COVID-19: An overview of the current pharmacological interventions, vaccines, and clinical trials

Current Insights and Molecular Docking Studies of the Drugs under Clinical Trial as RdRp Inhibitors in COVID-19 Treatment

Study Background & Objective: After the influenza pandemic (1918), COVID-19 was declared a Vth pandemic by the WHO in 2020. SARS-CoV-2 is an RNA-enveloped single-stranded virus. Based on the structure and life cycle, Protease (3CLpro), RdRp, ACE2, IL-6, and TMPRSS2 are the major targets for drug development against COVID-19. Pre-existing several drugs (FDA-approved) are used to inhibit the above targets in different diseases. In coronavirus treatment, these drugs are also in different clinical trial stages. Remdesivir (RdRp inhibitor) is the only FDA-approved medicine for coronavirus treatment. In the present study, by using the drug repurposing strategy, 70 preexisting clinical or under clinical trial molecules were used in scrutiny for RdRp inhibitor potent molecules in coronavirus treatment being surveyed via docking studies. Molecular simulation studies further confirmed the binding mechanism and stability of the most potent compounds.

MATERIAL AND METHODS

Docking studies were performed using the Maestro 12.9 module of Schrodinger software over 70 molecules with RdRp as the target and remdesivir as the standard drug and further confirmed by simulation studies.

RESULTS

The docking studies showed that many HIV protease inhibitors demonstrated remarkable binding interactions with the target RdRp. Protease inhibitors such as lopinavir and ritonavir are effective. Along with these, AT-527, ledipasvir, bicalutamide, and cobicistat showed improved docking scores. RMSD and RMSF were further analyzed for potent ledipasvir and ritonavir by simulation studies and were identified as potential candidates for corona disease.

CONCLUSION

The drug repurposing approach provides a new avenue in COVID-19 treatment.

COVID-19 and New-Onset Psychosis: A Comprehensive Review

Psychosis is a multifactorial condition that typically involves delusions, hallucinations, and disorganized thought, speech or behavior. The observation of an association between infectious epidemics and acute psychosis dates back to the last century. Recently, concerns have been expressed regarding COVID-19 and the risk for the development of new-onset psychosis. This article reviewed the current evidence of a possible link between SARS-CoV-2 and risk of psychosis as an acute or post-infectious manifestation of COVID-19. We here discuss potential neurobiological and environmental factors as well as a number of challenges in ascribing a causal pathogenic relationship between SARS-CoV-2 infection and new-onset psychosis.

Nitric Oxide and its Derivatives Containing Nasal Spray and Inhalation Therapy for the Treatment of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a major health concern worldwide and has evolved into different variants. SARS-CoV-2 possesses a spike glycoprotein on its envelope that binds to the angiotensin-converting enzyme 2 (ACE-2) receptor of the host cell via the receptor-binding domain (RBD) in the upper respiratory tract. Since the SARS-CoV-2 virus variants change the severity of the diesease and treatment scenarios, repurposing current medicines may provide a quick and appealing method with established safety features. The efficacy and safety of antiviral medicines against the coronavirus disease 2019 (COVID-19) have been investigated, and several of them are now undergoing clinical studies. Recently, it has been found that nitric oxide (NO) shows antiviral properties against SARS-CoV-2 and prevents the virus from binding to a host cell. In addition, NO is a well-known vasodilator and acts as an important coagulation mediator. With the fast-track development of COVID-19 treatments and vaccines, one avenue of research aimed at improving therapeutics is exploring different forms of drug delivery, including intranasal sprays and inhalation therapy. The nasal mucosa is more prone to be the site of infection as it is in more direct contact with the physical environment via air during inhalation and exhalation. Thus, the use of exogenous nasal NO therapy via the intranasal route displays a distinct advantage. Therefore, the objective of this review is to summarize the relevant actions of NO via the intranasal spray and inhalation delivery, its mechanism of action, and its use in the treatment of COVID-19.

Unmet need for COVID-19 vaccination coverage in Kenya

COVID-19 has impacted the health and livelihoods of billions of people since it emerged in 2019. Vaccination for COVID-19 is a critical intervention that is being rolled out globally to end the pandemic. Understanding the spatial inequalities in vaccination coverage and access to vaccination centres is important for planning this intervention nationally. Here, COVID-19 vaccination data, representing the number of people given at least one dose of vaccine, a list of the approved vaccination sites, population data and ancillary GIS data were used to assess vaccination coverage, using Kenya as an example. Firstly, physical access was modelled using travel time to estimate the proportion of population within 1 hour of a vaccination site. Secondly, a Bayesian conditional autoregressive (CAR) model was used to estimate the COVID-19 vaccination coverage and the same framework used to forecast coverage rates for the first quarter of 2022. Nationally, the average travel time to a designated COVID-19 vaccination site (n = 622) was 75.5 min (Range: 62.9 - 94.5 min) and over 87% of the population >18 years reside within 1 hour to a vaccination site. The COVID-19 vaccination coverage in December 2021 was 16.70% (95% CI: 16.66 - 16.74) - 4.4 million people and was forecasted to be 30.75% (95% CI: 25.04 - 36.96) - 8.1 million people by the end of March 2022. Approximately 21 million adults were still unvaccinated in December 2021 and, in the absence of accelerated vaccine uptake, over 17.2 million adults may not be vaccinated by end March 2022 nationally. Our results highlight geographic inequalities at sub-national level and are important in targeting and improving vaccination coverage in hard-to-reach populations. Similar mapping efforts could help other countries identify and increase vaccination coverage for such populations.

Response to Vaccines in Patients with Immune-Mediated Inflammatory Diseases: A Narrative Review

Patients with immune-mediated inflammatory diseases (IMIDs), such as rheumatoid arthritis and inflammatory bowel disease, are at increased risk of infection. International guidelines recommend vaccination to limit this risk of infection, although live attenuated vaccines are contraindicated once immunosuppressive therapy has begun. Biologic therapies used to treat IMIDs target the immune system to stop chronic pathogenic process but may also attenuate the protective immune response to vaccines. Here, we review the current knowledge regarding vaccine responses in IMID patients receiving treatment with biologic therapies, with a focus on the interleukin (IL)-12/23 inhibitors. B cell-depleting therapies, such as rituximab, strongly impair vaccines immunogenicity, and tumor necrosis factor (TNF) inhibitors and the cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) fusion protein abatacept are also associated with attenuated antibody responses, which are further diminished in patients taking concomitant immunosuppressants. On the other hand, integrin, IL-6, IL-12/23, IL-17, and B-cell activating factor (BAFF) inhibitors do not appear to affect the immune response to several vaccines evaluated. Importantly, treatment with biologic therapies in IMID patients is not associated with an increased risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or developing severe disease. However, the efficacy of SARS-CoV-2 vaccines on IMID patients may be reduced compared with healthy individuals. The impact of biologic therapies on the response to SARS-CoV-2 vaccines seems to replicate what has been described for other vaccines. SARS-CoV-2 vaccination appears to be safe and well tolerated in IMID patients. Attenuated but, in general, still protective responses to SARS-CoV-2 vaccination in the context of certain therapies warrant current recommendations for a third primary dose in IMID patients treated with immunosuppressive drugs.

Case Report: Associated Ocular Adverse Reactions With Inactivated COVID-19 Vaccine in China

The vaccine is still the best clinical measure for effective prevention and control of coronavirus disease 2019 (COVID-19). The vaccine-associated ocular adverse reactions should be noted in detail among the medical community. We reported twelve eyes of 9 patients presented at the Department of Ophthalmology, Qilu Hospital of Shandong University from March to August 2021 with ocular complaints following COVID-19 vaccination. The main inclusion criterion was the development of ocular symptoms within 14 days after receiving a dose of an inactivated COVID-19 vaccine. The mean (SD) age was 44.7 ± 16.5 years (range, 19–78 years), among which seven (77.8%) cases were women. The mean time of ocular adverse events was 7.1 days (range, 1–14 days) after receiving the inactivated COVID-19 vaccine. One patient was diagnosed with choroiditis, 1 with uveitis, 4 with keratitis, 1 with scleritis, 1 with acute retinal necrosis, and 1 with iridocyclitis. Although the causal relationship between vaccines and ocular adverse events cannot be established from this case series report, physicians should pay attention to the ocular adverse reactions following the COVID-19 vaccine administration.

Evaluation of neutralizing antibodies after vaccine BNT162b2: Preliminary data

It is well-known that the Coronavirus Disease 2019, which is caused by the beta-coronavirus severe acute respiratory syndrome (SARS-CoV-2), emerged in December 2019 followed by an outbreak first reported in Wuhan, China. Thus far, vaccination appears to be the only way to bring the pandemic to an end. In the present study, immunogenicity data was evaluated using LIAISON® SARS-CoV-2 TrimericS IgG assay (DiaSorin S.p.A) among a sample of 52 vaccinated healthcare workers, five of whom were previously infected with SARS-CoV-2 and 47 who were seronegative, over a time span of ≤90 days following the second dose of the BNT162b2 mRNA vaccine. The test detects antibodies against the Trimeric complex (S1, S2 and receptor binding domain). The overall mean value of the serum levels of IgG antibodies to SARS-CoV-2 30 days following the second dose of the vaccine was 1,901.8 binding arbitrary unit (BAU)/ml, after 60 days the mean value declined to 1,244.9 BAU/ml. The antibody levels then reached a plateau, as confirmed by the antibody test carried out 90 days following the second dose, which revealed a mean value of 1,032.4 BAU/ml (P<0.0001). A higher level was observed at all three times in male subjects compared with female subjects, and in younger male participants compared with female participants, although these differences did not reach a statistically significant level. Similarly, no significant difference was found in antibody values at different times according to age. After the second dose of the vaccine, two subjects were infected with SARS-CoV-2, and an increase in antibody values in the third assay was observed in both individuals.

A Novel COVID-19 Diagnosis Support System Using the Stacking Approach and Transfer Learning Technique on Chest X-Ray Images

COVID-19 is an infectious disease-causing flu-like respiratory problem with various symptoms such as cough or fever, which in severe cases can cause pneumonia. The aim of this paper is to develop a rapid and accurate medical diagnosis support system to detect COVID-19 in chest X-ray images using a stacking approach combining transfer learning techniques and KNN algorithm for selection of the best model. In deep learning, we have multiple approaches for building a classification system for analyzing radiographic images. In this work, we used the transfer learning technique. This approach makes it possible to store and use the knowledge acquired from a pretrained convolutional neural network to solve a new problem. To ensure the robustness of the proposed system for diagnosing patients with COVID-19 using X-ray images, we used a machine learning method called the stacking approach to combine the performances of the many transfer learning-based models. The generated model was trained on a dataset containing four classes, namely, COVID-19, tuberculosis, viral pneumonia, and normal cases. The dataset used was collected from a six-source dataset of X-ray images. To evaluate the performance of the proposed system, we used different common evaluation measures. Our proposed system achieves an extremely good accuracy of 99.23% exceeding many previous related studies.

Chemoprophylaxis under sporozoites-lumefantrine (CPS-LMF) immunization induce protective immune responses against Plasmodium yoelii sporozoites infection in mice

Malaria represents one of the major life-threatening diseases that poses a huge socio-economic impact, worldwide. Chemoprophylaxis vaccination using a relatively low number of wild-type infectious sporozoites represents an attractive and effective vaccine strategy against malaria. However, the role of immune responses to pre-erythrocytic versus blood-stage parasites in protection against different antimalarial drugs remains unclear. Here, in the present study, we explored the immune responses against the repetitive inoculation of live Plasmodium yoelii (P. yoelii) sporozoites in an experimental Swiss mouse model under antimalarial drug lumefantrine chemoprophylaxis (CPS-LMF). We monitored the liver stage parasitic load, pro/anti-inflammatory cytokines expression, and erythrocytic stage patency, following repetitive cycles of sporozoites inoculations. It was found that repetitive sporozoites inoculation under CPS-LMF results in delayed blood-stage infection during the fourth sporozoites challenge, while sterile protection was produced in mice following the fifth cycle of sporozoites challenge. Intriguingly, we observed a significant up-regulation of pro-inflammatory cytokines (IFN-γ, TNF-α and IL-12) and iNOS response and down-regulation of anti-inflammatory cytokines (IL-4, IL-10 and TGF-β) in the liver HMNC (hepatic mononuclear cells) and spleen cells after 4th and 5th cycle of sporozoites challenge in the CPS-LMF mice. Meanwhile, we also noticed that the liver stage parasites load under CPS-LMF immunization has gradually reduced after 2nd, 3rd, 4th and 5th sporozoites challenge. Overall, our study suggests that chemoprophylaxis vaccination under LMF drug cover develops strong immune responses and confer superior long-lasting protection against P. yoelii sporozoites. Furthermore, this vaccination strategy can be used to study the protective and stage-specific immunity against new protective antigens.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03022-0.

The SARS-CoV-2 spike protein is vulnerable to moderate electric fields

Most of the ongoing projects aimed at the development of specific therapies and vaccines against COVID-19 use the SARS-CoV-2 spike (S) protein as the main target. The binding of the spike protein with the ACE2 receptor (ACE2) of the host cell constitutes the first and key step for virus entry. During this process, the receptor binding domain (RBD) of the S protein plays an essential role, since it contains the receptor binding motif (RBM), responsible for the docking to the receptor. So far, mostly biochemical methods are being tested in order to prevent binding of the virus to ACE2. Here we show, with the help of atomistic simulations, that external electric fields of easily achievable and moderate strengths can dramatically destabilise the S protein, inducing long-lasting structural damage. One striking field-induced conformational change occurs at the level of the recognition loop L3 of the RBD where two parallel beta sheets, believed to be responsible for a high affinity to ACE2, undergo a change into an unstructured coil, which exhibits almost no binding possibilities to the ACE2 receptor. We also show that these severe structural changes upon electric-field application also occur in the mutant RBDs corresponding to the variants of concern (VOC) B.1.1.7 (UK), B.1.351 (South Africa) and P.1 (Brazil). Remarkably, while the structural flexibility of S allows the virus to improve its probability of entering the cell, it is also the origin of the surprising vulnerability of S upon application of electric fields of strengths at least two orders of magnitude smaller than those required for damaging most proteins. Our findings suggest the existence of a clean physical method to weaken the SARS-CoV-2 virus without further biochemical processing. Moreover, the effect could be used for infection prevention purposes and also to develop technologies for in-vitro structural manipulation of S. Since the method is largely unspecific, it can be suitable for application to other mutations in S, to other proteins of SARS-CoV-2 and in general to membrane proteins of other virus types.

The SARS-CoV-2 Spike protein is essential for viral infectivity and binds to the host receptor ACE2. Here, the authors present MD simulations of the Spike protein and its variants of concern and observe that the Spike protein is destabilised by moderate static electric fields, and undergoes field-induced conformational changes that hinder binding to ACE2.

Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19

As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning (ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare.

Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19

As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic since the 1918 flu. The main challenges in mitigating COVID-19 are effective vaccination, treatment, and agile containment strategies. In this review, we focus on the potential of Artificial Intelligence (AI) in COVID-19 surveillance, diagnosis, outcome prediction, drug discovery and vaccine development. With the help of big data, AI tries to mimic the cognitive capabilities of a human brain, such as problem-solving and learning abilities. Machine Learning (ML), a subset of AI, holds special promise for solving problems based on experiences gained from the curated data. Advances in AI methods have created an unprecedented opportunity for building agile surveillance systems using the deluge of real-time data generated within a short span of time. During the COVID-19 pandemic, many reports have discussed the utility of AI approaches in prioritization, delivery, surveillance, and supply chain of drugs, vaccines, and non-pharmaceutical interventions. This review will discuss the clinical utility of AI-based models and will also discuss limitations and challenges faced by AI systems, such as model generalizability, explainability, and trust as pillars for real-life deployment in healthcare.

Ciclesonide Inhaler Treatment for Mild-to-Moderate COVID-19: A Randomized, Open-Label, Phase 2 Trial

Although some intravenous drugs have been used to treat coronavirus disease 2019 (COVID-19), no effective antiviral agents are currently available in the outpatient setting. We aimed to evaluate the efficacy and adverse events of 14-day ciclesonide treatment vs. standard care for patients with mild-to-moderate COVID-19. A randomized, open-label, multicenter clinical trial of ciclesonide inhalers was conducted in patients with mild-to-moderate COVID-19. Patients were enrolled within 3 days of diagnosis or within 7 days from symptom onset and randomly assigned to receive either ciclesonide (320 µg inhalation twice per day for 14 days) or standard care. The primary endpoint was the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) eradication rate on day 14 from study enrollment. Clinical status was assessed once daily, and serial nasopharyngeal viral load was evaluated by quantitative reverse transcription polymerase chain reaction. There were 35 and 26 patients in the ciclesonide and standard care groups, respectively. The SARS-CoV-2 eradication rate at day 14 was significantly higher in the ciclesonide group (p = 0.021). In multivariate analysis, SARS-CoV-2 negative conversion within 14 days was 12 times more likely in the ciclesonide group (95% confidence interval, 1.187–125.240). Additionally, the clinical failure rate (high-flow nasal oxygen therapy or mechanical ventilation) was significantly lower in the ciclesonide group (p = 0.034). In conclusion, ciclesonide inhalation shortened SARS-CoV-2 viral shedding duration, and it may inhibit the progression to acute respiratory failure in patients with mild-to-moderate COVID-19. Clinical Trial Registration NCT04330586.

COVID-19 Research: Lessons from Non-Human Primate Models

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19). It emerged from China in December 2019 and rapidly spread across the globe, causing a pandemic with unprecedented impacts on public health and economy. Therefore, there is an urgent need for the development of curative treatments and vaccines. In humans, COVID-19 pathogenesis shows a wide range of symptoms, from asymptomatic to severe pneumonia. Identifying animal models of SARS-CoV-2 infection that reflect the clinical symptoms of COVID-19 is of critical importance. Nonhuman primates (NHPss) correspond to relevant models to assess vaccine and antiviral effectiveness. This review discusses the use of NHPs as models for COVID-19 research, with focus on the pathogenesis of SARS-CoV-2 infection, drug discovery and pre-clinical evaluation of vaccine candidates.

Association of Healthy Diet with Recovery Time from COVID-19: Results from a Nationwide Cross-Sectional Study

The world is still in need of an effective therapy to treat coronavirus disease-19 (COVID-19). This cross-sectional study was conducted on COVID-19 survivors in Saudi Arabia to investigate the influence of a healthy diet on the recovery time from COVID-19. A questionnaire was developed to assess participants' dietary habits, based on the 2015 Dutch food-based dietary guidelines. A total of 738 COVID-19 survivors participated in the study, of whom 237 (32.1%) were hospitalized for COVID-19 treatment while 501 (76.9%) were not hospitalized, and 320 (43.4%) were females and 418 (56.6%) were males. Overall, no significant difference was noted in healthy diet score between males and females; however, this score was significantly lower for Saudis compared to non-Saudis. Among the non-hospitalized patients, eating a more healthy diet was associated with a shorter duration of recovery (p < 0.05) and was significantly affected by gender (15.8 ± 9.3 male vs. 12.1 ± 8.9 female; p < 0.001) and marital status (12.1 ± 8.4 singles vs. 13.7 ± 9.3 married vs. 16.1 ± 11.8 divorced; p < 0.05). In contrast, no significant correlation was found with age or BMI. In this study, a more healthy diet was associated with a shorter duration of recovery from COVID-19. However, further studies are needed to thoroughly investigate the relationship between diet and recovery time from COVID-19.

Hybrid Deep-Learning and Machine-Learning Models for Predicting COVID-19

The COVID-19 pandemic has had a significant impact on public life and health worldwide, putting the world's healthcare systems at risk. The first step in stopping this outbreak is to detect the infection in its early stages, which will relieve the risk, control the outbreak's spread, and restore full functionality to the world's healthcare systems. Currently, PCR is the most prevalent diagnosis tool for COVID-19. However, chest X-ray images may play an essential role in detecting this disease, as they are successful for many other viral pneumonia diseases. Unfortunately, there are common features between COVID-19 and other viral pneumonia, and hence manual differentiation between them seems to be a critical problem and needs the aid of artificial intelligence. This research employs deep- and transfer-learning techniques to develop accurate, general, and robust models for detecting COVID-19. The developed models utilize either convolutional neural networks or transfer-learning models or hybridize them with powerful machine-learning techniques to exploit their full potential. For experimentation, we applied the proposed models to two data sets: the COVID-19 Radiography Database from Kaggle and a local data set from Asir Hospital, Abha, Saudi Arabia. The proposed models achieved promising results in detecting COVID-19 cases and discriminating them from normal and other viral pneumonia with excellent accuracy. The hybrid models extracted features from the flatten layer or the first hidden layer of the neural network and then fed these features into a classification algorithm. This approach enhanced the results further to full accuracy for binary COVID-19 classification and 97.8% for multiclass classification.

Understanding and predicting COVID-19 clinical trial completion vs. cessation

As of March 30 2021, over 5,193 COVID-19 clinical trials have been registered through Clinicaltrial.gov. Among them, 191 trials were terminated, suspended, or withdrawn (indicating the cessation of the study). On the other hand, 909 trials have been completed (indicating the completion of the study). In this study, we propose to study underlying factors of COVID-19 trial completion vs. cessation, and design predictive models to accurately predict whether a COVID-19 trial may complete or cease in the future. We collect 4,441 COVID-19 trials from ClinicalTrial.gov to build a testbed, and design four types of features to characterize clinical trial administration, eligibility, study information, criteria, drug types, study keywords, as well as embedding features commonly used in the state-of-the-art machine learning. Our study shows that drug features and study keywords are most informative features, but all four types of features are essential for accurate trial prediction. By using predictive models, our approach achieves more than 0.87 AUC (Area Under the Curve) score and 0.81 balanced accuracy to correctly predict COVID-19 clinical trial completion vs. cessation. Our research shows that computational methods can deliver effective features to understand difference between completed vs. ceased COVID-19 trials. In addition, such models can also predict COVID-19 trial status with satisfactory accuracy, and help stakeholders better plan trials and minimize costs.

Deep sequence modelling for predicting COVID-19 mRNA vaccine degradation

The worldwide coronavirus (COVID-19) pandemic made dramatic and rapid progress in the year 2020 and requires urgent global effort to accelerate the development of a vaccine to stop the daily infections and deaths. Several types of vaccine have been designed to teach the immune system how to fight off certain kinds of pathogens. mRNA vaccines are the most important candidate vaccines because of their capacity for rapid development, high potency, safe administration and potential for low-cost manufacture. mRNA vaccine acts by training the body to recognize and response to the proteins produced by disease-causing organisms such as viruses or bacteria. This type of vaccine is the fastest candidate to treat COVID-19 but it currently facing several limitations. In particular, it is a challenge to design stable mRNA molecules because of the inefficient in vivo delivery of mRNA, its tendency for spontaneous degradation and low protein expression levels. This work designed and implemented a sequence deep model based on bidirectional GRU and LSTM models applied on the Stanford COVID-19 mRNA vaccine dataset to predict the mRNA sequences responsible for degradation by predicting five reactivity values for every position in the sequence. Four of these values determine the likelihood of degradation with/without magnesium at high pH (pH 10) and high temperature (50 degrees Celsius) and the fifth reactivity value is used to determine the likely secondary structure of the RNA sample. The model relies on two types of features, namely numerical and categorical features, where the categorical features are extracted from the mRNA sequences, structure and predicted loop. These features are represented and encoded by numbers, and then, the features are extracted using embedding layer learning. There are five numerical features depending on the likelihood for each pair of nucleotides in the RNA. The model gives promising results because it predicts the five reactivity values with a validation mean columnwise root mean square error (MCRMSE) of 0.125 using LSTM model with augmentation and the codon encoding method. Codon encoding outperforms Base encoding in MCRMSE validation error using the LSTM model meanwhile Base encoding outperforms codon encoding due to less over-fitting and the difference between the training and validation loss error is 0.008.

An Overview of the Epidemiologic, Diagnostic and Treatment Approaches of COVID-19: What do We Know?

Background: In late December 2019, a new infectious respiratory disease (COVID-19) was reported in a number of patients with a history of exposure to the Huanan seafood market in China. The World Health Organization officially announced the COVID-19 pandemic on March 11, 2020. Here, we provided an overview of the epidemiologic, diagnostic and treatment approaches associated with COVID-19. Methods: We reviewed the publications indexed in major biomedical databases by December 20, 2020 or earlier (updated on May 16, 2021). Search keywords included a combination of: COVID-19, Coronavirus disease 2019, SARS-CoV-2, Epidemiology, Prevention, Diagnosis, Vaccine, and Treatment. We also used available information about COVID-19 from valid sources such as WHO. Results and Conclusion: At the time of writing this review, while most of the countries authorized COVID-19 vaccines for emergency use starting December 8, 2020, there is no a definite cure for it. This review synthesizes current knowledge of virology, epidemiology, clinical symptoms, diagnostic approaches, common treatment strategies, novel potential therapeutic options for control and prevention of COVID-19 infection, available vaccines, public health and clinical implications.

A comprehensive overview of vaccines developed for pandemic viral pathogens over the past two decades including those in clinical trials for the current novel SARS-CoV-2

The unprecedented coronavirus disease 2019 (COVID-19) is triggered by a novel strain of coronavirus namely, Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2). Researchers are working around the clock to control this pandemic and consequent waves of viral reproduction, through repurposing existing drugs as well as designing new vaccines. Several countries have hastened vaccine design and clinical trials to quickly address this outbreak. Currently, more than 250 aspirants against SARS-CoV-2 are in progress, including mRNA-replicating or non-replicating viral vectored-, DNA-, autologous dendritic cell-based-, and inactivated virus-vaccines. Vaccines work by prompting effector mechanisms such as cells/molecules, which target quickly replicating pathogens and neutralize their toxic constituents. Vaccine-stimulated immune effectors include adjuvant, affinity, avidity, affinity maturation, antibodies, antigen-presenting cells, B lymphocytes, carrier protein, CD4+ T-helper cells. In this review, we describe updated information on the various vaccines available over the last two decades, along with recent progress in the ongoing battle developing 63 diverse vaccines against SARS-CoV-2. The inspiration of our effort is to convey the current investigation focus on registered clinical trials (as of January 08, 2021) that satisfy the safety and efficacy criteria of international wide vaccine development.

Factors associated with the intention to obtain a COVID-19 vaccine among a racially/ethnically diverse sample of women in the USA

Widespread uptake of the COVID-19 vaccine is critical to halt the pandemic. At present, little is known about factors that will affect vaccine uptake, especially among diverse racial/ethnic communities that have experienced the highest burden of COVID. We administered an online survey to a Qualtrics respondent panel of women ages 27-45 years (N = 396) to assess vaccine intentions and attitudes, and trusted vaccine information sources. 56.8% intended to be vaccinated and 25.5% were unsure. In bivariate analyses, a greater percentage of non-Latina White (NLW) and Chinese women reported that they would be vaccinated, compared with Latina and non-Latina Black (NLB) women (p < 0.001). Those who were uninsured, unemployed and those with lower incomes were less likely to say that they would be vaccinated. In analyses stratified by race/ethnicity, NLB women remained significantly less likely to report that they would be vaccinated compared with NLW women (adjusted odds ratio: 0.47; 95% confidence interval: 0.23, 0.94), controlling for age, marital status, income, education, employment, and insurance status. When analyses were additionally controlled for beliefs in vaccine safety and efficacy, racial/ethnic differences were no longer significant (adjusted odds ratio: 0.64; 95% confidence interval: 0.31, 1.34). Given that NLB women were less likely to report the intention to be vaccinated, targeted efforts will be needed to promote vaccine uptake. It will be critical to emphasize that the vaccine is safe and effective; this message may be best delivered by trusted community members.

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) disease is a global rapidly spreading virus showing very high rates of complications and mortality. Till now, there is no effective specific treatment for the disease. Aloe is a rich source of isolated phytoconstituents that have an enormous range of biological activities. Since there are no available experimental techniques to examine these compounds for antiviral activity against SARS-CoV-2, we employed an in silico approach involving molecular docking, dynamics simulation, and binding free energy calculation using SARS-CoV-2 essential proteins as main protease and spike protein to identify lead compounds from Aloe that may help in novel drug discovery. Results retrieved from docking and molecular dynamics simulation suggested a number of promising inhibitors from Aloe. Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) calculations indicated that compounds 132, 134, and 159 were the best scoring compounds against main protease, while compounds 115, 120, and 131 were the best scoring ones against spike glycoprotein. Compounds 120 and 131 were able to achieve significant stability and binding free energies during molecular dynamics simulation. In addition, the highest scoring compounds were investigated for their pharmacokinetic properties and drug-likeness. The Aloe compounds are promising active phytoconstituents for drug development for SARS-CoV-2.

Synthesis and immunogenicity assessment of a gold nanoparticle conjugate for the delivery of a peptide from SARS-CoV-2

The development of vaccines is a crucial response against the COVID-19 pandemic and innovative nanovaccines could increase the potential to address this remarkable challenge. In the present study a B cell epitope (S_461-493) from the spike protein of SARS-CoV-2 was selected and its immunogenicity validated in sheep. This synthetic peptide was coupled to gold nanoparticles (AuNP) functionalized with SH-PEG-NH₂ via glutaraldehyde-mediated coupling to obtain the AuNP-S_461-493 candidate, which showed in s.c.-immunized mice a superior immunogenicity (IgG responses) when compared to soluble S_461-493; and led to increased expression of relevant cytokines in splenocyte cultures. Interestingly, the response triggered by AuNP-S_461-493 was similar in magnitude to that induced using a conventional strong adjuvant (Freund's adjuvant). This study provides a platform for the development of AuNP-based nanovaccines targeting specific SARS-CoV-2 epitopes.

Life-long passion for antiviral research and drug development: 80th birthday of Prof. Dr. Erik De Clercq

Since the 1950s, great efforts have been made to develop antiviral agents against many infectious diseases such as human immunodeficiency virus (HIV), hepatitis B virus (HBV), hepatitis C virus (HCV), human cytomegalovirus (HCMV), herpes simplex virus (HSV), and varicella-zoster virus (VZV). Among the list of nearly 106 antiviral agents approved in the past five decades, Prof. Erik De Clercq has contributed to the development of 7 antiviral drugs: tenofovir disoproxil fumarate (Viread®) for HIV and HBV treatment, tenofovir alafenamide (Vemlidy®) for HIV and HBV treatment, brivudine (Zostex®) for HSV-1 and VZV treatment, valacyclovir (Valtrex®) for HSV and VZV treatment, adefovir dipivoxil (Hepsera®) for HBV treatment, stavudine (Zerit®) for HIV treatment, and cidofovir (Vistide®) for treating HCMV retinitis in AIDS patients. In addition to the above antiviral drugs, his contributions include two anti-cancer drugs: rabacfosadine (Tanovea®-CA1) for canine lymphoma and plerixafor (Mozobil®) for multiple myeloma and non-Hodgkin's lymphoma. These achievements are driven by his life-long passions for antiviral research and successful collaborations worldwide. To honor the 80th birthday of Prof. Erik De Clercq, this study highlights his scientific achievements and the importance of life-long passions and collaborations in the success of antiviral research and drug development.

Insufficient social distancing may contribute to COVID-19 outbreak: The case of Ijuí city in Brazil

The coronavirus disease that emerged in 2019 (COVID-19) is highly contagious and has given way to a global pandemic. A present COVID-19 has high transmission rates worldwide, including in small Brazilian cities such as Ijuí. Located in the northwest part of the state of Rio Grande do Sul (RS) and with a population of 83,475, Ijuí was selected as the site of a population-based survey involving 2,222 subjects, from April to June 2020. Subjects were tested for the presence of antibodies against coronavirus (SARS-CoV-2) and answered questions regarding social distance adherence (SDA), daily preventive routines (DPR), comorbidities, and sociodemographic characteristics. In parallel, the local government registered the official COVID-19 cases in Ijuí, as well as the mobile social distancing index (MSDI). In this study, we demonstrate that there was a decrease in the levels of SDA, DPR and MSDI before the beginning of COVID-19 community transmission in Ijuí. Furthermore, we provide predictions for the number of COVID-19 cases, hospitalizations, and deaths in the city. We conclude that insufficient social distancing, as evidenced by different methods, may be related to the rapid increase of COVID-19 cases in Ijuí. Our study predicts an approaching outbreak of COVID-19 in Ijuí through community spread, which could be avoided or attenuated with increased levels of social distancing among the population.

Review on Up-to-Date Status of Candidate Vaccines for COVID-19 Disease

The global pandemic of COVID-19 caused by SARS-CoV-2 continues to spread and poses serious threats to public health and economic stability throughout the world. Thus, to protect the global population, developing safe and effective vaccines is mandatory to control the spread of SARS-CoV-2 pandemic. Since genomic sequences of SARS-CoV-2 and SARS-CoV-1 have similarity and use the same receptor (ACE2), it is important to learn from the development of SARS-CoV-1 vaccines for the development of SARS-CoV-2 vaccines. Normally vaccine development takes 10-15 years but vaccine development against SARS-CoV2 is going on at a very fast pace resulting in almost breakthrough methods of vaccine development by several research institutions. The whole process of vaccine development including clinical trials gets shortened and may be fast tracked to 15-18 months. Global collaborations and increased research efforts among the scientific community have led to more than 214 candidate vaccines globally. The current review highlights the different approaches and technologies used around the world for the design and development of the vaccines and also focuses on the recent status of the SARS-CoV-2 vaccine candidates under development by various institutions to combat the world threat of COVID-19 pandemic.

DNA vaccines against COVID-19: Perspectives and challenges

The coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is associated with several fatal cases worldwide. The rapid spread of this pathogen and the increasing number of cases highlight the urgent development of vaccines. Among the technologies available for vaccine development, DNA vaccination is a promising alternative to conventional vaccines. Since its discovery in the 1990s, it has been of great interest because of its ability to elicit both humoral and cellular immune responses while showing relevant advantages regarding producibility, stability, and storage. This review aimed to summarize the current knowledge and advancements on DNA vaccines against COVID-19, particularly those in clinical trials.

An Up-to-Date Overview of Therapeutic Agents for the Treatment of COVID-19 Disease

Acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has a great potential to overwhelm the world healthcare systems that may lead to high morbidity and mortality. It also affects world economic development in the future. Currently, no proven effective drugs or vaccines are available for the management of COVID-19 disease. The pace of normal drug development progression is unacceptable in the context of the current pandemic. Therefore, repurposing the existing drugs that were used for the treatment of malaria, Ebola, and influenza helps rapid drug development for COVID-19. Currently, several repurposing candidate drugs are in a clinical trial including, chloroquine monoclonal antibodies, convalescent plasma, interferon, and antiviral therapies. Antiviral drugs like arbidol, remdesiv and favirnavir are the most promising due to the similarities of the viruses regarding viral entry, fusion, uncoating, and replication. This review article provides an overview of the potential therapeutic agent, which displayed better clinical treatment outcomes. Moreover, with further understanding of the SARS-CoV-2 virus, new drugs targeting specific SARS-CoV-2 viral components arise, and investigations on these novels anti-SARSCoV- 2 agents are also reviewed.

Use of dexamethasone, remdesivir, convalescent plasma and prone positioning in the treatment of severe COVID-19 infection in pregnancy: A case report

Severe infection with COVID-19 virus in pregnancy offers unique management challenges for the obstetrician and critical care specialist. We report the case of a woman at 26 weeks of gestation with acute respiratory distress syndrome secondary to COVID-19 infection treated with dexamethasone, remdesivir, convalescent plasma and mechanical ventilation. Cesarean delivery was performed at 29 weeks due to worsening maternal status. This case offers insight into the assessment and successful use of treatment strategies, including dexamethasone, remdesivir, convalescent plasma, early prone positioning, conservative fluid management, permissive hypoxia and low tidal volume parameters with ventilator support for pregnancies affected by severe COVID-19 infection.

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Dexamethasone offers maternal and fetal benefits in severe COVID-19 infection.

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Lung protective ventilator settings can be used in pregnancy in COVID-related acute respiratory distress syndrome.

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Use of prone positioning for improved ventilation is well tolerated in pregnancy.

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Fetal heart rate tracing is a clinical indicator of maternal oxygenation status.

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Permissive hypoxia can be used to prevent barotrauma and advance fetal maturity.