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1.
BMJ Open ; 12(7): e057281, 2022 07 13.
Article in English | MEDLINE | ID: covidwho-1932731

ABSTRACT

OBJECTIVE: By using health code blockchain, cities can maximise the use of personal information while maximising the protection of personal privacy in the monitoring and evaluation of the effectiveness of listed vaccines. DESIGN: This study constructs an urban COVID-19 listed vaccine effectiveness (VE) monitoring, evaluation and application system based on the health code blockchain. This study uses this system and statistical simulation to analyse three urban application scenarios, namely evaluating the vaccination rate (VR) and determining the optimal vaccination strategy, evaluating herd immunity and monitoring the VE on variant. MAIN OUTCOME MEASURES: The primary outcomes first establish an urban COVID-19 listed VE monitoring, evaluation and application system by using the health code blockchain, combined with the dynamic monitoring model of VE, the evaluation index system of VE and the monitoring and evaluation system of personal privacy information use, and then three measures are analysed in urban simulation: one is to take the index reflecting urban population mobility as the weight to calculate the comprehensive VR, the second is to calculate the comprehensive basic reproduction number (R) in the presence of asymptomatic persons, the third is to compare the difference between the observed effectiveness and the true effectiveness of listed vaccines under virus variation. RESULTS: Combining this system and simulation, this study finds: (1) The comprehensive VR, which is weighted to reflect urban population mobility, is more accurate than the simple VR which does not take into account urban population mobility. Based on population mobility, the algorithm principle of urban optimal vaccination strategy is given. In the simulation of urban listed vaccination involving six regions, programmes 1 and 5 have the best protective effect among the eight vaccination programmes, and the optimal vaccination order is 3-5-2-4-6-1. (2) In the presence of asymptomatic conditions, the basic reproduction number, namely R0*(1-VR*VE), does not accurately reflect the effect of herd immunity, but the comprehensive basic reproduction number (R) should be used. The R is directly proportional to the proportion of asymptomatic people (aw) and the duration of the incubation period (ip), and inversely proportional to the VR, the VE and the number of days transmitted in the ip (k). In the simulation analysis, when symptomatic R0=3, even with aw=0.2, the R decreases to nearly 1 until the VR reaches 95%. When aw=0.8, even when the entire population is vaccinated, namely VR=1, the R is 1.688, and still significantly greater than 1. If the R is to be reduced to 1, the VE needs to be increased to 0.87. (3) This system can more comprehensively and accurately grasp the impact of the variant virus on urban VE. The traditional epidemiological investigation can lose the contacts of infected persons, which leads to the deviation between the observed effectiveness and the true effectiveness. Virus variation aggravates the loss, and then increases the deviation. Simulation case 1 assumes the unvaccinated rate of 0.8, the ongoing VR of 0.1, the completed VR of 0.1 and an average infection rate of 2% for the variant virus. If a vaccine is more than 90% effectiveness against the premutant virus, but only 80% effectiveness against the mutant virus, and because 80% of the unvaccinated people who are not infected are not observed, the observed effectiveness of the vaccine is 91.76%, it will lead to the wrong judgement that the VE against the variant virus is not decreased. Simulation case 2 assumes the unvaccinated rate of 0.8, the ongoing VR of 0.1, the completed VR of 0.1 and an average infection rate of 5% for the variant virus. Simulation finds that the higher the proportion of unvaccinated infected people who are not observed, the lower the estimate of observed effectiveness; and the lower the true effectiveness, the larger the gap between observed effectiveness and true effectiveness. Simulation case 3 assumes the unvaccinated rate of 0.2, the ongoing VR of 0.2, the completed VR of 0.6 and an average infection rate of 2% for the variant virus. Simulation finds that the higher the proportion of unobserved completed vaccination patients who are not infected, the lower the estimate of observed effectiveness; and the lower the true effectiveness, the larger the gap between observed effectiveness and true effectiveness. Simulation case 4 assumes the unvaccinated rate of 0.2, the ongoing VR of 0.2, the completed VR of 0.6 and an average infection rate of 5% for the variant virus. If a vaccine is more than 90% effectiveness against the premutant virus, but only 80% effectiveness against the mutant virus, and because 80% of the infected people with complete vaccination are not observed, the observed effectiveness of the vaccine is 91.95%, similar to case 1, it will lead to the wrong judgement that the VE against the variant virus is not decreased. CONCLUSION: Compared with traditional epidemiological investigation, this system can meet the challenges of accelerating virus variation and a large number of asymptomatic people, dynamically monitor and accurately evaluate the effectiveness of listed vaccines and maximise personal privacy without locking down the relevant area or city. This system established in this study could serve as a universal template for monitoring and evaluating the effectiveness of COVID-19 listed vaccines in cities around the world. If this system can be promoted globally, it will promote countries to strengthen unity and cooperation and enhance the global ability to respond to COVID-19.


Subject(s)
Blockchain , COVID-19 , Vaccines , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Humans , Vaccination
2.
Chem Commun (Camb) ; 58(54): 7466-7482, 2022 Jul 05.
Article in English | MEDLINE | ID: covidwho-1900677

ABSTRACT

The emerging COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed over six million lives globally to date. Despite the availability of vaccines, the pandemic still cannot be fully controlled owing to rapid mutation of the virus that renders enhanced transmissibility and antibody evasion. This is thus an unmet need to develop safe and effective therapeutic options for COVID-19, in particular, remedies that can be used at home. Considering the great success of multi-targeted cocktail therapy for the treatment of viral infections, metal-based drugs might represent a unique and new source of antivirals that resemble a cocktail therapy in terms of their mode of actions. In this review, we first summarize the role that metal ions played in SARS-CoV-2 viral replication and pathogenesis, then highlight the chemistry of metal-based strategies in the fight against SARS-CoV-2 infection, including both metal displacement and chelation based approaches. Finally, we outline a perspective and direction on how to design and develop metal-based antivirals for the fight against the current or future coronavirus pandemic.


Subject(s)
COVID-19 , Vaccines , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , COVID-19/drug therapy , Humans , Pandemics/prevention & control , SARS-CoV-2
3.
Chemical science ; 13(11):3216-3226, 2022.
Article in English | EuropePMC | ID: covidwho-1782305

ABSTRACT

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases. A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.

4.
Chem Sci ; 13(11): 3216-3226, 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1764224

ABSTRACT

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322232

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident. Methods: : We proposed a temporal deep learning method, based on a time-aware long short-term memory (T-LSTM) neural network and used an online open dataset, including blood samples of 485 patients from Wuhan, China, to train the model. Our method can grasp the dynamic relations in irregularly sampled time series, which is ignored by existing works. Specifically, our method predicted the outcome of COVID-19 patients by considering both the biomarkers and the irregular time intervals. Then, we used the patient representations, extracted from T-LSTM units, to subtype the patient stages and describe the disease progression of COVID-19. Results: : Using our method, the accuracy of the outcome of prediction results was more than 90% at 12 days and 98%, 95% and 93% at 3, 6, and 9 days, respectively. Most importantly, we found 4 stages of COVID-19 progression with different patient statuses and mortality risks. We ranked 40 biomarkers related to disease and gave the reference values of them for each stage. Top 5 is Lymph, LDH, hs-CRP, Indirect Bilirubin, Creatinine. Besides, we have found 3 complications - myocardial injury, liver function injury and renal function injury. Predicting which of the 4 stages the patient is currently in can help doctors better assess and cure the patient. Conclusions: : To combat the COVID-19 epidemic, this paper aims to help clinicians better assess and treat infected patients, provide relevant researchers with potential disease progression patterns, and enable more effective use of medical resources. Our method predicted patient outcomes with high accuracy and identified a four-stage disease progression. We hope that the obtained results and patterns will aid in fighting the disease.

6.
Chem Sci ; 13(8): 2238-2248, 2022 Feb 23.
Article in English | MEDLINE | ID: covidwho-1585745

ABSTRACT

The emergence of SARS-CoV-2 variants of concern compromises vaccine efficacy and emphasizes the need for further development of anti-SARS-CoV-2 therapeutics, in particular orally administered take-home therapies. Cocktail therapy has shown great promise in the treatment of viral infection. Herein, we reported the potent preclinical anti-SARS-CoV-2 efficacy of a cocktail therapy consisting of clinically used drugs, e.g. colloidal bismuth subcitrate (CBS) or bismuth subsalicylate (BSS), and N-acetyl-l-cysteine (NAC). Oral administration of the cocktail reduced viral loads in the lung and ameliorated virus-induced pneumonia in a hamster infection model. The mechanistic studies showed that NAC prevented the hydrolysis of bismuth drugs at gastric pH via the formation of the stable component [Bi(NAC)3], and optimized the pharmacokinetics profile of CBS in vivo. Combination of bismuth drugs with NAC suppressed the replication of a panel of medically important coronaviruses including Middle East respiratory syndrome-related coronavirus (MERS-CoV), Human coronavirus 229E (HCoV-229E) and SARS-CoV-2 Alpha variant (B.1.1.7) with broad-spectrum inhibitory activities towards key viral cysteine enzymes/proteases including papain-like protease (PLpro), main protease (Mpro), helicase (Hel) and angiotensin-converting enzyme 2 (ACE2). Importantly, our study offered a potential at-home treatment for combating SARS-CoV-2 and future coronavirus infections.

7.
International Journal of Environmental Research and Public Health ; 17(11), 2020.
Article in English | CAB Abstracts | ID: covidwho-1409566

ABSTRACT

An outbreak in Wuhan, China in late 2019 of a highly infectious new coronary pneumonia (COVID-19) led to the imposition of countrywide confinement measures from January to March 2020. This is a longitudinal study on changes in the mental health status of a college population before and after their COVID-19 confinement for the first two weeks, focusing on states of psychological distress, depression, anxiety and affectivity. The influence of possible stressors on their mental health were investigated, including inadequate supplies and fears of infection. Five hundred and fifty-five undergraduate students were recruited from Hebei Agricultural University in Baoding, China. The participants completed two online surveys-on anxiety and depression, and on positive and negative affect. One survey was conducted before the confinement and the other was conducted 15-17 days after the start of the confinement. Increases in negative affect and symptoms of anxiety and depression (p-values < 0.001) were observed after 2 weeks of confinement. Inadequate supplies of hand sanitizers, a higher year of study, and higher scores on anxiety and depression were common predictors of increased negative affect, anxiety, and depression across the confinement period. The results suggest that healthcare policymakers should carefully consider the appropriate confinement duration, and ensure adequate supplies of basic infection-control materials.

8.
Air Qual Atmos Health ; 15(1): 47-58, 2022.
Article in English | MEDLINE | ID: covidwho-1371386

ABSTRACT

To better understand the effects of COVID-19 on air quality in Taiyuan, hourly in situ measurements of PM2.5(particulate matter with an aerodynamic diameter less than 2.5 mm) and chemical components (water-soluble ions, organic carbon (OC), elemental carbon (EC), and trace elements) were conducted before (P1: 1 January-23 January 2020) and during (P2: 24 January-15 February 2020) the coronavirus disease 2019 (COVID-19) outbreak. The average concentrations of PM2.5 dropped from 122.0 µg/m3 during P1 to 83.3 µg/m3 during P2. Compared with P1, except for fireworks burning-related chemical components (K+, Mg2+, K, Cu, Ba), the concentrations of other chemical components of PM2.5 decreased by14.9-69.8%. Although the large decrease of some emission sources, fireworks burning still resulted in the occurrence of pollution events during P2. The analysis results of positive matrix factorization model suggested that six PM2.5 sources changed significantly before and during the outbreak of the epidemic. The contributions of vehicle emission, industrial process, and dust to PM2.5 decreased from 23.1%, 3.5%, and 4.0% during P1 to 7.7%, 3.4%, and 2.3% during P2, respectively, whereas the contributions of secondary inorganic aerosol, fireworks burning, and coal combustion to PM2.5 increased from 62.0%, 1.8%, and 5.5% to 71.5%, 9.0%, and 6.2%, respectively. The source apportionment results were also affected by air mass transport. The largest reductions of vehicle emission, industrial process, and dust source were distinctly seen for the air masses from northwest. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01082-y.

9.
BMC Med Inform Decis Mak ; 21(1): 45, 2021 02 08.
Article in English | MEDLINE | ID: covidwho-1069558

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident. METHODS: We proposed a temporal deep learning method, based on a time-aware long short-term memory (T-LSTM) neural network and used an online open dataset, including blood samples of 485 patients from Wuhan, China, to train the model. Our method can grasp the dynamic relations in irregularly sampled time series, which is ignored by existing works. Specifically, our method predicted the outcome of COVID-19 patients by considering both the biomarkers and the irregular time intervals. Then, we used the patient representations, extracted from T-LSTM units, to subtype the patient stages and describe the disease progression of COVID-19. RESULTS: Using our method, the accuracy of the outcome of prediction results was more than 90% at 12 days and 98, 95 and 93% at 3, 6, and 9 days, respectively. Most importantly, we found 4 stages of COVID-19 progression with different patient statuses and mortality risks. We ranked 40 biomarkers related to disease and gave the reference values of them for each stage. Top 5 is Lymph, LDH, hs-CRP, Indirect Bilirubin, Creatinine. Besides, we have found 3 complications - myocardial injury, liver function injury and renal function injury. Predicting which of the 4 stages the patient is currently in can help doctors better assess and cure the patient. CONCLUSIONS: To combat the COVID-19 epidemic, this paper aims to help clinicians better assess and treat infected patients, provide relevant researchers with potential disease progression patterns, and enable more effective use of medical resources. Our method predicted patient outcomes with high accuracy and identified a four-stage disease progression. We hope that the obtained results and patterns will aid in fighting the disease.


Subject(s)
COVID-19 , Deep Learning , Disease Progression , COVID-19/diagnosis , COVID-19/pathology , China , Forecasting , Humans , SARS-CoV-2
10.
SAGE Open Med ; 9: 2050312121989504, 2021.
Article in English | MEDLINE | ID: covidwho-1069536

ABSTRACT

In December 2019, the outbreak of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infection that started in Wuhan, Hubei Province, China, has spread to all world. Based on the accumulated data and knowledge on the coronavirus infection and immunology characteristics, this review would hope to give some hints on human immune response to SARS-CoV-2 infection in cancer patients. This insight may help in designing the appropriate immune intervention for treatment and the prophylactic/therapeutic methods against cancer under current coronavirus from immunopathology characteristics of SARS-CoV-2 and cancer entwisted with it. We should achieve accurate diagnosis and treatment for cancer patients through advantages of multidisciplinary diagnosis and treatment team. It is believed that we will eventually overcome the epidemic and win in the future.

11.
Chin J Integr Med ; 27(4): 245-251, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1061046

ABSTRACT

OBJECTIVE: To observe the changes of symptoms, Chinese medicine (CM) syndrome, and lung inflammation absorption during convalescence in patients with coronavirus disease 2019 (COVID-19) who had not totally recovered after hospital discharge and whether CM could promote the improvement process. METHODS: This study was designed as a prospective cohort and nested case-control study. A total of 96 eligible patients with COVID-19 in convalescence were enrolled from Beijing Youan Hospital and Beijing Huimin Hospital and followed up from the hospital discharged day. Patients were divided into the CM (64 cases) and the control groups (32 cases) based on the treatment with or without CM and followed up at 14, 28, 56, and 84 days after discharge. In the CM group, patients received the 28-day CM treatment according to two types of CM syndrome. Improvements in clinical symptoms, CM syndrome, and absorption of lung inflammation were observed. RESULTS: All the 96 patients completed the 84-day follow-up from January 21 to March 28, 2020. By the 84th day of follow-up, respiratory symptoms were less than 5%. There was no significant difference in the improvement rates of symptoms, including fatigue, sputum, cough, dry throat, thirst, and upset, between the two groups (P>0.05). Totally 82 patients (85.42%) showed complete lung inflammation absorption at the 84-day follow-up. On day 14, the CM group had a significantly higher absorption rate than the control group (P<0.05) and the relative risk of absorption for CM vs. control group was 3.029 (95% confidence interval: 1.026-8.940). The proportions of CM syndrome types changed with time prolonging: the proportion of the pathogen residue syndrome gradually decreased, and the proportion of both qi and yin deficiency syndrome gradually increased. CONCLUSIONS: Patients with COVID-19 in convalescence had symptoms and lung inflammation after hospital discharge and recovered with time prolonging. CM could improve lung inflammation for early recovery. The types of CM syndrome can be transformed with time prolonging. (Registration No. ChiCTR2000029430).


Subject(s)
COVID-19/drug therapy , Medicine, Chinese Traditional , Pneumonia/drug therapy , SARS-CoV-2 , Adult , Aged , Case-Control Studies , Convalescence , Female , Follow-Up Studies , Humans , Male , Middle Aged , Patient Discharge , Pneumonia/diagnostic imaging , Prospective Studies
12.
EBioMedicine ; 62: 103125, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-938894

ABSTRACT

BACKGROUND: The pharmacokinetics and appropriate dose regimens of favipiravir are unknown in hospitalized influenza patients; such data are also needed to determine dosage selection for favipiravir trials in COVID-19. METHODS: In this dose-escalating study, favipiravir pharmacokinetics and tolerability were assessed in critically ill influenza patients. Participants received one of two dosing regimens; Japan licensed dose (1600 mg BID on day 1 and 600 mg BID on the following days) and the higher dose (1800 mg/800 mg BID) trialed in uncomplicated influenza. The primary pharmacokinetic endpoint was the proportion of patients with a minimum observed plasma trough concentration (Ctrough) ≥20 mg/L at all measured time points after the second dose. RESULTS: Sixteen patients were enrolled into the low dose group and 19 patients into the high dose group of the study. Favipiravir Ctrough decreased significantly over time in both groups (p <0.01). Relative to day 2 (48 hrs), concentrations were 91.7% and 90.3% lower in the 1600/600 mg group and 79.3% and 89.5% lower in the 1800/800 mg group at day 7 and 10, respectively. In contrast, oseltamivir concentrations did not change significantly over time. A 2-compartment disposition model with first-order absorption and elimination described the observed favipiravir concentration-time data well. Modeling demonstrated that less than 50% of patients achieved Ctrough ≥20 mg/L for >80% of the duration of treatment of the two dose regimens evaluated (18.8% and 42.1% of patients for low and high dose regimen, respectively). Increasing the favipravir dosage predicted a higher proportion of patients reaching this threshold of 20 mg/L, suggesting that dosing regimens of ≥3600/2600 mg might be required for adequate concentrations. The two dosing regimens were well-tolerated in critical ill patients with influenza. CONCLUSION: The two dosing regimens proposed for uncomplicated influenza did not achieve our pre-defined treatment threshold.


Subject(s)
Amides , Influenza, Human/drug therapy , Oseltamivir , Pyrazines , Aged , Amides/administration & dosage , Amides/pharmacokinetics , Drug Therapy, Combination , Female , Humans , Influenza, Human/blood , Male , Middle Aged , Oseltamivir/administration & dosage , Oseltamivir/pharmacokinetics , Pyrazines/administration & dosage , Pyrazines/pharmacokinetics , Severity of Illness Index
13.
Nat Microbiol ; 5(11): 1439-1448, 2020 11.
Article in English | MEDLINE | ID: covidwho-841871

ABSTRACT

SARS-CoV-2 is causing a pandemic of COVID-19, with high infectivity and significant mortality1. Currently, therapeutic options for COVID-19 are limited. Historically, metal compounds have found use as antimicrobial agents, but their antiviral activities have rarely been explored. Here, we test a set of metallodrugs and related compounds, and identify ranitidine bismuth citrate, a commonly used drug for the treatment of Helicobacter pylori infection, as a potent anti-SARS-CoV-2 agent, both in vitro and in vivo. Ranitidine bismuth citrate exhibited low cytotoxicity and protected SARS-CoV-2-infected cells with a high selectivity index of 975. Importantly, ranitidine bismuth citrate suppressed SARS-CoV-2 replication, leading to decreased viral loads in both upper and lower respiratory tracts, and relieved virus-associated pneumonia in a golden Syrian hamster model. In vitro studies showed that ranitidine bismuth citrate and its related compounds exhibited inhibition towards both the ATPase (IC50 = 0.69 µM) and DNA-unwinding (IC50 = 0.70 µM) activities of the SARS-CoV-2 helicase via an irreversible displacement of zinc(II) ions from the enzyme by bismuth(III) ions. Our findings highlight viral helicase as a druggable target and the clinical potential of bismuth(III) drugs or other metallodrugs for the treatment of SARS-CoV-2 infection.


Subject(s)
Antiviral Agents/pharmacology , Betacoronavirus/drug effects , Bismuth/pharmacology , Coronavirus Infections/virology , Pneumonia, Viral/virology , Ranitidine/analogs & derivatives , Virus Replication/drug effects , Animals , Betacoronavirus/physiology , COVID-19 , Chemokines/metabolism , Chlorocebus aethiops , Coronavirus Infections/drug therapy , Cytokines/metabolism , Disease Models, Animal , HEK293 Cells , Humans , Lung/pathology , Lung/virology , Mesocricetus , Pandemics , Pneumonia, Viral/drug therapy , RNA Helicases/metabolism , Ranitidine/pharmacology , SARS-CoV-2 , Vero Cells , Viral Load
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