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1.
Redox Biol ; 48: 102199, 2021 Nov 26.
Article in English | MEDLINE | ID: covidwho-1537013

ABSTRACT

3CLpro is a key proteinase for SARS-CoV-2 replication and serves as an important target for antiviral drug development. However, how its activity is regulated intracellularly is still obscure. In this study, we developed a 3CLpro protease activity reporter system to examine the impact of various factors, including nutrient supplements, ions, pHs, or oxidative stress inducers, on 3CLpro protease activity. We found that oxidative stress could increase the overall activity of 3CLpro. Not altering the expression, oxidative stress decreased the solubility of 3CLpro in the lysis buffer containing 1% Triton-X-100. The Triton-X-100-insoluble 3CLpro was correlated with aggregates' formation and responsible for the increased enzymatic activity. The disulfide bonds formed between Cys85 sites of 3CLpro protomers account for the insolubility and the aggregation of 3CLpro. Besides being regulated by oxidative stress, 3CLpro impaired the cellular antioxidant capacity by regulating the cleavage of GPx1 at its N-terminus. This cleavage could further elevate the 3CLpro-proximate oxidative activity, favor aggregation and activation of 3CLpro, and thus lead to a positive feedback loop. In summary, we reported that oxidative stress transforms 3CLpro into a detergent-insoluble form that is more enzymatically active, leading to increased viral replication/transcription. Our study provided mechanistic evidence that suggests the therapeutic potential of antioxidants in the clinical treatment of COVID-19 patients.

3.
Non-conventional in English | [Unspecified Source], Grey literature | ID: grc-750455

ABSTRACT

BACKGROUND AND OBJECTIVES: Public health interventions were associated with reduction in coronavirus disease 2019 (COVID-19) transmission in China, but their impacts on COVID-19 epidemiology in other countries are unclear. We examined the associations of stay-at-home order (SAHO) and face-masking recommendation with epidemiology of laboratory-confirmed COVID-19 in the United States. METHODS: In this quasi-experimental study, we modeled the temporal trends in daily new cases and deaths of COVID-19, and COVID-19 time-varying reproduction numbers (Rt) in the United States between March 1 and April 20, 2020, and conducted simulation studies. RESULTS: The number and proportion of U.S. residents under SAHO increased between March 19 and April 7, and plateaued at 29,0829,980 and 88.6%, respectively. Trends in COVID-19 daily cases and Rt reduced after March 23 (P<0.001) and further reduced on April 3 (P<0.001), which was associated with implementation of SAHO by 10 states on March 23, and face-masking recommendation on April 3, respectively. The estimates of Rt eventually fell below/around 1.0 on April 13. Similar turning points were identified in the trends of daily deaths with a lag time. Early implementation and early-removal of SAHO would be associated with significantly reduced and increased daily new cases and deaths, respectively.

4.
Sustain Cities Soc ; 75: 103327, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1386610

ABSTRACT

Most of the COVID-19 cases in Singapore have primarily come from foreign worker dormitories. This people group is especially vulnerable partly because of behavioural habits, but the built environment they live in also plays a significant role. These dormitories are typically densely populated, so the living conditions are cramped. The short lease given to most dormitories also means the design does not typically focus on environmental performance, like good natural ventilation. This paper seeks to understand how these dormitories' design affects natural ventilation and, subsequently, the spread of the COVID-19 particles by looking at two existing worker dorms in Singapore. Findings show that some rooms are poorly orientated against the prevailing wind directions, so there is dominant stagnant air in these rooms, leading to respiratory droplets' long residence times. These particles can hover in the air for 10 min and more. Interventions like increased bed distance and removing upper deck beds only showed limited ventilation improvements in some rooms. Comparatively, internal wind scoops' strategic placement was more effective at directing wind towards more stagnant zones. Large canyon aspect ratios were also effective at removing particles from higher elevations.

6.
Infect Dis Ther ; 10(4): 1907-1931, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1321900

ABSTRACT

In the context of the coronavirus disease 2019 (COVID-19) pandemic, the global healthcare community has raced to find effective therapeutic agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To date, dexamethasone is the first and an important therapeutic to significantly reduce the risk of death in COVID-19 patients with severe disease. Due to powerful anti-inflammatory and immunosuppressive effects, dexamethasone could attenuate SARS-CoV-2-induced uncontrolled cytokine storm, severe acute respiratory distress syndrome and lung injury. Nevertheless, dexamethasone treatment is a double-edged sword, as numerous studies have revealed that it has significant adverse impacts later in life. In this article, we reviewed the literature regarding the adverse effects of dexamethasone administration on different organ systems as well as related disease pathogenesis in an attempt to clarify the potential harms that may arise in COVID-19 patients receiving dexamethasone treatment. Overall, taking the threat of COVID-19 pandemic into account, we think it is necessary to apply dexamethasone as a pharmaceutical therapy in critical patients. However, its adverse side effects cannot be ignored. Our review will help medical professionals in the prognosis and follow-up of patients treated with dexamethasone. In addition, given that a considerable amount of uncertainty, confusion and even controversy still exist, further studies and more clinical trials are urgently needed to improve our understanding of the parameters and the effects of dexamethasone on patients with SARS-CoV-2 infection.

7.
J Clin Transl Sci ; 5(1): e124, 2021.
Article in English | MEDLINE | ID: covidwho-1297280

ABSTRACT

Introduction: During the COVID-19 pandemic, some K-12 schools resumed in-person classes with varying degrees of mitigation plans in the fall 2020. Physical distancing and face coverings can minimize SARS-CoV-2 spread, the virus that causes COVID-19. However, no research has focused on adherence to mitigation strategies during school days. Thus, we sought to develop a systematic observation protocol to capture COVID-19 mitigation strategy adherence in school environments: The Systematic Observation of COVID-19 Mitigation (SOCOM). Methods: We extended previously validated and internationally used tools to develop the SOCOM training and implementation protocols to assess physical-distancing and face-covering behaviors. SOCOM was tested in diverse indoor and outdoor settings (classrooms, lunchrooms, physical education [PE], and recess) among diverse schools (elementary, secondary, and special needs). Results: For the unique metrics of physical-distancing and face-covering behaviors, areas with less activity and a maximum of 10-15 students were more favorable for accurately capturing data. Overall proportion of agreement was high for physical distancing (90.9%), face covering (88.6%), activity type (89.2%), and physical activity level (87.9%). Agreement was lowest during active recess, PE, and observation areas with ≥20 students. Conclusions: Millions of children throughout the USA are likely to return to school in the months ahead. SOCOM is a relatively inexpensive research tool that can be implemented by schools to determine mitigation strategy adherence and to assess protocols that allow students return to school safely and slow the spread of COVID-19.

9.
Int J Biol Sci ; 17(8): 1925-1939, 2021.
Article in English | MEDLINE | ID: covidwho-1266906

ABSTRACT

Background: Angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) allow entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into host cells and play essential roles in cancer therapy. However, the functions of ACE2 and TMPRSS2 in kidney cancer remain unclear, especially as kidneys are targets for SARS-CoV-2 infection. Methods: UCSC Xena project, the Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) databases (GSE30589 and GSE59185) were searched for gene expression in human tissues, gene expression data, and clinical information. Several bioinformatics methods were utilized to analyze the correlation between ACE2 and TMPRSS2 with respect to the prognosis of kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). Results: ACE2 expression was significantly upregulated in tumor tissue, while its downregulation was associated with low survival in KIRC and KIRP patients. TMPRSS2 was downregulated in KIRC and KIRP, and its expression was not correlated with patient survival. According to clinical risk factor-based prediction models, ACE2 exhibits predictive accuracy for kidney cancer prognosis and is correlated with metabolism and immune infiltration. In an animal model, ACE2 expression was remarkably downregulated in SARS-CoV-2-infected cells compared to in the control. Conclusion: ACE2 expression is highly correlated with various metabolic pathways and is involved in immune infiltration.it plays a crucial role than TMPRSS2 in diagnosing and prognosis of kidney cancer patients. The overlap in ACE2 expression between kidney cancer and SARS-CoV-2 infection suggests that patients with KIRC or KIRP are at high risk of developing serious symptoms.


Subject(s)
Angiotensin-Converting Enzyme 2/biosynthesis , COVID-19/complications , Carcinoma, Renal Cell/complications , Kidney Neoplasms/complications , Receptors, Virus/biosynthesis , SARS-CoV-2 , Adult , Aged , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/physiology , Animals , Carcinoma, Renal Cell/immunology , Carcinoma, Renal Cell/metabolism , Carcinoma, Renal Cell/mortality , Chlorocebus aethiops , Down-Regulation , Drug Resistance, Neoplasm , Female , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Humans , Kaplan-Meier Estimate , Kidney Neoplasms/immunology , Kidney Neoplasms/metabolism , Kidney Neoplasms/mortality , Lymphocytes, Tumor-Infiltrating/immunology , Male , Middle Aged , Models, Animal , Neoplasm Proteins/biosynthesis , Neoplasm Proteins/genetics , Organ Specificity , Prognosis , Proportional Hazards Models , Receptors, Virus/genetics , Renin-Angiotensin System/physiology , Serine Endopeptidases/biosynthesis , Serine Endopeptidases/genetics , Serine Endopeptidases/physiology , Tissue Array Analysis , Vero Cells
10.
J Med Internet Res ; 23(4): e26994, 2021 04 16.
Article in English | MEDLINE | ID: covidwho-1256255

ABSTRACT

BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.


Subject(s)
COVID-19/psychology , Mental Health Services/statistics & numerical data , Mental Health , Telemedicine/statistics & numerical data , Adult , COVID-19/epidemiology , Female , Humans , Male , Mental Disorders/therapy , Pandemics , SARS-CoV-2/isolation & purification , Surveys and Questionnaires , Technology , United States/epidemiology
11.
J Am Med Inform Assoc ; 28(8): 1765-1776, 2021 07 30.
Article in English | MEDLINE | ID: covidwho-1246728

ABSTRACT

OBJECTIVE: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online. MATERIALS AND METHODS: We developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data. RESULTS: Our public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems. DISCUSSION AND CONCLUSIONS: We present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems.


Subject(s)
Algorithms , COVID-19 , Computer Communication Networks , Confidentiality , Electronic Health Records , Information Storage and Retrieval/methods , Natural Language Processing , Common Data Elements , Female , Humans , Logistic Models , Male , Registries
12.
Explor Res Hypothesis Med ; : 1-10, 2020 Jul 08.
Article in English | MEDLINE | ID: covidwho-1207927

ABSTRACT

Background and objectives: Public health interventions have reduced coronavirus disease 2019 (COVID-19) transmission in several countries, but their impacts on COVID-19 epidemics in the USA are unclear. We examined associations of stay-at-home order (SAHO) and face-masking recommendation with COVID-19 epidemics in the USA. Methods: In this quasi-experimental interrupted time-series study, we modeled temporal trends in daily new cases and deaths of laboratory-confirmed COVID-19 cases, and COVID-19 time-varying reproduction numbers in the USA between March 1 and April 20, 2020. In addition, we conducted simulation analyses. Results: The number of residents under SAHO increased since March 19 and plateaued at 290,829,980 (88.6% of the U.S. population) on April 7. Trends in COVID-19 time-varying reproduction numbers peaked on March 23, further reduced on April 3, and fell below/around 1.0 on April 13. Early-implementation and early-lift of SAHO would reduce and increase COVID-19 epidemics, respectively. Multivariable piecewise log-linear regression revealed the states' neighboring relationship with New York was linked to COVID-19 daily new cases and deaths. There were two turning points in daily new-case trend, being March 28 (slope-changes = -0.09) and April 3 (slope-changes = -0.09), which appeared to be associated with implementation of SAHO on March 28 (affecting 48.5% of the US population in 22 states and District of Columbia), and face-masking recommendation on April 3, respectively. There were also two turning points in daily new-death trend, being April 9 (slope-changes = -0.06) and April 19 (slope-changes = -0.90). Conclusions: We identified two turning points of COVID-19 daily new cases or deaths in the USA, which seem to be linked to implementation of SAHO and the Center for Disease Control's face-masking recommendation.

13.
J Med Internet Res ; 23(4): e26994, 2021 04 16.
Article in English | MEDLINE | ID: covidwho-1171242

ABSTRACT

BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.


Subject(s)
COVID-19/psychology , Mental Health Services/statistics & numerical data , Mental Health , Telemedicine/statistics & numerical data , Adult , COVID-19/epidemiology , Female , Humans , Male , Mental Disorders/therapy , Pandemics , SARS-CoV-2/isolation & purification , Surveys and Questionnaires , Technology , United States/epidemiology
14.
J Am Med Inform Assoc ; 28(7): 1564-1573, 2021 07 14.
Article in English | MEDLINE | ID: covidwho-1123294

ABSTRACT

OBJECTIVE: Facial masks are an essential personal protective measure to fight the COVID-19 (coronavirus disease) pandemic. However, the mask adoption rate in the United States is still less than optimal. This study aims to understand the beliefs held by individuals who oppose the use of facial masks, and the evidence that they use to support these beliefs, to inform the development of targeted public health communication strategies. MATERIALS AND METHODS: We analyzed a total of 771 268 U.S.-based tweets between January to October 2020. We developed machine learning classifiers to identify and categorize relevant tweets, followed by a qualitative content analysis of a subset of the tweets to understand the rationale of those opposed mask wearing. RESULTS: We identified 267 152 tweets that contained personal opinions about wearing facial masks to prevent the spread of COVID-19. While the majority of the tweets supported mask wearing, the proportion of anti-mask tweets stayed constant at about a 10% level throughout the study period. Common reasons for opposition included physical discomfort and negative effects, lack of effectiveness, and being unnecessary or inappropriate for certain people or under certain circumstances. The opposing tweets were significantly less likely to cite external sources of information such as public health agencies' websites to support the arguments. CONCLUSIONS: Combining machine learning and qualitative content analysis is an effective strategy for identifying public attitudes toward mask wearing and the reasons for opposition. The results may inform better communication strategies to improve the public perception of wearing masks and, in particular, to specifically address common anti-mask beliefs.


Subject(s)
Attitude to Health , COVID-19/prevention & control , Machine Learning , Masks , Social Media , Humans , Public Opinion , United States
16.
Aging (Albany NY) ; 12(19): 18878-18888, 2020 Oct 08.
Article in English | MEDLINE | ID: covidwho-841406

ABSTRACT

In this retrospective study we assessed the efficacy and safety of tocilizumab in patients with critical or severe coronavirus disease 2019 (COVID-19). We enrolled 181 patients admitted to Huoshenshan Hospital (Wuhan, China) with confirmed COVID-19 between January 2020 and February 2020. Ninety-two patients were treated with tocilizumab, and 89 patients were treated conventionally. We analyzed the clinical manifestations, changes in CT scan images, and laboratory tests before and after tocilizumab treatment, and compared these results with the conventionally treated group. A significant reduction in the level of C-reactive protein was observed 1 week after tocilizumab administration. In some cases this meant the end of the IL-6-related cytokine storm. In addition, tocilizumab relieved fever, cough, and shortness of breath with no reported adverse drug reactions. These findings suggest tocilizumab improves clinical outcomes and is effective for treatment of patients with critical or severe COVID-19. However, future clinical trials are needed to better understand the impact of tocilizumab interference with IL-6 and provide a therapeutic strategy for treatment of COVID-19.

17.
medRxiv ; 2020 Sep 23.
Article in English | MEDLINE | ID: covidwho-808753

ABSTRACT

There is an urgent need to answer questions related to COVID-19's clinical course and associations with underlying conditions and health outcomes. Multi-center data are necessary to generate reliable answers, but centralizing data in a single repository is not always possible. Using a privacy-protecting strategy, we launched a public Questions & Answers web portal (https://covid19questions.org) with analyses of comorbidities, medications and laboratory tests using data from 202 hospitals (59,074 COVID-19 patients) in the USA and Germany. We find, for example, that 8.6% of hospitalizations in which the patient was not admitted to the ICU resulted in the patient returning to the hospital within seven days from discharge and that, when adjusted for age, mortality for hospitalized patients was not significantly different by gender or ethnicity.

19.
Viruses ; 12(9):1051, 2020.
Article | MDPI | ID: covidwho-783823

ABSTRACT

As evidence has mounted that virus-infected cells, such as cancer cells, negatively regulate the function of T-cells via immune checkpoints, it has become increasingly clear that viral infections similarly exploit immune checkpoints as an immune system escape mechanism. Although immune checkpoint therapy has been successfully used in cancer treatment, numerous studies have suggested that such therapy may also be highly relevant for treating viral infection, especially chronic viral infections. However, it has not yet been applied in this manner. Here, we reviewed recent findings regarding immune checkpoints in viral infections, including COVID-19, and discussed the role of immune checkpoints in different viral infections, as well as the potential for applying immune checkpoint blockades as antiviral therapy.

20.
Med Hypotheses ; 144: 110178, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-704009

ABSTRACT

The outbreak of coronavirus disease 2019 (COVID-19) has posed a severe threat to global health management system since it has been detected in the human body. This pandemic was prompted by severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) and rapidly developed into a public emergency with an alarming increase in cases and deaths. The increasing explorations to SARS-CoV-2 infection guide us to consider whether bone lesion is followed by this pathologic process. We especially focus on the underlying pathobiology that SARS-CoV-2 possibly mediated in bone remodeling and analyze the association of bone destruction with ACE2 in COVID-19 incidence, for preferable understanding the pathogenesis and providing necessary clinical management in orthopedics.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , Bone Diseases/complications , Bone and Bones/metabolism , COVID-19/metabolism , Animals , Antiviral Agents/therapeutic use , Bone Diseases/virology , Bone and Bones/pathology , COVID-19/complications , COVID-19/virology , Humans , Immune System , Mice , Models, Theoretical , Muscles/pathology , Orthopedics , SARS-CoV-2
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