage of low molecular weight heparin and administering regional citrate anticoagulation. Patients who fail anticoagulation may be switched to peritoneal dialysis. In conclusion, COVID-19 poses a heightened risk of extracorporeal coagulation during CRRT. This study underscores the importance of anticoagulant treatment in CRRT for infected patients with kidney failure and holds significant implications for clinical practice. In future, the epidemics of COVID-19 or any other pandemic, the metrics in this study can be referenced to determine coagulation risk, as well as relevant therapeutic practices may be considered.

Impact of Immunosuppressants and Vaccination on COVID-19 Outcomes in Autoimmune Patients and Solid Organ Transplant Recipients: A Nationwide Propensity Score-Matched Study

PURPOSE

This study investigates the impact of varying degrees of immunosuppression on the clinical outcomes of immunocompromised individuals, particularly those with autoimmune diseases or post-solid organ transplant statuses, in the context of COVID-19. By focusing on these highly vulnerable populations, the study underscores the significant health inequalities faced by immunocompromised patients, who experience disproportionately worse outcomes in comparison to the general population.

METHODS

A retrospective cohort analysis of the K-COV-N dataset was conducted, comparing the effects of immunosuppression in autoimmune and transplant groups with matched control groups. Propensity score matching was employed to minimize inequalities in baseline characteristics, ensuring a more equitable comparison between immunocompromised and non-immunocompromised individuals. Outcomes included COVID-19-related in-hospital mortality, 28-day mortality, ICU admissions, and the need for respiratory support among 323,890 adults in the Republic of Korea. Patients with cancer or other immunosuppressive conditions, such as HIV, were excluded. Subgroup analyses assessed the influence of specific immunosuppressive medications and vaccination extent.

RESULTS

Significantly elevated in-hospital mortality was found for patients with autoimmune diseases (adjusted Odds Ratio [aOR] 2.749) and transplant recipients (aOR 7.567), with similar patterns in other outcomes. High-dose steroid use and a greater number of immunosuppressant medications markedly increased the risk of poor outcomes. Vaccination emerged as a protective factor, with a single dose substantially improving outcomes for autoimmune patients and at least two doses necessary for transplant recipients.

CONCLUSIONS

Immunocompromised patients, particularly those with autoimmune diseases and transplant recipients, are highly vulnerable to severe COVID-19 outcomes. High-dose steroid use and multiple immunosuppressants further increase risks. Vaccination significantly improves outcomes, with at least one dose benefiting autoimmune patients and two doses necessary for transplant recipients. Personalized vaccination schedules based on immunosuppression levels are essential to mitigate healthcare inequalities and improve outcomes, particularly in underserved populations, informing both clinical and public health strategies.

A vaccination-based COVID-19 model: Analysis and prediction using Hamiltonian Monte Carlo

Compartmental models have emerged as robust computational frameworks and have yielded remarkable success in the fight against COVID-19. This study proposes a vaccination-based compartmental model for COVID-19 transmission dynamics. The model reflects the specific stages of COVID-19 infection and integrates a vaccination strategy, allowing for a comprehensive analysis of how vaccination rates influence the disease spread. We fit this model to daily confirmed COVID-19 cases in Tennessee, United States of America (USA), from June 4 to November 26, 2021, in a Bayesian inference approach using the Hamiltonian Monte Carlo (HMC) algorithm. First, excluding vaccination dynamics from the model, we estimated key epidemiological parameters like infection, recovery, and disease-induced death rates. This analysis yielded a basic reproduction number (R 0 ) of 1.5. Second, we incorporated vaccination dynamics and estimated the vaccination rate for three vaccines: 0.0051 per day for both Pfizer and Moderna and 0.0059 per day for Janssen. The fitted curves show reductions in the epidemic peak for all three vaccines. Pfizer and Moderna vaccines bring the peak down from 8,029 infected cases to 5,616 infected cases, while the Janssen vaccine reduces it, to 6,493 infected cases. Simulations of the model by varying the vaccination rate and vaccine efficacy were performed. A highly effective vaccine (95% efficacy) with a daily vaccination rate of 0.006 halved COVID-19 infections, reducing cases from 8,029 to around 4,000. The results also show that the model's prediction accuracy for new observations improves with the number of observed data used to train the model.

COVID-19 is associated with cardiac structural and functional remodelling in healthy middle-aged and older individuals

BACKGROUND

Coronavirus disease 2019 (COVID-19) was declared a global pandemic in 2019. It remains uncertain to what extent COVID-19 effects the heart in heathy individuals. To evaluate the effect of the COVID-19 on cardiac structure and function in middle-aged and older individuals.

METHODS

A single-centre prospective observational study enroled a total of 124 participants (84 with history of COVID-19 [COVID-19 group] and 40 without a history of COVID-19 [non-COVID group]). All participants underwent echocardiography with speckle tracking to assess cardiac structure and function at rest and during peak exercise.

RESULTS

There were no differences in left and right ventricular diastolic function (p ≥ 0.05) between the COVID-19 and non-COVID-19 groups. Participants in COVID-19 group demonstrated higher left ventricular mass (130 ± 39.8 vs. 113 ± 27.2 g, p = 0.008) and relative wall thickness (0.38 ± 0.07 vs. 0.36 ± 0.13, p = 0.049). Left ventricular global longitudinal strain was reduced in the COVID-19 group at rest and at peak-exercise (rest: 18.3 ± 2.01 vs. 19.3 ± 1.53%, p = 0.004; peak exercise: 19.1 ± 2.20 vs. 21.0 ± 1.58%, p ≤ 0.001). However, no difference was seen in resting left ventricular ejection fraction (58 ± 2.89 vs. 59 ± 2.51%, p = 0.565) between groups. Right ventricular fractional area change was reduced in the COVID-19 group (p = 0.012).

CONCLUSION

Cardiac structural and functional remodelling was observed in middle-aged and older otherwise healthy individuals with a history of COVID-19.

Evaluation of the mental health status of intensive care unit healthcare workers at the beginning of COVID-19 pandemic

Objective

During pandemic periods, mental health issues are highly prevalent, particularly among healthcare workers who are at a higher risk of developing psychiatric disorders. The aim of this study is to evaluate the mental health status of the intensive care unit (ICU) healthcare workers, who play a vital role in managing the COVID-19 pandemic, in terms of the quality of sleep, levels of depressive and anxiety symptoms, stress and to determine the factors that affect their mental health.

Methods

The research was conducted in April 2020 and incorporated a total of 79 participants working in an university hospital ICUs in Turkey. Pittsburgh Sleep Quality Index (PSQI), Depression Anxiety Stress Scale 42 (DASS-42), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) were applied.

Results

Among the participants, 58 individuals comprising 73.4% of the cohort were working in the ICUs, managing patients infected with COVID-19. Those working in ICUs with COVID-19 patients had significantly higher DASS-S, BAI, and BDI scores. Doctors' BDI scores were significantly lower compared to both nurses and other healthcare workers. Participants exhibiting COVID-19 symptoms manifested significantly higher BAI scores in compared to those without such symptoms.

Conclusion

Healthcare workers involved in ICUs with COVID-19 patients were more significantly affected psychologically, doctors had lower depressive symptoms as compared to other healthcare workers. In addition, individuals with COVID-19 symptoms demonstrated significantly higher levels of anxiety. The findings of our study emphasize the significance of providing psychological support to healthcare workers throughout pandemics.

Exploring Niclosamide as a Multi-target Drug Against SARS-CoV-2: Molecular Dynamics Simulation Studies on Host and Viral Proteins

Niclosamide has emerged as a promising repurposed drug against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In vitro studies suggested that niclosamide inhibits the host transmembrane protein 16F (hTMEM16F), crucial for lipid scramblase activity, which consequently reduces syncytia formation that aids viral spread. Based on other in vitro reports, niclosamide may also target viral proteases such as papain-like protease (PLpro) and main protease (Mpro), essential for viral replication and maturation. However, the precise interactions by which niclosamide interacts with these multiple targets remain largely unclear. Docking and molecular dynamics (MD) simulation studies were undertaken based on a homology model of the hTMEM16F and available crystal structures of SARS-CoV-2 PLpro and Mpro. Niclosamide was observed to bind stably throughout a 400 ns MD simulation at the extracellular exit gate of the hTMEM16F tunnel, forming crucial interactions with residues spanning the TM1-TM2 loop (Gln350), TM3 (Phe481), and TM5-TM6 loop (Lys573, Glu594, and Asp596). Among the SARS-CoV-2 proteases, niclosamide was found to interact effectively with conserved active site residues of PLpro (Tyr268), exhibiting better stability in comparison to the control inhibitor, GRL0617. In conclusion, our in silico analyses support niclosamide as a multi-targeted drug inhibiting viral and host proteins involved in SARS-CoV-2 infections.

Children with sickle cell disease: are they protected from serious COVID-19?

Background

COVID-19, the pandemic that hit the world in 2020, resulted in millions of deaths, with the elderly and adults succumbing to the disease more often than children. However, the presence of underlying morbidities increased the risk of death. Sickle cell disease (SCD) was previously classified as a major risk factor for severe COVID-19 disease. However, presently, there are only a limited number of studies that identify the clinical course of children with SCD and COVID-19.

Methods

We conducted a retrospective observational study on children with SCD admitted due to COVID-19 at three different institutions in Saudi Arabia between March 2020 and March 2022. We studied the demographic and clinical characteristics of patients admitted to the hospital.

Results

Seventy-six patients with SCD had PCR-confirmed SARS-CoV-2 during the study period; 50.0% of our patient population were children (6-12 years old). Gender was evenly distributed, with 53.9% girls and 46.1% boys. Symptoms more commonly related to the COVID-19 infection included fever, cough, malaise, and vomiting. Chest x-ray findings revealed mild and non-specific symptoms only in approximately one-third (28) of the included children. The most common symptoms associated with SCD were vaso-occlusive crisis (47.4%) and abdominal pain (11.8%). The overall general appearance of most of the patients was reassuring. The median length of hospital stay was 4.2 ± 2.7 days. The mean white blood cell count was 11.4 ± 5.2 × 109/L, and the mean hemoglobin level was 8.3 ± 1.5 g/dl. Despite the fact that higher levels of mean D-dimer, lactate dehydrogenase, and ferritin were reported in these patients, the clinical outcome was not affected. All recruited patients received hydroxyurea as maintenance therapy. The outcome of our study was reassuring, with no significant morbidity or mortality observed among the recruited patients.

Conclusion

Despite SCD being a chronic disease with known specific complications, there has been a claim that COVID-19 infection adds further risk. The results of this study suggest that the overall outcome of COVID-19 was favorable, with no reported mortality. Further research is needed to understand the factors that contributed to this favorable outcome. In children with SCD, it is still questionable whether hydroxyurea is one of the protective factors against severe COVID-19. Validation through large-scale research is recommended.

The Peculiar Emergence of Mpox (Monkeypox): Directions for the Search for the Natural Reservoir and Vaccination Strategies

Background/Objectives: Mpox (monkeypox) is a zoonosis with origins in a currently unknown African reservoir. The first epidemiological accounts of mpox date back to the early 1980s, yet mpox only emerged as a pandemic threat in 2022-2023, more than 40 years later. This scenario is very different from those of other emerging diseases such as HIV and SARS, which immediately spread globally, in fully susceptible populations, starting from patients zero. Methods: We use mathematical modeling to illustrate the dynamics of mpox herd immunity in small communities in touch with the mpox natural reservoir. In particular, we employ an SEIR stochastic model. Results: The peculiar emergence of mpox can be explained by its relationship with smallpox, which was eradicated through universal mass vaccination in 1980. Mpox first emerged in small rural communities in touch with mpox's animal reservoir and then spread globally. The relative isolation of these communities and their herd-immunity dynamics against mpox worked to delay the introduction of mpox in large urban centers. Conclusions: Mathematical modeling suggests that the search for the mpox animal reservoir would be most fruitful in communities with high mpox seroprevalence and small outbreaks. These are communities is tight contact with the mpox natural reservoir. We propose vaccinating individuals in communities in these communities to severely reduce the importation of cases elsewhere.

Changes in household use of disinfectant and cleaning products during the first lockdown period in France

BACKGROUND

Few studies evaluated the use of Household Disinfectant and Cleaning Products (HDCPs) during the COVID-19 pandemic, but no population-based cohorts used longitudinal data. We studied changes in HDCPs during the first lockdown, based on longitudinal data from the French population-based NutriNet-Santé and CONSTANCES cohorts.

METHODS

Based on standardized questionnaires on household cleaning tasks in 2018-2019 and around the first lockdown in France (March17-May3 2020), we compared the duration of weekly use of HDCPs (< 1 day/week, < 10 min/week; 10-30 min/week; > 30 min/week) and the household cleaning help (yes/no) before and during the lockdown period by Bhapkar and McNemar's tests. Moreover, we assessed self-reported changes in the frequency of HDCPs during the lockdown from before (unchanged/increased).

RESULTS

Analyses were carried on 31,105 participants of NutriNet-Santé (48 years, 75% women, 81% ≥ high school diploma) and 49,491 of CONSTANCES (47 years, 51% women, 87% ≥ high school diploma). During the lockdown, compared with 2018-2019, duration of HDCPs use increased (> 30 min; NutriNet-Santé: 44% versus 18%; CONSTANCES: 63% versus 16%) and household help decreased (NutriNet-Santé: 5% versus 40%; CONSTANCES: 3% versus 56%). Regarding the frequency of HDCPs use, 55% of participants of NutriNet-Santé (57% women/49% men) and 83% of CONSTANCES (86% women/81% men) reported an increased use since the beginning of the lockdown, significantly higher among women (p < 0.0001).

CONCLUSIONS

The frequency and duration of weekly use of HDCPs has significantly increased since the pandemic. As the use of HDCPs is associated with health issues, further studies are now needed to evaluate the potential health impacts of these changes.

The SARS-unique domain (SUD) of SARS-CoV-2 nsp3 protein inhibits the antiviral immune responses through the NF-κB pathway

Nuclear factor κB (NF-κB) plays a crucial role in various cellular processes, including inflammatory and immune responses. Its activation is tightly regulated by the IKK (IκB kinase) complex. Upon severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the virus is initially recognized by the innate immune system and typically activates the NF-κB pathway, leading to a severe inflammatory response. However, the influence of viral proteins upon pro-inflammatory pathway is complicated. Here, we demonstrated that the viral protein nsp3 of SARS-CoV-2 exhibits an unusual function, which attenuated the NF-κB-mediated inflammatory response against SARS-CoV-2 infection in a unique manner. nsp3 interacted with the essential NF-κB modulator NEMO/IKKγ and promoted its polyubiquitylation via the E3 ubiquitin ligase CBL (Cbl Proto-Oncogene). Consequently, polyubiquitylated NEMO undergoes proteasome-dependent degradation, which disrupts NF-κB activation. Moreover, we found that the SARS unique domain (SUD) in nsp3 of SARS-CoV-2 is essential for inducing NEMO degradation, whereas this function is absent in SUD of SARS-CoV. The reduced activation of pro-inflammatory response at an early stage could mask the host immune response and faciliate excessive viral replication. Conversely, this finding may partially explain why SARS-CoV-2 causes a less inflammatory reaction than SARS-CoV, resulting in more mild or moderate COVID-19 cases and greater transmissibility. Given that NEMO is important for NF-κB activation, we propose that inhibiting polyubiquitylation and degradation of NEMO upon SARS-CoV-2 infection is a novel strategy to modulate the host inflammatory response.

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population

BACKGROUND

With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application.

METHODS

Our study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules.

RESULTS

The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001).

CONCLUSIONS

Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

The Impact of the COVID-19 Pandemic on the Stroke Unit of a Portuguese Community Hospital

It is essential to understand the consequences of the COVID-19 pandemic on stroke care, contemplating the potential health and economic consequences of missed diagnoses or treatments. This study examined the pandemic's effects on stroke epidemiology, clinical characteristics, and treatment in a hospital setting, comparing data from March 2020 to February 2021 with the homologous period the previous year. A secondary analysis focused on the state of emergency periods (March 19 to May 2 and November 6 to February 28). The sample included 730 stroke admissions, with 343 during the pandemic. There was a 24.75% reduction in the average daily occupancy rate (p<0.001) and a slight decrease in average daily admissions, especially in June from 132% to 74% (p=0.01). There was a moderate negative correlation between the number of COVID-19 cases and occupancy rates in January (r{s}=-0.422, p=0.01) and February (r{s}=-0.532, p=0.01). Admissions for ischemic stroke decreased by 7.2% (p=0.026), particularly mild events, with a 6.8% decrease in lacunar syndromes (p=0.048). Mechanical thrombectomy (MT) increased by 5.4% (p=0.046), while intravenous thrombolysis (IVT) decreased by 2.8% (p=0.048), especially in severe stroke cases (-21.4%, p=0.001). The pandemic period documented more MT procedures than IVT. Hemorrhagic stroke admissions increased by 6.7% (p=0.01). The analysis suggests a reduction in mild ischemic stroke admissions and fewer patients undergoing IVT for severe strokes during the pandemic. Broader-scale studies are necessary to confirm these findings. Considering the documented decline in diagnosis and treatment, minimizing the impact on stroke care during potential sanitary crises is paramount.

Rapid response to a COVID-19 outbreak at a nightclub in Kagoshima prefecture, Japan, in the early phase of the COVID-19 pandemic, June and July 2020: A descriptive epidemiological study

INTRODUCTION

During COVID-19 pandemic in Japan, nightclubs were identified as high-risk locations for COVID-19 outbreaks, but an outbreak investigation in this setting is challenging because of the anonymous and opportunistic nature of interactions.

METHODS

The joint rapid response team collected epidemiological data, conducted descriptive epidemiology to determine the characteristics of cases associated with the nightclub, and implemented countermeasures. Polymerase chain reaction (PCR) tests were performed by the Local Institute of Public Health, Kagoshima University, and several commercial laboratories.

RESULTS

Between June 15 and July 20, 2020, 121 individuals tested positive for SARS-CoV-2 (59 confirmed and 62 asymptomatic) of whom 8 were nightclub staff who had no travel history of outside Kagoshima, 66 were guests, and 47 were subsequent contacts. The median age was 32 years (interquartile range: 24-43 years). One individual showed severe symptoms but there were no fatal. The epidemic curve showed one peak on June 30 and July 1 with a limited number of cases subsequently. Of the 121 cases, 116 and 5 were in individuals living in and outside Kagoshima Prefecture, respectively. Haplotype network analysis showed 5 genome-wide single-nucleotide variants between the isolates before and during this outbreak.

CONCLUSIONS

There is a possibility that unidentified guests from outside Kagoshima Prefecture could infect staff who could subsequently spread the virus to guests and other staff, who were mainly a younger population. The rapid outbreak response enabled onward transmission in the community to be minimized. This outbreak investigation could provide insights for effective responses to challenging situations in future pandemic.

Evaluation of the therapeutic action of original antiviral drug in SARS-CoV-2

Purpose of this article is to study the possible direct antiviral effect of "Armenikum" on SARS-CoV-2, conduct an in vitro study on the SARS-CoV-2 encephalomocarditis virus, and an in vivo study on the Syrian hamster model. Human coronavirus SARS-CoV-2 (delta strain) was used as the virus. Two groups of four-specimen hamsters were used to study the therapeutic activity of the drug during 48 h after infecting. One group of hamsters served as positive control and was infected with the virus at a similar dose as experimental one and was used as a control of pathology induced by the viral infection till the end of the experiment. Another group of hamsters (four of them) was injected physiological solution and was used as a control. The Syrian hamsters underwent a clinical blood test and computed tomography. "Armenikum" in the form of an injection has a significant antiviral effect on the human coronavirus SARS-CoV-2, credibly reducing the titers of the virus and the time of its elimination from the Syrian hamsters, significantly mitigating the viral infection. "Armenikum" in the form of an injection drug almost completely removes the pathological effect of the virus in the lungs of the hamsters.

The first five years of SARS-CoV-2: inpatient treatment updates and future directions

INTRODUCTION

In December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in adults with pneumonia in Wuhan, China.

AREAS COVERED

It is now believed that several billion humans have been infected with SARS-CoV-2 and more than ten million have died from coronavirus disease 2019 (COVID-19), the disease caused by SARS-CoV-2.

EXPERT OPINION

The first five years of the SARS-CoV-2 pandemic have been marked by unfathomable suffering as well as remarkable scientific progress. This manuscript examines what has been learned about the treatment of inpatients with COVID-19 and explores how the therapeutic approach may evolve in the years ahead.

Metabolic changes assessed by 1H MR spectroscopy in the corpus callosum of post-COVID patients

OBJECTIVE

Many patients with long COVID experience neurological and psychological symptoms. Signal abnormalities on MR images in the corpus callosum have been reported. Knowledge about the metabolic profile in the splenium of the corpus callosum (CCS) may contribute to a better understanding of the pathophysiology of long COVID.

MATERIALS AND METHODS

Eighty-one subjects underwent proton MR spectroscopy examination. The metabolic concentrations of total N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (Cr), myo-inositol (mI), and NAA/Cho in the CCS were statistically compared in the group of patients containing 58 subjects with positive IgG COVID-19 antibodies or positive SARS-CoV-2 qPCR test at least two months before the MR and the group of healthy controls containing 23 subjects with negative IgG antibodies.

RESULTS

An age-dependent effect of SARS-CoV-2 on Cho concentrations in the CCS has been observed. Considering the subjective threshold of age = 40 years, older patients showed significantly increased Cho concentrations in the CCS than older healthy controls (p = 0.02). NAA, Cr, and mI were unchanged. All metabolite concentrations in the CCS of younger post-COVID-19 patients remained unaffected by SARS-CoV-2. Cho did not show any difference between symptomatic and asymptomatic patients (p = 0.91).

DISCUSSION

Our results suggest that SARS-CoV-2 disproportionately increases Cho concentration in the CCS among older post-COVID-19 patients compared to younger ones. The observed changes in Cho may be related to the microstructural reorganization in the CCS also reported in diffusion measurements rather than increased membrane turnover. These changes do not seem to be related to neuropsychological problems of the post-COVID-19 patients. Further metabolic studies are recommended to confirm these observations.

Epigallocatechin-3-Gallate Inhibits Atrial Fibrosis and Reduces the Occurrence and Maintenance of Atrial Fibrillation and its Possible Mechanisms

BACKGROUND

Atrial fibrosis is one of the main causes of the onset and recurrence of atrial fibrillation (AF), for which there is no effective treatment. The aim of this study was to investigate the effect and mechanism of epigallocatechin-3-gallate (EGCG) on AF in rats.

METHODS

The rat model of AF was established by rapid pacing induction after angiotensin-II (Ang-II) induced atrial fibrosis to verify the relationship between atrial fibrosis and the AF. The expression levels of TGF-β/Smad3 pathway molecules and lysyl oxidase (LOX) in AF were detected. Subsequently, EGCG was used to intervene Ang-II-induced atrial fibrosis to explore the role of EGCG in the treatment of AF and its inhibitory mechanism on fibrosis. It was further verified that EGCG inhibited the production of collagen and the expression of LOX through the TGF-β/Smad3 pathway at the cellular level.

RESULTS

The results showed that the induction rate and maintenance time of AF in rats increased with the increase of the degree of atrial fibrosis. Meanwhile, the expressions of Col I, Col III, molecules related to TGF-β/Smad3 pathway, and LOX increased significantly in the atrial tissues of rats in the Ang-II induced group. EGCG could reduce the occurrence and maintenance time of AF by inhibiting the degree of Ang-induced rat atrial fibrosis. Cell experiments confirmed that EGCG could reduce the synthesis of collagen and the expression of LOX in cardiac fibroblast induced by Ang-II. The possible mechanism is to down-regulate the expression of genes and proteins related to the TGF-β/Smad3 pathway.

CONCLUSION

EGCG could downregulate the expression levels of collagen and LOX by inhibiting the TGF-β/Smad3 signaling pathway, alleviating Ang-II-induced atrial fibrosis, which in turn inhibited the occurrence and curtailed the duration of AF.

The optimal spatially-dependent control measures to effectively and economically eliminate emerging infectious diseases

Non-pharmaceutical interventions (NPIs) are effective in mitigating infections during the early stages of an infectious disease outbreak. However, these measures incur significant economic and livelihood costs. To address this, we developed an optimal control framework aimed at identifying strategies that minimize such costs while ensuring full control of a cross-regional outbreak of emerging infectious diseases. Our approach uses a spatial SEIR model with interventions for the epidemic process, and incorporates population flow in a gravity model dependent on gross domestic product (GDP) and geographical distance. We applied this framework to identify an optimal control strategy for the COVID-19 outbreak caused by the Delta variant in Xi'an City, Shaanxi, China, between December 2021 and January 2022. The model was parameterized by fitting it to daily case data from each district of Xi'an City. Our findings indicate that an increase in the basic reproduction number, the latent period or the infectious period leads to a prolonged outbreak and a larger final size. This indicates that diseases with greater transmissibility are more challenging and costly to control, and so it is important for governments to quickly identify cases and implement control strategies. Indeed, the optimal control strategy we identified suggests that more costly control measures should be implemented as soon as they are deemed necessary. Our results demonstrate that optimal control regimes exhibit spatial, economic, and population heterogeneity. More populated and economically developed regions require a robust regular surveillance mechanism to ensure timely detection and control of imported infections. Regions with higher GDP tend to experience larger-scale epidemics and, consequently, require higher control costs. Notably, our proposed optimal strategy significantly reduced costs compared to the actual expenditures for the Xi'an outbreak.

Science-based exit from stringent countermeasures against COVID-19: Mortality prediction using immune landscape between 2021 and 2022 in Japan

Background

Stringent public health and social measures against COVID-19 infection were implemented to avoid an overwhelming hospital caseload and excessive number of deaths, especially among elderly people. We analyzed population-level immunity and predicted mortality, calculated as the potential number of deaths on a given calendar date in Japan, to develop a science-based exit strategy from stringent control measures.

Methods

Immune proportions were inferred by age group using vaccination coverage data and the estimated number of naturally infected individuals. Immunity against symptomatic illness and death were estimated separately, allowing for inference of the immune fraction that was protected against either COVID-19-related symptomatic infection or death. By multiplying the infection fatality risk by age group for the immune fraction, the potential number of deaths was obtained.

Results

Accounting for a second and third dose of messenger RNA vaccine in the present-day population, approximately 155,000 potential deaths would be expected among people aged ≥ 60 years if all individuals were infected at the very end of 2022. A fourth dose (i.e., second booster) with a coverage identical to that of the third dose could reduce mortality by 60%. In all examined settings, the largest number of deaths occurred among people aged 80 years and older.

Conclusions

Our estimates can help policymakers understand the mortality impact of the COVID-19 epidemic in a quantitative manner and the critical importance of timely immunization so as to assist in decision making.

Research progress on the use of Salvia miltiorrhiza Bunge extracts in the treatment of pulmonary diseases

Salvia miltiorrhiza Bunge extracts, known for their diverse biological activities, often have remarkable efficacy in treating pulmonary diseases overlooked due to their specific cardiovascular actions. With the recent outbreak of COVID-19, research into pulmonary-related diseases has garnered significant attention. Salvia miltiorrhiza Bunge extracts can be broadly categorized into lipophilic and hydrophilic components; however, a comprehensive summary of their mechanisms in treating pulmonary diseases is lacking. Therefore, this review aims to systematically summarize the therapeutic mechanisms of 10 major Salvia miltiorrhiza Bunge extracts in treating pulmonary fibrosis, lung cancer, acute lung injury, and chronic obstructive pulmonary disease, with the goal of identifying promising options for efficacious therapies.

Obesity as a Risk Factor for the Severity of COVID-19 in Pediatric Patients: Possible Mechanisms-A Narrative Review

Obesity, the current pandemic, is associated with alarming rises among children and adolescents, and the forecasts for the near future are worrying. The present paper aims to draw attention to the short-term effects of the excess adipose tissue in the presence of a viral infection, which can be life-threatening for pediatric patients, given that the course of viral infections is often severe, if not critical. The COVID-19 pandemic has been the basis of these statements, which opened the door to the study of the repercussions of obesity in the presence of a viral infection. Since 2003, with the discovery of SARS-CoV-1, interest in the study of coronaviruses has steadily increased, with a peak during the pandemic. Thus, obesity has been identified as an independent risk factor for COVID-19 infection and is correlated with a heightened risk of severe outcomes in pediatric patients. We sought to determine the main mechanisms through which obesity is responsible for the unfavorable evolution in the presence of a viral infection, with emphasis on the disease caused by SARS-CoV-2, in the hope that future studies will further elucidate this aspect, enabling prompt and effective intervention in obese patients with viral infections, whose clinical progression is likely to be favorable.

Myelin oligodendrocyte glycoprotein-associated transverse myelitis after SARS-CoV-2 infection: A case report

BACKGROUND

Cases of myelin oligodendrocyte glycoprotein (MOG) antibody-related disease have a history of coronavirus disease 2019 infection or its vaccination before disease onset. Severe acute respiratory syndrome virus 2 (SARS-CoV-2) infection has been considered to be a trigger of central nervous system autoimmune diseases.

CASE SUMMARY

Here we report a 20-year male with MOG-associated transverse myelitis after a SARS-CoV-2 infection. The patient received a near-complete recovery after standard immunological treatments.

CONCLUSION

Attention should be paid to the evaluation of typical or atypical neurological symptoms that may be triggered by SARS-CoV-2 infection.

Biomechanics Model to Characterize Atomic Force Microscopy-Based Virus-Host Cell Adhesion Measurements

We present a model for virus-cell adhesion that can be used for quantitative extraction of adhesive properties from atomic force microscopy (AFM)-based force spectroscopy measurements. We extend a previously reported continuum model of viral cell interactions based on a single parameter representing adhesive energy density by using a cohesive zone model in which adhesion is represented by two parameters, a pull-off stress and associated characteristic displacement. This approach accounts for the deformability of the adhesive receptors, such as the Spike protein and transmembrane immunoglobulin and mucin domain (TIM) family that mediate adhesion of SARS-CoV-2 and Ebola viruses, and the omnipresent glycocalyx. Our model represents receptors as a Winkler foundation and aims to predict the pull-off force needed to break the adhesion between the virus and the cell. By comparing the force-separation curves simulated by the model and experimental data, we found that the model can effectively explain the AFM pull-off force trace, thus allowing quantification of the adhesion parameters. Our model provides a more refined understanding of viral cell adhesion and also establishes a framework for interpreting and predicting AFM force spectroscopy measurements.

Automating COVID-19 epidemiological situation reports based on multiple data sources, the Netherlands, 2020 to 2023

BACKGROUND

During the COVID-19 pandemic, the National Institute for Public Health and the Environment in the Netherlands developed a pipeline of scripts to automate and streamline the production of epidemiological situation reports (epi‑sitrep). The pipeline was developed for the Automation of Data Import, Summarization, and Communication (hereafter called the A-DISC pipeline).

OBJECTIVE

This paper describes the A-DISC pipeline and provides a customizable scripts template that may be useful for other countries wanting to automate their infectious disease surveillance processes.

METHODS

The A-DISC pipeline was developed using the open-source statistical software R. It is organized in four modules: Prepare, Process data, Produce report, and Communicate. The Prepare scripts set the working environment (e.g., load packages). The (data-specific) Process data scripts import, validate, verify, transform, save, analyze, and summarize data as tables and figures and store these data summaries. The Produce report scripts gather summaries from multiple data sources and integrate them into a RMarkdown document - the epi‑sitrep. The Communicate scripts send e-mails to stakeholders with the epi‑sitrep.

RESULTS

As of March 2023, up to ten data sources were automatically summarized into tables and figures by A-DISC. These data summaries were featured in routine extensive COVID-19 epi‑sitreps, shared as open data, plotted on RIVM's website, sent to stakeholders and submitted to European Centre for Disease Prevention and Control via the European Surveillance System -TESSy [38].

DISCUSSION

In the face of an unprecedented high number of cases being reported during the COVID-19 pandemic, the A-DISC pipeline was essential to produce frequent and comprehensive epi‑sitreps. A-DISC's modular and intuitive structure allowed for the integration of data sources of varying complexities, encouraged collaboration among people with various R-scripting capabilities, and improved data lineage. The A-DISC pipeline remains under active development and is currently being used in modified form for the automatization and professionalization of various other disease surveillance processes at the RIVM, with high acceptance from the participant epidemiologists.

CONCLUSION

The A-DISC pipeline is an open-source, robust, and customizable tool for automating epi‑sitreps based on multiple data sources.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Seafood Wholesale Market. Here, we analyze environmental qPCR and sequencing data collected in the Huanan market in early 2020. We demonstrate that market-linked severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic diversity is consistent with market emergence and find increased SARS-CoV-2 positivity near and within a wildlife stall. We identify wildlife DNA in all SARS-CoV-2-positive samples from this stall, including species such as civets, bamboo rats, and raccoon dogs, previously identified as possible intermediate hosts. We also detect animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them with those from farms and other markets. This analysis provides the genetic basis for a shortlist of potential intermediate hosts of SARS-CoV-2 to prioritize for serological and viral sampling.

Impact of short-term exposure to ambient air pollutants and meteorological factors on COVID-19 incidence and mortality: A retrospective study from Dammam, Saudi Arabia

The symptoms of COVID-19 included fever with or without respiratory syndrome, but patients subsequently developed pulmonary abnormalities. Exposure to air pollution, meanwhile, is associated with complications such as acute respiratory inflammations, asthma attack, and deaths from cardiorespiratory disease. To analyze the association of the air quality index (AQI), ambient air pollutants (PM10, SO2 and O3) and meteorological parameters (temperature and relative humidity [RH]) with COVID-19 incidence and mortality, a retrospective study was conducted to examine COVID-19 infection, meteorological parameters, ambient air quality and ambient air pollutants in Dammam from 1 January to 30 April 2021. Data of COVID-19 incidence and mortality for Dammam were retrieved from Saudi Arabia Ministry of Health's publicly accessible database. Meteorological data, AQI and average PM10, SO2 and O3 values were extracted from the publicly available website of Ministry of Environment, Water and Agriculture. The correlation of COVID-19 incidence and mortality with the independent variables was analysed by Pearson's correlation test or Spearman's rho test as applicable, and a p-value less than 0.05 was considered significant. COVID-19 incidence exhibited a positive correlation with temperature (r = 0.537, p = .0001) and a negative correlation with RH (r=-0.487, p=.0001). No correlation was observed between the meteorological variables and COVID-19 mortality. COVID-19 incidence showed a positive correlation with AQI (r=0.269, p=.015) and with the ambient air pollutants SO2 and O3 (r=0.258, p=.018), and COVID-19 mortality showed a positive correlation with PM10 (r s  = 0.344, p=.002). Short-term exposure to O3, SO2 and higher temperature had direct relationship with COVID-19 incidence, while RH had inverse relationship. PM10 is positively associated with COVID-19 mortality.

Surveillance strategies for SARS-CoV-2 infections through one health approach

Coronavirus disease-2019 (COVID-19), caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), is an emergent disease that threatens global health. Public health structures and economic activities have been disrupted globally by the COVID-19 pandemic. Over 556.3 million confirmed cases and 6.3 million deaths have been reported. However, the exact mechanism of its emergence in humans remains unclear. SARS-CoV-2 is believed to have a zoonotic origin, suggesting a spillover route from animals to humans, which is potentially facilitated by wildlife farming and trade. The COVID-19 pandemic highlighted the importance of the One Health approach in managing threats of zoonosis in the human-animal-environment interaction. Implementing vigilant surveillance programs by adopting the One Health concept at the interfaces between wildlife, livestock, and humans is the most pertinent, practical, and actionable strategy for preventing and preparing for future pandemics of zoonosis, such as COVID-19 infection. This review summarizes the updated evidence of CoV infections in humans and animals and provides an appropriate strategy for preventive measures focused on surveillance systems through an On Health approach.

Oral Health Status and Dental Services Utilisation Among a Vulnerable Sample of Pregnant Women

INTRODUCTION AND AIMS

Oral health conditions during pregnancy can negatively impact both mother and fetus, highlighting the importance of maintaining dental care. In Canada, significant disparities exist between general and dental healthcare access, with limited evidence on oral health status and dental care utilisation among pregnant women. This study aimed to provide initial insights into self-perceived oral health status and dental utilisation patterns among a vulnerable sample of pregnant women in southwestern Ontario.

METHODS

This cross-sectional study recruited a convenient sample of pregnant women referred to the Family Medicine and Obstetrics Clinic, serving those without a family physician. Data were collected using a self-administered questionnaire adapted from the Canadian Health Measure Survey, the Canadian Community Health Survey, and the Survey of Maternal Health. Andersen and Newman's framework for health service utilisation was used as the theoretical framework. Descriptive and univariable analyses were conducted, followed by a forward stepwise selection of variables with p-values < 0.1 from the univariable analyses.

RESULTS

One-hundred-fifty patients were approached and 130 (86.7%) completed the questionnaire. Of these, 96 (73.9%) reported their oral health as good/excellent while 34 (26.2%) reported having poor/fair oral health. Education level and quality of life were the strongest predictors of oral health status. While 101 (77.7%) visited a dentist within the last 2 years, only 35 (26.9%) had a dental visit during pregnancy. Toothbrushing frequency was the main predictor of time since last dental visit, with no other predictive factors once toothbrushing was considered.

CONCLUSION

The study sample showed relatively positive self-perceived oral health and dental visit patterns. However, the low rate of dental visits during pregnancy highlights the need for better integration of dental care into prenatal care. To ensure maternal and child health, pregnant women should be a high priority in policies aimed at improving access to dental care.

Non-Conventional Prognostic Markers in Life-Threatening COVID-19 Cases-When Less Is More

Background/Objectives: In this study, we aimed to compare the predictive power of non-conventional (neutrophil/lymphocyte ratio-NLR; platelet/lymphocyte ratio-PLR) and conventional markers (C-reactive protein-CRP; procalcitonin-PCT; interleukin-6-IL-6) in terms of disease progression and mortality in severe SARS-CoV-2 patients. Methods: In this prospective observatory study, blood samples were collected daily, focusing on the established inflammatory markers. Critically ill COVID-19 patients who required ICU admission were included. Patient treatment followed established COVID-19 protocols, and the data analysis was performed using SPSS with non-normal distribution methods. The study cohort primarily included patients infected with the delta variant. Results: A mortality rate of 76.6% was observed among 167 patients during the study period. Significant differences in conventional and non-conventional markers between survivor and non-survivor groups were observed. The PCT levels were significantly elevated (p < 0.005) in the deceased group. Among the non-conventional markers, the NLR was consistently higher in non-survivors and emerged as a significant predictor of mortality, whereas the PLR was not elevated among the non-survivors. ROC analyses indicated that PCT and the NLR were the markers with the highest predictive power for mortality. The multivariate logistic regression analysis identified NLR, PCT, CRP, and IL-6 as significant predictors of mortality across different days. The NLR showed a consistent, though not always statistically significant, association with increased mortality risk, particularly on Days 2 and 5. Conclusions: The NLR's accessibility and simplicity of determination make it a valuable and practical tool for monitoring inflammatory processes in viral infections. Our findings suggest that incorporating NLR analysis into routine clinical practice could enhance the early identification of high-risk patients, thereby improving patient management and outcomes.

Immediate shock and residual stress: Unmasking the dual dynamics of covid-19 on the mental health of health professionals in China

Background

The pandemic of 2019 has created large scale disruption around the globe. It has posed extraordinary hurdles for Chinese health workers, affecting their mental health with respect to situations in the present as well as the future. Recognising the dynamic features of these mental health issues among health professionals is critical for developing effective support systems.

Objectives

This study aims to explore the dual impact of COVID-19 on the mental health of health professionals in China, both during and after the pandemic; to explore the probable underlying factors causing these mental health issues; to identify both adaptive and maladaptive coping behaviours employed by the health personnel; and to assess the organisational and social support to mitigate the effect of the pandemic on the mental health of the Chinese health professionals.

Method

To address these objectives an explorative qualitative research design has been adopted involving analysis of previous researches in the relevant field.

Results

The study confirms anxiety, depression, sleep disorders, PTSD, and burnout among medical personnel as immediate shock and residual stress, along with its demographic variations. Few maladaptive coping behaviours have been identified that can lead to delayed psychological effects even after a pandemic.

Conclusion

The key findings underscore the complicated interaction of immediate and delayed mental health challenges among health professionals, advocating for the deployment of tailored treatments and policy modifications to address the ever changing needs of this vital workforce.

The Functions of SARS-CoV-2 Receptors in Diabetes-Related Severe COVID-19

Angiotensin-converting enzyme 2 (ACE2) is considered a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor of high importance, but due to its non-ubiquitous expression, studies of other proteins that may participate in virus internalisation have been undertaken. To date, many alternative receptors have been discovered. Their functioning may provide an explanation for some of the events observed in severe COVID-19 that cannot be directly explained by the model in which ACE2 constitutes the central point of infection. Diabetes mellitus type 2 (T2D) can induce severe COVID-19 development. Although many mechanisms associated with ACE2 can lead to increased SARS-CoV-2 virulence in diabetes, proteins such as basigin (CD147), glucose-regulated protein 78 kDa (GRP78), cluster of differentiation 4 (CD4), transferrin receptor (TfR), integrins α5β1/αvβ3, or ACE2 co-receptors neuropilin 2 (NRP2), vimentin, and even syalilated gangliosides may also be responsible for worsening the COVID-19 course. On the other hand, some others may play protective roles. Understanding how diabetes-associated mechanisms can induce severe COVID-19 via modification of virus receptor functioning needs further extensive studies.

Antiviral Activity of Graphene Oxide-Silver Nanocomposites Against Murine Betacoronavirus

Background

The high infectivity of coronaviruses has led to increased interest in developing new strategies to prevent virus spread. Silver nanoparticles (AgNPs) and graphene oxide (GO) have attracted much attention in the antiviral field. We investigated the potential antiviral activity of GO and AgNPs combined in the nanocomposite GO-Ag against murine betacoronavirus MHV using an in vitro model.

Methods

GO, AgNPs, and GO-Ag characterization (size distribution, zeta potential, TEM visualization, FT-IR, and EDX analysis) and XTT assay were performed. The antiviral activity of GO-Ag nanocomposites was evaluated by RT-qPCR and TCID50 assays. The results were compared with free AgNPs and pure GO. Cell growth and morphology of MHV-infected hepatocytes treated with GO-Ag composites were analyzed by JuLI™Br. Immunofluorescence was used to visualize the cell receptor used by MHV. Ultrastructural SEM analysis was performed to examine cell morphology after MHV infection and GO-Ag composite treatment.

Results

A significant reduction in virus titer was observed for all nanocomposites tested, ranging from 3.2 to 7.3 log10 TCID50. The highest titer reduction was obtained for GO 5 µg/mL - Ag 25 µg/mL in the post-treatment method. These results were confirmed by RT-qPCR analysis. The results indicate that GO-Ag nanocomposites exhibited better antiviral activity compared to AgNPs and GO. Moreover, the attachment of AgNPs to the GO flake platform reduced their cytotoxicity. In addition, the GO-Ag composite modulates the distribution of the Ceacam1 cell receptor and can modulate cell morphology.

Conclusion

Graphene oxide sheets act as a stabilizing agent, inhibiting the accumulation of AgNPs and reducing their cellular toxicity. The GO-Ag composite can physically bind and inhibit murine betacoronavirus from entering cells. Furthermore, the constant presence of GO-Ag can inhibit MHV replication and significantly limit its extracellular release. In conclusion, GO-Ag shows promise as an antiviral coating on solid surfaces to minimize virus transmission and spread.

ƩS COVID-19 is a rapid high throughput and sensitive one-step quadruplex real-time RT-PCR assay

Real-time reverse transcription polymerase chain reaction (RT-PCR), a standard method recommended for the diagnosis of coronavirus disease 2019 (COVID-19) requires 2-4 h to get the result. Although antigen test kit (ATK) is used for COVID-19 screening within 15-30 min, the drawback is its limited sensitivity. Hence, a rapid one-step quadruplex real-time RT-PCR assay: termed ƩS COVID-19 targeting ORF1ab, ORF3a, and N genes of SARS-CoV-2; and Avocado sunblotch viroid (ASBVd) as an internal control was developed. Based on strategies including designing high melting temperature primers with short amplicons, applying a fast ramp rate, minimizing hold time, and reducing the range between denaturation and annealing/extension temperatures; the assay could be accomplished within 25 min. The limit of detection of ORF1ab, ORF3a, and N genes were 1.835, 1.310, and 1 copy/reaction, respectively. Validation was performed in 205 combined nasopharyngeal and oropharyngeal swabs. The sensitivity, specificity, positive predictive value, and negative predictive value were 92.8%, 100%, 100%, and 97.1%, respectively with 96.7% accuracy. Cohen's Kappa was 0.93. The newly developed rapid real-time RT-PCR assay was highly sensitive, specific, and fast, making it suitable for use as an alternative method to support laboratory diagnosis of COVID-19 in outpatient and emergency departments.

Bioinformatics and systems biology analysis revealed PMID26394986-Compound-10 as potential repurposable drug against covid-19

The global health pandemic known as COVID-19, which stems from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a significant concern worldwide. Several treatment methods exist for COVID-19; however, there is an urgent demand for previously established drugs and vaccines to effectively combat the disease. Since, discovering new drugs poses a significant challenge, making the repurposing of existing drugs can potentially reduce time and costs compared to developing entirely new drugs from scratch. The objective of this study is to identify hub genes and associated repurposed drugs targeting them. We analyzed differentially expressed genes (DEGs) by analyzing RNA-seq transcriptomic datasets and integrated with genes associated with COVID-19 present in different databases. We detected 173 Covid-19 associated genes for the construction of a protein-protein interaction (PPI) network which resulted in the identification of the top 10 hub genes/proteins (STAT1, IRF7, MX1, IRF9, ISG15, OAS3, OAS2, OAS1, IRF3, and IRF1). Hub genes were subjected to GO functional and KEGG pathway enrichment analyses, which indicated some key roles and signaling pathways that were strongly related to SARS-CoV-2 infections. We conducted drug repurposing analysis using CMap, TTD, and DrugBank databases with these 10 hub genes, leading to the identification of Piceatannol, CKD-712, and PMID26394986-Compound-10 as top-ranked candidate drugs. Finally, drug-gene interactions analysis through molecular docking and validated via molecular dynamic simulation for 80 ns suggests PMID26394986-Compound-10 as the only potential drug. Our research demonstrates how in silico analysis might produce repurposing candidates to help respond faster to new disease outbreaks.Communicated by Ramaswamy H. Sarma.

Comparison of Helicobacter pylori in hospitalized COVID-19 patients with and without gastrointestinal symptoms

Background and Aim

Helicobacter pylori plays an important role in causing digestive diseases. The purpose of this study is to investigate Helicobacter pylori in COVID-19 patients with and without gastrointestinal symptoms.

Methods

In this case-control study, all patients with COVID-19 admitted to Imam Khomeini Hospital in Jiroft city in 2021 were convenience sampled and divided into two homogeneous groups. Ninety-five patients with COVID-19, who presented with gastrointestinal symptoms, were included in the case group, while 95 patients with COVID-19 without gastrointestinal symptoms were included in the control group. Noninvasive diagnostic methods, including serology and stool antigen tests, were used to identify Helicobacter pylori in the studied patients.

Results

Fifty-three people (55.8%) from the case group had Helicobacter pylori, and 48 (50.5%) from the control group had Helicobacter pylori. Among the 53 people from the case group, 27 (50.9%) were men and 26 (49.1%) were women. Nineteen people (35.8%) were taking pantoprazole, 10 people (18.8%) were taking nonsteroidal anti-inflammatory drugs, 20 people (37.7%) were taking narcotics, and 7 people (13.2%) had peptic ulcer. Seven people (13.2%) had an H2 blocker, and 21 people had an underlying disease. A significant relationship between infection with Helicobacter pylori and the use of pantoprazole, nonsteroidal anti-inflammatory drugs, narcotics, peptic ulcer, underlying disease, and H2 blocker in COVID-19 patients with gastrointestinal symptoms and without gastrointestinal symptoms was present (P-value < 0.05).

Conclusion

The prevalence of Helicobacter pylori infection in patients with COVID-19, who have gastrointestinal symptoms, is high and should be considered as a treatment criterion for people infected with COVID-19.

Nanogold amplified electrochemiluminescence/electrochemistry in bipolar silica nanochannel array for ultrasensitive detection of SARS-CoV-2 pseudoviruses

The prompt and accurate point-of-care test (POCT) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in infected persons or virus-containing environmental samples is of great importance. The present work reports a highly integrated electrochemiluminescence/electrochemical (ECL/EC) sensor for determination of SARS-CoV-2 pseudoviruses, in which bio-recognition element (SARS-CoV-2 IgG antibody), bifunctional probe (tris (2,2'-bipyridyl) ruthenium (Ru(bpy)32+)), and amplification material (gold nanoparticles (Au NPs)) are designed into bipolar silica nanochannel array (bp-SNA). bp-SNA consisting of homogeneous two-layer mesoporous silica films bears inner silanol groups and outer amino groups, generating a solid "electrostatic nanocage" for stable confinement of Ru(bpy)32+ and Au NPs inside the nanochannels and further providing functional sites for covalent modification of SARS-CoV-2 IgG antibody. Owing to the preconcentration capacity of bp-SNA and amplified effect of Au NPs, ECL or EC signals of Ru(bpy)32+ can be remarkably promoted and thereby increase the analytical performance, which can be diminished by immunorecognization of target SARS-CoV-2 pseudoviruses on the sensing interface. The developed integrated ECL/EC sensor based on Ru@AuNPs/bp-SNA modified solid indium tin oxide electrode enables the sensitive analysis of SARS-CoV-2 pseudoviruses by ECL mode with a linear range of 50 TU mL-1-5000 TU mL-1, as well as the EC mode with a linear range of 100 TU mL-1-5000 TU mL-1. Moreover, the designed sensor showed satisfactory results in the analyses of saliva and pond water samples. When flexible electrode substate (polyethylene terephthalate) is employed, Ru@AuNPs/bp-SNA has great potential to integrate with KN95 face masks for direct detection of SARS-CoV-2 pseudoviruses produced from breathing, talking and coughing processes, which could provide an efficient platform for POCT diagnosis.

Desires and attitudes of outpatients and physicians regarding the use of teleurology during the pandemic: a prospective survey study

OBJECTIVE

It is not known to date how many patients admitted to urology outpatient clinics are willing to use telemedicine. We aimed to investigate knowledge levels and attitudes concerning the utilization of teleurology by patients applying to urology outpatient clinics.

METHODS

This prospective multicentre survey study included 334 patients aged 18-65 years who applied to an urology outpatient clinics. The patients were asked questions about their attitudes and expectations regarding teleurology. Diseases were divided into seven subgroups due to the broad spectrum of diagnoses. Physicians' and patients' opinions on whether it was possible to manage the current medical condition via teleurology were recorded.

RESULTS

69.5% of patients stated that they had sufficient technical skills to use teleurology by themselves for medical examination. 55.4% of patients and 78.4% of physicians responded that the existing complaints were suitable for teleurology. Both patients and physicians deemed genital system diseases and urinary tract infections suitable for teleurology (p<0.001, p<0.001 for physicians, and p<0.001, p<0.001 for patients), whereas urine transport, storage and emptying disorders (p=0.003) and benign prostatic hyperplasia (p=0.029) were deemed to be suitable for teleurology only by the physicians.

CONCLUSION

Our study shows that (i) the majority of our patient population has a telecommunications infrastructure suitable for teleurology, (ii) teleurology has aroused interest among patients, particularly during the pandemic period, and (iii) physicians and patients have high expectations that the problem can be solved with teleurology in suitable patients.

Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study

Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but addressing heterogeneity in the system poses a challenge. In this study, we propose a novel modelling framework integrating the spatio-temporal heterogeneity of susceptible individuals into homogeneous models, by introducing a continuous recruitment process for the susceptibles. A neural network approximates the recruitment rate to develop a Universal Differential Equations (UDE) model. Simultaneously, we pre-set a specific form for the recruitment rate and develop a mechanistic model. Data from a COVID Omicron variant outbreak in Shanghai are used to train the UDE model using deep learning methods and to calibrate the mechanistic model using MCMC methods. Subsequently, we project the attack rate and peak of new infections for the first Omicron wave in China after the adjustment of the dynamic zero-COVID policy. Our projections indicate an attack rate and a peak of new infections of 80.06% and 3.17% of the population, respectively, compared with the homogeneous model's projections of 99.97% and 32.78%, thus providing an 18.6% improvement in the prediction accuracy based on the actual data. Our simulations demonstrate that heterogeneity in the susceptibles decreases herd immunity for ~37.36% of the population and prolongs the outbreak period from ~30 days to ~70 days, also aligning with the real case. We consider that this study lays the groundwork for the development of a new class of models and new insights for modelling heterogeneity.

Reconstruction of the unbinding pathways of new inhibitors of the SARS-CoV-2 papain-like protease using molecular dynamics simulation

Developing novel antiviral drugs against the SARS-CoV-2 virus and COVID-19 disease is imperative as the vaccines may not offer absolute protection. PLpro plays a crucial role in the viral life cycle, making it an attractive target for drug development. Several PLpro inhibitors have been developed, and their 3D structures in complex with PLpro are available. In this work, we employed Supervised Molecular Dynamics (SuMD), a specific Unbiased Molecular Dynamics (UMD) method, to investigate unbinding pathways of the novel inhibitors of PLpro (PDB IDs: 7LBR, 7RZC, 7SDR and 7E35) and GRL0617 (PDB ID: 7JRN) as a reference. We conducted three simulations for each ligand and achieved unbinding events in the nanosecond timescale in all simulations. We found that unbinding events are commonly affected by altering the conformation of the BL2 loop, which is caused by the natural fluctuations of the loop that are required to trap the substrate and throw out the product. BL2 loop is crucial for keeping the ligand and unbinding and acts as a double-edged sword. Any inhibitor designed to be effective must prevent the loop's natural fluctuations. We perceived that increasing ligands interactions with the binding pocket interior and the BL2 loop will help prevent natural fluctuation of the BL2 loop, Although the interactions with the binding pocket's inner side are more critical than the BL2 loop. These findings may be helpful in developing more potent inhibitors against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.