A Comprehensive Overview on COVID-19: Future Perspectives

COVID-AMD database for coronavirus-infected animal models with comparative analysis tools

Respiratory infections caused by coronaviruses have posed serious and unpredictably public health threats; reliable animal models continue to be essential for advancing our understanding of the virus's transmission, pathophysiology, and immunological mechanisms. In response to the critical need for centralized resources in coronavirus research, the COVID-AMD database (Coronavirus Disease Animal Model Database, https://www.uc-med.net/CoV-AMD ) has been developed as an integrated platform. Data was gathered from public literature databases, refined and integrated using ETL (Extract, Transform, Load) methodology. After data conversion and cleaning, COVID-AMD was implemented using MySQL relational database with jQuery and JBoss. COVID-AMD database consolidates comprehensive data on animal models infected with various CoVs, including MERS-CoV, SARS-CoV, and SARS-CoV-2, featuring methodologies for establishing infection models, clinical features, and phenotypic data. It catalogs 869 animal models across 29 species and 312 virus strains, covering five diseases and ten infection routes. With global and advanced search capabilities, it facilitated data preprocessing, integration, analysis, and visualization, and provided tools for comparative analysis, model recommendation and omics analysis based on model and phenotype data. The open access to this rich repository aims to enable rapid identification of animal models for CoVs, thereby accelerating the development and clinical trial progression of prospective therapeutics and vaccines.

Effect of post COVID-19 on body composition, physical fitness, sleep quality and quality of life among young adults: a cross-sectional study of matched pairs

Background

Coronavirus 2019 (COVID-19) causes lung tissue inflammation, affects mental health, and disturbs sleep and the musculoskeletal system. This study aimed to investigate the effects of COVID-19 on physical function and quality of life by comparing the body composition, physical fitness, sleep quality and quality of life between Thai young adults with and without post COVID-19 infection.

Methods

A cross-sectional study was comprised of two matched groups (post COVID-19 group and non COVID-19 group) with 36 participants in each group. Data about body composition, physical fitness, sleep quality and quality of life were collected using the bioelectrical impedance analysis, the 1-min sit-to-stand test, the hand grip strength test, the Pittsburgh sleep quality questionnaire and the EuroQol-5D-5L, respectively. Independent samples T-test, Mann-Whitney U test and Chi-square test were used to compare between the two groups.

Results

The changes in oxygen saturation and respiratory rate after the physical fitness test and the sleep quality analysis showed a statistically significant difference between the groups with and without post COVID-19 infection (p = 0.006, p = 0.003 and p = 0.003, respectively). However, quality of life and body composition were not significantly different between groups.

Conclusions

COVID-19 influenced the changes in oxygen saturation and respiratory rate after the physical fitness test and the sleep quality analysis in young adults. The results should be utilized to facilitate physical rehabilitation for COVID-19-infected individuals following infection. Those who have not been infected with COVID-19 must be informed of self-protection measures to avoid contracting the virus.

Investigating the Hepcidin Gene Polymorphisms in COVID-19-Associated Mucormycosis Susceptibility: A Clinical-Laboratory Study

Background

Following the coronavirus disease 2019 outbreak (COVID-19), it became a worrisome health burden worldwide. COVID-19-associated mucormycosis emergence, characterized by dysregulated inflammation and iron metabolism, exacerbated the prognosis of affected patients. Given the significance of hepcidin in regulating inflammation and iron metabolism, this study investigated the significance of hepcidin single nucleotide polymorphisms (SNP) in COVID-19-associated mucormycosis development, along with the association between the clinical and laboratory factors and COVID-19-associated mucormycosis.

Methods

From September 2021 to November 2021, COVID-19 patients with and without mucormycosis were enrolled in this cross-sectional study. Their medical records and laboratory results were investigated. SNP genotyping was performed using Sanger sequencing. Hardy-Weinberg Equilibrium, Pearson's Chi square, and student t test were used for analyzing the data using SPSS software version 25. P<0.05 was regarded as statistically significant.

Results

Here, 110 COVID-19 patients with and without mucormycosis were investigated. Elevated levels of urea, aspartate aminotransferase, lactate dehydrogenase, and increased ratio of polymorphonuclear neutrophil to lymphocytes were associated with decreased risk of COVID-19-associated mucormycosis in patients (all P<0.05). Moreover, diabetes mellitus increased the risk of mucormycosis (P=0.028). In contrast to patients without mucormycosis, patients with mucormycosis did not display 442 GA and SNP335 GT genotypes. Unlike patients without mucormycosis, none of the patients with mucormycosis had SNP442 GA and SNP335 GT genotypes. Regarding SNP 443 C>T, and the combination of SNPs 582 A>G and 443 C>T, CC genotype and AA+CC genotypes were associated with increased lactate dehydrogenase levels in COVID-19 patients, respectively.

Conclusion

Regarding SNP 443 C>T, the CC genotype was associated with increased lactate dehydrogenase levels in COVID-19 patients. In terms of SNP 582 A>G and SNP 443 C>T, COVID-19 patients with AA+CC genotypes had higher levels of LDH. None of the patients with mucormycosis had SNP442 GA and SNP335 GT genotypes.

Identification of South African Plant-Based Bioactive Compounds as Potential Inhibitors against the SARS-CoV-2 Receptor

The expected progress in SARS-CoV-2 vaccinations, as anticipated in 2020 and 2021, has fallen short, exacerbating global disparities due to a lack of universally recognized "safe and effective" vaccines. This study focuses on extracts of South African medicinal plants, Artemisia annua and Artemisia afra, to identify metabolomic bioactive compounds inhibiting the binding of the SARS-CoV-2 spike protein to ACE2 receptors. The extracts were monitored for cytotoxicity using a resazurin cell viability assay and xCELLigence real-time cell analyzer. Chemical profiling was performed using UPLC-MS/MS, orthogonal projection to latent structures (OPLS), and evaluated using principle component analysis (PCA) models. Identified bioactive compounds were subjected to in vitro SARS-CoV-2 enzyme inhibition assay using standard methods and docked into the spike (S) glycoprotein of SARS-CoV-2 using Schrodinger® suite followed by molecular dynamics simulation studies. Cell viability assays revealed non-toxic effects of extracts on HEK293T cells at lower concentrations. Chemical profiling identified 81 bioactive compounds, with compounds like 6″-O-acetylglycitin, 25-hydroxyvitamin D3-26,23-lactone, and sesaminol glucoside showing promising binding affinity. Molecular dynamics simulations suggested less stable binding, but in vitro studies demonstrated the ability of these compounds to interfere with SARS-CoV-2 spike protein's binding to the human ACE2 receptor. Sesaminol glucoside emerged as the most effective inhibitor against this interaction. This study emphasizes the importance of multiplatform metabolite profiling and chemometrics to understand plant extract composition. This finding is of immense significance in terms of unravelling metabolomics bioactive compounds inhibiting the binding of the SARS-CoV-2 spike protein to ACE2 receptors and holds promise for phytotherapeutics against SARS-CoV-2.

Future challenges of direct-to-consumer genetic testing for sustainable safety in the Republic of Korea's skin care market: a systematic review

Background

Social distancing due to the pandemic is accelerating the fragmentation of Korean society in the megatrend of continuous individualization after industrialization. In this context, consumers are turning to direct-to-consumer (DTC) genetic testing for tailored skin healthcare strategies. However, there are still concerns about the safety of personal information in DTC genetic testing. The purpose of this review article is to examine the sustainable safety of DTC genetic testing for customized dermatology products, focusing on skin healthcare market after coronavirus disease 2019 (COVID-19).

Methods

A systematic review approach was used in this study. Using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flow chart, a total of 920 references were selected from PubMed, Medline, and Scopus. The composition of a total of 59 references from professional papers was finally reviewed. To this end, the most relevant recent literature was added, and the reference period was limited to 2018 to 2023 based on a 6-year period.

Results

With the practice of mask wearing since COVID-19, various methods are being used to strengthen the skin's immune system, and maintain and promote skin health. There is a need to have a method to increase the safety of DTC genetic testing for sustainable skin healthcare market.

Conclusions

It is concluded that there is a need to continue to develop more sustainable and safer security applications (apps) in the field of customized dermatology cosmetics to address the privacy issues and improve the accuracy of DTC genetic testing.

Generation and Characterization of a Multi-Functional Panel of Monoclonal Antibodies for SARS-CoV-2 Research and Treatment

The Coronavirus disease 2019 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) is an ongoing threat to global public health. To this end, intense efforts are underway to develop reagents to aid in diagnostics, enhance preventative measures, and provide therapeutics for managing COVID-19. The recent emergence of SARS-CoV-2 Omicron variants with enhanced transmissibility, altered antigenicity, and significant escape of existing monoclonal antibodies and vaccines underlines the importance of the continued development of such agents. The SARS-CoV-2 spike protein and its receptor binding domain (RBD) are critical to viral attachment and host cell entry and are primary targets for antibodies elicited from both vaccination and natural infection. In this study, mice were immunized with two synthetic peptides (Pep 1 and Pep 2) within the RBD of the original Wuhan SARS-CoV-2, as well as the whole RBD as a recombinant protein (rRBD). Hybridomas were generated, and a panel of three monoclonal antibodies, mAb CU-P1-1 against Pep 1, mAb CU-P2-20 against Pep 2, and mAb CU-28-24 against rRBD, was generated and further characterized. These mAbs were shown by ELISA to be specific for each immunogen/antigen. Monoclonal antibody CU-P1-1 has limited applicability other than in ELISA approaches and basic immunoblotting. Monoclonal antibody CU-P2-20 is shown to be favorable for ELISA, immunoblotting, and immunohistochemistry (IHC), however, not live virus neutralization. In contrast, mAb CU-28-24 is most effective at live virus neutralization as well as ELISA and IHC. Moreover, mAb CU-28-24 is active against rRBD proteins from Omicron variants BA.2 and BA.4.5 as determined by ELISA, suggesting this mAb may neutralize live virus of these variants. Each of the immunoglobulin genes has been sequenced using Next Generation Sequencing, which allows the expression of respective recombinant proteins, thereby eliminating the need for long-term hybridoma maintenance. The synthetic peptides and hybridomas/mAbs and quantitative antigen-binding data are under the intellectual property management of the Clemson University Research Foundation, and the three CDRs have been submitted as an invention disclosure for further patenting and commercialization.

Effects of SARS-CoV-2 infection on hypothyroidism and subclinical hypothyroidism: a meta-analysis

Background

In recent years, the outbreak of COVID-19 caused by SARS-CoV-2 has been witnessed globally. However, the impact of SARS-CoV-2 infection on thyroid dysfunction and subclinical thyroid dysfunction remains unclear. Therefore, this meta-analysis aimed to assess the effects of SARS-CoV-2 infection on thyroid dysfunction and its relationship with the severity of COVID-19.

Methods

We systematically searched databases including PubMed, Willey Library, Embase, Web of Science, CNKI, Wanfang, and VIP. We focused on randomized controlled trials, case-control studies, and cohort studies published between December 2019 and August 2023, examining the association between SARS-CoV-2 infection and hypothyroidism, with a specific emphasis on the severity of the infection. The quality of the research was assessed using the Newcastle-Ottawa Scale (NOS), while statistical analysis was conducted using the meta and metafor packages in R 4.2.1 software.

Results

For the meta-analysis, a total of eight articles were identified based on strict inclusion and exclusion criteria. For the association between SARS-CoV-2 infection and hypothyroidism, three studies (266 samples) comparing TSH levels of COVID-19 and control groups showed no difference in TSH levels [SMD=-0.04,95%CI(-1.22,1.15),P=0.95]. Additionally, two studies examining TT3 (a sample of 176 cases) and two studies examining TT4 (a sample of 176 cases) also showed no difference in TT3 and TT4 between the COVID-19 group and the control group, respectively. However, when evaluating the severity of COVID-19, six studies (565 samples) showed that TSH in the severe group was significantly lower than in the mild group [SMD = -0.55, 95% CI (-0.96, -0.14)], while FT3 was also lower in the severe group [SMD = -0.96, 95% CI (-1.24, -0.67)]. No noticeable differences were observed between the severe and mild groups in their TT3, FT4, and TT4 levels.

Conclusion

SARS-CoV-2 infection may have detrimental effects on thyroid function in individuals with severe symptoms. More research is needed to confirm and explore this relationship.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023486042.

Time series analysis of daily reported number of new positive cases of COVID-19 in Japan from January 2020 to February 2023

This study investigated temporal variations of the COVID-19 pandemic in Japan using a time series analysis incorporating maximum entropy method (MEM) spectral analysis, which produces power spectral densities (PSDs). This method was applied to daily data of COVID-19 cases in Japan from January 2020 to February 2023. The analyses confirmed that the PSDs for data in both the pre- and post-Tokyo Olympics periods show exponential characteristics, which are universally observed in PSDs for time series generated from nonlinear dynamical systems, including the so-called susceptible/exposed/infectious/recovered (SEIR) model, well-established as a mathematical model of temporal variations of infectious disease outbreaks. The magnitude of the gradient of exponential PSD for the pre-Olympics period was smaller than that of the post-Olympics period, because of the relatively high complex variations of the data in the pre-Olympics period caused by a deterministic, nonlinear dynamical system and/or undeterministic noise. A 3-dimensional spectral array obtained by segment time series analysis indicates that temporal changes in the periodic structures of the COVID-19 data are already observable before the commencement of the Tokyo Olympics and immediately after the introduction of mass and workplace vaccination programs. Additionally, the possibility of applying theoretical studies for measles control programs to COVID-19 is discussed.

SARS-CoV-2-Associated Multisystem Inflammatory Syndrome in Children (MIS-C): A Case Report from Iraq

The novel coronavirus disease (COVID-19) continues to evolve. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-associated multisystem inflammatory syndrome in children (MIS-C) is a rare post-COVID-19 complication that affects children with critical outcomes. Few MIS-C reports were available from Arab-Asian ethnicities. We here describe a presentation mimicking a head injury overlapping the manifestations of MIS-C in a child from Iraq. A 10-year-old boy presented with blunt trauma in a shock-like status, and a head injury was suspected. Since he was febrile two days before the trauma, another pathology was assumed. Imaging and laboratory evaluations were performed, and after excluding gross neurosurgical etiology, he was initially treated as a toxic shock syndrome. Meanwhile, he was deteriorating with continuous fever, impaired consciousness, and seizure on the following day. Although not considered initially, close monitoring with a multidisciplinary approach and serial investigations revealed that the child met the criteria of MIS-C. SARS-CoV-2 IgG was shown to be high, while the RT-PCR of COVID-19 was negative. Once he received immunoglobulin and methylprednisolone, he improved dramatically. In conclusion, this report aimed to increase awareness about MIS-C among health workers and emphasized the need for a multidisciplinary team approach in Iraq due to the importance of timely treatment.

Machine learning with multimodal data for COVID-19

In response to the unprecedented global healthcare crisis of the COVID-19 pandemic, the scientific community has joined forces to tackle the challenges and prepare for future pandemics. Multiple modalities of data have been investigated to understand the nature of COVID-19. In this paper, MIDRC investigators present an overview of the state-of-the-art development of multimodal machine learning for COVID-19 and model assessment considerations for future studies. We begin with a discussion of the lessons learned from radiogenomic studies for cancer diagnosis. We then summarize the multi-modality COVID-19 data investigated in the literature including symptoms and other clinical data, laboratory tests, imaging, pathology, physiology, and other omics data. Publicly available multimodal COVID-19 data provided by MIDRC and other sources are summarized. After an overview of machine learning developments using multimodal data for COVID-19, we present our perspectives on the future development of multimodal machine learning models for COVID-19.

Fucosylated N-glycans as early biomarkers of COVID-19 severity

Background

The pathological mechanisms of SARS-CoV-2 in humans remain unclear and the unpredictability of COVID-19 progression may be attributed to the absence of biomarkers that contribute to the prognosis of this disease. Therefore, the discovery of biomarkers is needed for reliable risk stratification and to identify patients who are more likely to progress to a critical stage.

Methods

Aiming to identify new biomarkers we analysed N-glycan traits in plasma from 196 patients with COVID-19. Samples were classified into three groups according to their severity (mild, severe and critical) and obtained at diagnosis (baseline) and at 4 weeks of follow-up (postdiagnosis), to evaluate their behaviour through disease progression. N-glycans were released with PNGase F and labelled with Rapifluor-MS, followed by their analysis by LC-MS/MS. The Simglycan structural identification tool and Glycostore database were employed to predict the structure of glycans.

Results

We determined that plasma from SARS-CoV-2-infected patients display different N-glycosylation profiles depending on the disease severity. Specifically, levels of fucosylation and galactosylation decreased with increasing severity and Fuc1Hex5HexNAc5 was identified as the most suitable biomarker to stratify patients at diagnosis and distinguish mild from critical outcomes.

Conclusion

In this study we explored the global plasma glycosignature, reflecting the inflammatory state of the organs during the infectious disease. Our findings show the promising potential of glycans as biomarkers of COVID-19 severity.

Thrombosis with Thrombocytopenia Syndrome (TTS) After ChAdOx1 nCoV-19 Immunization: An Investigative Case Report

BACKGROUND Thrombosis with thrombocytopenia syndrome (TTS), including vaccine-induced immune thrombotic thrombocytopenia (VITT), is an extremely rare adverse effect, mostly seen after initial vaccination with the viral vector-based AstraZeneca-Oxford COVID-19 vaccine. It is characterized by mild to severe thrombocytopenia and venous or arterial thrombosis. CASE REPORT Herein, we present a case of an 18-year-old male patient who developed Level 1 TTS (probable VITT) eight days after immunization with the ChADOx1 nCOV-19 vaccine (Covishield; AZ-Oxford). Initial investigations revealed severe thrombocytopenia, hemiparesis, and intracranial hemorrhage, after which the patient was treated conservatively. However, a decompressive craniotomy was performed later due to patient deterioration. One week after surgery, the patient developed bilious vomiting, lower-gastrointestinal bleeding, and abdominal distension. An abdominal CT scan was performed that showed thrombosis of the portal vein with occlusion of the left iliac vein. The patient underwent an exploratory laparotomy followed by resection and anastomosis of the small bowel due to massive gut gangrene. Due to persistent thrombocytopenia after surgery, intravenous immune globulin (IVIG) was administered. The platelet count increased thereafter, and the patient stabilized. He was discharged on the 33rd day after admission and was followed up for a year. No post-hospitalization complications were observed in the follow-up period. CONCLUSIONS Although vaccines have been proven to be highly safe and effective to end the Coronavirus Disease 2019 (COVID-19) caused pandemic, there is still a small risk of developing rare complications, including TTS and VITT. Early diagnosis and prompt intervention are key for patient management.

COVID-19 therapy and vaccination: a clinical narrative review

The SARS-CoV-2 pandemic is the most globally impacting health issue our world has faced over the last century. As of January 7, 2022, around 300 million cases have been reported worldwide, with over 5 million deaths. The SARS-CoV-2 infection causes a hyperactive host immune response leading to an excessive inflammatory reaction with the release of many cytokines - cytokine storm - commonly noticed in acute respiratory distress syndrome, sepsis and fulminant multiorgan failure. Since the beginning of the pandemic, the scientific medical community has worked on therapeutic procedures that interfere with the exaggerated immune response. Thromboembolic complications are widespread in patients who are critically ill with COVID-19. Anticoagulant therapy was initially considered a cornerstone in hospitalized patients and even in the early post-discharge period; however, later trials have aborted the clinical benefits except for suspicion of or confirmed thrombosis. Immunomodulatory therapies are still crucial in moderate to severe COVID-19. Immunomodulator therapies include various medications from steroids to hydroxychloroquine, tocilizumab and Anakinra. Anti-inflammatory agents, vitamin supplements and antimicrobial therapy had initial encouraging evidence, but there are limited data to review. Convalescent plasma, immunoglobulins, eculizumab, neutralizing IgG1 monoclonal antibodies and remdesivir have positively impacted inpatient mortality and hospital length of stay. Eventually, wide population vaccination was proven to be the best tool to overcome the SARS-CoV-2 pandemic and help humanity return to regular life. Many vaccines and various strategies have been used since December 2020. This review discusses how the SARS-CoV-2 pandemic has progressed and surged, and summarizes the safety and efficacy of the most used therapies and vaccines in the light of recent evidence.

Stem cell- derived extracellular vesicles as new tools in regenerative medicine - Immunomodulatory role and future perspectives

In the last few decades, the practical use of stem cells (SCs) in the clinic has attracted significant attention in the regenerative medicine due to the ability of these cells to proliferate and differentiate into other cell types. However, recent findings have demonstrated that the therapeutic capacity of SCs may also be mediated by their ability to secrete biologically active factors, including extracellular vesicles (EVs). Such submicron circular membrane-enveloped vesicles may be released from the cell surface and harbour bioactive cargo in the form of proteins, lipids, mRNA, miRNA, and other regulatory factors. Notably, growing evidence has indicated that EVs may transfer their bioactive content into recipient cells and greatly modulate their functional fate. Thus, they have been recently envisioned as a new class of paracrine factors in cell-to-cell communication. Importantly, EVs may modulate the activity of immune system, playing an important role in the regulation of inflammation, exhibiting broad spectrum of the immunomodulatory activity that promotes the transition from pro-inflammatory to pro-regenerative environment in the site of tissue injury. Consequently, growing interest is placed on attempts to utilize EVs in clinical applications of inflammatory-related dysfunctions as potential next-generation therapeutic factors, alternative to cell-based approaches. In this review we will discuss the current knowledge on the biological properties of SC-derived EVs, with special focus on their role in the regulation of inflammatory response. We will also address recent findings on the immunomodulatory and pro-regenerative activity of EVs in several disease models, including in vitro and in vivo preclinical, as well as clinical studies. Finally, we will highlight the current perspectives and future challenges of emerging EV-based therapeutic strategies of inflammation-related diseases treatment.

Pain in COVID-19: Quis est culpa?

<b>Background</b>: At present, during the coronavirus disease (COVID-19) pandemic, chronic pain is becoming more prominent, and it is also associated with the post-COVID-19 syndrome. Thanks to quick decisions on the therapy and as part of COVID-19 prevention, we have succeeded in stabilising the situation all over the world. On the other hand, ‘quick decisions’ have contributed to other significant issues which we are beginning to deal with now: in the effort to defeat the virus, many experts regarded the adverse effects of the medications used to be of secondary importance.<br /> <b>Purpose:</b> The article aims to demonstrate the side effects of treatment with various drugs (and their combinations) that are used to treat COVID-19 disease.<br /> <b>Method: </b>From the beginning of January until mid-May, the COVID-19 department of the 2nd Surgical Clinic of the Faculty of Medicine of the Comenius University in Bratislava (University Hospital Bratislava, Hospital of Saints Cyril and Methodius) treated 221 patients with moderate and severe course of COVID-19 (2nd wave of the pandemic). We saw some adverse effects and lack of effect of certain drugs for COVID-19.<br /> <b>Results: </b>The benefits of preventive measures compared to treatment are enormous. For example, corticoids can impair metabolism, cause diabetes, or suppress immunity. Antibiotics may cause colitis and blood pressure medications may negatively impact blood circulation.<br /> <b>Conclusion: </b>Preventive measures such as vaccination and activation of intrinsic antiviral immune systems are based on an incomparable benefit. Important in the process of the activation of antiviral immunity (linked to interferon synthesis) in the prevention of COVID-19 is the improvement of vitamin D deficit and the use of other micronutrients.<br /> <b>Practical value:</b> The results of the study will be valuable in the field of medicine, for virologists, pharmacologists, pharmacists, and medical professionals.

Association of underlying comorbidities and progression of COVID-19 infection amongst 2586 patients hospitalised in the National Capital Region of India: a retrospective cohort study

This study is conducted to observe the association of diabetes (DM), hypertension (HTN) and chronic kidney disease (CKD) on the prognosis and mortality of COVID-19 infection in hospital admitted patients with above mentioned comorbidities. This is a single centre, observational, retrospective study carried out at Sir Ganga Ram Hospital, Delhi, India. The burden of comorbidities on the prognosis and clinical outcome of COVID-19 patients admitted patients from April 8, 2020, to October 4, 2020. Chi-square and relative risk test were used to observe the association of comorbidities and disease prognosis. A total of 2586 patients were included in the study consisting of 69.6% of male patients. All the comorbidities were significantly associated with ICU admission and mortality. The relative risk showed that CKD is most prone to severity as well as mortality of the COVID-19 infection followed by HTN and DM. Further with the increase in number of underlying comorbidities, the risk of ICU admission and mortality also increases. Relative risk of the severity of COVID-19 infection in younger patients with underlying comorbidities are relatively at higher risk of severity of disease as well as to mortality compared to the elderly patients with similar underlying condition. Similarly, it is found that females are relatively at higher risk of mortality as compared to the males having same comorbid conditions except for the hypertensive patients. Diabetes, hypertension and CKD, all are associated with progression of COVID-19 disease to severity and higher mortality risk. The number of underlying comorbid condition is directly proportional to the progression of disease severity and mortality.

Pathogenic Mechanism and Multi-omics Analysis of Oral Manifestations in COVID-19

Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease that seriously threatens human life. The clinical manifestations of severe COVID-19 include acute respiratory distress syndrome and multiple organ failure. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID-19, spreads through contaminated droplets. SARS-CoV-2 particles have been detected in the saliva of COVID-19 patients, implying that the virus can infect and damage the oral cavity. The oral manifestations of COVID-19 include xerostomia and gustatory dysfunction. Numerous studies showed that the four structural proteins of SARS-CoV-2 are its potential pathogenic factors, especially the S protein, which binds to human ACE2 receptors facilitating the entry of the virus into the host cells. Usually, upon entry into the host cell, a pathogen triggers the host’s immune response. However, a mount of multi-omics and immunological analyses revealed that COVID-19 is caused by immune dysregulation. A decrease in the number and phenotypes of immune cells, IFN-1 production and excessive release of certain cytokines have also been reported. In conclusion, this review summarizes the oral manifestations of COVID-19 and multi-omics analysis of SARS-CoV-2 infection.

A preliminary analysis of the secondary sex ratio decline after the COVID-19 pandemic in Japan

Objectives

The secondary sex ratio (SSR, i.e., the number of male births per 100 female births) has long been proposed as a sentinel health indicator. Studies have suggested that exogenous environmental stressors reduce SSR after 3 to 6 months (via disproportionate male fetus deaths) and after 9 months (via reduced male conception). We aimed to examine whether SSR declined after the coronavirus disease 2019 (COVID‐19) pandemic in Japan.

Methods

We used monthly vital statistics records collected between January 2013 and April 2021 (the ‐number of male and female live births, in particular). Using information reported before the pandemic struck Japan (i.e., January 2013 to January 2020), we predicted SSRs for the months after the pandemic (i.e., February 2020 to April 2021) and compared reported and predicted SSRs. We also stratified the analysis by including two groups of prefectures with different degrees of possible influence from the pandemic.

Results

We observed a significant reduction in SSR during December 2020 of 102.81 (i.e., 9–10 months after the pandemic affected the country), which was below the lower bound of the 95% prediction intervals (103.12–106.33). This was the lowest SSR observed during the 100‐month study period. In addition, the reduction in SSR during December 2020 was more pronounced in the more seriously affected prefectures.

Conclusion

In Japan, we found a significant reduction in SSR (i.e., fewer male live births) 9–10 months after COVID‐19 was declared a pandemic. This suggests the onset of the COVID‐19 pandemic was a significant population‐level stressor.

Conformational dynamics and allosteric modulation of the SARS-CoV-2 spike

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects cells through binding to angiotensin-converting enzyme 2 (ACE2). This interaction is mediated by the receptor-binding domain (RBD) of the viral spike (S) glycoprotein. Structural and dynamic data have shown that S can adopt multiple conformations, which controls the exposure of the ACE2-binding site in the RBD. Here, using single-molecule Förster resonance energy transfer (smFRET) imaging, we report the effects of ACE2 and antibody binding on the conformational dynamics of S from the Wuhan-1 strain and in the presence of the D614G mutation. We find that D614G modulates the energetics of the RBD position in a manner similar to ACE2 binding. We also find that antibodies that target diverse epitopes, including those distal to the RBD, stabilize the RBD in a position competent for ACE2 binding. Parallel solution-based binding experiments using fluorescence correlation spectroscopy (FCS) indicate antibody-mediated enhancement of ACE2 binding. These findings inform on novel strategies for therapeutic antibody cocktails.

COVID-19 lockdown and natural resources: a global assessment on the challenges, opportunities, and the way forward

BACKGROUND

The Coronavirus (COVID-19) is a global pandemic caused by SARS-CoV-2, which has an enormous effect on human lives and the global environment. This review aimed to assess the global scientific evidence on the impact of COVID-19 lockdown on natural resources using international databases and search engines. Thus, the unprecedented anthropause due to COVID-19 has positive and negative effects on natural resources.

MAIN BODY

This review showed that the unprecedented pandemic lockdown events brought a negative impact on the physical environment, including pollution associated with a drastic increase in person protective equipment, deforestation, illegal poaching and logging, overfishing, disruption of the conservation program and projects. It is noted that the spread of pandemic diseases could be aggravated by environmental pollution and a rapid increase in the global population. Despite these negative impacts of COVID-19, the anthropause appear to have also several positive effects on natural resources such as short term reduction of indoor and outdoor environmental pollutants (PM2.5, PM10, NO2, SO2, CO, and CO2), reduction in noise pollutions from ships, boats, vehicles, and planes which have positive effects on aquatic ecosystems, water quality, birds behaviour, wildlife biodiversity, and ecosystem restoration.

CONCLUSION

Therefore, governments and scientific communities across the globe have called for a green recovery to COVID-19 and implement multi-actor interventions and environmentally friendly technologies to improve and safeguard sustainable environmental and biodiversity management and halt the next pandemic.

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

The global coronavirus disease 2019 (COVID-19) pandemic has demonstrated the range of disease severity and pathogen genomic diversity emanating from a singular virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2). This diversity in disease manifestations and genomic mutations has challenged healthcare management and resource allocation during the pandemic, especially for countries such as India with a bigger population base. Here, we undertake a combinatorial approach toward scrutinizing the diagnostic and genomic diversity to extract meaningful information from the chaos of COVID-19 in the Indian context. Using methods of statistical correlation, machine learning (ML), and genomic sequencing on a clinically comprehensive patient dataset with corresponding with/without respiratory support samples, we highlight specific significant diagnostic parameters and ML models for assessing the risk of developing severe COVID-19. This information is further contextualized in the backdrop of SARS-CoV-2 genomic features in the cohort for pathogen genomic evolution monitoring. Analysis of the patient demographic features and symptoms revealed that age, breathlessness, and cough were significantly associated with severe disease; at the same time, we found no severe patient reporting absence of physical symptoms. Observing the trends in biochemical/biophysical diagnostic parameters, we noted that the respiratory rate, total leukocyte count (TLC), blood urea levels, and C-reactive protein (CRP) levels were directly correlated with the probability of developing severe disease. Out of five different ML algorithms tested to predict patient severity, the multi-layer perceptron-based model performed the best, with a receiver operating characteristic (ROC) score of 0.96 and an F1 score of 0.791. The SARS-CoV-2 genomic analysis highlighted a set of mutations with global frequency flips and future inculcation into variants of concern (VOCs) and variants of interest (VOIs), which can be further monitored and annotated for functional significance. In summary, our findings highlight the importance of SARS-CoV-2 genomic surveillance and statistical analysis of clinical data to develop a risk assessment ML model.

Exercising under COVID-2x: Conceptualizing Future Green Spaces in Australia’s Neighborhoods

The COVID-19 pandemic has proven to be a social and economic disruptor on a global scale, severely curtailing people’s ability to travel and engage in many recreation activities. Periodic lockdown and stay-at-home orders have exacerbated the situation. In this social climate, urban green spaces have attained a high significance for the maintenance of the physical and mental health of the population. Given the presence of similar coronaviruses in animal populations, it can be predicted that future epidemics and even pandemics will occur. Urban planning needs to incorporate the lessons learnt during COVID-19 in order to future-proof our communities. This paper reviews the role that urban green spaces played during the COVID-19 pandemic. Based on these observations, the paper discusses a range of options for the provision of pandemic-sensitive spaces for physical exercise and mental recreation. Design concepts for long-term planning adjustments as well as for future ad-hoc solutions are provided. These include the provision of social distancing ‘pods’ embedded in design and landscaping of permanent parks, the design of ad-hoc, socially distanced ‘parklets’ on a quietened street and a rethink of the design of curb-to-boundary setbacks (nature strip) in residential streets.

Conformational dynamics and allosteric modulation of the SARS-CoV-2 spike

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects cells through binding to angiotensin-converting enzyme 2 (ACE2). This interaction is mediated by the receptor-binding domain (RBD) of the viral spike (S) glycoprotein. Structural and dynamic data have shown that S can adopt multiple conformations, which controls the exposure of the ACE2-binding site in the RBD. Here, using single-molecule Förster resonance energy transfer (smFRET) imaging we report the effects of ACE2 and antibody binding on the conformational dynamics of S from the Wuhan-1 strain and the B.1 variant (D614G). We find that D614G modulates the energetics of the RBD position in a manner similar to ACE2 binding. We also find that antibodies that target diverse epitopes, including those distal to the RBD, stabilize the RBD in a position competent for ACE2 binding. Parallel solution-based binding experiments using fluorescence correlation spectroscopy (FCS) indicate antibody-mediated enhancement of ACE2 binding. These findings inform on novel strategies for therapeutic antibody cocktails.