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1.
Am J Infect Control ; 50(8): 844-848, 2022 08.
Article in English | MEDLINE | ID: covidwho-2000226

ABSTRACT

BACKGROUND: Methylene blue (MB) and riboflavin (RB) are light-activated dyes with demonstrated antimicrobial activity. They require no specialized equipment, making them attractive for widespread use. Due to COVID-19-related worldwide shortages of surgical masks, simple, safe, and effective decontamination methods for reusing masks have become desirable in clinical and public settings. MATERIAL AND METHODS: We examined the decontamination of SARS-CoV-2 Beta variant on surgical masks and Revolution-Zero Environmentally Sustainable (RZES) reusable masks using these photoactivated dyes. We pre-treated surgical masks with 2 MB concentrations, 2 RB concentrations, and 2 combinations of MB and RB. We also tested 7 MB concentrations on RZES masks. RESULTS: Photoactivated MB consistently inactivated SARS-CoV-2 at >99.9% for concentrations of 2.6 µM or higher within 30 min on RZES masks and 5 µM or higher within 5 min on disposable surgical masks. RB alone showed a lower, yet still significant inactivation (∼93-99%) in these conditions. DISCUSSION: MB represents a cost-effective, rapid, and widely deployable decontamination method for SARS-CoV-2. The simplicity of MB formulation makes it ideal for mask pre-treatment in low-resource settings. CONCLUSIONS: The results demonstrate that MB effectively decontaminates SARS-CoV-2 at concentrations above 5 µM on surgical masks and above 10 µM on RZES masks.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/prevention & control , Coloring Agents/pharmacology , Humans , Masks
2.
Am J Infect Control ; 50(8): 857-862, 2022 08.
Article in English | MEDLINE | ID: covidwho-2000224

ABSTRACT

BACKGROUND: Global shortage of personal protective equipment (PPE), as consequence of the COVID-19 global pandemic, has unmasked significant resource inequities prompting efforts to develop methods for safe PPE decontamination for reuse. The World Health Organization (WHO) in their Rational Use of PPE bulletin cited the use of a photodynamic dye, methylene blue, and light exposure as a viable option for N95 respirator decontamination. Because WHO noted that methylene blue (MB) would be applied to surfaces through which health care workers breathe, we hypothesized that little to no MB will be detectable by spectroscopy when the PPE is subjected to MB at supraphysiologic airflow rates. METHODS: A panel of N95 respirators, medical masks, and cloth masks were sprayed with 5 cycles of 1,000 uM MB solution. Mask coupons were subjected to the equivalent of 120 L/min of 100% humidified air flow. Effluent gas was trapped in an aqueous solution and the resultant fluid was sampled for MB absorbance with a level of detection of 0.004 mg/m3. RESULTS: No detectable MB was identified for any mask using Ultraviolet-Visible spectroscopy. CONCLUSIONS: At 500-fold the amount of MB applied to N95 respirators and medical masks as were used for the decontamination study cited in the WHO Rational Use of PPE bulletin, no detectable MB was observed, thus providing safety evidence for the use of methylene blue and light exposure for mask decontamination.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/prevention & control , Decontamination/methods , Equipment Reuse , Humans , Methylene Blue , N95 Respirators
4.
Research in engineering design ; : 1-24, 2022.
Article in English | EuropePMC | ID: covidwho-1897760

ABSTRACT

Lower costs and higher employee satisfaction are some of the benefits driving organizations to adopt dispersed and virtual working arrangements. Despite these advantages, product design engineering teams—those who develop physical products—have not widely adopted this working style due to perceived critical dependence on physical facilities and the belief that it is ineffective to communicate technical details virtually. This paper uses the mass shift in working conditions caused by the COVID-19 pandemic to explore the feasibility of virtual and distributed work in product design engineering. We conducted 20 semi-structured interviews with product design engineers working virtually to uncover current challenges of, and the beginning of promising strategies for, effective virtual engineering work. We categorize and analyze Tangible Design activities, Intangible Design activities, and Communication and Project Management activities throughout the product design process. Contrary to present opinions, we found that much of a product design engineer's work is realizable in a virtual and distributed setting. However, there are still many challenges, especially when attempting Tangible Design activities—those that require physical products and tools—from home. These challenges, missing from existing virtual product design engineering literature, include but are not limited to individuals’ lessened sense of accountability, fewer de-risking opportunities before product sign-off, and limited supervision of production staff. Product design engineers described novel strategies that emerged organically to mitigate these challenges, such as creating digital alternatives for engineering reviews and sign-offs and leveraging rapid prototyping. Recent advances in technology, an increased commitment to reducing environmental impact, and better work-life balance expectations from new generations of workers will only push society faster towards a distributed working model. Thus, it is critical that we use this opportunity to understand the existing challenges for distributed product design engineers, so that organizations can best prepare and become resilient to future shocks.

5.
Advances in Decision Sciences ; 26(1):1-37, 2022.
Article in English | ProQuest Central | ID: covidwho-1887662

ABSTRACT

Purpose: Trust is essential for organizations' cooperative relationships during COVID-19. Authentic leadership and social exchange relationships are required to increase trust during a crisis. However, leader behaviors during COVID-19 have effects on the relationships among authentic leadership, social exchange relationships, and trust in organizations to understand their effects. The moderating effects of leader behaviors during COVID-19 on the relationships among authentic leadership, social exchange relationships, and trust in organizations are investigated. Design/ Methodology/Approach: Hierarchical multiple regression with interaction terms is used to examine interactions of leader behaviors during COVID-19 on the relationships between variables. Moreover, bootstrapping is performed to explore the mediating role of social exchange relationships between authentic leadership and trust in organizations. Findings: The findings indicate that authentic leadership positively affects social exchange relationships and trust, whereas social exchange relationships positively affect trust. Moreover, a social exchange relationship has a mediating effect between authentic leadership and trust. Both leader behaviors are regrading (a) managerial ability with ethics and (b) a positive working relationship based on work from home as moderators, positively influencing authentic leadership, social exchange relationships, and trust. Practical implications: This paper suggests that authentic leadership increases the quality of social exchange relationships and trust. Leader behavior qualities and leader-follower relationships based on social exchange theory are essential for improving trust even after postCOVID-19. Finally, based on the social exchange theory, leader behavior qualities and leaderfollower relationships can motivate positive relationships in organizations. The chief executive officers (CEOs) and the organizational management teams benefit from the outcomes of this paper to comprehend which factors affect relationships and trust changes in organizations.

6.
Sustainability ; 14(10):5883, 2022.
Article in English | MDPI | ID: covidwho-1855771

ABSTRACT

During the pandemic, government policies such as social distancing and telework have impacted trust and working or social exchange relationships in the workplace. The behavior of leaders is critical for good leadership, employees' trust, and social exchange relationships. Therefore, the main objective of this study was to assess the associations among authentic leadership, trust, and social exchange relationships under the influence of leader behavior. A regression-based approach was used to test the moderating and mediating effects. The results show that authentic leadership positively impacts trust and social exchange relationships, whereas trust directly affects social exchange relationships. During COVID-19, leader behaviors with ability, ethics, and positive relationships have had a positive impact on the association between authentic leadership, trust, and social exchange relationships. Additionally, trust positively mediates authentic leadership and social exchange relationships. The findings of this paper suggest that authentic leadership promotes trust and high-quality social exchange relationships. Moreover, based on leader behaviors during COVID-19, the ability to manage change effectively, boost employees' work motivation, provide support, and take appropriate action is essential for authentic leadership to increase trust and foster a positive working relationship based on social exchange. Finally, regarding social exchange theory, high-quality leader behaviors and the leader–follower relationships drive positive associations among variables. These results will help organizational management teams to find methods to improve their organizational working relationships. The implication is that the abilities, ethics, and supportive and positive relationship behaviors of leaders are essential for effective management to improve leadership, trust, and social exchange relationships. Leaders should have the ability to manage work and people, even with teleworkers. Therefore, leader behaviors are important to maintain organizational sustainability. Further discussion on theoretical and practical implications is provided in the section.

7.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337015

ABSTRACT

The SARS-CoV-2 RNA-dependent RNA polymerase coordinates viral RNA synthesis as part of an assembly known as the replication-transcription complex (RTC) 1 . Accordingly, the RTC is a target for clinically approved antiviral nucleoside analogs, including remdesivir 2 . Faithful synthesis of viral RNAs by the RTC requires recognition of the correct nucleotide triphosphate (NTP) for incorporation into the nascent RNA. To be effective inhibitors, antiviral nucleoside analogs must compete with the natural NTPs for incorporation. How the SARS-CoV-2 RTC discriminates between the natural NTPs, and how antiviral nucleoside analogs compete, has not been discerned in detail. Here, we use cryo-electron microscopy to visualize the RTC bound to each of the natural NTPs in states poised for incorporation. Furthermore, we investigate the RTC with the active metabolite of remdesivir, remdesivir triphosphate (RDV-TP), highlighting the structural basis for the selective incorporation of RDV-TP over its natural counterpart ATP 3,4 . Our results elucidate the suite of interactions required for NTP recognition, informing the rational design of antivirals. Our analysis also yields insights into nucleotide recognition by the nsp12 NiRAN, an enigmatic catalytic domain essential for viral propagation 5 . The NiRAN selectively binds GTP, strengthening proposals for the role of this domain in the formation of the 5’ RNA cap 6 .

8.
Nat Struct Mol Biol ; 29(3): 250-260, 2022 03.
Article in English | MEDLINE | ID: covidwho-1735263

ABSTRACT

The SARS-CoV-2 nonstructural proteins coordinate genome replication and gene expression. Structural analyses revealed the basis for coupling of the essential nsp13 helicase with the RNA-dependent RNA polymerase (RdRp) where the holo-RdRp and RNA substrate (the replication-transcription complex or RTC) associated with two copies of nsp13 (nsp132-RTC). One copy of nsp13 interacts with the template-RNA in an opposing polarity to the RdRp and is envisaged to drive the RdRp backward on the RNA template (backtracking), prompting questions as to how the RdRp can efficiently synthesize RNA in the presence of nsp13. Here we use cryogenic-electron microscopy and molecular dynamics simulations to analyze the nsp132-RTC, revealing four distinct conformational states of the helicases. The results indicate a mechanism for the nsp132-RTC to turn backtracking on and off, using an allosteric mechanism to switch between RNA synthesis or backtracking in response to stimuli at the RdRp active site.


Subject(s)
COVID-19 , SARS-CoV-2 , Cryoelectron Microscopy , Humans , RNA Helicases/chemistry , Viral Nonstructural Proteins/chemistry , Virus Replication
9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-318315

ABSTRACT

Recent advances in single particle cryogenic electron microscopy (cryo-EM) have enabled the structural determination of numerous protein assemblies at high resolution, yielding unprecedented insights into their function. However, despite its extraordinary capabilities, cryo-EM remains time-consuming and resource-intensive. It is therefore beneficial to have a means for rapidly assessing and optimizing the quality of samples prior to lengthy cryo-EM analyses. To do this, we have developed a native mass spectrometry (nMS) platform that provides rapid feedback on sample quality and highly streamlined biochemical screening. Because nMS enables accurate mass analysis of protein complexes, it is well-suited for routine evaluation of the composition, integrity, and homogeneity of samples prior to their plunge-freezing on EM grids. We demonstrate the utility of our nMS-based platform for facilitating cryo-EM studies using structural characterizations of exemplar bacterial transcription complexes as well as the replication-transcription assembly from the SARS-CoV-2 virus that is responsible for the COVID-19 pandemic.Funding: This work is supported by the Pels Foundation to The Rockefeller University, NIH grants P41 GM109824 and P41 GM103314 to BTC, R35 GM118130 to SAD, and R01 GM114450 to EAC. Access to the cryo-EM microscopes and support was through The Rockefeller University Evelyn Gruss Lipper Cryo-EM Resource Center and at The Simons Electron Microscopy Center (SEMC), National Resource for Automated Molecular Microscopy (NRAMM), and National Center for CryoEM Access and Training (NCCAT) at the NYSBC, supported by NIH NIGMS (P41 GM103310), NYSTAR, the Simons Foundation (SF349247), the NIH Common Fund Transformative High Resolution CryoElectron Microscopy program (U24 GM129539) and NY State Assembly Majority. Conflict of Interest: The authors declare there are no competing interests.

10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308203

ABSTRACT

Unsupervised machine learning can interpret logarithmic returns and conditional volatility in commodity markets. k-means and hierarchical clustering can generate a financial ontology of markets for fuels, precious and base metals, and agricultural commodities. Manifold learning methods such as multidimensional scaling (MDS) and t-distributed stochastic neighbor embedding (t-SNE) enable the visualization of comovement and other financial relationships in three dimensions.Different methods of unsupervised learning excel at different tasks. k-means clustering based on logarithmic returns works well with MDS to classify commodities and to create a spatial ontology of commodities trading, A strikingly different application involves k-means clustering of the matrix transpose, such that conditional volatility is evaluated by trading date rather than by commodity. This approach can isolate the two most calamitous temporal regimes of the past two decades: the global financial crisis of 2008-09 and the immediate reaction to the Covid-19 pandemic. Temporal clustering of trading days, unlike the corresponding spatial task of clustering commodities, is better visualized through t-SNE than through MDS.

11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308202

ABSTRACT

A suite of clustering methods, applied to the matrix of conditional volatility by trading days and individual assets or asset classes, can identify critical periods in markets for crude oil, refined fuels, and other commodities. Unsupervised machine learning provides a viable alternative to rules-based and subjective definitions of crises in financial markets and the broader economy. Five clustering methods—affinity propagation, mean-shift, spectral, k-means, and hierarchical agglomerative clustering—can identify anomalous periods in commodities trading. These methods identified the financial crisis of 2008–09 and the initial stages of the Covid-19 pandemic. Applied to four energy-related markets—Brent, West Texas intermediate, gasoil, and gasoline—the same methods identified additional periods connected to events such as the September 11 terrorist attacks and the 2003 Persian Gulf war. t-distributed stochastic neighbor embedding facilities the visualization of commodity trading regimes. Future applications of these methods include the definition of bull and bear markets and the identification of recessions and recoveries in the real economy.

12.
Eur J Radiol ; : 110153, 2022 Jan 07.
Article in English | MEDLINE | ID: covidwho-1611709

ABSTRACT

PURPOSE: Worldwide, radiologists are experiencing increasing clinical workloads with associated increased burnout. This paper will review burnout definitions, prevalence, and causes. We will also share data from a survey of US neuroradiologists as an example of the impact of work-work imbalances from clinical overload. This article examines the impact on several key job indicators and upon the quality of the neuroradiology work environment in one nation. Finally, we will review proposals for ameliorating and preventing radiologist burnout. METHOD: A survey was sent to members of the American Society of Neuroradiology (ASNR) practicing in the US. Selected measures included workhours and volume, burnout symptoms, subjectively reported errors, participation in non-clinical activities, perceived interpretation quality, results communication, and consideration of early retirement. RESULTS: Survey respondents (n = 412) included 57.5% with teaching responsibilities. Cutbacks in teaching, mentoring, research and/or practice building were reported by 86.2% of respondents. Subjective errors were reported as occurring sometimes or more frequently in the majority of respondents (56.9%) and were increased with faster than optimal speeds of interpretation (P < 0.001) and signing (P < 0.001). At least one burnout measure was reported by 85.2% of respondents. CONCLUSIONS: Increasing clinical demands in conjunction with a more challenging work environment impacts the ability of radiologists to perform core non-interpretive duties that are critical for success in both private and academic practice and is associated with burnout symptoms and adverse effects on quality. While this survey does not prove causation, the trends and findings are concerning and warrant both close monitoring and appropriate intervention.

13.
Non-conventional in English | [Unspecified Source], Grey literature | ID: grc-750506

ABSTRACT

SARS-CoV-2 is the causative agent of the 2019-2020 pandemic. The SARS-CoV-2 genome is replicated-transcribed by the RNA-dependent RNA polymerase holoenzyme (subunits nsp7/nsp82/nsp12) along with a cast of accessory factors. One of these factors is the nsp13 helicase. Both the holo-RdRp and nsp13 are essential for viral replication and are targets for treating the disease COVID-19. Here we present cryo-electron microscopic structures of the SARS-CoV-2 holo-RdRp with an RNA template-product in complex with two molecules of the nsp13 helicase. The Nidovirus-order-specific N-terminal domains of each nsp13 interact with the N-terminal extension of each copy of nsp8. One nsp13 also contacts the nsp12-thumb. The structure places the nucleic acid-binding ATPase domains of the helicase directly in front of the replicating-transcribing holo-RdRp, constraining models for nsp13 function. We also observe ADP-Mg2+ bound in the nsp12 N-terminal nidovirus RdRp-associated nucleotidyltransferase domain, detailing a new pocket for anti-viral therapeutic development.

14.
Energies ; 14(19):6099, 2021.
Article in English | MDPI | ID: covidwho-1438562

ABSTRACT

The identification of critical periods and business cycles contributes significantly to the analysis of financial markets and the macroeconomy. Financialization and cointegration place a premium on the accurate recognition of time-varying volatility in commodity markets, especially those for crude oil and refined fuels. This article seeks to identify critical periods in the trading of energy-related commodities as a step toward understanding the temporal dynamics of those markets. This article proposes a novel application of unsupervised machine learning. A suite of clustering methods, applied to conditional volatility forecasts by trading days and individual assets or asset classes, can identify critical periods in energy-related commodity markets. Unsupervised machine learning achieves this task without rules-based or subjective definitions of crises. Five clustering methods—affinity propagation, mean-shift, spectral, k-means, and hierarchical agglomerative clustering—can identify anomalous periods in commodities trading. These methods identified the financial crisis of 2008–2009 and the initial stages of the COVID-19 pandemic. Applied to four energy-related markets—Brent, West Texas intermediate, gasoil, and gasoline—the same methods identified additional periods connected to events such as the September 11 terrorist attacks and the 2003 Persian Gulf war. t-distributed stochastic neighbor embedding facilitates the visualization of trading regimes. Temporal clustering of conditional volatility forecasts reveals unusual financial properties that distinguish the trading of energy-related commodities during critical periods from trading during normal periods and from trade in other commodities in all periods. Whereas critical periods for all commodities appear to coincide with broader disruptions in demand for energy, critical periods unique to crude oil and refined fuels appear to arise from acute disruptions in supply. Extensions of these methods include the definition of bull and bear markets and the identification of recessions and recoveries in the real economy.

15.
Infect Control Hosp Epidemiol ; 43(7): 876-885, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1275836

ABSTRACT

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic has resulted in shortages of personal protective equipment (PPE), underscoring the urgent need for simple, efficient, and inexpensive methods to decontaminate masks and respirators exposed to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). We hypothesized that methylene blue (MB) photochemical treatment, which has various clinical applications, could decontaminate PPE contaminated with coronavirus. DESIGN: The 2 arms of the study included (1) PPE inoculation with coronaviruses followed by MB with light (MBL) decontamination treatment and (2) PPE treatment with MBL for 5 cycles of decontamination to determine maintenance of PPE performance. METHODS: MBL treatment was used to inactivate coronaviruses on 3 N95 filtering facepiece respirator (FFR) and 2 medical mask models. We inoculated FFR and medical mask materials with 3 coronaviruses, including SARS-CoV-2, and we treated them with 10 µM MB and exposed them to 50,000 lux of white light or 12,500 lux of red light for 30 minutes. In parallel, integrity was assessed after 5 cycles of decontamination using multiple US and international test methods, and the process was compared with the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method. RESULTS: Overall, MBL robustly and consistently inactivated all 3 coronaviruses with 99.8% to >99.9% virus inactivation across all FFRs and medical masks tested. FFR and medical mask integrity was maintained after 5 cycles of MBL treatment, whereas 1 FFR model failed after 5 cycles of VHP+O3. CONCLUSIONS: MBL treatment decontaminated respirators and masks by inactivating 3 tested coronaviruses without compromising integrity through 5 cycles of decontamination. MBL decontamination is effective, is low cost, and does not require specialized equipment, making it applicable in low- to high-resource settings.


Subject(s)
COVID-19 , Virus Diseases , COVID-19/prevention & control , Decontamination/methods , Equipment Reuse , Humans , Masks , Methylene Blue/pharmacology , N95 Respirators , Personal Protective Equipment , SARS-CoV-2
16.
Resources Policy ; 73:102162, 2021.
Article in English | ScienceDirect | ID: covidwho-1272699

ABSTRACT

Unsupervised machine learning can interpret logarithmic returns and conditional volatility in commodity markets. This article applies machine learning in order to visualize and interpret log returns and conditional volatility in commodities trading. We emphasize two classes of unsupervised learning methods: clustering and manifold learning for the reduction of dimensionality. We source daily prices from September 18, 2000 through July 31, 2020, for precious metals, base metals), energy commodities and agricultural commodities. Our results highlight that at the very least, returns-based clusters conform more closely to traditional boundaries between precious metals, base metals, fuels, temperate-climate agricultural commodities, and tropical agricultural commodities. On the other hand, volatility-based clustering succeeds in identifying periods of extreme market distress, such as the global financial crisis of 2008–09 and the Covid-19 pandemic.

17.
Sustainability ; 13(11):6181, 2021.
Article in English | MDPI | ID: covidwho-1259598

ABSTRACT

In context of the recent COVID-19 pandemic, smart hospitals’ contributions to pre-medical, remote diagnosis, and social distancing has been further vetted. Smart hospital management evolves with new technology and knowledge management, which needs an evaluation system to prioritize its associated criteria and sub-criteria. The global effect of the COVID-19 pandemic further necessitates a comprehensive research of smart hospital management. This paper will utilize Analytical Hierarchy Process (AHP) within Multiple Criteria Decision Making (MCDM) to establish a smart hospital evaluation system with evaluation criteria and sub-criteria, which were then further prioritized and mapped to BIM-related alternatives to inform asset information management (AIM) practices. This context of this study included the expert opinions of six professionals in the smart hospital field and collected 113 responses from hospital-related personnel. The results indicated that functionalities connected to end users are critical, in particular IoT’s Network Core Functionalities, AI’s Deep Learning and CPS’s Special Network Technologies. Furthermore, BIM’s capability to contribute to the lifecycle management of assets can relate and contribute to the asset-intensive physical criteria of smart hospitals, in particular IoT, service technology innovations and their sub-criteria.

18.
Proc Natl Acad Sci U S A ; 118(19)2021 05 11.
Article in English | MEDLINE | ID: covidwho-1254144

ABSTRACT

Backtracking, the reverse motion of the transcriptase enzyme on the nucleic acid template, is a universal regulatory feature of transcription in cellular organisms but its role in viruses is not established. Here we present evidence that backtracking extends into the viral realm, where backtracking by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) may aid viral transcription and replication. Structures of SARS-CoV-2 RdRp bound to the essential nsp13 helicase and RNA suggested the helicase facilitates backtracking. We use cryo-electron microscopy, RNA-protein cross-linking, and unbiased molecular dynamics simulations to characterize SARS-CoV-2 RdRp backtracking. The results establish that the single-stranded 3' segment of the product RNA generated by backtracking extrudes through the RdRp nucleoside triphosphate (NTP) entry tunnel, that a mismatched nucleotide at the product RNA 3' end frays and enters the NTP entry tunnel to initiate backtracking, and that nsp13 stimulates RdRp backtracking. Backtracking may aid proofreading, a crucial process for SARS-CoV-2 resistance against antivirals.


Subject(s)
COVID-19/virology , SARS-CoV-2/physiology , Virus Replication/genetics , Adenosine Monophosphate/pharmacology , Antiviral Agents/pharmacology , COVID-19/genetics , COVID-19/metabolism , Coronavirus RNA-Dependent RNA Polymerase/metabolism , Cryoelectron Microscopy/methods , DNA Helicases/metabolism , Genome, Viral , Humans , Molecular Dynamics Simulation , RNA Helicases/metabolism , RNA, Viral/genetics , RNA, Viral/metabolism , RNA-Dependent RNA Polymerase/metabolism , RNA-Dependent RNA Polymerase/physiology , SARS-CoV-2/drug effects , SARS-CoV-2/genetics , Viral Nonstructural Proteins/genetics
19.
JCI Insight ; 6(9)2021 05 10.
Article in English | MEDLINE | ID: covidwho-1228934

ABSTRACT

SARS coronavirus 2 (SARS-CoV-2) is a novel viral pathogen that causes a clinical disease called coronavirus disease 2019 (COVID-19). Although most COVID-19 cases are asymptomatic or involve mild upper respiratory tract symptoms, a significant number of patients develop severe or critical disease. Patients with severe COVID-19 commonly present with viral pneumonia that may progress to life-threatening acute respiratory distress syndrome (ARDS). Patients with COVID-19 are also predisposed to venous and arterial thromboses that are associated with a poorer prognosis. The present study identified the emergence of a low-density inflammatory neutrophil (LDN) population expressing intermediate levels of CD16 (CD16Int) in patients with COVID-19. These cells demonstrated proinflammatory gene signatures, activated platelets, spontaneously formed neutrophil extracellular traps, and enhanced phagocytic capacity and cytokine production. Strikingly, CD16Int neutrophils were also the major immune cells within the bronchoalveolar lavage fluid, exhibiting increased CXCR3 but loss of CD44 and CD38 expression. The percentage of circulating CD16Int LDNs was associated with D-dimer, ferritin, and systemic IL-6 and TNF-α levels and changed over time with altered disease status. Our data suggest that the CD16Int LDN subset contributes to COVID-19-associated coagulopathy, systemic inflammation, and ARDS. The frequency of that LDN subset in the circulation could serve as an adjunct clinical marker to monitor disease status and progression.


Subject(s)
Blood Coagulation Disorders/blood , Blood Coagulation Disorders/etiology , COVID-19/blood , COVID-19/complications , Neutrophils/immunology , SARS-CoV-2 , Adult , Aged , Aged, 80 and over , Biomarkers/blood , Blood Coagulation Disorders/immunology , COVID-19/immunology , Cytokines/blood , Female , GPI-Linked Proteins/blood , Hospitalization , Humans , Inflammation Mediators/blood , Male , Middle Aged , Neutrophils/classification , Pandemics , Phagocytosis , Platelet Activation , Receptors, IgG/blood , Respiratory Distress Syndrome/blood , Respiratory Distress Syndrome/etiology , Respiratory Distress Syndrome/immunology , Severity of Illness Index
20.
Proc Natl Acad Sci U S A ; 118(19)2021 05 11.
Article in English | MEDLINE | ID: covidwho-1196910

ABSTRACT

Backtracking, the reverse motion of the transcriptase enzyme on the nucleic acid template, is a universal regulatory feature of transcription in cellular organisms but its role in viruses is not established. Here we present evidence that backtracking extends into the viral realm, where backtracking by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) may aid viral transcription and replication. Structures of SARS-CoV-2 RdRp bound to the essential nsp13 helicase and RNA suggested the helicase facilitates backtracking. We use cryo-electron microscopy, RNA-protein cross-linking, and unbiased molecular dynamics simulations to characterize SARS-CoV-2 RdRp backtracking. The results establish that the single-stranded 3' segment of the product RNA generated by backtracking extrudes through the RdRp nucleoside triphosphate (NTP) entry tunnel, that a mismatched nucleotide at the product RNA 3' end frays and enters the NTP entry tunnel to initiate backtracking, and that nsp13 stimulates RdRp backtracking. Backtracking may aid proofreading, a crucial process for SARS-CoV-2 resistance against antivirals.


Subject(s)
COVID-19/virology , SARS-CoV-2/physiology , Virus Replication/genetics , Adenosine Monophosphate/pharmacology , Antiviral Agents/pharmacology , COVID-19/genetics , COVID-19/metabolism , Coronavirus RNA-Dependent RNA Polymerase/metabolism , Cryoelectron Microscopy/methods , DNA Helicases/metabolism , Genome, Viral , Humans , Molecular Dynamics Simulation , RNA Helicases/metabolism , RNA, Viral/genetics , RNA, Viral/metabolism , RNA-Dependent RNA Polymerase/metabolism , RNA-Dependent RNA Polymerase/physiology , SARS-CoV-2/drug effects , SARS-CoV-2/genetics , Viral Nonstructural Proteins/genetics
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