Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review

Machine learning-driven optimization of mRNA-lipid nanoparticle vaccine quality with XGBoost/Bayesian method and ensemble model approaches

To enhance the efficiency of vaccine manufacturing, this study focuses on optimizing the microfluidic conditions and lipid mix ratios of messenger RNA-lipid nanoparticles (mRNA-LNP). Different mRNA-LNP formulations (n = 24) were developed using an I-optimal design, where machine learning tools (XGBoost/Bayesian optimization and self-validated ensemble (SVEM)) were used to optimize the process and predict lipid mix ratio. The investigation included material attributes, their respective ratios, and process attributes. The critical responses like particle size (PS), polydispersity index (PDI), Zeta potential, pKa, heat trend cycle, encapsulation efficiency (EE), recovery ratio, and encapsulated mRNA were evaluated. Overall prediction of SVEM (>97%) was comparably better than that of XGBoost/Bayesian optimization (>94%). Moreover, in actual experimental outcomes, SVEM prediction is close to the actual data as confirmed by the experimental PS (94-96 nm) is close to the predicted one (95-97 nm). The other parameters including PDI and EE were also close to the actual experimental data.

Characterization of an engineered ACE2 protein for its improved biological features and its transduction into MSCs: A novel approach to combat COVID-19 infection

Transduced MSCs that express engineered ACE2 could be highly beneficial to combat COVID-19. Engineered ACE2 can act as decoy targets for the virus, preventing its entry into healthy lung cells. To this end, genetic engineering techniques were used to integrate the ACE2 gene into the MSCs genome. The MSCs were evaluated for proper expression and functionality. The mutated form of ACE2 was characterized using various techniques such as protein expression analysis, binding affinity against spike protein, thermal stability assessment, and enzymatic activity assays. The functionality of the mACE2 was assessed on SARS-CoV-2 using the virus-neutralizing test. The obtained results indicated that by introducing specific mutations in the ACE2 gene, the resulting mutant ACE2 had enhanced interaction with viral spike protein, its thermal stability was increased, and its enzymatic function was inhibited as a decoy receptor. Moreover, the mACE2 protein showed higher efficacy in the neutralization of the SARS-CoV-2. In conclusion, this study proposes a novel approach with potential benefits such as targeted drug delivery and reduced side effects on healthy tissues. These transduced MSCs can also be used in combination with other anti-COVID-19 treatments. Design of similar engineered biomolecules with desired properties could also be used to target other diseases.

Assessment of immunopathological responses of a novel non-chemical biocide in C57BL/6 for safe disinfection usage

BACKGROUND

Water electrospray technology has been developed and extensively studied for its physical properties and potential application as a non-chemical biocide against airborne pathogens. However, there are still concerns regarding the safety and potential toxicity of inhaling water electrospray (WE) particles. To address these potential hazards and offer insights into the impact of WE on humans, we analyzed the immunopathological response to WE by employing an intranasal challenge C57BL/6 mouse model. This analysis aimed to compare the effects of WE with those of sodium hypochlorite (SH), a well-known biocidal agent.

RESULTS

The study findings suggest that the WE did not trigger any pathological immune reactions in the intranasal-challenged C57BL/6 mouse model. Mice challenged with WE did not experience body weight loss, and there was no increase in inflammatory cytokine production compared to SH-treated mice. Histopathological analysis revealed that WE did not cause any damage to the lung tissue. In contrast, mice treated with SH exhibited significant lung tissue damage, characterized by the infiltration of neutrophils and eosinophils. Transcriptomic analysis of lung tissue further confirmed the absence of a pathological immune response in mice treated with WE compared to those treated with SH. Upon intranasal challenge with WE, the C57BL/6 mouse model did not show any evidence of immunopathological damage.

CONCLUSIONS

The results of this study suggest that WE is a safe technology for disinfecting airborne pathogens. It demonstrated little to no effect on immune system activation and pathological outcomes in the intranasal challenge C57BL/6 mouse model. These findings not only support the potential use of WE as an effective and safe method for air disinfection but also highlight the value of the intranasal challenge of the C57BL/6 mouse model in providing significant immunopathological insights for assessing the inhalation of novel materials for potential use.

Designing novel peptides for detecting the Omicron variant, specifying SARS-CoV-2, and simultaneously screening coronavirus infections

In this study in silico a candidate diagnostic peptide-based tool was designed in four stages including diagnosis of coronavirus diseases, simultaneously identifying of COVID-19 and SARS from other members of this family, specific identification of SARS-CoV2, and diagnosis of COVID-19 Omicron. Designed candidate peptides consist of four immunodominant peptides from the proteins of the SARS-CoV-2 spike (S) and membrane (M). The tertiary structure of each peptide was predicted. The stimulation ability of the humoral immunity for each peptide was evaluated. Finally, in silico cloning was performed to develop an expression strategy for each peptide. These four peptides have suitable immunogenicity, appropriate construct, and the ability to be expressed in E.coli. These results must be experimentally validated in vitro and in vivo to ensure the immunogenicity of the kit.Communicated by Ramaswamy H. Sarma.

Evaluation of self-collected nasal, urine, and saliva samples for molecular detection of SARS-CoV-2 using an EUA approved RT-PCR assay and a laboratory developed LAMP SARS-CoV-2 test

As the SARS-CoV-2 virus spread throughout the world, millions of positive cases of COVID-19 were registered and, even though there are millions of people already vaccinated against SARS-CoV-2, a large part of the global population remains vulnerable to contracting the virus. Massive nasopharyngeal sample collection in Puerto Rico at the beginning of the pandemic was limited by the scarcity of trained personnel and testing sites. To increase SARS-CoV-2 molecular testing availability, we evaluated the diagnostic accuracy of self-collected nasal, saliva, and urine samples using the TaqPath reverse transcription polymerase chain reaction (RT-PCR) COVID-19 kit to detect SARS-CoV-2. We also created a colorimetric loop-mediated isothermal amplification (LAMP) laboratory developed test (LDT) to detect SARS-CoV-2, as another strategy to increase the availability of molecular testing in community-based laboratories. Automated RNA extraction was performed in the KingFisher Flex instrument, followed by PCR quantification of SARS-CoV-2 on the 7500 Fast Dx RT-PCR using the TaqPath RT-PCR COVID-19 molecular test. Data was interpreted by the COVID-19 Interpretive Software from Applied Biosystems and statistically analyzed with Cohen's kappa coefficient (k). Cohen's kappa coefficient (k) for paired nasal and saliva samples showed moderate agreement (0.52). Saliva samples exhibited a higher viral load. We also observed 90% concordance between LifeGene-Biomarks' SARS-CoV-2 Rapid Colorimetric LAMP LDT and the TaqPath RT-PCR COVID-19 test. Our results suggest that self-collected saliva is superior to nasal and urine samples for COVID-19 testing. The results also suggest that the colorimetric LAMP LDT is a rapid alternative to RT-PCR tests for the detection of SARS-CoV-2. This test can be easily implemented in clinics, hospitals, the workplace, and at home; optimizing the surveillance and collection process, which helps mitigate global public health and socioeconomic upheaval caused by airborne pandemics.

Association between SARS-CoV-2 gene specific Ct values and COVID-19 associated in-hospital mortality

Background

Since there are currently no specific SARS-CoV-2 prognostic viral biomarkers for predicting disease severity, there has been interest in using SARS-CoV-2 polymerase chain reaction (PCR) cycle-threshold (Ct) values to predict disease progression.

Objective

This study assessed the association between in-hospital mortality of hospitalized COVID-19 cases and Ct-values of gene targets specific to SARS-CoV-2.

Methods

Clinical data of hospitalized COVID-19 cases from Gauteng Province from April 2020-July 2022 were obtained from a national surveillance system and linked to laboratory data. The study period was divided into pandemic waves: Asp614Gly/wave1 (7 June-22 Aug 2020); beta/wave2 (15 Nov 2020-6 Feb 2021); delta/wave3 (9 May-18 Sept 2021) and omicron/wave4 (21 Nov 2021-22 Jan 2022). Ct-value data of genes specific to SARS-CoV-2 according to testing platforms (Roche-ORF gene; GeneXpert-N2 gene; Abbott-RdRp gene) were categorized as low (Ct < 20), mid (Ct20-30) or high (Ct > 30).

Results

There were 1205 recorded cases: 836(69.4%; wave1), 122(10.1%;wave2) 21(1.7%; wave3) and 11(0.9%;in wave4). The cases' mean age(±SD) was 49 years(±18), and 662(54.9%) were female. There were 296(24.6%) deaths recorded: 241(81.4%;wave1), 27 (9.1%;wave2), 6 (2%;wave3), and 2 (0.7%;wave4) (p < 0.001). Sample distribution by testing platforms was: Roche 1,033 (85.7%), GeneXpert 169 (14%) and Abbott 3 (0.3%). The median (IQR) Ct-values according to testing platform were: Roche 26 (22-30), GeneXpert 38 (36-40) and Abbott 21 (16-24). After adjusting for sex, age and presence of a comorbidity, the odds of COVID-19 associated death were high amongst patients with Ct values 20-30[adjusted Odds Ratio (aOR) 2.25; 95% CI: 1.60-3.18] and highest amongst cases with Ct-values <20 (aOR 3.18; 95% CI: 1.92-5.27), compared to cases with Ct-values >30.

Conclusion

Although odds of COVID19-related death were high amongst cases with Ct-values <30, Ct values were not comparable across different testing platforms, thus precluding the comparison of SARS-CoV-2 Ct-value results.

From Detection to Protection: Antibodies and Their Crucial Role in Diagnosing and Combatting SARS-CoV-2

Understanding the antibody response to SARS-CoV-2, the virus responsible for COVID-19, is crucial to comprehending disease progression and the significance of vaccine and therapeutic development. The emergence of highly contagious variants poses a significant challenge to humoral immunity, underscoring the necessity of grasping the intricacies of specific antibodies. This review emphasizes the pivotal role of antibodies in shaping immune responses and their implications for diagnosing, preventing, and treating SARS-CoV-2 infection. It delves into the kinetics and characteristics of the antibody response to SARS-CoV-2 and explores current antibody-based diagnostics, discussing their strengths, clinical utility, and limitations. Furthermore, we underscore the therapeutic potential of SARS-CoV-2-specific antibodies, discussing various antibody-based therapies such as monoclonal antibodies, polyclonal antibodies, anti-cytokines, convalescent plasma, and hyperimmunoglobulin-based therapies. Moreover, we offer insights into antibody responses to SARS-CoV-2 vaccines, emphasizing the significance of neutralizing antibodies in order to confer immunity to SARS-CoV-2, along with emerging variants of concern (VOCs) and circulating Omicron subvariants. We also highlight challenges in the field, such as the risks of antibody-dependent enhancement (ADE) for SARS-CoV-2 antibodies, and shed light on the challenges associated with the original antigenic sin (OAS) effect and long COVID. Overall, this review intends to provide valuable insights, which are crucial to advancing sensitive diagnostic tools, identifying efficient antibody-based therapeutics, and developing effective vaccines to combat the evolving threat of SARS-CoV-2 variants on a global scale.

A novel nanoliposome model platform mimicking SARS-CoV-2 as a bioreceptor to dissect the amperometric response in biosensor applications

In this study, we proposed to investigate the response of an electrochemical-based immunosensor via nanoliposomes carrying the SARS-CoV-2 Spike-S1 protein. In this regard, we prepared RNA encapsulated nanoliposome functionalized with a specific SARS-CoV-2 Spike-S1 protein as a SARS-CoV-2 model. Then, this new nanoliposome mimicking SARS-CoV-2 was used as the bio-recognizing agent of an immunosensor developed to detect the SARS-CoV-2 within the scope of the study. The working electrode of the immunosensor was coated with chitosan polymer, decorated with SARS-CoV-2 Spike antibody, to achieve antibody-antigen matching on the electrode surface. SARS-CoV-2 mimicking nanoliposomes at various concentrations was used to achieve an amperometric response and the analytical parameters of the sensor were calculated from the relationship between the immunosensor's current values depending on the number of these matches with regard to varying antigen concentrations. Linear measurement range, LOD and measurement sensitivity were calculated as 53 pM-8 nM, 3.79 pM and 55.47 μA nM-1 cm-2, respectively. The standard deviation of the same measurements in the developed immunosensor was 0.33 %.

Ultrasensitive lateral-flow assays via plasmonically active antibody-conjugated fluorescent nanoparticles

Lateral-flow assays (LFAs) are rapid and inexpensive, yet they are nearly 1,000-fold less sensitive than laboratory-based tests. Here we show that plasmonically active antibody-conjugated fluorescent gold nanorods can make conventional LFAs ultrasensitive. With sample-to-answer times within 20 min, plasmonically enhanced LFAs read out via a standard benchtop fluorescence scanner attained about 30-fold improvements in dynamic range and in detection limits over 4-h-long gold-standard enzyme-linked immunosorbent assays, and achieved 95% clinical sensitivity and 100% specificity for antibodies in plasma and for antigens in nasopharyngeal swabs from individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Comparable improvements in the assay's performance can also be achieved via an inexpensive portable scanner, as we show for the detection of interleukin-6 in human serum samples and of the nucleocapsid protein of SARS-CoV-2 in nasopharyngeal samples. Plasmonically enhanced LFAs outperform standard laboratory tests in sensitivity, speed, dynamic range, ease of use and cost, and may provide advantages in point-of-care diagnostics.

Sensitive and rapid detection of influenza A virus for disease surveillance using dual-probe electrochemical biosensor

Influenza A virus (IAV) can cause influenza, a highly infectious zoonotic respiratory disease, and early detection is essential to prevent and control its rapid spread in the population. Given the limitations of traditional detection methods in clinical laboratories, we report a large surface TPB-DVA COFs (TPB: 1,3,5-Tris(4-aminophenyl) benzene, DVA: 1,4-Benzenedicarboxaldehyd, COFs: Covalent organic frameworks) nanomaterial modified electrochemical DNA biosensor, which has dual-probe specific recognition and signal amplification. The biosensor enables quantitative detection of influenza A viruses' complementary DNA (cDNA) from 10 fM to 1 × 10³ nM (LOD = 5.42 fM) with good specificity and high selectivity. The reliability of the biosensor and portable device was verified by comparing the virus concentrations in animal tissues with those measured by digital droplet PCR (ddPCR) (P > 0.05). Moreover, the potential for influenza surveillance in this work was demonstrated by detecting the tissue samples from mice at different stages of infection. In summary, the good performance of this electrochemical DNA biosensor we proposed suggested it has the potential to be a rapid detection device for the influenza A virus, which could assist doctors or other professionals in obtaining rapid and accurate results for outbreak investigation and disease diagnosis.

COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

Dental calculus - An emerging bio resource for past SARS CoV2 detection, studying its evolution and relationship with oral microflora

The most grievous threat to human health has been witnessed worldwide with the recent outbreak of Corona virus disease 2019 (COVID-19). There is mounting evidence available regarding theconnect of COVID -19 and oral cavity, particularly periodontal disease. The current review provides an update on the diagnostic potential of dental calculus and how this bio resource may help in providing us huge amount of diagnostic regarding the causative virus. Contemporary standard method of diagnosis via nasopharyngeal swabs (NPS) is tedious, may enhance the risk of aerosol contamination by inducing sneezing and detects the presence of active infection only.However,dental calculus being a mineralized deposit serves as a reservoir for biomoleculesand provides detection of past SARS CoV2 infection. Further, the abundance of information that can be obtained from this remarkable mineralized deposit on teeth regarding the viral genome, its evolution and interactions with the oral microflora shall enhance the understanding of the viral disease process and its connection with the periodontal disease. Additional diagnostic information, which may be obtained from this simple bio reservoir can complement the contemporary diagnostic strategies adopted in the management of COVID-19pandemic and enhance our existing knowledge for developing improvised novel approaches to mitigate the effects of mutated variants of the infectious agent.

SARS-COV-2 IgG specific antibodies persistence in recovered COVID-19 individuals and its association with severity and time of illness

In order to accurately interpret the immune response to COVID-19, it is critical to know how long serum antibodies to COVID-2 persist. This study aimed to describe the serum IgG responses to SARS-CoV-2 in patients with mild, moderate, and severe COVID-19 infection in Birjand, South Khorasan province, Iran. The study was performed on individuals whose COVID-19 disease was confirmed by RT-PCR and recovered from the disease. After completing the questionnaire, blood samples were collected from 4 different groups based on the time of the test at two, four, six, and eight months' post-recovery. Then, SARS-COV-2 virus-specific IgG nucleocapsid antibody level in patients was measured using the enzyme-linked immunosorbent assay (ELISA). In total, 206 patients (mean age 44.19 ± 14.9, 51% man) were included in the survey. Serum prevalence of specific IgG antibodies in patients with mild, moderate, and severe COVID-19 disease was 51.5%, 64% and 78.9%, respectively. Furthermore, serum prevalence of COVID-19 specific IgG antibody level in two, four, six, and eight months after recovery were 80.8, 69.1, 43.2 and 41.8%, respectively (p < 0.05). The multiple logistic regression model showed that the variables of age and the time elapsed after recovery had a significant relationship with the positive antibody test of recovered COVID-19 patients (P < 0.05). But other variables had no significant relationship with the result of antibody test (P > 0.05). In the present report, we attempted to characterize the antibody response against SARS-CoV-2 in patients with mild, moderate, and severe COVID-19, with the aim of better elucidating the humoral immune response after recovery from SARS-CoV-2 infection.

Investigation and comparison of graphene nanoribbon and carbon nanotube based SARS-CoV-2 detection sensors: An ab initio study

The rapid detection of SARS-CoV-2, the pathogen of the Covid-19 pandemic, is obviously of great importance for stopping the spread of the virus by detecting infected individuals. Here, we report the ab initio analysis results of graphene nanoribbon (GNR) and carbon nanotube (CNT) based SARS-CoV-2 detection sensors which are experimentally demonstrated in the literature. The investigated structures are the realistic molecular models of the sensors that are employing 1-pyrenebutyric acid N-hydroxysuccinimide ester as the antibody linker. Density functional theory in conjunction with non-equilibrium Green's function formalism (DFT-NEGF) is used to obtain the transmission spectra, current-voltage and resistance-voltage characteristics of the sensors before and after the attachment of the SARS-CoV-2 spike protein. The operation mechanism of the GNR and CNT based SARS-CoV-2 sensors are exposed using the transmission spectrum analysis. Moreover, it is observed that GNR based sensor has more definitive detection characteristics compared to its CNT based counterpart.

Combating the Progression of Novel Coronavirus SARS-CoV-2 Infectious Disease: Current State and Future Prospects in Molecular Diagnostics and Drug Discovery

A highly infectious and life-threatening virus was first reported in Wuhan, China, in late 2019, and it rapidly spread all over the world. This novel virus belongs to the coronavirus family and is associated with severe acute respiratory syndrome (SARS), causing respiratory disease known as COVID-19. In March 2020, WHO has declared the COVID-19 outbreak a global pandemic. Its morbidity and mortality rates are swiftly rising day by day, with the situation becoming more severe and fatal for the comorbid population. Many COVID-19 patients are asymptomatic, but they silently spread the infection. There is a need for proper screening of infected patients to prevent the epidemic transmission of disease and for early curative interventions to reduce the risk of developing severe complications from COVID-19. To date, the diagnostic assays are of two categories, molecular detection of viral genetic material by real-time RTpolymerase chain reaction and serological test, which relies on detecting antiviral antibodies. Unfortunately, there are no effective prophylactics and therapeutics available against COVID-19. However, a few drugs have shown promising antiviral activity against it, and these presently are being referred for clinical trials, albeit FDA has issued an Emergency Use Authorization (EUA) for the emergency use of a few drugs for SARSCoV- 2 infection. This review provides an insight into current progress, challenges and future prospects of laboratory detection methods of COVID-19, and highlights the clinical stage of the major evidence-based drugs/vaccines recommended against the novel SARS-CoV-2 pandemic virus.

A probabilistic epidemiological model for infectious diseases: The case of COVID-19 at global-level

This study has developed a probabilistic epidemiological model a few weeks after the World Health Organization declared COVID-19 a pandemic (based on the little data available at that time). The aim was to assess relative risks for future scenarios and evaluate the effectiveness of different management actions for 1 year ahead. We quantified, categorized, and ranked the risks for scenarios such as business as usual, and moderate and strong mitigation. We estimated that, in the absence of interventions, COVID-19 would have a 100% risk of explosion (i.e., more than 25% infections in the world population) and 34% (2.6 billion) of the world population would have been infected until the end of simulation. We analyzed the suitability of model scenarios by comparing actual values against estimated values for the first 6 weeks of the simulation period. The results proved to be more suitable with a business-as-usual scenario in Asia and moderate mitigation in the other continents. If everything went on like this, we would have 55% risk of explosion and 22% (1.7 billion) of the world population would have been infected. Strong mitigation actions in all continents could reduce these numbers to, 7% and 3% (223 million), respectively. Although the results were based on the data available in March 2020, both the model and probabilistic approach proved to be practicable and could be a basis for risk assessment in future pandemic episodes with unknown virus, especially in the early stages, when data and literature are scarce.

The correlation between IgM and IgG antibodies with blood profile in patients infected with severe acute respiratory syndrome coronavirus

OBJECTIVES

This study aimed to determine the levels of IgM and IgG antibody response to the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 in coronavirus disease 2019 (COVID-19) patients with different disease severity.

METHODS

IgM and IgG antibody levels were evaluated via enzyme-linked immunosorbent assay (ELISA). In total, 100 patients with confirmed SARS-CoV-2 infection were enrolled in this study and viral RNA was detected by using Real-time PCR technique. Clinical and laboratory data were collected and analyzed after hospital admission for COVID-19 and two months post-admission.

RESULTS

The level of anti-SARS-CoV-2 antibody IgG was significantly higher in the severe patients than those in moderate and mild groups, 2 months after admission. Also, level of IgG was positively associated with increased WBC, NUT and LYM counts in sever than mild or moderate groups after admission to hospital.

CONCLUSION

Our findings suggested that patients with severe illness might experience longer virus exposure times and have a stronger antibody response against viral infection. Thus, they have longer time immunity compared with other groups.

Rapid, label-free and low-cost diagnostic kit for COVID-19 based on liquid crystals and machine learning

We report a label-free method for detection of the SARS-CoV-2 virus in nasopharyngeal swab samples without purification steps and multiplication of the target which simplifies and expedites the analysis process. The kit consists of a textile grid on which liquid crystals (LC) are deposited and the grid is placed in a crossed polarized microscopy. The swab samples are subsequently placed on the LCs. In the presence of a particular biomolecule, the direction of LCs changes locally based on the properties of the biomolecule and forms a particular pattern. As the swab samples are not perfectly purified, image processing and machine learning techniques are employed to detect the presence of specific molecules or quantify their concentrations in the medium. The method can differentiate negative and positive COVID-19 samples with an accuracy of 96% and also differentiate COVID-19 from influenza types A and B with an accuracy of 93%. The kit is portable, simple to manufacture, convenient to operate, cost effective, rapid and sensitive. The simplicity of the specimen processing, the speed of image acquisition, and fast diagnostic operations enable the deployment of the proposed technique for performing extensive on-spot screening of COVID-19 in public places.

A comparison between SARS-CoV-1 and SARS-CoV2: an update on current COVID-19 vaccines

Since the outbreak of the novel coronavirus disease 2019 (COVID-19) in Wuhan, China, many health care systems have been heavily engaged in treating and preventing the disease, and the year 2020 may be called as "historic COVID-19 vaccine breakthrough". Due to the COVID-19 pandemic, many companies have initiated investigations on developing an efficient and safe vaccine against the virus. From Moderna and Pfizer in the United States to PastocoVac in Pasteur Institute of Iran and the University of Oxford in the United Kingdom, different candidates have been introduced to the market. COVID-19 vaccine research has been facilitated based on genome and structural information, bioinformatics predictions, epitope mapping, and data obtained from the previous developments of severe acute respiratory syndrome coronavirus (SARS-CoV or SARS-CoV-1) and middle east respiratory syndrome coronavirus (MERS-CoV) vaccine candidates. SARS-CoV genome sequence is highly homologous to the one in COVID-19 and both viruses use the same receptor, angiotensin-converting enzyme 2 (ACE2). Moreover, the immune system responds to these viruses, partially in the same way. Considering the on-going COVID-19 pandemic and previous attempts to manufacture SARS-CoV vaccines, this paper is going to discuss clinical cases as well as vaccine challenges, including those related to infrastructures, transportation, possible adverse reactions, utilized delivery systems (e.g., nanotechnology and electroporation) and probable vaccine-induced mutations.

What Contributes to COVID-19 Vaccine Hesitancy? A Systematic Review of the Psychological Factors Associated with COVID-19 Vaccine Hesitancy

Vaccine hesitancy plays a crucial role in worldwide pandemic-control efforts. The multifaceted nature of vaccine hesitancy entails many psychological factors that are widely discussed in the literature, although few studies specifically compile these factors. Thus, this systematic review aims to synthesize the psychological factors contributing to vaccine hesitancy. As per the PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines, a systematic search was conducted on electronic databases PubMed, Scopus, Science Direct, PsycNET, and Web of Science, and a manual search was conducted on Google Scholar. Out of the 2289 articles obtained, 79 studies that met the inclusion criteria were deemed eligible for the review. The findings highlight appraisals of the COVID-19 pandemic, vaccine safety and side effects, vaccine confidence/trust, trust in government and healthcare professionals, scepticism around vaccine production, conspiracy beliefs, emotions, and information and knowledge about the vaccine as the major psychological factors contributing to vaccine hesitancy. Concerningly, misinformation on COVID-19 vaccination spread through social media platforms, increasing vaccine hesitancy. Recommendations for government authorities, healthcare professionals, and implications for future research are also outlined.

Virus-Like Particles of SARS-CoV-2 as Virus Surrogates: Morphology, Immunogenicity, and Internalization in Neuronal Cells

The engineering of virus-like particles (VLPs) is a viable strategy for the development of vaccines and for the identification of therapeutic targets without using live viruses. Here, we report the generation and characterization of quadruple-antigen SARS-CoV-2 VLPs. VLPs were generated by transient transfection of two expression cassettes in adherent HEK293T cells─one cassette containing Mpro for processing of three structural proteins (M, E, and N), and the second cassette expressing the Spike protein. Further characterization revealed that the VLPs retain close morphological and antigenic similarity with the native virus and also bind strongly to the SARS-CoV-2 receptor hACE-2 in an in vitro binding assay. Interestingly, the VLPs were found to internalize into U87-MG cells through cholesterol-rich domains in a dynamin-dependent process. Finally, our results showed that mice immunized with VLPs induce robust humoral and cellular immune responses mediated by enhanced levels of IL-4, IL-17, and IFNγ. Taken together, our results demonstrate that VLPs mimic the native virus and induce a strong immune response, indicating the possible use of these particles as an alternative vaccine candidate against SARS-CoV-2. VLPs can also be effective in mapping the initial stages of virus entry and screening inhibitors.

Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study

Objectives: To develop and internally validate two clinical risk scores to detect coronavirus disease 2019 (COVID-19) during local outbreaks.

Methods: Medical records were extracted for a retrospective cohort of 336 suspected patients admitted to Baodi hospital between 27 January to 20 February 2020. Multivariate logistic regression was applied to develop the risk-scoring models, which were internally validated using a 5-fold cross-validation method and Hosmer-Lemeshow (H-L) tests.

Results: Fifty-six cases were diagnosed from the cohort. The first model was developed based on seven significant predictors, including age, close contact with confirmed/suspected cases, same location of exposure, temperature, leukocyte counts, radiological findings of pneumonia and bilateral involvement (the mean area under the receiver operating characteristic curve [AUC]:0.88, 95% CI: 0.84–0.93). The second model had the same predictors except leukocyte and radiological findings (AUC: 0.84, 95% CI: 0.78–0.89, Z = 2.56, p = 0.01). Both were internally validated using H-L tests and showed good calibration (both p > 0.10).

Conclusion: Two clinical risk scores to detect COVID-19 in local outbreaks were developed with excellent predictive performances, using commonly measured clinical variables. Further external validations in new outbreaks are warranted.

"Intention to receive COVID-19 vaccine among healthcare workers: a comparison between two surveys"

BACKGROUND

Considering the importance of intention to receive COVID-19 vaccine among healthcare workers and its role in maintaining their health and inhibiting the epidemic spread of Covid-19, the present study was done to identify the changes in intention to receive COVID-19 vaccine rate in two different time points and it's determinants based on the dimensions of the health belief model among healthcare workers in Iran.

METHODS

Two cross-sectional surveys performed to investigate COVID-19 vaccination intent and associated factors based on the health belief model. The first conducted on 1244 participants from August 18 to 23, 2020, and the second on 1514 participants from February 5 to April 29, 2021, both using a questionnaire of intent to accept COVID-19 vaccination. The questionnaire distribution platform in both surveys was similarly, WhatsApp and Telegram social and working virtual groups of HCWs. Data were analyzed with SPSS-16 software for descriptive and analytical statistics.

RESULTS

In the first survey, 58.4% (95% CI: 0.55-0.61%) of healthcare workers intended to receive the COVID-19 vaccine, the rate dropped to 45.7% (95% CI: 0.43-0.48%) in the second survey (P < 0.001). The regression analysis indicated six factors that were significantly associated with higher intention to receive COVID-19 vaccine: being a female (OR = 1.84, 95% CI (1.11-3.03)), history of Covid-19 infection (OR = 1.54, 95% CI (1.09-2.18), perceptions of Covid-19 disease (OR = 1.13, 95% CI (1.01-1.28)), perceived benefits of COVID-19 vaccine (OR = 1.34, 95% CI (1.22-1.47)), prosocial norms for COVID-19 vaccination (OR = 1.25, 95% CI (1.21-1.29)), and COVID-19 vaccine safety/cost concerns (OR = 1.25, 95% CI (1.17-1.33)).

CONCLUSIONS

Present study showed an undesirable rate of intention to receive COVID-19 vaccine among healthcare workers, especially decreasing over the time, emphasize the need of interventions to promote healthcare workers' intention to receive the vaccine and reduce the spread of COVID-19 disease.

Recent Advances in Understanding SARS-CoV-2 Infection and Updates on Potential Diagnostic and Therapeutics for COVID-19

Abstract:

A more focused approach is needed to understand the SARS-CoV-2 virulence, structure, and genomics to devise more effective diagnostic and treatment interventions as this virus can evade the immune attack and causes life-threatening complications such as cytokine storm. The spread of the virus is still amplifying and causing thousands of new cases worldwide. It is essential to review current diagnostics and treatment approaches to pave the way to correct or modify our current practices to make more effective interventions against COVID-19. COVID-19 vaccine development has moved at a breakneck pace since the outbreak began, utilizing practically all possible platforms or tactics to ensure the success of vaccines. A total of 42 vaccine candidates have already entered clinical trials, including promising results from numerous vaccine candidates in phase 1 or phase 2 trials. Further, many existing drugs are being explored on broad-spectrum antiviral medications for their use in clinical recovery against COVID- 19. The present review attempts to re-examine the SARS-CoV-2 structure, its viral life cycle, clinical symptoms and pathogenesis, mode of transmission, diagnostics, and treatment strategies that may be useful for resorting to more effective approaches for controlling COVID-19. Various antiviral drugs and vaccination strategies with their strengths and weaknesses are also discussed in the paper to augment our understanding of COVID-19 management.

Evaluation of Two Broadly Used Commercial Methods for Detection of Respiratory Viruses with a Recently Added New Target for Detection of SARS-CoV-2

The clinical symptoms caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are nonspecific and can be associated with most other respiratory viruses that cause acute respiratory tract infections (ARI). Because the clinical differentiation of COVID-19 patients from those with other respiratory viruses is difficult, the evaluation of automated methods to detect important respiratory viruses together with SARS-CoV-2 seems necessary. Therefore, this study compares two molecular assays for the detection of respiratory viruses, including SARS-CoV-2: the Respiratory Viruses 16-Well Assay (AusDiagnostics, Pty Ltd., Mascot, Australia) and the Allplex™ RV Essential Assay coupled with the Allplex™-nCoV Assay (Seegene Inc., Seoul, Korea). The two methods (AusDiagnostics and Alplex^TM-nCoV Assay SARS-CoV-2) had 98.6% agreement with the reference method, cobas 6800, for the detection of SARS-CoV-2. Agreement between the AusDiagnostics assay and the Alplex^TM RV Essential Assay for the detection of seven respiratory viruses was 99%. In our experience, the Respiratory Viruses 16-Well Assay proved to be the most valuable and useful medium-throughput method for simultaneous detection of important respiratory viruses and SARS-CoV-2. The main advantages of the method are high specificity for all targets included and their simultaneous detection and medium throughput with the option of having multiple instruments provide a constant run.

A Review on Potential Electrochemical Point-of-Care Tests Targeting Pandemic Infectious Disease Detection: COVID-19 as a Reference

Fast and accurate point-of-care testing (POCT) of infectious diseases is crucial for diminishing the pandemic miseries. To fight the pandemic coronavirus disease 2019 (COVID-19), numerous interesting electrochemical point-of-care (POC) tests have been evolved to rapidly identify the causal organism SARS-CoV-2 virus, its nucleic acid and antigens, and antibodies of the patients. Many of those electrochemical biosensors are impressive in terms of miniaturization, mass production, ease of use, and speed of test, and they could be recommended for future applications in pandemic-like circumstances. On the other hand, self-diagnosis, sensitivity, specificity, surface chemistry, electrochemical components, device configuration, portability, small analyzers, and other features of the tests can yet be improved. Therefore, this report reviews the developmental trend of electrochemical POC tests (i.e., test platforms and features) reported for the rapid diagnosis of COVID-19 and correlates any significant advancements with relevant references. POCTs incorporating microfluidic/plastic chips, paper devices, nanomaterial-aided platforms, smartphone integration, self-diagnosis, and epidemiological reporting attributes are also surfed to help with future pandemic preparedness. This review especially screens the low-cost and easily affordable setups so that management of pandemic disease becomes faster and easier. Overall, the review is a wide-ranging package for finding appropriate strategies of electrochemical POCT targeting pandemic infectious disease detection.

Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening

Novel drug compound hunting was carried out for SARS-CoV-2 proteins with low mutation susceptibility. The probability of escape mutation and drug resistance is lower if conserved microbial proteins are targeted by therapeutic drugs. Mutation rate of all SARS-CoV-2 proteins were analyzed via multiple sequence alignment Non-Structural Protein 13 and Non-Structural Protein 16 were selected for the current study due to low mutation rate among viral strains and significant functionality. Cross-species mutation rate analysis for NSP13 and NSP16 showed these are well-conserved proteins among four coronaviral species. Viral helicase inhibitors, identified using literature-mining, were docked against NSP13. Pharmacophore-based screening of 11,375 natural compounds was conducted for NSP16. Stabilities of top compounds inside human body were confirmed via molecular dynamic simulation. ADME properties and LD₅₀ values of the helicase inhibitors and Ambinter natural compounds were analyzed. Compounds against NSP13 showed binding affinities between −10 and −5.9 kcal/mol whereby ivermectin and scutellarein showed highest binding energies of −10 and −9.9 kcal/mol. Docking of 18 hit compounds against NSP16 yielded binding affinities between −8.9 and −4.1 kcal/mol. Hamamelitannin and deacyltunicamycin were the top compounds with binding affinities of −8.9 kcal/mol and −8.4 kcal/mol. The top compounds showed stable ligand–protein interactions in molecular dynamics simulation. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, high binding affinity and molecular interactions. Conversion of these compounds into drugs after in vitro experimentation can become better treatment options to elevate COVID management.

COVID-19 Global Pandemic Fight by Drugs: A Mini-Review on Hope and Hype

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Coronavirus disease 2019 (Covid-19), a serious disease caused by the Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2), was firstly identified in the city of Wuhan of China in December 2019, which then spread and became a global issue due to its high transmission rate. To date, the outbreak of COVID-19 has resulted in infection to 230,868,745 people and the death of 4,732,669 patients. It has paralyzed the economy of all the countries worldwide. Considering the possible mutations of SARS-CoV-2, the current medical emergency requires a longer time for drug design and vaccine development. Drug repurposing is a promising option for potent therapeutics against the pandemic. The present review encompasses various drugs or appropriate combinations of already FDA-approved antimalarial, antiviral, anticancer, anti-inflammatory, and antibiotic therapeutic candidates for use in the clinical trials as a ray of hope against COVID-19. It is expected to deliver better clinical and laboratory outcomes of drugs as a prevention strategy for the eradication of the disease.

Association Between Dimensions of Professional Burnout and Turnover Intention Among Nurses Working in Hospitals During Coronavirus Disease (COVID-19) Pandemic in Iran Based on Structural Model

Purpose

This study was done to assess the dimensions of professional burnout and turnover intention among nurses working in hospitals during the coronavirus disease 2019 (COVID-19) pandemic in Iran based on a structural model.

Methods

This cross-sectional study was performed among 170 nurses working in two referral hospitals of COVID-19 in Tehran Province, Iran, from September to December 2020. Data were collected using the sociodemographic form, Maslach Burnout Inventory (MBI), and Turnover Intention Questionnaire. Data were analyzed with SPSS and Amos software version 22 using independent t-test, ANOVA, and structural equation model.

Results

The mean scores for burnout in emotional fatigue, depersonalization, and personal accomplishment dimensions were 25.38 ± 7.55, 9.47 ± 4.40, and 34.94 ± 7.80, respectively, moreover for the turnover intention, the score was 6.51 ± 3.17. The reduced personal accomplishment was identified as a positive predictor of turnover intention (p = 0.01). Work position and interest in attending the organization were significantly correlated with the turnover intention (p < 0.05).

Conclusions

There is an immediate need to prepare nurses to cope better with the COVID-19 outbreak. Work-related stressors during the COVID-19 pandemic have led to an increase in nurses' burnout and turnover intention. Identifying and managing the factors related to professional burnout will make it possible to prevent the nurses' turnover intention in such critical situations.

Clinical and Biochemical Characteristics of COVID-19 in a Primary Care Center in the South Batinah Region of Oman

Objectives

The main purpose of this study was to identify the clinical and biochemical profile of coronavirus disease 2019 (COVID-19) and sex differences in Rustaq Polyclinic in South Batinah Governorate.

Methods

This study is a retrospective chart review of COVID-19 patients diagnosed in Rustaq Polyclinic in the South Batinah region of Oman. The medical charts of 150 patients from November 10, 2020, to November 24, 2021, at Rustaq Polyclinic were retrospectively reviewed, and clinical and laboratory parameters were extracted. Information regarding the patients’ demographics, risk factors, clinical symptoms or signs, and laboratory findings on admission were obtained. Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS) software version 24.0 (IBM Corp., Armonk, NY, USA).

Results

A total of 150 study participant data were added to the analysis. Of those, 97 (64.7%) were male and 53 (35.3%) were female, with a median age of 32 and 39 among males and females, respectively. Male and female age (p=0.017) and marital status (p=0.003) were significantly different. No significant difference (p≥0.05) was observed between male and female study participants regarding their history of travel, history of contact with COVID-19-positive patients, diabetes, hypertension, stroke, and home management. Similarly, no significant difference (p≥0.05) was observed between males and females regarding their clinical presentations.

Conclusion

Many symptomatic patients have shown influenza-like symptoms such as fever, respiratory symptoms such as cough, sore throat, headache, myalgia, and loss of smell. The spectrum of symptomatic infection ranges from mild to severe, and most infections are not severe. It is imperative to equip ourselves with adequate understanding and protective measures such as vaccination and diverse treatment modalities against the constantly changing nature of novel coronaviruses.

In Silico Prediction of New Mutations That Can Improve the Binding Abilities Between 2019-nCoV Coronavirus and Human ACE2

The Coronavirus Disease 2019 (COVID-19) has become an international public health emergency, posing a serious threat to human health and safety around the world. The 2019-nCoV coronavirus spike protein was confirmed to be highly susceptible to various mutations, which can trigger apparent changes of virus transmission capacity and the pathogenic mechanism. In this article, the binding interface was obtained by analyzing the interaction modes between 2019-nCoV coronavirus and the human ACE2. Based on the "SIFT server" and the "bubble" identification mechanism, 9 amino acid sites were selected as potential mutation-sites from the 2019-nCoV-S1-ACE2 binding interface. Subsequently, a total number of 171 mutant systems for 9 mutation-sites were optimized for binding-pattern comparsion analysis, and 14 mutations that may improve the binding capacity of 2019-nCoV-S1 to ACE2 were selected. The Molecular Dynamic Simulations were conducted to calculate the binding free energies of all the 14 mutant systems. Finally, we found that most of the 14 mutations on the 2019-nCoV-S1 protein could enhance the binding ability between 2019-nCoV coronavirus and human ACE2. Among which, the binding capacities for G446R, Y449R and F486Y mutations could be increased by 20 percent, and that for S494R mutant increased even by 38.98 percent. We hope this research could provide significant help for the future epidemic detection, drug and vaccine development.

Structure-based identification of potential SARS-CoV-2 main protease inhibitors

To address coronavirus disease (COVID-19), currently, no effective drug or vaccine is available. In this regard, molecular modeling approaches are highly useful to discover potential inhibitors of the main protease (Mpro) enzyme of SARS-CoV-2. Since, the Mpro enzyme plays key roles in mediating viral replication and transcription; therefore, it is considered as an attractive drug target to control SARS-CoV-2 infection. By using structure-based drug design, pharmacophore modeling, and virtual high throughput drug screening combined with docking and all-atom molecular dynamics simulation approach, we have identified five potential inhibitors of SARS-CoV-2 Mpro. MD simulation studies revealed that compound 54035018 binds to the Mpro with high affinity (ΔGbind -37.40 kcal/mol), and the complex is more stable in comparison with other protein-ligand complexes. We have identified promising leads to fight COVID-19 infection as these compounds fulfill all drug-likeness properties. However, experimental and clinical validations are required for COVID-19 therapy.Communicated by Ramaswamy H. Sarma.

Virtual screening and molecular dynamics simulation analysis of Forsythoside A as a plant-derived inhibitor of SARS-CoV-2 3CLpro

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a more severe strain of coronavirus (CoV) that was first emerged in China in 2019. Available antiviral drugs could be repurposed and natural compounds with antiviral activity could be safer and cheaper source of medicine for SARS-CoV-2. 78 natural antiviral compounds database was identified from literature and virtual screening technique was applied to identify potential 3-chymotrypsin-like protease (3CLpro) inhibitors. Molecular docking studies were conducted to analyze the main protease (3CLpro) and inhibitors interactions with key residues of active site of target protein (PDB ID: 6LU7), active site constitute the part of active domain I and II of 3CLpro. 10 compounds with highest dock score were subjected to calculate ADMET parameters to figure out drug-likeness. Molecular dynamic (MD) simulation of the selected lead was performed by Amber simulation package to understand the conformational changes in docked complex. MD simulations analysis (RMSD, RMSF, Rg, BF, HBs, and SASA plots) of lead bounded with 3CLpro, hence revealed the important structural turns and twists during MD simulations from 0 to 100 ns. MM-PBSA/GBSA methods has also been applied for the estimation binding free energy (BFE) of the selected lead-complex. The present study has identified lead compound “Forsythoside A” an active extract of Forsythia suspense as SARS-CoV-2 3CLpro inhibitor that can block the viral replication and translation. Structural analysis of target protein and lead compound performed in this study could contribute to the development of potential drug against SARS-CoV-2 infection.

Antiviral Biodegradable Food Packaging and Edible Coating Materials in the COVID-19 Era: A Mini-Review

With the onset of the COVID-19 pandemic in late 2019, and the catastrophe faced by the world in 2020, the food industry was one of the most affected industries. On the one hand, the pandemic-induced fear and lockdown in several countries increased the online delivery of food products, resulting in a drastic increase in single-use plastic packaging waste. On the other hand, several reports revealed the spread of the viral infection through food products and packaging. This significantly affected consumer behavior, which directly influenced the market dynamics of the food industry. Still, a complete recovery from this situation seems a while away, and there is a need to focus on a potential solution that can address both of these issues. Several biomaterials that possess antiviral activities, in addition to being natural and biodegradable, are being studied for food packaging applications. However, the research community has been ignorant of this aspect, as the focus has mainly been on antibacterial and antifungal activities for the enhancement of food shelf life. This review aims to cover the different perspectives of antiviral food packaging materials using established technology. It focuses on the basic principles of antiviral activity and its mechanisms. Furthermore, the antiviral activities of several nanomaterials, biopolymers, natural oils and extracts, polyphenolic compounds, etc., are discussed.

Inhibition of the IFN-α JAK/STAT Pathway by MERS-CoV and SARS-CoV-1 Proteins in Human Epithelial Cells

Coronaviruses (CoVs) have caused several global outbreaks with relatively high mortality rates, including Middle East Respiratory Syndrome coronavirus (MERS)-CoV, which emerged in 2012, and Severe Acute Respiratory Syndrome (SARS)-CoV-1, which appeared in 2002. The recent emergence of SARS-CoV-2 highlights the need for immediate and greater understanding of the immune evasion mechanisms used by CoVs. Interferon (IFN)-α is the body's natural antiviral agent, but its Janus kinase/signal transducer and activators of transcription (JAK/STAT) signalling pathway is often antagonized by viruses, thereby preventing the upregulation of essential IFN stimulated genes (ISGs). Therapeutic IFN-α has disappointingly weak clinical responses in MERS-CoV and SARS-CoV-1 infected patients, indicating that these CoVs inhibit the IFN-α JAK/STAT pathway. Here we show that in lung alveolar A549 epithelial cells expression of MERS-CoV-nsp2 and SARS-CoV-1-nsp14, but not MERS-CoV-nsp5, increased basal levels of total and phosphorylated STAT1 & STAT2 protein, but reduced IFN-α-mediated phosphorylation of STAT1-3 and induction of MxA. While MERS-CoV-nsp2 and SARS-CoV-1-nsp14 similarly increased basal levels of STAT1 and STAT2 in bronchial BEAS-2B epithelial cells, unlike in A549 cells, they did not enhance basal pSTAT1 nor pSTAT2. However, both viral proteins reduced IFN-α-mediated induction of pSTAT1-3 and ISGs (MxA, ISG15 and PKR) in BEAS-2B cells. Furthermore, even though IFN-α-mediated induction of pSTAT1-3 was not affected by MERS-CoV-nsp5 expression in BEAS-2B cells, downstream ISG induction was reduced, revealing that MERS-CoV-nsp5 may use an alternative mechanism to reduce antiviral ISG induction in this cell line. Indeed, we subsequently discovered that all three viral proteins inhibited STAT1 nuclear translocation in BEAS-2B cells, unveiling another layer of inhibition by which these viral proteins suppress responses to Type 1 IFNs. While these observations highlight cell line-specific differences in the immune evasion effects of MERS-CoV and SARS-CoV-1 proteins, they also demonstrate the broad spectrum of immune evasion strategies these deadly coronaviruses use to stunt antiviral responses to Type IFN.

DNA aptamer selection for SARS-CoV-2 spike glycoprotein detection

The rapid spread of SARS-CoV-2 infection throughout the world led to a global public health and economic crisis triggering an urgent need for the development of low-cost vaccines, therapies and high-throughput detection assays. In this work, we used a combination of Ideal-Filter Capillary Electrophoresis SELEX (IFCE-SELEX), Next Generation Sequencing (NGS) and binding assays to isolate and validate single-stranded DNA aptamers that can specifically recognize the SARS-CoV-2 Spike glycoprotein. Two selected non-competing DNA aptamers, C7 and C9 were successfully used as sensitive and specific biological recognition elements for the development of electrochemical and fluorescent aptasensors for the SARS-CoV-2 Spike glycoprotein with detection limits of 0.07 fM and 41.87 nM, respectively.

Plasmon-enhanced Quantitative Lateral Flow Assay for Femtomolar Detection of SARS-CoV-2 Antibodies and Antigens

Lateral flow assays (LFAs) are the cornerstone of point-of-care diagnostics. Although rapid and inexpensive, they are 1000-fold less sensitive than laboratory-based tests and cannot be used for definitive negative diagnosis. Here, we overcome this fundamental limitation by employing plasmonically-enhanced nanoscale colorimetric and fluorescent labels. Plasmonic LFAs (p-LFAs) enabled ultrasensitive detection and quantification of low abundance analytes, without compromising the direct visual detection of conventional LFAs. Dynamic ranges and limits of detection were up to 100-fold superior to "gold standard" ELISA (enzyme-linked immunosorbent assay). p-LFAs had sample-to-answer time of 20 min, compared to 4 hours for ELISA, while achieving over 95% analytical sensitivity and 100% analytical specificity for antibodies and antigens of SARS-CoV-2 in human specimens. We also demonstrate that the p-LFAs enable quantitative detection of the target analytes in a standard-free manner. p-LFAs offer potential as a broadly adaptable point-of-care diagnostic platform that outperforms standard laboratory tests in sensitivity, speed, dynamic range, ease of use, and cost.

Antibody Response to SARS-CoV-2 in Relation to the Contributing Factors in COVID-19 Patients

Human health has always been challenged by variety of viral infections, but severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has surpassed all previous viral diseases and emerged as a major health challenge around the globe. Real-time polymerase chain reaction (PCR) is the gold standard for the diagnosis of SARS-CoV-2 and serological assay provides a compliment to diagnosis after second week of infection. The aim of the study is the characterization of antibody response to SARS-CoV-2 in the blood sample of diagnosed coronavirus disease 2019 (COVID-19) patients, and its potential association with factors such as age, gender, time, and symptoms. Serum from 248 confirmed SARS-CoV-2 patients was investigated for antibodies. Elecsys anti-SARS chemiluminescent immune assay was performed for the detection of nucleocapsid-specific antibodies. Association of antibody response with gender, age, and time after onset of symptoms was analyzed. Among 248 PCR positive SARS-CoV-2 patients, 214 (86.3%) have virus-specific antibody signals. Antibodies positivity rate was higher in male patient patients as compared with female patients (90.8% vs. 79.2%, p = 0.009). Patients aged 30-40 years had the highest antibody positivity rate as compared with other groups (89.10%, p = 0.04). Patients age group >60 years had a lower positivity rate (75%, p = 0.04). The increasing trend in the antibodies detection with time was observed, maximum positive antibodies response rate observed at 8 weeks. Patients were categorized on the basis of clinical symptoms into asymptomatic, mild, and moderate; 17.7% were asymptomatic, 60.5% showed mild symptoms, and 21.8% showed moderate symptoms of the disease. Males were seen to be more asymptomatic as compared with females (i.e., 59.1% to 40.9%). The serological test for SARS-CoV-2 has a high sensitivity at >2 weeks after the positive PCR result or onset of illness. In addition, the serological response differs among patients based on gender, age, as well as time between the onset of symptoms or PCR confirmation and sample collection for the study of antibody response.

Outbreak of COVID-19: A Detailed Overview and Its Consequences

INTRODUCTION

After the outbreak from Wuhan City of China, COVID-19, caused by SARS-CoV-2, has become a pandemic worldwide in a very short span of time. The high transmission rate and pathogenicity of this virus have made COVID-19 a major public health concern globally. Basically, the emergence of SARS-CoV-2 is the third introduction of a highly infectious human epidemic coronavirus in the twenty-first century. Various research groups have claimed bats to be the natural host of SARS-CoV-2. However, the intermediate host and mode of transmission from bat to humans are not revealed yet. The COVID-19 cost hundreds and thousands of lives and millions are facing the consequences. The objective of this chapter was to analyze the outbreak of COVID-19 and problems faced globally.

METHODS

All published relevant literature from scientific sources and reputed news channels are considered to write the current review.

RESULTS

Generally, elder persons and more particularly people with underlying medical conditions are found to be highly vulnerable to severe infection and prone to fatal outcomes. Unfortunately, there is no specific treatment with clinically approved drugs or vaccines to treat this disease. Several research groups have been investigating the efficacies of several antiviral and repurposed drugs. Currently, most of the SARS-COV-2 vaccines are at the preclinical or clinical stage of development. The latest research progress on the epidemiology, clinical characteristics, pathogenesis, diagnosis, and current status of therapeutic intervention indicates that still a specific drug or vaccine needs to come up for the effective treatment of the pandemic COVID-19. It is observed that various aspects of social life, economic status, and healthcare systems are majorly affected by this pandemic.

CONCLUSION

It is concluded that the outbreak of COVID-19 has severely affected each and every field, such as social, scientific, industrial, transport, and medical sectors. Irrespective of tremendous efforts globally, few vaccines are now available for the prevention of the disease. Specific drug is not available publicly for the treatment of COVID-19. Prevention of air pollution that can aggravate COVID-19 has been suggested. Therefore, as of now, social distancing and sanitization practices are the only options available for the prevention of the disease for many.

Clinical Characteristics of Coronavirus Disease 2019 (COVID-19): A Comparison Between Laboratory-Confirmed and Clinically Suspected Patients

To investigate the characteristic findings between laboratory-confirmed and clinically suspected patients with COVID-19. In this retrospective study, we included patients admitted to the Xiangya Hospital from Jan 24 to Feb 10, 2020. Two researchers separately collected and sorted out the patients’ epidemiological, demographic, clinical, laboratory, and radiologic findings. SPSS was performed to analyze the collected data. 241 patients were admitted, including 28 (45.5; IQR, 34.0–52.5) confirmed and 213 (42.0; IQR, 30.0–57.0) suspected patients. The prevalence of COVID-19 disease in males was significantly higher than in females (64.3% vs. 35.7%, P = 0.033). Before admission of the confirmed and suspected undiagnosed cases, the onset of symptoms is often manifested as respiratory symptoms such as fever (35.7% vs. 27.7%) and cough (30.7% vs. 32.1%). Twenty patients (71.4%) had an exposure history to high-risk areas, and 14 patients (50.0%) traveled or lived in a high-risk area in the confirmed group, which was significantly different from the suspected group. The pulmonary imaging of the patients in the confirmed group was primarily manifested as ground-glass opacity (89.3%). A total of 499 nucleic acid testing (NAT) was performed to determine the 28 COVID-19 positive throat swabs among the 241 patients. Whether there is a history of high-risk area exposure in the epidemiological investigation is essential in distinguishing the suspected patients from the confirmed patients. Multiple nucleic acid tests were used as the basis for the diagnosis of COVID-19, and during CT examination, ground-glass opacity was used as a COVID-19 indicator.

Trail registration Trail registration number. 202012195, Date of registration: 2020.12.22 “retrospectively registered”.

Development of the DNA-based biosensors for high performance in detection of molecular biomarkers: More rapid, sensitive, and universal

The molecular biomarkers are molecules that are closely related to specific physiological states. Numerous molecular biomarkers have been identified as targets for disease diagnosis and biological research. To date, developing highly efficient probes for the precise detection of biomarkers has become an attractive research field which is very important for biological and biochemical studies. During the past decades, not only the small chemical probe molecules but also the biomacromolecules such as enzymes, antibodies, and nucleic acids have been introduced to construct of biosensor platform to achieve the detection of biomarkers in a highly specific and highly efficient way. Nevertheless, improving the performance of the biosensors, especially in clinical applications, is still in urgent demand in this field. A noteworthy example is the Corona Virus Disease 2019 (COVID-19) that breaks out globally in a short time in 2020. The COVID-19 was caused by the virus called SARS-CoV-2. Early diagnosis is very important to block the infection of the virus. Therefore, during these months scientists have developed dozens of methods to achieve rapid and sensitive detection of the virus. Nowadays some of these new methods have been applied for producing the commercial detection kit and help people against the disease worldwide. DNA-based biosensors are useful tools that have been widely applied in the detection of molecular biomarkers. The good stability, high specificity, and excellent biocompatibility make the DNA-based biosensors versatile in application both in vitro and in vivo. In this paper, we will review the major methods that emerged in recent years on the design of DNA-based biosensors and their applications. Moreover, we will also briefly discuss the possible future direction of DNA-based biosensors design. We believe this is helpful for people interested in not only the biosensor field but also in the field of analytical chemistry, DNA nanotechnology, biology, and disease diagnosis.

Phytoconstituents in the Management of Covid-19: Demystifying the Fact

The 2019-nCoV (COVID-19; novel coronavirus disease-2019) outbreak is caused by the coronavirus, and its continued spread is responsible for increasing deaths, social and economic burden. COVID-19 created a chaotic situation worldwide and claimed the lives of over 5,027,183 and 248,467,363 confirmed cases have been reported so far as per the data published by WHO (World Health Organization) till 5^th November 2021. Scientific communities all over the world are toiling to find a suitable therapeutic drug for this deadly disease. Although till date no promising drug has been discovered for this COVID-19. However, as per the WHO, over 102 COVID-19 vaccines are in clinical development and 185 in pre-clinical development. Naturally occurring phytoconstituents possess considerable chemical richness in the form of anti-viral and anti-parasitic potential and have been extensively exploited for the same globally. Still, phytomedicine-based therapies are considered as the best available treatment option to minimize and treat the symptoms of COVID-19 because of the least possible side effects compared to synthetic drugs recommended by the physicians/clinicians. In this review, the use of plant chemicals as a possible therapeutic agent for severe acute respiratory syndrome coronavirus 2 (SARS CoV2) is highlighted with their proposed mechanism of action, which will prove fruitful and effective in finding a cure for this deadly disease.

Insights on Epidemiology, Pathogenesis, Diagnosis and Possible Treatment of COVID-19 Infection

The sudden outbreak of the novel coronavirus infection (COVID-19, SARS-CoV-2 virus) is posing a significant threat by affecting millions of people across the globe showing mild to severe symptoms of pneumonia and acute respiratory distress. The absence of precise information on primary transmission, diagnosis, prognosis, and therapeutics for patients with COVID-19 makes prevention and control tough. In the current scenario, only supportive treatment is available, which in turn possess a biggest challenge for scientists to develop specific drugs and vaccines for COVID-19. Further, India, with the second largest populated country and fluctuating climatic conditions quarterly, has high vulnerability towards COVID-19 infection. Thus, this highlights the importance of a better understanding of the COVID-19 infection, pathology, diagnosis and its treatment. The present review article has been intended to discuss the COVID-19 biology, mechanism of infection in humans with primary effects on pregnancy, the nervous system, diabetes, and cardiovascular disease. The article will also discuss the drug repurposing strategy as an alternative line of treatment and clinical practices recommended by the World Health Organization and other government agencies and represent the COVID-19 scenario with the Indian context.

APOA1 Level is Negatively Correlated with the Severity of COVID-19

Objective

We used public data to analyze the proteomics, metabolomics and transcriptomics characteristics of COVID-19 patients to identify potential therapeutic targets. More importantly, we also collected clinical data for verification to make the analysis results more reliable.

Methods

Download the serum proteomics and metabolomics data of COVID-19 patients and describe their changes in serum proteins and metabolites, and use bioinformatics analysis methods to identify potential biomarkers and therapeutic targets. Finally, clinical data and experimental data of cell infection were combined for verification.

Results

It was found that the serum apolipoprotein A1 (APOA1) protein level in COVID-19 patients was down-regulated (log2FC = −0.39, false discovery rate (FDR) < 0.001), and the degree of reduction in the severe group was more significant (kruskal-test p = 2.5e-05). What is more, APOA1 was not only expressed lower in male patients (Wilcox-test p = 0.012), but also negatively correlated with C-reactive protein (CRP, r = −0.37, p = 0.019). The experiment data from SARS-CoV-2 infected cells further showed that the protein and transcript level of APOA1 gradually decreased as the infection time increased, and the transcription level (log₂FC = −8.3, FDR = 0.0015) was more down-regulated than protein level (log2FC = −0.95, FDR = 0.0014). More importantly, the collected clinical data also confirmed that APOA1 was down-regulated in COVID-19 patients (kruskal-test p = 0.001), and APOA1 levels are negatively correlated with IL6 (r = −0.396, p = 2.22e-07), D-dimers (DD, r = −0.262, p = 8.19e-04), prothrombin time (PT, r = −0.464, p = 6.68e-10) and thrombin time (TT, r = −0.279, p = 3.46e-04).

Conclusion

The degree of down-regulation of APOA1 is positively correlated with the severity of COVID-19, and the expression level of APOA1 is negatively correlated with CRP, IL6, DD, PT, TT, and positively correlated with HD and LDL. This indicates that APOA1 may be a key molecule in tandem acute inflammatory response, coagulation abnormalities and cholesterol metabolism disorder in COVID-19, and could be a potential therapeutic target.

Are we in this together? Changes in anti-immigrant sentiments during the COVID-19 pandemic

The COVID-19 pandemic is posing a threat to people all across the globe. According to traditional literature, threat perceptions induce anti-immigrant sentiments, as ingroup identity and self-interest are strengthened at the expense of the outgroup. In this study, we investigate whether the COVID-19 pandemic indeed increases anti-immigrant sentiments, or that this type of threat elicits other or no group related responses. We also look at whether such responses are expressed more strongly among specific subgroups in Dutch society. To do so, we use unique longitudinal panel data based on the European Values Study 2017, with a repeated measure in May 2020, during the national 'intelligent lockdown' in the Netherlands. Based on structural equation modeling, we demonstrate that anti-immigrant sentiments have not increased due to (perceived threat of) the COVID-19 pandemic. In fact, negative opinions towards immigrants decreased between 2017 and 2020 in the Netherlands, for which we provide alternative explanations. Although some subgroups do experience more threat than others due to the coronavirus, such as women, first generation immigrants, and the elderly, this does not lead to more negative feelings towards outgroups. Whether this is due to the fact that individuals feel threatened by everyone, regardless of group membership, should be explored in future research.

A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province, China

The aim of this research was to develop a quantitative method for clinicians to predict the probability of improved prognosis in patients with coronavirus disease 2019 (COVID-19). Data on 104 patients admitted to hospital with laboratory-confirmed COVID-19 infection from 10 January 2020 to 26 February 2020 were collected. Clinical information and laboratory findings were collected and compared between the outcomes of improved patients and non-improved patients. The least absolute shrinkage and selection operator (LASSO) logistics regression model and two-way stepwise strategy in the multivariate logistics regression model were used to select prognostic factors for predicting clinical outcomes in COVID-19 patients. The concordance index (C-index) was used to assess the discrimination of the model, and internal validation was performed through bootstrap resampling. A novel predictive nomogram was constructed by incorporating these features. Of the 104 patients included in the study (median age 55 years), 75 (72.1%) had improved short-term outcomes, while 29 (27.9%) showed no signs of improvement. There were numerous differences in clinical characteristics and laboratory findings between patients with improved outcomes and patients without improved outcomes. After a multi-step screening process, prognostic factors were selected and incorporated into the nomogram construction, including immunoglobulin A (IgA), C-reactive protein (CRP), creatine kinase (CK), acute physiology and chronic health evaluation II (APACHE II), and interaction between CK and APACHE II. The C-index of our model was 0.962 (95% confidence interval (CI), 0.931-0.993) and still reached a high value of 0.948 through bootstrapping validation. A predictive nomogram we further established showed close performance compared with the ideal model on the calibration plot and was clinically practical according to the decision curve and clinical impact curve. The nomogram we constructed is useful for clinicians to predict improved clinical outcome probability for each COVID-19 patient, which may facilitate personalized counselling and treatment.

Essentials of COVID-19 and treatment approaches

The coronavirus family is as old as the 1930s when it first showed symptoms in chicken. The virus thereafter kept evolving and it has significantly taken over a large percentage of people worldwide in the form of this new pandemic. As of the present day, there is no treatment available for coronavirus disease 2019 (COVID-19) (caused by the severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]), although supportive therapy and preventive measures have shown a tremendous control rate among certain patients. Drugs like remdesivir, camostat, nafamostat, ritonavir/lopinavir, several monoclonal antibodies, and CPs are in their early phases of trials. There are approved by the WHO under an emergency use authorization program. Favipiravir has entered its phase 3 clinical trial and is supported by evidence to show no or less adverse effects in patients infected with SARS-CoV-2. Vaccine development is accelerating its pace, and vaccines will probably become available by the end of the year 2020.

A novel statistical method predicts mutability of the genomic segments of the SARS-CoV-2 virus

The SARS-CoV-2 virus has made the largest pandemic of the 21st century, with hundreds of millions of cases and tens of millions of fatalities. Scientists all around the world are racing to develop vaccines and new pharmaceuticals to overcome the pandemic and offer effective treatments for COVID-19 disease. Consequently, there is an essential need to better understand how the pathogenesis of SARS-CoV-2 is affected by viral mutations and to determine the conserved segments in the viral genome that can serve as stable targets for novel therapeutics. Here, we introduce a text-mining method to estimate the mutability of genomic segments directly from a reference (ancestral) whole genome sequence. The method relies on calculating the importance of genomic segments based on their spatial distribution and frequency over the whole genome. To validate our approach, we perform a large-scale analysis of the viral mutations in nearly 80,000 publicly available SARS-CoV-2 predecessor whole genome sequences and show that these results are highly correlated with the segments predicted by the statistical method used for keyword detection. Importantly, these correlations are found to hold at the codon and gene levels, as well as for gene coding regions. Using the text-mining method, we further identify codon sequences that are potential candidates for siRNA-based antiviral drugs. Significantly, one of the candidates identified in this work corresponds to the first seven codons of an epitope of the spike glycoprotein, which is the only SARS-CoV-2 immunogenic peptide without a match to a human protein.