Nigelladine A among Selected Compounds from Nigella sativa Exhibits Propitious Interaction with Omicron Variant of SARS-CoV-2: An In Silico Study

COVID-19 has been a threat to the entire world for more than two years since its outbreak in December 2019 in Wuhan city of China. SARS-CoV-2, the causative agent, had been reported to mutate over time exposing new variants. To date, no impeccable cure for the disease has been unveiled. This study outlines an extensive in silico approach to scrutinize certain phytochemical compounds of Nigella sativa (mainly the black cumin seeds) targeting the spike protein and the main protease (Mpro) enzyme of the Omicron variant of SARS-CoV-2. The objective of this study is to investigate the extracted compounds with a view to developing a potential inhibitor against the concerned SARS-CoV-2 variant. The investigation contemplates drug-likeness analysis, molecular docking study, ADME and toxicity prediction, and molecular dynamics simulation which have been executed to elucidate different phytochemical and pharmacological properties of the tested compounds. Based on drug-likeness parameters, a total of 96 phytochemical compounds from N. sativa have been screened in the study. Interestingly, Nigelladine A among the compounds exhibited the highest docking score with both the targets with the same binding affinity which is −7.8 kcal/mol. However, dithymoquinone, kaempferol, Nigelladine B, Nigellidine, and Nigellidine sulphate showed mentionable docking scores. Molecular dynamics up to 100 nanoseconds were simulated under GROMOS96 43a1 force field for the protein-ligand complexes exhibiting the top-docking score. The root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), and the number of hydrogen bonds have been evaluated during the simulation. From the findings, the present study suggests that Nigelladine A showed the most promising results among the selected molecules. This framework, however, interprets only a group of computational analyses on selected phytochemicals. Further investigations are required to validate the compound as a promising drug against the selected variant of SARS-CoV-2.

Insight into vaccination and meteorological factors on daily COVID-19 cases and mortality in Bangladesh

The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind––showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (−0.89, 95% confidence interval (CI): 1.62 to −0.21) and (−1.31, 95%CI: 2.32 to −0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (−0.87, 95% CI: 1.54 to −0.21) and (−3.11, 95%CI: 4.44 to −1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to −0.38 and for deaths: 1.55, 95%CI: 2.88 to −0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions. Graphical Image 1

Insight into vaccination and meteorological factors on daily COVID-19 cases and mortality in Bangladesh.

The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind--showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (-0.89, 95% confidence interval (CI): 1.62 to -0.21) and (-1.31, 95%CI: 2.32 to -0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (-0.87, 95% CI: 1.54 to -0.21) and (-3.11, 95%CI: 4.44 to -1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to -0.38 and for deaths: 1.55, 95%CI: 2.88 to -0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions.

Systems thinking on the gendered impacts of COVID-19 in Bangladesh: A systematic review.

The COVID-19 pandemic has disproportionately affected women and threatens to overturn four decades of progress in Sustainable Development Goal (SDG) 5: Gender Equality and Women's Empowerment. To better grasp the key areas of concern that gender inequality exists, gender studies and sex-disaggregated evidence are required. Using the PRISMA technique, this review paper is the first attempt to present a comprehensive and current picture of the gendered dimensions of the COVID-19 pandemic in Bangladesh regarding economic well-being, resource endowments, and agency. This study found that women were more likely to face hardship as widows, mothers, or sole breadwinners after the loss of husbands and male household members because of the pandemic. The evidence suggests that the advancement of women during this pandemic was hampered by poor reproductive health outcomes; girls' dropping out of school; job loss; less income; a comparable wage gap; a lack of social security; unpaid work burnout; increased emotional, physical, and sexual abuse; an increase in child marriages; and less participation in leadership and decision-making. Our study found inadequate sex-disaggregated data and gender studies on COVID-19 in Bangladesh. However, our research concludes that policies must account for gender disparities and male and female vulnerability across multiple dimensions to achieve inclusive and effective pandemic prevention and recovery.

Effects of Antidepressants on COVID-19 Outcomes: Retrospective Study on Large-Scale Electronic Health Record Data.

BACKGROUND: Antidepressants exert an anticholinergic effect in varying degrees, and various classes of antidepressants can produce a different effect on immune function. While the early use of antidepressants has a notional effect on COVID-19 outcomes, the relationship between the risk of COVID-19 severity and the use of antidepressants has not been properly investigated previously owing to the high costs involved with clinical trials. Large-scale observational data and recent advancements in statistical analysis provide ample opportunity to virtualize a clinical trial to discover the detrimental effects of the early use of antidepressants. OBJECTIVE: We primarily aimed to investigate electronic health records for causal effect estimation and use the data for discovering the causal effects of early antidepressant use on COVID-19 outcomes. As a secondary aim, we developed methods for validating our causal effect estimation pipeline. METHODS: We used the National COVID Cohort Collaborative (N3C), a database aggregating health history for over 12 million people in the United States, including over 5 million with a positive COVID-19 test. We selected 241,952 COVID-19-positive patients (age >13 years) with at least 1 year of medical history. The study included a 18,584-dimensional covariate vector for each person and 16 different antidepressants. We used propensity score weighting based on the logistic regression method to estimate causal effects on the entire data. Then, we used the Node2Vec embedding method to encode SNOMED-CT (Systematized Nomenclature of Medicine-Clinical Terms) medical codes and applied random forest regression to estimate causal effects. We used both methods to estimate causal effects of antidepressants on COVID-19 outcomes. We also selected few negatively effective conditions for COVID-19 outcomes and estimated their effects using our proposed methods to validate their efficacy. RESULTS: The average treatment effect (ATE) of using any one of the antidepressants was -0.076 (95% CI -0.082 to -0.069; P<.001) with the propensity score weighting method. For the method using SNOMED-CT medical embedding, the ATE of using any one of the antidepressants was -0.423 (95% CI -0.382 to -0.463; P<.001). CONCLUSIONS: We applied multiple causal inference methods with novel application of health embeddings to investigate the effects of antidepressants on COVID-19 outcomes. Additionally, we proposed a novel drug effect analysis-based evaluation technique to justify the efficacy of the proposed method. This study offers causal inference methods on large-scale electronic health record data to discover the effects of common antidepressants on COVID-19 hospitalization or a worse outcome. We found that common antidepressants may increase the risk of COVID-19 complications and uncovered a pattern where certain antidepressants were associated with a lower risk of hospitalization. While discovering the detrimental effects of these drugs on outcomes could guide preventive care, identification of beneficial effects would allow us to propose drug repurposing for COVID-19 treatment.

Insight into SARS-CoV-2 Omicron variant immune escape possibility and variant independent potential therapeutic opportunities.

The Omicron, the latest variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in November 2021 in Botswana, South Africa. Compared to other variants of SARS-CoV-2, the Omicron is the most highly mutated, with 50 mutations throughout the genome, most of which are in the spike (S) protein. These mutations may help the Omicron to evade host immunity against the vaccine. Epidemiological studies suggest that Omicron is highly infectious and spreads rapidly, but causes significantly less severe disease than the wild-type strain and the other variants of SARS-CoV-2. With the increased transmissibility and a higher rate of re-infection, Omicron has now become a dominant variant worldwide and is predicted to be able to evade vaccine-induced immunity. Several clinical studies using plasma samples from individuals receiving two doses of US Food and Drugs Administration (FDA)-approved COVID-19 vaccines have shown reduced humoral immune response against Omicron infection, but T cell-mediated immunity was well preserved. In fact, T cell-mediated immunity protects against severe disease, and thus the disease caused by Omicron remains mild. In this review, I surveyed the current status of Omicron variant mutations and mechanisms of immune response in the context of immune escape from COVID-19 vaccines. I also discuss the potential implications of therapeutic opportunities that are independent of SARS-CoV-2 variants, including Omicron. A better understanding of vaccine-induced immune responses and variant-independent therapeutic interventions that include potent antiviral, antioxidant, and anti-cytokine activities may pave the way to reducing Omicron-related COVID-19 complications, severity, and mortality. Collectively, these insights point to potential research gaps and will aid in the development of new-generation COVID-19 vaccines and antiviral drugs to combat Omicron, its sublineages, or upcoming new variants of SARS-CoV-2.

Nigelladine A among Selected Compounds from Nigella sativa Exhibits Propitious Interaction with Omicron Variant of SARS-CoV-2: An In Silico Study.

COVID-19 has been a threat to the entire world for more than two years since its outbreak in December 2019 in Wuhan city of China. SARS-CoV-2, the causative agent, had been reported to mutate over time exposing new variants. To date, no impeccable cure for the disease has been unveiled. This study outlines an extensive in silico approach to scrutinize certain phytochemical compounds of Nigella sativa (mainly the black cumin seeds) targeting the spike protein and the main protease (Mpro) enzyme of the Omicron variant of SARS-CoV-2. The objective of this study is to investigate the extracted compounds with a view to developing a potential inhibitor against the concerned SARS-CoV-2 variant. The investigation contemplates drug-likeness analysis, molecular docking study, ADME and toxicity prediction, and molecular dynamics simulation which have been executed to elucidate different phytochemical and pharmacological properties of the tested compounds. Based on drug-likeness parameters, a total of 96 phytochemical compounds from N. sativa have been screened in the study. Interestingly, Nigelladine A among the compounds exhibited the highest docking score with both the targets with the same binding affinity which is -7.8 kcal/mol. However, dithymoquinone, kaempferol, Nigelladine B, Nigellidine, and Nigellidine sulphate showed mentionable docking scores. Molecular dynamics up to 100 nanoseconds were simulated under GROMOS96 43a1 force field for the protein-ligand complexes exhibiting the top-docking score. The root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), and the number of hydrogen bonds have been evaluated during the simulation. From the findings, the present study suggests that Nigelladine A showed the most promising results among the selected molecules. This framework, however, interprets only a group of computational analyses on selected phytochemicals. Further investigations are required to validate the compound as a promising drug against the selected variant of SARS-CoV-2.

BAuth-ZKP-A Blockchain-Based Multi-Factor Authentication Mechanism for Securing Smart Cities.

The overwhelming popularity of technology-based solutions and innovations to address day-to-day processes has significantly contributed to the emergence of smart cities. where millions of interconnected devices and sensors generate and share huge volumes of data. The easy and high availability of rich personal and public data generated in these digitalized and automated ecosystems renders smart cities vulnerable to intrinsic and extrinsic security breaches. Today, with fast-developing technologies, the classical username and password approaches are no longer adequate to secure valuable data and information from cyberattacks. Multi-factor authentication (MFA) can provide an effective solution to minimize the security challenges associated with legacy single-factor authentication systems (both online and offline). This paper identifies and discusses the role and need of MFA for securing the smart city ecosystem. The paper begins by describing the notion of smart cities and the associated security threats and privacy issues. The paper further provides a detailed description of how MFA can be used for securing various smart city entities and services. A new concept of blockchain-based multi-factor authentication named "BAuth-ZKP" for securing smart city transactions is presented in the paper. The concept focuses on developing smart contracts between the participating entities within the smart city and performing the transactions with zero knowledge proof (ZKP)-based authentication in a secure and privacy-preserved manner. Finally, the future prospects, developments, and scope of using MFA in smart city ecosystem are discussed.

Adapting international clinical trials during COVID-19 and beyond.

BACKGROUND: The COVID-19 pandemic and resulting restrictions, particularly travel restrictions, have had significant impact on the conduct of global clinical trials. Our clinical trials programme, which relied on in-person visits for training, monitoring and capacity building across nine low- and middle-income countries, had to adapt to those unprecedented operational challenges. We report the adaptation of our working model with a focus on the operational areas of training, monitoring and cross-site collaboration. THE NEW WORKING MODEL: Adaptations include changing training strategies from in-person site visits with three or four team members to a multi-pronged virtual approach, with generic online training for good clinical practice, the development of a library of study-specific training videos, and interactive virtual training sessions, including practical laboratory-focused training sessions. We also report changes from in-person monitoring to remote monitoring as well as the development of a more localized network of clinical trial monitors to support hybrid models with in-person and remote monitoring depending on identified risks at each site. We established a virtual network across different trial and study sites with the objective to further build capacity for good clinical practice-compliant antimalarial trials and foster cross-country and cross-study site collaboration. CONCLUSION: The forced adaptation of these new strategies has come with advantages that we did not envisage initially. This includes improved, more frequent engagement through the established network with opportunities for increased south-to-south support and a substantially reduced carbon footprint and budget savings. Our new approach is challenging for study sites with limited prior experience but this can be overcome with hybrid models. Capacity building for laboratory-based work remains difficult using a virtual environment. The changes to our working model are likely to last, even after the end of the pandemic, providing a more sustainable and equitable approach to our research.

COVID-19 and Diarrhea: Putative Mechanisms and Management.

BACKGROUND: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19), has recently posed a threat to global health by spreading at a high rate and taking millions of lives worldwide. Along with the respiratory symptoms, there are gastrointestinal manifestations and one of the most common gastrointestinal symptoms is diarrhea which is seen in a significant percentage of COVID-19 patients. LITERATURE REVIEW: Several studies have shown the plausible correlation between overexpressed angiotensin converting enzyme 2 (ACE2) in enterocytes and SARS-CoV-2, as ACE2 is the only known receptor for the virus entry. Along with the dysregulated ACE2, there are other contributing factors such as gut microbiome dysbiosis, adverse effects of antiviral and antibiotics for treating infections and inflammatory response to SARS-CoV-2 which bring about increased permeability of gut cells and subsequent occurrence of diarrhea. Few studies found that the SARS-CoV-2 is capable of damaging liver cells too. No single effective treatment option is available. LIMITATIONS: Confirmed pathophysiology is still unavailable. Studies regarding global population are also insufficient. CONCLUSION: In this review, based on the previous works and literature, we summarized the putative molecular pathophysiology of COVID-19 associated diarrhea, concomitant complications and the standard practices of management of diarrhea and hepatic manifestations in international setups.

SAR Based Review on Diverse Heterocyclic Compounds with Various Potential Molecular Targets in the Fight against Covid-19: A Medicinal Chemist Perspective.

Coronavirus disease (COVID-19) was reported to be transmitted from bats to humans and, became a pandemic in 2020. COVID-19 is responsible for millions of deaths worldwide and still, the numbers are increasing. Further, despite the availability of vaccines, mutation in the virus continuously poses a threat of re-emergence of the more lethal form of the virus. So far, the repurposing of drugs has been exercised heavily for the identification of therapeutic agents against COVID-19, which led FDA to approve many drugs for the same e.g., remdesivir, favipiravir, ribavirin, etc. The anti-COVID drugs explored via other approaches include nirmatrelvir (used in combination with ritonavir as Paxlovid), tixagevimab and cilgavimab (both used in combination with each other) and others. However, these approved drugs failed to achieve a significant clinical outcome. Globally, natural bioactive have also been explored for anti-COVID-19 effects, based on their traditional medicinal values. Although the clinical findings suggest that FDA-approved drugs and natural bioactives can help reducing the overall mortality rate but the significant clinical outcome was not achieved. Therefore, the focus has been shifted towards new drug development. In line with that, a lot of work has been done and still going on to explore heterocyclic compounds as potent anti-COVID-19 drugs. Several heterocyclic scaffolds have been previously reported with potent antiinflammatory, anticancer, anti-viral, antimicrobial and anti-tubercular effects. Few of them are under consideration for clinical trials whereas others are under preclinical investigation. Hence, this review discusses the evidence of rationally designed and tested heterocyclic compounds acting on different targets against COVID-19. The present manuscript will help the researches and will serve as a pivotal resource in the design and development of novel anti-COVID-19 drugs.

Exploring the Antecedents of Supply Chain Viability in a Pandemic Context: An Empirical Study on the Commercial Flower Supply Chain of an Emerging Economy

The global supply chain (SC) has faced unprecedented disruptions fueled by the COVID-19 virus. While scholarly research has explored various dimensions to counter the epidemic and bolster the SC, the literature is still dispersed and fragmented in managing the SC toward sustainable operational performance. We strengthened the notion of the SC by extending it toward the SC viability (SCV) approach. The objective of the study is to determine the factors to propose a model for sustainable SC viability in a pandemic context. We built our theoretical model based on the viable supply chain (VSC) theory. The study assessed the hypotheses using partial least square-based structural equation modelling with data from 428 flower-producing cum trading enterprises. The research found that supply chain integration and supply risk control positively influence ensuring SCV. Besides, supply chain resilience mediates the effect of SC integration and risk control on SCV. By exploring the role of SC integration, SC resilience, and SC risk control, the study contributes to SC viability theory. Our research fills the gap in the domain of SC viability dimension. From our study, the academicians and firms can get fresh antecedents of SC viability as an emerging sustainable SC management approach.

Future of Orthodontics-A Systematic Review and Meta-Analysis on the Emerging Trends in This Field.

Technology is rapidly evolving in the modern world, and the accompanying developments due to its influence are shaping each and every aspect of our life, with the field of orthodontics being no exception. This systematic review and meta-analysis aimed to examine such trends in orthodontics and hypothesize which ones would emerge and continue in the near future. After a thorough search of online journals using keywords such as "3D printing," "Aligners," "Artificial intelligence," "Future trends," "Orthodontics," and "Teleorthodontics" across databases of PubMed-MEDLINE, Web of Science, Cochrane, and Scopus, a total of 634 papers were initially recovered. Technological advancements in 3D printing, Computer-aided design and Computer-aided manufacturing (CAD/CAM), biopolymers and Teleorthodontics were the most important categories of development seen across the 17 studies that we selected for our review. All the investigations selected for this systematic review depicted aspects of orthodontics that were influenced by rapid technological changes and could potentially become mainstream in the coming times. However, caution was sought to be observed in the usage/adoption of some of these trends, with social media usage amongst both patients as well as orthodontists being a prime example of this.

Exploring challenges and mitigation strategies towards practicing Teledentistry.

BACKGROUND: Since the beginning of the COVID-19 pandemic, many dentists have opted for Teledentistry as a mechanism for patient consultation, oral lesion evaluation, diagnosis, and monitoring. The current study explores the challenges faced and potential solutions proposed by dentists practicing Teledentistry in a developing country like Pakistan. METHODS: A qualitative case study was carried out from January to December 2021. A purposive maximum variation sample of 10 dentists was interviewed in two focus groups. The interview guide was developed using the technology-organization-environment framework. The data was transcribed verbatim using otter.ai. The analysis involved immersion in the data and open coding. The conceptually related codes were synthesized into themes and subthemes. FINDINGS: The study found various Personnel, Technological and Organizational challenges, and potential solutions from those practicing Teledentistry. The challenges included operational cost, minimal financial returns, lack of awareness, hardware and software support, and other challenges related to the availability of specialization, accessibility, and institutional encouragement. They suggested Institutional Based Practice, staff training, hiring, development of government regulations, and supporting infrastructures such as designated space, central registry, internet, and using/building software to provide 3D images as solutions. CONCLUSION: Teledentists face Personnel, Technological and Organizational challenges and related potential solutions from those practicing Teledentistry in Pakistan. Government should encourage Teledentistry to reduce long-term costs, encourage preventive services and enable rural access to dental care. They should also involve all stakeholders to develop regulations for practicing Teledentistry in Pakistan.

COVID19-induced immunosuppression and aggressive progression of primary cranial vault lymphoma presenting as a management challenge, a case report, and a literature review.

Background: We needs to study Primary Large cell Non-Hodgkin's Lymphoma of the cranial vault, which is rare, and its association with COVID19 has not been reported, which may have an immunosuppressive effect to aggravate its progression. Patient details: Our patient, a 53-year-old male, noticed fast growth of posterior cranial vault lesion from 2 to 10 cm size in last 6 months after COVID 19 affliction. MRI brain with contrast revealed lesions suggesting meningioma. The whole-body PET scan was normal. Following Subtotal excision of the mass, histopathology revealed large B-cell Non-Hodgkin's lymphoma (DLBCL). Immunohistochemistry showed positive results for CD10, CD20, CD45 (LCA), ALK, and BCL-VE with a Ki-67 index of 90-95%. Following radiotherapy and chemotherapy patient is disease-free on imaging and doing well at 5 months of follow-up. Conclusions: Early intervention with excisional biopsy and timely chemo and radiotherapy in favorable immunostaining may add survival benefits even in malignant features induced by immunosuppressing diseases such as COVID19 in diffuse large B-cell lymphoma (DLBCL) of the scalp.

Adaptation and Change in Practices in Neuro-Intervention during COVID-19 Pandemic: Experience from Department of Interventional Neurology at Referral Tertiary Care Hospital in Bangladesh

Background: Different adaptation and changes have been practiced during COVID-19 pandemic. Objective: In this paper we investigated the impact of the COVID-19 pandemic on service delivery in the department of interventional neurology and adaptation of the department to the changed environment. Methodology: This was a retrospective analysis of diagnostic digital subtraction angiography (DSA) procedures done from January 2018 to December 2020 and were analyzed to detect significant breaks in time trend. Results: A total of 358, 426 and 251 patients got admitted for DSA in consecutive three years from 2018 to 2020 respectively. There was a sudden drop in the number of DSA procedures from 30 to 50 patients per month in the pre-COVID era before March 2020 to less than 10 patients per month during the COVID period of March to June 2020. However, the situation gradually improved following the introduction of RT-PCR test for SARS CoV-2 in June 2020. A poison regression showed a significant increase in monthly DSA procedures in the year 2019 compared to the year 2018, but a significant decrease in the pandemic year of 2020. Conclusion: By incorporating COVID-19 testing as a pre-requisite test before DSA procedures, the department of interventional neurology recovered from experiencing a significant drop in the number of performed DSA procedures in the initial periods of the pandemic to reaching a level observed in the pre-COVID era.

Direct Nasal Swab for Rapid Test and Saliva as an Alternative Biological Sample for RT-PCR in COVID-19 Diagnosis.

Accurate and early diagnoses are prerequisites for prompt treatment. For coronavirus disease 2019 (COVID-19), it is even more crucial. Currently, choice of methods include rapid diagnostic tests and reverse transcription polymerase chain reaction (RT-PCR) using samples mostly of respiratory origin and sometimes saliva. We evaluated two rapid diagnostic tests with three specimen types using viral transport medium (VTM) containing naso-oropharyngeal (NOP) swabs, direct nasal and direct nasopharyngeal (NP) samples from 428 prospective patients. We also performed RT-PCR for 428 NOP VTM and 316 saliva samples to compare results. The sensitivity of the SD Biosensor Standard Q COVID-19 antigen (Ag) test kit drastically raised from an average of 65.55% (NOP VTM) to 85.25% (direct nasal samples), while RT-PCR was the gold standard. For the CareStart kit, the sensitivity was almost similar for direct NP swabs; the average was 84.57%. The specificities were ≥95% for both SD Biosensor Standard Q and CareStart COVID-19 Ag tests in all platforms. The kits were also able to detect patients with different variants as well. Alternatively, RT-PCR results from saliva and NOP VTM samples showed high sensitivities of 96.45% and 95.48% with respect to each other as standard. The overall results demonstrated high performance of the rapid tests, indicating the suitability for regular surveillance at clinical facilities when using direct nasal or direct NP samples rather than NOP VTM. Additionally, the analysis also signifies not showed that RT-PCR of saliva can be used as an choice of method to RT-PCR of NOP VTM, providing an easier, non-invasive sample collection method. IMPORTANCE There are several methods for the diagnosis of coronavirus disease 2019 (COVID-19), and the choice of methods depends mostly on the resources and level of sensitivity required by the user and health care providers. Still, reverse transcription polymerase chain reaction (RT-PCR) has been chosen as the best method using direct naso-oropharyngeal swabs. There are also other methods of fast detection, such as rapid diagnostic tests (RDTs), which offer result within 15 to 20 min and have become quite popular for self-testing and in the clinical setting. The major drawback of the currently used RT-PCR method is compliance, as it may cause irritation, and patients often refuse to test in such a way. RDTs, although inexpensive, suffer from low sensitivity due to technical issues. In this article, we propose saliva as a noninvasive source for RT-PCR samples and evaluate various specimen types at different times after infection for the best possible output from COVID-19 rapid tests.

Clinical Evaluation of Three Commercial RT-PCR Kits for Routine COVID-19 Diagnosis.

Amongst the multiple ways to diagnose coronavirus disease-2019 (COVID-19), reverse transcription polymerase chain reaction (RT-PCR) remains the reference gold standard, providing fast and accurate results. This study evaluated and compared the performance of three commercially available COVID-19 RT-PCR kits-Aridia® COVID-19 Real-Time PCR Test (CTK Biotech, Inc., Poway, CA, USA), Novel Coronavirus (2019-nCoV) Nucleic Acid Detection Kit (Sansure Biotech Inc., Changsha, China) and AllplexTM 2019-nCoV assay (Seegene Inc., Seoul, Republic of Korea) for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A total of 326 clinically suspected patients were enrolled for the study, and among them, 209 were diagnosed as positive and 117 as negative when tested with the reference method, US CDC 2019-Novel Coronavirus (2019-nCoV) Real Time RT-PCR Diagnostic Panel. The Aridia® kit showed total agreement with the reference test, with a sensitivity of 100% (95% CI: 98.25% to 100.0%) and a specificity of 100% (96.90% to 100.00%). The AllplexTM kit also showed 100% specificity (95% CI: 96.90% to 100.00%), but a lower sensitivity (98.09%, 95% CI: 95.17% to 99.48%). Among the three kits, the Novel Coronavirus (2019-nCoV) Nucleic Acid Detection Kit showed the worst performance, with a sensitivity of 98.6% (95% CI: 95.9% to 99.7%) and a specificity of 95.73, 95% (CI: 90.31% to 98.60%). While all these kits conform to the requirement for routine molecular diagnosis with high performances, the Aridia® COVID-19 Real-Time PCR Test showed the best performance among the three kits.

Pre COVID-19 molecular epidemiology of respiratory syncytial virus (RSV) among children in Bangladesh.

Epidemiological data of specific respiratory pathogens from the pre-COVID-19 period are essential to determine the effects of the COVID-19 pandemic on other respiratory infections. In this study, we revealed the pre-COVID-19 molecular epidemiology of respiratory syncytial virus (RSV) among children in Bangladesh. We tested 3170 samples collected from 2008 to 2012 for a panel of respiratory viruses; RSV, human metapneumovirus (hMPV), human parainfluenza viruses (hPIV) 1, 2, 3, and adenovirus. Five hundred fifty-five samples (17.5 %) were positive for RSV, including 2.5% having co-infections with other viruses. Genotypic characterization of RSV showed that RSV-A (82%) contributed more acute respiratory infections than RSV-B (18%). Clinical features were similar with RSV-A and RSV-B infections. However, children with RSV-B were more likely to have upper respiratory infections (URI) (10% vs. 29%, p = 0.03). Among RSV-A cases, hospitalization was higher for ON1 cases (25%, ON1 vs. 8%, NA1, p = 0.04), whereas the recovery without a disability was higher among the NA1 cases (56%, ON1 vs. 88%, NA1, p = 0.02). The time to the most recent common ancestor (TMRCA) for RSV in Bangladesh was 1949 for RSV-A and 1944 for RSV-B. This study revealed the genotypic diversity and evolutionary relatedness of RSV strains in Bangladesh and provided pre-COVID molecular epidemiology data to understand better the COVID-19 impact on upcoming RSV epidemiology in Bangladesh.