Coupled models of genomic surveillance and evolving pandemics with applications for timely public health interventions.

Disease surveillance systems provide early warnings of disease outbreaks before they become public health emergencies. However, pandemics containment would be challenging due to the complex immunity landscape created by multiple variants. Genomic surveillance is critical for detecting novel variants with diverse characteristics and importation/emergence times. Yet, a systematic study incorporating genomic monitoring, situation assessment, and intervention strategies is lacking in the literature. We formulate an integrated computational modeling framework to study a realistic course of action based on sequencing, analysis, and response. We study the effects of the second variant's importation time, its infectiousness advantage and, its cross-infection on the novel variant's detection time, and the resulting intervention scenarios to contain epidemics driven by two-variants dynamics. Our results illustrate the limitation in the intervention's effectiveness due to the variants' competing dynamics and provide the following insights: i) There is a set of importation times that yields the worst detection time for the second variant, which depends on the first variant's basic reproductive number; ii) When the second variant is imported relatively early with respect to the first variant, the cross-infection level does not impact the detection time of the second variant. We found that depending on the target metric, the best outcomes are attained under different interventions' regimes. Our results emphasize the importance of sustained enforcement of Non-Pharmaceutical Interventions on preventing epidemic resurgence due to importation/emergence of novel variants. We also discuss how our methods can be used to study when a novel variant emerges within a population.

Lessons we learned during the past four challenging years in the COVID-19 era: pharmacotherapy, long COVID complications, and vaccine development.

About four years have passed since the detection of the first cases of COVID-19 in China. During this lethal pandemic, millions of people have lost their lives around the world. Since the first waves of COVID-19 infection, various pharmacotherapeutic agents have been examined in the management of COVID-19. Despite all these efforts in pharmacotherapy, drug repurposing, and design and development of new drugs, multiple organ involvement and various complications occurred during COVID-19. Some of these complications became chronic and long-lasting which led to the "long COVID" syndrome appearance. Therefore, the best way to eradicate this pandemic is prophylaxis through mass vaccination. In this regard, various vaccine platforms including inactivated vaccines, nucleic acid-based vaccines (mRNA and DNA vaccines), adenovirus-vectored vaccines, and protein-based subunit vaccines have been designed and developed to prevent or reduce COVID-19 infection, hospitalization, and mortality rates. In this focused review, at first, the most commonly reported clinical presentations of COVID-19 during these four years have been summarized. In addition, different therapeutic regimens and their latest status in COVID-19 management have been listed. Furthermore, the "long COVID" and related signs, symptoms, and complications have been mentioned. At the end, the effectiveness of available COVID-19 vaccines with different platforms against early SARS-CoV-2 variants and currently circulating variants of interest (VOI) and the necessity of booster vaccine shots have been summarized and discussed in more detail.

Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study.

BACKGROUND: The outbreak of SARS-CoV-2 in 2019 has necessitated the rapid and accurate detection of COVID-19 to manage patients effectively and implement public health measures. Artificial intelligence (AI) models analyzing cough sounds have emerged as promising tools for large-scale screening and early identification of potential cases. OBJECTIVE: This study aimed to investigate the efficacy of using cough sounds as a diagnostic tool for COVID-19, considering the unique acoustic features that differentiate positive and negative cases. We investigated whether an AI model trained on cough sound recordings from specific periods, especially the early stages of the COVID-19 pandemic, were applicable to the ongoing situation with persistent variants. METHODS: We used cough sound recordings from 3 data sets (Cambridge, Coswara, and Virufy) representing different stages of the pandemic and variants. Our AI model was trained using the Cambridge data set with subsequent evaluation against all data sets. The performance was analyzed based on the area under the receiver operating curve (AUC) across different data measurement periods and COVID-19 variants. RESULTS: The AI model demonstrated a high AUC when tested with the Cambridge data set, indicative of its initial effectiveness. However, the performance varied significantly with other data sets, particularly in detecting later variants such as Delta and Omicron, with a marked decline in AUC observed for the latter. These results highlight the challenges in maintaining the efficacy of AI models against the backdrop of an evolving virus. CONCLUSIONS: While AI models analyzing cough sounds offer a promising noninvasive and rapid screening method for COVID-19, their effectiveness is challenged by the emergence of new virus variants. Ongoing research and adaptations in AI methodologies are crucial to address these limitations. The adaptability of AI models to evolve with the virus underscores their potential as a foundational technology for not only the current pandemic but also future outbreaks, contributing to a more agile and resilient global health infrastructure.

Vitamin D: A key player in COVID-19 immunity and lessons from the pandemic to combat immune-evasive variants.

As of the 7th of July 2024, 775,754,322 confirmed cases of COVID-19, including 7,053,902 deaths worldwide, had been reported to the WHO (World Health Organization). Nevertheless, untill the 15th of July 2024, a total of 13,578,710,228 vaccine doses had been administered, with almost no country spared from COVID-19 attacks. The pathophysiology of this virus is complicated, and several symptoms require a deep understanding of the actual mechanisms. It is unclear why some patients develop severe symptoms while others do not, although literature suggests a role for vitamin D. Vitamin D plays a crucial role in the infection or in ameliorating the severity of symptoms. The mechanism of action of vitamin D and vitamin D deficiency (VDD) is well understood. VDD is associated with increased hospitalization of severely ill patients and increased levels of COVID-19-caused mortality. Recent studies suggest that vitamin D levels and genetic variations in the vitamin D receptor (VDR) gene significantly impact the severity and outcomes of COVID-19, especially in the infections caused by Delta and Omicron variants. Furthermore, VDD causes immune system dysregulation upon infection with SARS-CoV-2, indicating that vitamin D sufficiency is crucial in fighting against COVID-19 infection. The therapeutic effect of vitamin D raises interest in its potential role as a prophylactic and treatment adjunct. We evaluate the immunomodulatory effects of vitamin D and its ability to enhance the efficacy of new antiviral drugs like molnupiravir and paxlovid against SARS-CoV-2. This review discusses the role of vitamin D sufficiency and VDD in COVID-19 initiation and progression, emphasizing the molecular mechanisms by which vitamin D exerts its actions as a proactive step for the next pandemic. However, there is still no clear evidence of vitamin D's impact on prevention and treatment, leading to contradictory findings. Therefore, large-scale randomized trials are required to reach a definitive conclusion. A bibliometric analysis of publications related to vitamin D, immunity, and COVID-19 revealed a significant increase in research activity in this area, particularly in 2020-2024, underscoring the growing recognition of vitamin D's potential role in the context of the pandemic.

A comparison of transmissibility of SARS-CoV-2 variants of concern.

BACKGROUND: The World Health Organization (WHO) has currently detected five Variants of Concern of SARS-CoV-2 having the WHO labels of 'Alpha', 'Beta', 'Gamma', 'Delta' and 'Omicron'. We aimed to assess and compare the transmissibility of the five VOCs in terms of basic reproduction number, time-varying reproduction number and growth rate. METHODS: Publicly available data on the number of analyzed sequences over two-week windows for each country were extracted from covariants.org and GISAID initiative database. The ten countries which reported the highest number of analyzed sequences for each of the five variants were included in the final dataset and was analyzed using R language. The epidemic curves for each variant were estimated utilizing the two-weekly discretized incidence data using local regression (LOESS) models. The basic reproduction number was estimated with the exponential growth rate method. The time-varying reproduction number was calculated for the estimated epidemic curves by the ratio of the number of new infections generated at time step t to the total infectiousness of infected individuals at time t, using the EpiEstim package. RESULTS: The highest R0 for the variants Alpha (1.22), Beta (1.19), Gamma (1.21), Delta (1.38) and Omicron (1.90) were reported from Japan, Belgium, the United States, France and South Africa, respectively. Nine out of ten epidemic curves with the highest estimated growth rates and reproduction numbers were due to the Omicron variant indicating the highest transmissibility. CONCLUSIONS: The transmissibility was highest in the Omicron variant followed by Delta, Alpha, Gamma and Beta respectively.

Long-term outcomes in COVID-19 patients admitted to intensive care in Denmark: A nationwide observational study.

BACKGROUND: Among ICU patients with COVID-19, it is largely unknown how the overall outcome and resource use have changed with time, different genetic variants, and vaccination status. METHODS: For all Danish ICU patients with COVID-19 from March 10, 2020 to March 31, 2022, we manually retrieved data on demographics, comorbidities, vaccination status, use of life support, length of stay, and vital status from medical records. We compared patients based on the period of admittance and vaccination status and described changes in epidemiology related to the Omicron variant. RESULTS: Among all 2167 ICU patients with COVID-19, 327 were admitted during the first (March 10-19, 2020), 1053 during the second (May 20, 2020 to June 30, 2021) and 787 during the third wave (July 1, 2021 to March 31, 2022). We observed changes over the three waves in age (median 72 vs. 68 vs. 65 years), use of invasive mechanical ventilation (81% vs. 58% vs. 51%), renal replacement therapy (26% vs. 13% vs. 12%), extracorporeal membrane oxygenation (7% vs. 3% vs. 2%), duration of invasive mechanical ventilation (median 13 vs. 13 vs. 9 days) and ICU length of stay (median 13 vs. 10 vs. 7 days). Despite these changes, 90-day mortality remained constant (36% vs. 35% vs. 33%). Vaccination rates among ICU patients were 42% as compared to 80% in society. Unvaccinated versus vaccinated patients were younger (median 57 vs. 73 years), had less comorbidity (50% vs. 78%), and had lower 90-day mortality (29% vs. 51%). Patient characteristics changed significantly after the Omicron variant became dominant including a decrease in the use of COVID-specific pharmacological agents from 95% to 69%. CONCLUSIONS: In Danish ICUs, the use of life support declined, while mortality seemed unchanged throughout the three waves of COVID-19. Vaccination rates were lower among ICU patients than in society, but the selected group of vaccinated patients admitted to the ICU still had very severe disease courses. When the Omicron variant became dominant a lower fraction of SARS-CoV-2 positive patients received COVID treatment indicating other causes for ICU admission.

Spike-directed vaccination elicits robust spike-specific T-cell response, including to mutant strains.

Although most studies describing coronavirus disease 2019 vaccine responses have focused on antibodies, there is increasing evidence that T cells play a critical role. Here the authors evaluated T-cell responses in seronegative donors before and after vaccination to define responses to the severe acute respiratory syndrome coronavirus 2 reference strain as well as to mutations in the variant strains Alpha/B.1.1.7 and Beta/B.1.351. The authors observed enhanced T-cell responses to reference and variant spike strains post-vaccination.

Comparison of clinical features and perinatal outcomes between pre-variant and post-variant periods in pregnant women with SARS-CoV-2: analysis of 1935 cases.

PURPOSE: To compare the clinical features and perinatal outcomes of pregnant women with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pre-variant and post-variant periods. METHODS: This prospective cohort study includes pregnant women with SARS-CoV-2 who were followed-up at Ankara City Hospital between 11, March 2020 and 15, September 2021. Demographic features, clinical characteristics and pregnancy outcomes were compared between the pre-variant (n = 1416) and post-variant (n = 519) groups. RESULTS: The rates of severe and critical cases significantly increased in the post-variant group (9.7% vs 2%, p < 0.001). The rates of respiratory support (26.8% vs 7.3%, p < 0.001), ICU admission (12.9% vs 1.8%, p < 0.001) and maternal mortality (2.9% vs 0.4%, p < 0.001) were significantly higher in the post-variant group. A significant increase was observed for pregnancy complications in the post-variant group (45.6% vs 18.8%, p = 0.007). The rates of preterm delivery (26.4% vs 4.4%, p < 0.001) and NICU admission (34% vs 18.8%, p < 0.001) were significantly higher in the post-variant group. Positive, weak, statistically significant correlations were observed between the post-variant period, disease severity and maternal mortality (r = 0.19, r = 0.12 and p < 0.001). CONCLUSION: Post-variant COVID-19 period was associated with a severe course of the disease and increased rates of adverse obstetric outcomes in pregnant patients.

A fractional-order model with different strains of COVID-19.

This study examines the dynamics of COVID-19 variants using a Caputo-Fabrizio fractional order model. The reproduction ratio R 0 and equilibrium solutions are determined. The purpose of this article is to use a non-integer order derivative in order to present information about the model solutions, uniqueness, and existence using a fixed point theory. A detailed analysis of the existence and uniqueness of the model solution is conducted using fixed point theory. For the computation of the iterative solution of the model, the fractional Adams-Bashforth method is used. Using the estimated values of the model parameters, numerical results are used to support the significance of the fractional-order derivative. The graphs provide useful information about the complexity of the model, and provide reliable information about the model for any case, integer or non-integer. Also, we demonstrate that any variant with the largest basic reproduction ratio will automatically outperform the other variant.

The myocardial and neuronal infectivity of SARS-CoV-2 and detrimental outcomes.

The epidemiological outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), alias COVID-19, began in Wuhan, Hubei, China, in late December and eventually turned into a pandemic that has led to over 3.71 million deaths and over 173 million infected cases worldwide. In addition to respiratory manifestations, COVID-19 patients with neurological and myocardial dysfunctions exhibit a higher risk of in-hospital mortality. The immune function tends to be affected by cardiovascular risk factors and is thus indirectly related to the prognosis of COVID-19 patients. Many neurological symptoms and manifestations have been reported in COVID-19 patients; however, detailed descriptions on the prevalence and characteristic features of these symptoms are restricted due to insufficient data. It is thus advisable for clinicians to be vigilant for both cardiovascular and neurological manifestations to detect them at an early stage to avoid inappropriate management of COVID-19 and to address the manifestations adequately. Patients with severe COVID-19 are notably more susceptible to developing cardiovascular and neurological complications than non-severe COVID-19 patients. This review focuses on the consequential outcomes of COVID-19 on cardiovascular and neuronal functions, including other influencing factors.

COVID-19 diagnosis, vaccination during pregnancy, and adverse pregnancy outcomes of 865,654 women in England and Wales: a population-based cohort study.

Background: The extent to which COVID-19 diagnosis and vaccination during pregnancy are associated with risks of common and rare adverse pregnancy outcomes remains uncertain. We compared the incidence of adverse pregnancy outcomes in women with and without COVID-19 diagnosis and vaccination during pregnancy. Methods: We studied population-scale linked electronic health records for women with singleton pregnancies in England and Wales from 1 August 2019 to 31 December 2021. This time period was divided at 8th December 2020 into pre-vaccination and vaccination roll-out eras. We calculated adjusted hazard ratios (HRs) for common and rare pregnancy outcomes according to the time since COVID-19 diagnosis and vaccination and by pregnancy trimester and COVID-19 variant. Findings: Amongst 865,654 pregnant women, we recorded 60,134 (7%) COVID-19 diagnoses and 182,120 (21%) adverse pregnancy outcomes. COVID-19 diagnosis was associated with a higher risk of gestational diabetes (adjusted HR 1.22, 95% CI 1.18-1.26), gestational hypertension (1.16, 1.10-1.22), pre-eclampsia (1.20, 1.12-1.28), preterm birth (1.63, 1.57-1.69, and 1.68, 1.61-1.75 for spontaneous preterm), very preterm birth (2.04, 1.86-2.23), small for gestational age (1.12, 1.07-1.18), thrombotic venous events (1.85, 1.56-2.20) and stillbirth (only within 14-days since COVID-19 diagnosis, 3.39, 2.23-5.15). HRs were more pronounced in the pre-vaccination era, within 14-days since COVID-19 diagnosis, when COVID-19 diagnosis occurred in the 3rd trimester, and in the original variant era. There was no evidence to suggest COVID-19 vaccination during pregnancy was associated with a higher risk of adverse pregnancy outcomes. Instead, dose 1 of COVID-19 vaccine was associated with lower risks of preterm birth (0.90, 0.86-0.95), very preterm birth (0.84, 0.76-0.94), small for gestational age (0.93, 0.88-0.99), and stillbirth (0.67, 0.49-0.92). Interpretation: Pregnant women with a COVID-19 diagnosis have higher risks of adverse pregnancy outcomes. These findings support recommendations towards high-priority vaccination against COVID-19 in pregnant women. Funding: BHF, ESRC, Forte, HDR-UK, MRC, NIHR and VR.

Identifying a more severe emergent COVID-19 variant using Emergency Departments' routinely collected clinical measures.

Objective: To determine whether a clinical scoring system (the mPRIEST score) could be used to identify an emerging coronavirus disease 2019 (COVID-19) variant with increased clinical severity. Design: Cross sectional study comparing two time periods (Delta and Omicron waves). Setting: Public Emergency Departments in Northern Sydney Local Health District. Participants: Patients presenting during August 2021 (Delta wave) and January 2022 (Omicron wave) with confirmed COVID-19. Data on age, gender, temperature, heart rate, systolic blood pressure, respiratory rate, oxygen saturation and mental status were extracted from patients' electronic medical records to assess clinical disease severity at presentation. Main outcome measures: Modified Pandemic Respiratory Infection Emergency System Triage (mPRIEST) score calculated using routinely collected data. Results: A sample of 262 records of COVID-19 positive patients presenting during the Delta and initial Omicron waves were reviewed with 205 having COVID-19 as their primary diagnosis. During the Delta wave 48.1% had scores above 4 compared to 35.1% for the Omicron wave (p = 0.03). The median score was also significantly higher for the Delta group (4 vs 3; p = 0.01). Hospitalisations, admissions to ICU and deaths during admission were higher among patients presenting during the Delta wave than among those presenting during the Omicron wave. Conclusion: The mPRIEST score was significantly higher for patients for whom the predominant circulating variant was Delta than those for whom the predominant circulating variant was Omicron. This finding is consistent with international reporting of severity measured by hospital admission data and demonstrates the score's possible ability to identify an emergent strain with higher morbidity and mortality.

Temporal assessment of disparities in California COVID-19 mortality by industry: a population-based retrospective cohort study.

PURPOSE: To assess changes in the COVID-19 mortality rate and disparities over variants or waves by industry. METHODS: We identified COVID-19 deaths that occurred between January 2020 and May 2022 among California workers aged 18-64 years using death certificates, and estimated Californians at risk using the Current Population Survey. The waves in deaths were wave 1: March-June 2020, wave 2: July-November 2020, wave 3/Epsilon and Alpha variants: December 2020-May 2021, wave 4/Delta variant: June 2021-January 2022, and wave 5/Omicron variant: February-May 2022. We used Poisson regression to generate wave-specific mortality rate ratios (MRR) and included an interaction term between industry and wave in different models to assess significance of the change in MRR. RESULTS: In all waves of the pandemic, healthcare, other services, manufacturing, transportation, and retail trade industries had higher mortality rates than the professional, scientific, and technical industry. The healthcare industry had the highest relative rate earlier in the pandemic, while other services, utilities, and accommodation and food services industries had substantial increases in MRR in later waves. CONCLUSIONS: Industries that consistently had disproportionate COVID-19 mortality may have benefitted from protections that consider workers' increased exposure and vulnerability to severe outcomes.

Differences in the inflammatory response among hospitalized patients with distinct variants of SARS-CoV-2.

The SARS-CoV-2 variants demonstrate diverse transmission patterns, modifications in infectivity, and immune response. Changes in disease manifestation may be attributed to vaccination and the virus's reduced capacity to induce inflammation. Objectives: To investigate the relationship between the inflammatory response and the characteristics of COVID-19 across successive waves. Methods: A retrospective cross-sectional study was conducted to evaluate sociodemographic, clinical, and laboratory data of Alpha (G1), Delta (G2), and Omicron (G3) variants. Results: A total of 300 patients from a hospital in Madrid, Spain, were included. The groups exhibited similar sociodemographic and baseline characteristics. The Alpha variant predominantly affected younger patients, while the Omicron variant affected patients with a higher prevalence of comorbidities. The Alpha group had the lowest vaccination rate compared to the highest rate in the Omicron group. The Alpha group received a higher proportion of tocilizumab compared to the other groups. Despite these differences, the severity scores were similar among the three variants. Regarding laboratory parameters, differences were observed in haemoglobin, D-dimer, alkaline phosphatase, and potassium levels. The Omicron variant showed higher D-dimer levels (p=0.04). In the multivariate analysis, differences in leukocyte count, haemoglobin, alkaline phosphatase, and potassium levels were consistently observed among patients from different waves. Omicron exhibited a higher absolute leukocyte count than the Alpha variant (p=0.003). Conclusion: No significant differences were found in inflammation biomarkers among the three variants. Furthermore, there were no significant disparities in mortality or disease severity. The level of inflammatory response in patients may be determined by the severity of COVID-19, rather than the specific viral variant.

Organic-Inorganic Hybrid Nanocomposites for Nanotheranostics: Special Focus on Preventing Emerging Variants of SARS-COV-2.

The worldwide emerging cases of various respiratory viral diseases and the current escalation of novel coronavirus disease (COVID-19) make people considerably attentive to controlling these viruses through innovative methods. Most re-emerging respiratory diseases envelop RNA viruses that employ attachment between the virus and host cell to get an entry form using the host cell machinery. Emerging variants of COVD-19 also bring about a constant threat to public health as it has wide infectivity and can quickly spread to infect humans. This review focuses on insights into the current investigations to prevent the progression of incipient variants of Severe Acute Respiratory Syndrome Coronavirus (SARS-COV-2) along with similar enveloped RNA viruses that cause respiratory illness in humans and animals. Nanotheranostics is a trailblazing arena of nanomedicine that simultaneously helps prevent or treat diseases and diagnoses. Nanoparticle coating and nanofibers were extensively explored, preventing viral contaminations. Several studies have proven the virucidal activities of metal nanoparticles like copper, silver, and titanium against respiratory viral pathogens. Worldwide many researchers have shown surfaces coated with ionic nanoparticles like zinc or titanium act as potent antiviral agents against RNA viruses. Carbon nanotubes, quantum dots, silica nanoparticles (NPs), polymeric and metallic nanoparticles have also been explored in the field of nanotheranostics in viral detection. In this review, we have comprehensively discussed different types of metallic, ionic, organic nanoparticles and their hybrids showing substantial antiviral properties to stop the progression of the novel coronavirus disease focused on three key classes: prevention, diagnostics, and treatment.

Assessment of GO-Based Protein Interaction Affinities in the Large-Scale Human-Coronavirus Family Interactome.

SARS-CoV-2 is a novel coronavirus that replicates itself via interacting with the host proteins. As a result, identifying virus and host protein-protein interactions could help researchers better understand the virus disease transmission behavior and identify possible COVID-19 drugs. The International Committee on Virus Taxonomy has determined that nCoV is genetically 89% compared to the SARS-CoV epidemic in 2003. This paper focuses on assessing the host-pathogen protein interaction affinity of the coronavirus family, having 44 different variants. In light of these considerations, a GO-semantic scoring function is provided based on Gene Ontology (GO) graphs for determining the binding affinity of any two proteins at the organism level. Based on the availability of the GO annotation of the proteins, 11 viral variants, viz., SARS-CoV-2, SARS, MERS, Bat coronavirus HKU3, Bat coronavirus Rp3/2004, Bat coronavirus HKU5, Murine coronavirus, Bovine coronavirus, Rat coronavirus, Bat coronavirus HKU4, Bat coronavirus 133/2005, are considered from 44 viral variants. The fuzzy scoring function of the entire host-pathogen network has been processed with ~180 million potential interactions generated from 19,281 host proteins and around 242 viral proteins. ~4.5 million potential level one host-pathogen interactions are computed based on the estimated interaction affinity threshold. The resulting host-pathogen interactome is also validated with state-of-the-art experimental networks. The study has also been extended further toward the drug-repurposing study by analyzing the FDA-listed COVID drugs.

Identifying promising druggable binding sites and their flexibility to target the receptor-binding domain of SARS-CoV-2 spike protein.

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for viral infection. The interaction of its receptor-binding domain (RBD) with the human angiotensin-converting enzyme 2 (ACE2) protein is required for the virus to enter the host cell. We identified RBD binding sites to block its function with inhibitors by combining the protein structural flexibility with machine learning analysis. Molecular dynamics simulations were performed on unbound or ACE2-bound RBD conformations. Pockets estimation, tracking and druggability prediction were performed on a large sample of simulated RBD conformations. Recurrent druggable binding sites and their key residues were identified by clustering pockets based on their residue similarity. This protocol successfully identified three druggable sites and their key residues, aiming to target with inhibitors for preventing ACE2 interaction. One site features key residues for direct ACE2 interaction, highlighted using energetic computations, but can be affected by several mutations of the variants of concern. Two highly druggable sites, located between the spike protein monomers interface are promising. One weakly impacted by only one Omicron mutation, could contribute to stabilizing the spike protein in its closed state. The other, currently not affected by mutations, could avoid the activation of the spike protein trimer.

Drug repurposing and sequence analysis in S-glycoprotein variants reveals critical signature patterns and destabilization of receptor-binding domain in omicron variant.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus since its emergence in 2019 has yielded several new viral variants with varied infectivity, disease severity, and antigenicity. Although most mutations are expected to be relatively neutral, mutations at the Spike region of the genome have shown to have a major impact on the viral transmission and infection in humans. Therefore, it is crucial to survey the structures of spike protein across the global virus population to contextualize the rate of therapeutic success against these variants. In this study, high-frequency mutational variants from different geographic regions were pooled in order to study the structural evolution of the spike protein through drug docking and MD simulations. We investigated the mutational burden in the spike subregions and have observed that the different variants harbour unique signature patterns in the spike subregions, with certain domains being highly prone to mutations. Further, the MD simulations and docking study revealed that different variants show differential stability when docked for the same set of drug targets. This work sheds light on the mutational burden and the stability landscape of the spike protein across the variants from different geographical regions.Communicated by Ramaswamy H. Sarma.

Structural insights into ACE2 interactions and immune activation of SARS-CoV-2 and its variants: an in-silico study.

The initial interaction between COVID-19 and the human body involves the receptor-binding domain (RBD) of the viral spike protein with the angiotensin-converting enzyme 2 (ACE2) receptor. Likewise, the spike protein can engage with immune-related proteins, such as toll-like receptors (TLRs) and pulmonary surfactant proteins A (SP-A) and D (SP-D), thereby triggering immune responses. In this study, we utilize computational methods to investigate the interactions between the spike protein and TLRs (specifically TLR2 and TLR4), as well as (SP-A) and (SP-D). The study is conducted on four variants of concern (VOC) to differentiate and identify common virus behaviours. An assessment of the structural stability of various variants indicates slight changes attributed to mutations, yet overall structural integrity remains preserved. Our findings reveal the spike protein's ability to bind with TLR4 and TLR2, prompting immune activation. In addition, our in-silico results reveal almost similar docking scores and therefore affinity for both ACE2-spike and TLR4-spike complexes. We demonstrate that even minor changes due to mutations in all variants, surfactant A and D proteins can function as inhibitors against the spike in all variants, hindering the ACE2-RBD interaction.Communicated by Ramaswamy H. Sarma.

Wave comparisons of clinical characteristics and outcomes of COVID-19 admissions - Exploring the impact of treatment and strain dynamics.

OBJECTIVES: Dexamethasone has now been incorporated into the standard of care for COVID-19 hospital patients. However, larger intensive care unit studies have failed to show discernible improvements in mortality in the recent wave. We aimed to investigate the impacts of these factors on disease outcomes in a UK hospital study. METHODS: This retrospective observational study reports patient characteristics, interventions and outcomes in COVID-19 patients from a UK teaching hospital; cohort 1, pre 16th June-2020 (pre-dexamethasone); cohort 2, 17th June to 30th November-2020 (post-dexamethasone, pre-VOC 202,012/01 as dominant strain); cohort 3, 1st December-2020 to 3rd March-2021 (during establishment of VOC202012/01 as the dominant strain). RESULTS: Dexamethasone treatment was more common in cohorts 2 and 3 (42.7% and 51.6%) compared with cohort 1 (2.5%). After adjusting for risk, odds of death within 28 days were 2-fold lower in cohort 2 vs 1 (OR:0.47,[0.27,0.79],p = 0.006). Mortality was higher cohort 3 vs 2 (20% vs 14%); but not significantly different to cohort 1 (OR: 0.86,[0.64, 1.15],p = 0.308). CONCLUSIONS: The real world finding of lower mortality following dexamethasone supports the published trial evidence and highlights ongoing need for research with introduction of new treatments and ongoing concern over new COVID-19 variants.