Associated factors for mortality in a COVID-19 colombian cohort: is the third wave relevant when Mu variant was predominant epidemiologically?

OBJECTIVES: To evaluate the association between Colombia's third wave when the Mu variant was predominant epidemiologically (until 75%) in Colombia and COVID-19 all-cause in-hospital mortality. METHODS: In this retrospective cohort, we included hospitalized patients ≥18 years with SARS-CoV-2 infection between March 2020 to September 2021 in ten hospitals from three cities in Colombia. Description analysis, survival, and multivariate Cox regression analyses were performed to evaluate the association between the third epidemic wave and in-hospital mortality. RESULTS: A total of 25,371 patients were included. The age-stratified time-to-mortality curves showed differences according to epidemic waves in patients ≥75 years (log-rank test p = 0.012). In the multivariate Cox analysis, the third wave was not associated with increased mortality relative to the first wave (aHR 0.95; 95%CI 0.84-1.08), but there was an interaction between age ≥75 years and the third wave finding a lower HR for mortality (aHR 0.56, 95%CI 0.36-0.86). CONCLUSIONS: We did not find an increase in in-hospital mortality during the third epidemic wave in which the Mu variant was predominant in Colombia. The reduced hazard in mortality in patients ≥75 years hospitalized in the third wave could be explained by the high coverage of SARS-CoV-2 vaccination in this population and patients with underlying conditions.

Covid-19 variants: Impact on transmissibility and virulence

The genetic evolution of SARS-CoV-2 began in February 2020, with G614 spike protein strains superseding D614 strains globally. Since then with each subsequent mutations, the SARS-CoV-2 variants of concern, namely Alpha, Beta, Gamma, Delta and Omicron, superseded the previous one to become the dominant strain during the pandemic. By the end of November 2022, the Omicron variant and its descendent lineages account for 99.9% of sequences reported globally. All five VOCs have mutations located in the RBD of the spike protein, resulting in increased affinity of the spike protein to the ACE2 receptors resulting in enhanced viral attachment and its subsequent entry into the host cells. In vitro studies showed the mutations in spike protein help increase the viral fitness, enhancing both transmissibility and replication. In general, Alpha, Beta, Gamma, and Delta variants, were reported with higher transmissibility of 43-90%, around 50%, 170-240%, or 130-170% than their co-circulating VOCs, respectively. The Omicron however was found to be 2.38 times and 3.20 times more transmissible than Delta among the fully-vaccinated and booster-vaccinated households. Even the SARS-Cov-2 Omicron subvariants appear to be inherently more transmissible than the ones before. With the broader distribution, enhanced evasion, and improved transmissibility, SARS-CoV-2 variants infection cause severe diseases due to immune escape from host immunity and faster replication. Reports have shown that each subsequent VOC, except Omicron, cause increased disease severity compared with those infected with other circulating variants. The Omicron variant infection however, appears to be largely associated with a lower risk of hospitalisation, ICU admission, mechanical ventilation, and even a shorter length of hospital stay. It has been shown that the relatively much slower replication of the Omicron variants in the lung, resulted in a less severe disease.Copyright © 2022, Malaysian Society of Pathologists. All rights reserved.

Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants.

Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estimate the epidemiological dynamics of emerging lineages have the potential to serve as an early warning system. However, these methods assume that genomic data are uniformly reported across circulating lineages. In this study, we analyze differences in reporting delays among SARS-CoV-2 VOCs as a plausible explanation for the timing of the global response to the former VOC Mu. Mu likely emerged in South America in mid-2020, where its circulation was largely confined. In this study, we demonstrate that Mu was designated as a VOC ∼1 year after it emerged and find that the reporting of genomic data for Mu differed significantly than that of other VOCs within countries, states, and individual laboratories. Our findings suggest that nonsystematic biases in the reporting of genomic data may have delayed the global response to Mu. Until they are resolved, the surveillance gaps that affected the global response to Mu could impede the rapid and accurate assessment of future emerging variants.

Reduced neutralization against Delta, Gamma, Mu, and Omicron BA.1 variants of SARS-CoV-2 from previous non-Omicron infection.

The understanding of the host immune response to SARS-CoV-2 variants of concern is critical for improving diagnostics, therapy development, and vaccines. Here, we analyzed the level of neutralizing antibodies against SARS-CoV-2 D614G, Delta, Gamma, Mu, and Omicron variants in D614G infected healthcare workers during a follow-up up to 6 months after recovery. We followed up 76 patients: 60.5% were women and 39.5% men. The 96.1% and 3.9% were symptomatic and asymptomatic, respectively. The most frequent symptoms were headache, myalgia, and cough. The 65.8%, 65.8%, and 92.1% of the infected individuals were positive for neutralizing antibodies against D614G variant at 2, 4, and 6 months of follow-up, respectively. The 26.3%, 48.7% and 65.8% of patients neutralized Delta variant, 19.7%, 32.9% and 52.6% of patients neutralized Gamma, 7.9%, 19.7% and 44.7% of patients neutralized Mu, and 4.0%, 9.2% and 15.8% of patients neutralized Omicron. Low neutralization against Gamma and Mu variants was observed during the follow-up, and very low against the Omicron variant was detected during the same period. The median of neutralizing antibody titers against D614G and Delta variants increased significantly during the follow-up. An association was observed between the levels of neutralizing antibodies against D614G and Delta variants and the severity of the disease. Our results suggest an immune escape from neutralizing antibodies with the Omicron variant because of the many mutations localized in the S protein.

Urban Farming: The Reluctant Utopia

The old conceptual dichotomy between the city and the countryside has often been a historical stumbling block for architects and urban planners. Whilst there have been many attempts to bring the city closer to the natural environment, some on grand scales, more modest experiments have often gleaned better results. Daniele Belleri is a partner at design and innovation office CRA-Carlo Ratti Associati, where he is in charge of all editorial and curatorial projects. He and the practice's founder, architect and engineer Carlo Ratti – who is director of the Senseable City Lab at the Massachusetts Institute of Technology (MIT) – together explore our contemporary options. Copyright © 2023 John Wiley & Sons, Ltd.

Effect of Proximal Oxygen Adding to a Bag Valve Mask with a Mechanical Filter in Healthy Volunteers: A Randomized Crossover Trial

Background: Preoxygenation using a bag valve mask (BVM) with a filter is recommended to reduce the risk of viral transmission. Preoxygenation in hypoxaemic patients may require a positive end-expiratory pressure (PEEP) valve. Applying a filter to a BVM with or without a PEEP valve can increase resistance and work of breathing. Objective(s): To evaluate the efficacy of proximal oxygen added to BVM with mechanical filter in healthy volunteers. Material(s) and Method(s): The present study was a crossover trial that randomized 48 volunteers to receive four preoxygenation techniques: BVM with a filter as group F, BVM with a filter and proximal oxygen as group FO, BVM with a filter and PEEP valve as group FP, and BVM with a filter, PEEP valve, and proximal oxygen as group FPO. Fraction of expired oxygen (FEO2) and continuous positive airway pressure (CPAP) were measured. Comfort was assessed using a numerical rating scale (NRS). The primary outcome was FEO2 at five minutes. Result(s): Data from 46 volunteers were analyzed. Adding oxygen proximal to the filter in the FO group increased FEO2 at five minutes by 7.07% (95% CI 4.87 to 9.26) and decreased the time to reach FEO2 90% by 301.74 seconds (95% CI 282.82 to 320.66) compared with the times in group F. Similarly, supplemental proximal oxygen including a PEEP valve increased FEO2 at five minutes by 6.07% (95% CI 3.87 to 8.26) and decreased the time to reach FEO2 90% by 242.13 seconds (95% CI 223.21 to 261.05). CPAP was 2.27, 3.61, 11.65, and 13.14 mmHg in group F, FO, FP, and FPO, respectively. The NRS score was 6.51 and 6.07 in groups F and FO, and 3.15 and 3.70 in groups FP and FPO, respectively. Conclusion(s): Adding proximal oxygen to a BVM with a filter improved the efficacy of preoxygenation. Copyright © 2023 JOURNAL OF THE MEDICAL ASSOCIATION OF THAILAND.

Leveraging Artificial Intelligence in Blockchain-Based E-Health for Safer Decision Making Framework

Machine learning-based (ML) systems are becoming the primary means of achieving the highest levels of productivity and effectiveness. Incorporating other advanced technologies, such as the Internet of Things (IoT), or e-Health systems, has made ML the first choice to help automate systems and predict future events. The execution environment of ML is always presenting contrasting types of threats, such as adversarial poisoning of training datasets or model parameters manipulation. Blockchain technology is known as a decentralized network of blocks that symbolizes means of protecting block content integrity and ensuring secure execution of operations.Existing studies partially incorporated Blockchain into the learning process. This paper proposes a more extensive secure way to protect the decision process of the learning model. Using smart contracts, this study executed the model's decision by the reversal engineering of the learning model's decision function from the extracted learning parameters. We deploy Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) classifiers decision functions on-chain for more comprehensive integration of Blockchain. The effectiveness of this proposed approach is measured by applying a case study of medical records. In a safe environment, SVM prediction scores were found to be higher than MLP. However, MLP had higher time efficiency.

Driving Sustainable Airport Business with Big Data Analytics Services: A Multichannel Approach

Business performance has increased dramatically owing to the increase use of multichannel services in global markets posed by COVID-19 pandemic new normal. The viability of commercial airports depends on strong business models that integrates multichannel services such as digital services, cloud services and big data analytics services to its building blocks. This paper examines how multichannel services and big data analytics services can be used to optimize and enhance airport business building blocks to its business models to increase airports' revenue and business value. A case study was conducted to analyze PNG's airport authority's (National Airports Corporation (NAC) existing business models in comparison to the Osterwalder's business model building blocks. A sustainable business model was proposed that integrates digital and web-based technologies to boost the model's commercial and operational viability. © 2022 ACM.

Deep Learning Based COVID-19 Detection: Challenges and Future Directions

Coronavirus (COVID-19) is an ecumenical pandemic that has affected the whole world drastically by raising a global calamitous situation. Due to this pernicious disease, millions of people have lost their lives. The scientists are still far from knowing how to tackle the coronavirus due to its multiple mutations found around the globe. Standard testing technique called Polymerase Chain Reaction (PCR) for the clinical diagnosis of COVID-19 is expensive and time consuming. However, to assist specialists and radiologists in COVID-19 detection and diagnosis, deep learning plays an important role. Many research efforts have been done that leverage deep learning techniques and technologies for the identification or categorization of COVID-19 positive patients, and these techniques are proved to be a powerful tool that can automatically detect or diagnose COVID-19 cases. In this paper, we identify significant challenges regarding deep learning-based systems and techniques that use different medical imaging modalities, including Cough and Breadth, Chest X-ray, and Computer Tomography (CT) to combat COVID-19 outbreak. We also pinpoint important research questions for each category of challenges. IEEE

Patients Admitted to Pediatric Intensive Care with Sars-Cov2: Results from a Nationwide Multicentre Study

BACKGROUND AND AIM: Admission to PICU due to SARS-CoV2 infection in children is unfrequent. However there are few pediatric patients who may require intensive care management. The aim of our study was to describe characteristics and evolution of those patients admitted to Spanish PICUs due to SARS-CoV2 infection. METHOD(S): A multicentre nationwide prospective registry involving all Spanish PICUs was carried out between 1st of march 2020 and 30 November 2021. RESULT(S): During the study period 299 patients where admitted to the participating units. Median age was 8.9 years (IQR 4.4 -12.2). 208 patients (69,6%) where diagnosed of Multisystem Inflamatory Syndrome associated to SARS-CoV2 (MIS-C). 225 patients (75.3%) where previously healthy. Main reason for admission was shock (which was present in 55.9% of patients). Respiratory difficulty was present only in 40.8% of patients. 50.5% of patients required vasoactive drugs, which was more frequent among those presenting with MIS-C (66.5% vs 20.9%, p<0.001). Only 17.4% of patients required mechanical ventilation, which was less frequent in patients with MIS-C (11.1% vs 34.1% p<0.001). 9 patients (3%) included in the registry died. Death was more frequent among patients with previous diseases (9.6% vs 0.9%, p<0.001) and less frequent in those admitted due to MIS-C (0.5% vs 9.3%, p<0.001). CONCLUSION(S): MIS-C was the most frequent cause of admission to PICU in Spain related to SARS-CoV2 infection. Most patients were admitted presenting shock and required vasoactive drugs, but only a few mechanical ventilation. Mortality rate was low. Prognosis was more favourable in those admitted due to MIS-C.

Music and Stress During COVID-19 Lockdown: Influence of Locus of Control and Coping Styles on Musical Preferences

The imposition of strict lockdown by the government of India during the first outbreak of COVID-19 had a remarkable impact on the well-being/wellness of the citizens. Studies around the globe demonstrated music as one of the effective strategies to enhance well-being during the lockdown. However, response to stressful events is modulated by individual characteristics like coping styles and locus of control (internal/external dependence) which have received little attention. The present chapter examined the use of music to cope with COVID-19 lockdown by these individual traits and their musical preferences during this period. A factor analysis yielded four music dimensions preferred by the participants during the lockdown: intense and electronic;cultural, emotional, and melodious;Indian contemporary and popular;and devotional music. Among the music genres, new and old Bollywood music were the most preferred genres. Participants with a higher internal locus of control, emotion, and problem-focused coping style demonstrated greater use of music in coping with stress. Problem-focused coping showed significant positive correlations with all the music dimensions, and emotion-focused coping style correlated with intense and electronic music;cultural, emotional, and melodious music;and devotional music. Internals showed no correlation with the different music genres. Externals showed a preference for intense and electronic and Indian contemporary and popular music. Listening to music had a significant positive effect on people high in emotion-focused and problem-focused coping styles and internal locus of control. However, it was not necessarily effective for people endorsing high external locus of control and avoidant coping. It implies that it can be used as a self-administered tool and therapeutically for people who engage in these coping styles and locus of control. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Neutralizing Antibody Responses Elicited by Inactivated Whole Virus and Genetic Vaccines against Dominant SARS-CoV-2 Variants during the Four Epidemic Peaks of COVID-19 in Colombia.

Several SARS-CoV-2 variants of concern (VOC) and interest (VOI) co-circulate in Colombia, and determining the neutralizing antibody (nAb) responses is useful to improve the efficacy of COVID-19 vaccination programs. Thus, nAb responses against SARS-CoV-2 isolates from the lineages B.1.111, P.1 (Gamma), B.1.621 (Mu), AY.25.1 (Delta), and BA.1 (Omicron), were evaluated in serum samples from immunologically naïve individuals between 9 and 13 weeks after receiving complete regimens of CoronaVac, BNT162b2, ChAdOx1, or Ad26.COV2.S, using microneutralization assays. An overall reduction of the nAb responses against Mu, Delta, and Omicron, relative to B.1.111 and Gamma was observed in sera from vaccinated individuals with BNT162b2, ChAdOx1, and Ad26.COV2.S. The seropositivity rate elicited by all the vaccines against B.1.111 and Gamma was 100%, while for Mu, Delta, and Omicron ranged between 32 to 87%, 65 to 96%, and 41 to 96%, respectively, depending on the vaccine tested. The significant reductions in the nAb responses against the last three dominant SARS-CoV-2 lineages in Colombia indicate that booster doses should be administered following complete vaccination schemes to increase the nAb titers against emerging SARS-CoV-2 lineages.

Differential Evolution to Optimize A Long-term Multi-strain Model of COVID-19 in South Africa

A limited number of studies have been conducted to investigate the dynamics of COVID-19 disease spread in South Africa and these existing studies have mostly focussed on mathematical analysis of a relatively short time period near the initial outbreak of COVID-19 in South Africa. The current study therefore attempted to extend on previous studies by applying a Susceptible- Exposed - Infected - Removed (SEIR) disease model to analyse the long-term dynamics of COVID-19 in South Africa, taking into account multiple waves of infection potentially caused by different virus strains. A Differential Evolution (DE) algorithm was used to fit the proposed model to real-world data, and this was done on both a geographically local and global scale to investigate the differences between these two approaches. Results revealed that a local approach provided a more accurate model fit to data than a global approach and that the method proposed in this work could give valuable insights into disease dynamics. © 2022 IEEE.

Natalizumab extended-interval dosing in a real-life context: efficacy study

Introduction: Natalizumab (NTZ) is a widely used second-line treatment for multiple sclerosis (MS), administered with a fourweeks infusion interval. Extending the interval between two infusions could reduce the economic costs of this therapy, the incidence of rare side effects such as progressive multifocal leukoencephalopathy and improve the patients' quality of life with less frequent day-hospitalizations. Aim(s): At the Fondation Rothschild Hospital in Paris, for sanitary reasons during COVID-19 lockdown, patients were systematically switched to a 6-weeks NTZ extended-interval dosing (EID) from April 2020 to the present day. In this monocentric retrospective study, we aimed at evaluating the clinical and radiological efficacy of NTZ EID compared to the 4 weeks standard-interval dosing (SID) in adult patients with active MS. Method(s): We screened the local pharmacy database for NTZ administration and included all adult patients diagnosed with MS and treated with NTZ for at least 6 months with a SID, before being treated with an EID for at least 12 months. Data about disease activity, treatments received, MRI and clinical data were retrospectively collected from the local French MS observatory (OFSEP) database. The primary outcomes were the incidence of MS attacks, new MRI lesions or the presence of gadoliniumenhancing lesions during NTZ SID or EID. Result(s): A total of 49 patients were included for final analysis. 21 (42.9%) were male, with a median MS duration from the first symptom to NTZ introduction of 60 [30, 110] months. Patients were treated for a median time of 34.6 [15.1, 72.4] months by a SID, followed by a median time of 18.6 [14.7, 20.6] months by an EID. The mean EDSS before EID was 2.0 [1.5, 3.0] and 1.5 [0.0, 2.8] during EID. During natalizumab SID, one patient (2%) presented a new MS attack, 5/45 patients (11%) had new MRI lesions, with gadolinium enhanced lesions in 1/45 (2%) patient. This did not differ significantly during natalizumab EID where no MS attack were observed (p = 1), new MRI lesions were present in 1/41 (2%) patient and no gadolinium-enhancing lesion was found. Patients were followed for a median time of 130 [78, 205] months in total. Conclusion(s): We did not observe more clinical attacks or MRI activity signs when extending the interval between NTZ infusions from 4 to 6 weeks. Data from randomized controlled trials are needed to allow better consideration of side-effects and safety.

SARS-CoV-2 variants C.1.2 and B.1.621 (Mu) partially evade neutralization by antibodies elicited upon infection or vaccination.

Rapid spread of SARS-CoV-2 variants C.1.2 and B.1.621 (Mu variant) in Africa and the Americas, respectively, as well as a high number of mutations in the viral spike proteins raised concerns that these variants might pose an elevated threat to human health. Here, we show that C.1.2 and B.1.621 spike proteins mediate increased entry into certain cell lines but do not exhibit increased ACE2 binding. Further, we demonstrate that C.1.2 and B.1.621 are resistant to neutralization by bamlanivimab but remain sensitive to inhibition by antibody cocktails used for COVID-19 therapy. Finally, we show that C.1.2 and B.1.621 partially escape neutralization by antibodies induced upon infection and vaccination, with escape of vaccine-induced antibodies being as potent as that measured for B.1.351 (Beta variant), which is known to be highly neutralization resistant. Collectively, C.1.2 and B.1.621 partially evade control by vaccine-induced antibodies, suggesting that close monitoring of these variants is warranted.

A database for retrieving information on SARS-CoV-2 S protein mutations based on correlation network analysis.

BACKGROUND: Over a million genomes and mutational analyses of SARS-CoV-2 are available in public databases, which reveal the phylogenetic tree of the virus. Although these data have enabled scientists to closely track the evolution and transmission dynamics of the virus at global and local scales, the Mu variant, recently identified in infections in South America, shows an unusual combination of mutations, and it is difficult to visualize these atypical characteristics in public databases based on a phylogenetic tree. RESULTS: The Vcorn SARS-CoV-2 database was constructed to provide information on COVID-19 infections and mutations in the S protein of the virus based on correlation network analysis. A correlation network was constructed using the recall index of one mutation to another mutation. The network includes several network modules in which nodes represent mutations and are tightly connected to each other. Individual network modules contain mutations of single variants, such as the alpha and delta variants. In the network constructed to emphasize mutations of the Mu variant using the database, the mutations were found to be located in multiple network modules, indicating that the mutations of the variant may have originated from multiple variants or be located at a basal position with a high frequency of mutation. CONCLUSIONS: Vcorn SARS-CoV-2 provides information on COVID-19 and S protein mutations of SARS-CoV-2 via correlation network analysis. The network based on the analysis illustrates the unusual S protein mutations of the Mu variant. The database is freely available at http://www.plant.osakafu-u.ac.jp/~kagiana/vcorn/sarscov2/ .

42nd International Congress of the European Association of Poisons Centres and Clinical Toxicologists

The proceedings contain 209 papers. The topics discussed include: an illicit drug early warning system utilizing comprehensive toxicological analysis of emergency department presentations in Victoria, Australia;4-fluoroamphetamine (4-FA) intoxication results in exaggerated blood pressure effects compared to 3,4-methylenedioxymethamphetamine (MDMA) and amphetamine: a retrospective analysis;single nucleotide polymorphisms of mu opioid receptor gene OPRM1 in emergency department patients with acute opioid overdose;ketamine in acute recreational poisonings in the Balearic Islands;the neuro-respiratory effects of pregabalin and the potential deleterious effects of its combination with diazepam or morphine ? a rat investigation;cobaltism from metal-on-metal (MoM) hip implants: how to manage and treat with acetylcysteine;analytically-confirmed polydrug use is more common in drug misuse patients attending emergency departments in Scotland compared with those in England and Wales;and it is not always COVID-19: a case of respiratory failure from lung damage associated with electronic cigarettes (EVALI).

Environmental conditions, mobile digital culture, mobile usability, knowledge of app in COVID-19 risk mitigation: A structural equation model analysis.

Introduction: The mobile digital culture (MDC) supports individual lives, communities, and real-time organizational surveillance during COVID-19 emergencies. Hence, the study examined the advancement in smart health devices evidence in smartphone apps technologies in surveillance, control, and tracking potential virus areas among high-risk populations. Objective: The study explored how environmental condition and MDC mediates between knowledge of App and mobile usability in the prevention of COVID-19 infection in high-risk areas. Methods: Using the concept of UTAUT, the study conceptualized that mobile usability, MDC, knowledge of App and environmental condition, are essential for COVID-19 mitigation. A cross-sectional method was adopted through an online survey to assess data from n = 459 mobile users. The association of the study models was appraised through structural equation models (Amos v.24.0). Result: We found mobile usability, knowledge of App, and MDC were statistically significant to COVID-19 mitigation. Environment condition as mediator had no effect in the study models. However, moderating effect of MDC shows a negative influence on the association between COVID-19 mitigation and knowledge of apps. Conclusion: Future policies should consider the development of mHealth technology to improve end-user experience. Also, future policies should entail data privacy to reduce the infringement of data collected. This approach will lead to a confidential, high acceptance of usability of mHealth apps infectious disease prevention.

Evasion of vaccine-induced humoral immunity by emerging sub-variants of SARS-CoV-2.

Background: Emergence of vaccine-escaping SARS-CoV-2 variants is a serious problem for global public health. The currently rampant Omicron has been shown to possess remarkable vaccine escape; however, the selection pressure exerted by vaccines might pave the way for other escape mutants in the near future. Materials & methods: For detection of neutralizing antibodies, the authors used the recently developed HiBiT-based virus-like particle neutralization test system. Sera after vaccination (two doses of Pfizer/BioNTech mRNA vaccine) were used to evaluate the neutralizing activity against various strains of SARS-CoV-2. Results: Beta+R346K, which was identified in the Philippines in August 2021, exhibited the highest vaccine resistance among the tested mutants. Surprisingly, Mu+K417N mutant exhibited almost no decrease in neutralization. Imdevimab retained efficacy against these strains. Conclusions: Mutations outside the receptor-binding domain contributed to vaccine escape. Both genomic surveillance and phenotypic analysis synergistically accelerate identifications of vaccine-escaping strains.

Prior to the Omicron variant, the SARS-CoV-2 Beta sub-variant found in the Philippines in August 2021 exhibited remarkable vaccine-escaping capacity. Although Omicron is, at the time of writing, causing most of the infections globally, both genomic surveillance and phenotypic analysis should be reinforced to accelerate the identification of newly emerging vaccine-escaping SARS-CoV-2 variants.

How Do Point Mutations Enhancing the Basic Character of the RBDs of SARS-CoV-2 Variants Affect Their Transmissibility and Infectivity Capacities?

The spread of SARS-CoV-2 variants in the population depends on their ability to anchor the ACE2 receptor in the host cells. Differences in the electrostatic potentials of the spike protein RBD (electropositive/basic) and ACE2 receptor (electronegative/acidic) play a key role in both the rapprochement and the recognition of the coronavirus by the cell receptors. Accordingly, point mutations that result in an increase in electropositively charged residues, e.g., arginine and lysine, especially in the RBD of spike proteins in the SARS-CoV-2 variants, could contribute to their spreading capacity by favoring their recognition by the electronegatively charged ACE2 receptors. All SARS-CoV-2 variants that have been recognized as being highly transmissible, such as the kappa (κ), delta (δ) and omicron (o) variants, which display an enhanced electropositive character in their RBDs associated with a higher number of lysine- or arginine-generating point mutations. Lysine and arginine residues also participate in the enhanced RBD-ACE2 binding affinity of the omicron variant, by creating additional salt bridges with aspartic and glutamic acid residues from ACE2. However, the effects of lysine- and arginine-generating point mutations on infectivity is more contrasted, since the overall binding affinity of omicron RBD for ACE2 apparently results from some epistasis among the whole set of point mutations.