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1.
Science of The Total Environment ; : 158350, 2022.
Article in English | ScienceDirect | ID: covidwho-2004490

ABSTRACT

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

2.
Sensors and Actuators B: Chemical ; : 132526, 2022.
Article in English | ScienceDirect | ID: covidwho-1984047

ABSTRACT

The early detection of biomarker proteins in clinical samples is of great significance for the diagnosis of diseases. However, it is still a challenge to detect low-concentration protein. Herein, a label-free aptamer-based amplification assay, termed the ATC-TA system, that allows fluorescence detection of very low numbers of protein without time-consuming washing steps and pre-treatment was developed. The target induces a conformational change in the allosteric aptasensor, triggers the target cycling and transcription amplification, and ultimately converts the input of the target protein into the output of the light-up aptamer (R-Pepper). It exhibits ultrahigh sensitivity with a detection limit of 5.62 fM at 37 ℃ and the accuracy is comparable to conventional ELISA. ATC-TA has potential application for the detection of endogenous PDGF-BB in serum samples to distinguish tumor mice from healthy mice at an early stage. It also successfully detects exogenous SARS-CoV-2 spike proteins in human serum. Therefore, this high-sensitive, universality, easy-to-operate and cost-effective biosensing platform holds great clinical application potential in early clinical diagnosis.

3.
Edge-of-Things in Personalized Healthcare Support Systems ; : 377-412, 2022.
Article in English | EuropePMC | ID: covidwho-1918828

ABSTRACT

The Internet of Things (IoT) is a technology built upon various physical objects equipped with different types of sensors, which are connected together using communication methods. These devices have been applied to several domains, especially healthcare. In addition to the numerous benefits that IoT has demonstrated in healthcare, this technology is being adopted for combating the recent COVID-19 pandemic. The key role of IoT in COVID-19 could be classified into five major tasks: Monitoring, Diagnosing, Tracing, Disinfecting, and Vaccinating. This chapter reviews the state-of-art applications of IoT based on these tasks in order to better mitigate this virus. Additionally, potential areas for applying IoT systems to fight against COVID-19 or even future pandemics will be demonstrated.

4.
Sci Total Environ ; 844: 157040, 2022 Jun 29.
Article in English | MEDLINE | ID: covidwho-1907760

ABSTRACT

Wastewater-based epidemiology (WBE) is useful in predicting temporal fluctuations of COVID-19 incidence in communities and providing early warnings of pending outbreaks. To investigate the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in communities, a 12-month study between September 1, 2020, and August 31, 2021, prior to the Omicron surge, was conducted. 407 untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) in southeastern Michigan. N1 and N2 genes of SARS-CoV-2 were quantified using RT-ddPCR. Daily confirmed COVID-19 cases for the City of Detroit, and Wayne, Macomb, Oakland counties between September 1, 2020, and October 4, 2021, were collected from a public data source. The total concentrations of N1 and N2 genes ranged from 714.85 to 7145.98 gc/L and 820.47 to 6219.05 gc/L, respectively, which were strongly correlated with the 7-day moving average of total daily COVID-19 cases in the associated areas, after 5 weeks of the viral measurement. The results indicate a potential 5-week lag time of wastewater surveillance preceding COVID-19 incidence for the Detroit metropolitan area. Four statistical models were established to analyze the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in the study areas. Under a 5-week lag time scenario with both N1 and N2 genes, the autoregression model with seasonal patterns and vector autoregression model were more effective in predicting COVID-19 cases during the study period. To investigate the impact of flow parameters on the correlation, the original N1 and N2 gene concentrations were normalized by wastewater flow parameters. The statistical results indicated the optimum models were consistent for both normalized and non-normalized data. In addition, we discussed parameters that explain the observed lag time. Furthermore, we evaluated the impact of the omicron surge that followed, and the impact of different sampling methods on the estimation of lag time.

5.
Sustainability ; 14(10):6372, 2022.
Article in English | MDPI | ID: covidwho-1857423

ABSTRACT

The COVID-19 outbreak caused huge losses for the catering industry. The outbreak's influence on consumers' risk perception and risk attitude was an important factor for these heavy losses. The aim of this study was to investigate the change in epidemic risk perception, risk attitude, and the consumers' willingness to consume products from restaurants during the spread of the COVID-19 epidemic. The study collected 502 questionnaires at the end of 2021, and structural analysis was conducted using SPSS 26.0 and AMOS 20.0 statistical programs. The results showed that consumers' awareness of the coronavirus pandemic (consumers' epidemic risk perception) had a significant positive effect on their decision-making behavior under uncertain conditions (risk attitude);consumers' decision-making behavior under uncertain conditions (risk attitude) had a significant negative effect on their willingness to purchase from restaurants;consumers' awareness of the coronavirus pandemic (consumers' epidemic risk perception) had a significant negative effect on their willingness to consume products from restaurants;and risk attitude played a mediating role in the influence of consumers' epidemic risk perception on their willingness to consume products from restaurants. This study can provide guidance and reference for restaurants on how to deal with the epidemic situation, help them undertake risk prevention work and reduce losses, and promote the healthy and sustainable development of the restaurant.

6.
Front Immunol ; 13: 834988, 2022.
Article in English | MEDLINE | ID: covidwho-1817941

ABSTRACT

Patients with COVID-19 present with a wide variety of clinical manifestations. Thromboembolic events constitute a significant cause of morbidity and mortality in patients infected with SARS-CoV-2. Severe COVID-19 has been associated with hyperinflammation and pre-existing cardiovascular disease. Platelets are important mediators and sensors of inflammation and are directly affected by cardiovascular stressors. In this report, we found that platelets from severely ill, hospitalized COVID-19 patients exhibited higher basal levels of activation measured by P-selectin surface expression and had poor functional reserve upon in vitro stimulation. To investigate this question in more detail, we developed an assay to assess the capacity of plasma from COVID-19 patients to activate platelets from healthy donors. Platelet activation was a common feature of plasma from COVID-19 patients and correlated with key measures of clinical outcome including kidney and liver injury, and APACHEIII scores. Further, we identified ferritin as a pivotal clinical marker associated with platelet hyperactivation. The COVID-19 plasma-mediated effect on control platelets was highest for patients that subsequently developed inpatient thrombotic events. Proteomic analysis of plasma from COVID-19 patients identified key mediators of inflammation and cardiovascular disease that positively correlated with in vitro platelet activation. Mechanistically, blocking the signaling of the FcγRIIa-Syk and C5a-C5aR pathways on platelets, using antibody-mediated neutralization, IgG depletion or the Syk inhibitor fostamatinib, reversed this hyperactivity driven by COVID-19 plasma and prevented platelet aggregation in endothelial microfluidic chamber conditions. These data identified these potentially actionable pathways as central for platelet activation and/or vascular complications and clinical outcomes in COVID-19 patients. In conclusion, we reveal a key role of platelet-mediated immunothrombosis in COVID-19 and identify distinct, clinically relevant, targetable signaling pathways that mediate this effect.


Subject(s)
Blood Platelets/immunology , COVID-19/immunology , Complement C5a/metabolism , Receptor, Anaphylatoxin C5a/metabolism , Receptors, IgG/metabolism , SARS-CoV-2/physiology , Thromboembolism/immunology , Adult , Aminopyridines/pharmacology , Cells, Cultured , Female , Hospitalization , Humans , Male , Morpholines/pharmacology , Platelet Activation , Pyrimidines/pharmacology , Severity of Illness Index , Signal Transduction , Syk Kinase/antagonists & inhibitors
7.
Front Psychol ; 13: 862965, 2022.
Article in English | MEDLINE | ID: covidwho-1785419

ABSTRACT

As coronavirus disease 2019 (COVID-19) swept the world in early 2020, all the Chinese universities and colleges adopted online learning to fulfill the directive saying "classes suspended but learning continues." Understanding the impact of this large-scale online learning experience on the future online learning intention of Chinese university students can help design better blended-learning activities. This study applies flow experience and theory of planned behavior (TPB) to construct a theoretical framework for assumption making and the assumptions made are validated by data gained from questionnaires. A total of 6,933 students from 54 institutions in China participated in the investigation, with 5,456 valid questionnaires returned. This study employs partial least squares (PLS) regression and confirmative factor analysis (CFA) to analyze and estimate the measurement model and the structural model. The results indicate that the experience of home-based learning significantly influenced the attitudes of Chinese university students, which in turn had a positive influence on their intention to continue online learning. The research findings provide a theoretical framework and practical guidelines on building a scientific online learning platform with appropriate online learning environments and tasks for a post-COVID-19 era blended-learning in Chinese universities.

8.
CPT Pharmacometrics Syst Pharmacol ; 11(7): 833-842, 2022 07.
Article in English | MEDLINE | ID: covidwho-1782684

ABSTRACT

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a "batch" effect to the mixed effects model may be used when a significant "batch" effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.


Subject(s)
COVID-19 , COVID-19/drug therapy , Cross-Over Studies , Humans , Pandemics , Pharmaceutical Preparations , Therapeutic Equivalency
9.
Frontiers in pharmacology ; 12, 2021.
Article in English | EuropePMC | ID: covidwho-1695095

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) has already spread around the world. The modality of traditional Chinese medicine (TCM) combined with Western medicine (WM) approaches is being used to treat COVID-19 patients in China. Several systematic reviews (SRs) are available highlighting the efficacy and safety of TCM combined with WM approaches in COVID-19 patients. However, their evidence quality is not completely validated. Purpose: We aimed to assess the methodological quality and the risk of bias of the included SRs, assess the evidence quality of outcomes, and present their trends and gaps using the evidence mapping method. Methods: PubMed, Cochrane Library, Embase, CNKI, CBM, and Wanfang Data were searched from inception until March 2021 to identify SRs pertaining to the field of TCM combined with WM approaches for COVID-19. The methodological quality of the SRs was assessed using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2), the risk of bias of the included SRs was assessed with the Risk of Bias in Systematic Review (ROBIS) tool, and the evidence quality of outcomes was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Results: In total, 23 SRs were found eligible. Twenty-one were rated of moderate confidence by AMSTAR 2, while 12 were rated at low risk using the ROBIS tool. In addition, most outcomes were graded as having moderate quality using the GRADE system. We found that the combined use of TCM and WM approaches could improve the CT recovery rate, effective rate, viral nucleic acid negative conversion rate, and the disappearance rate of fever, cough, and shortness of breath. Also, these approaches could decrease the conversion rate from mild to critical, white blood cell counts, and lymphocyte counts and shorten the time to viral assay conversion and the length of hospital stay. Conclusion: TCM combined with WM approaches had advantages in efficacy, laboratory, and clinical symptom outcomes of COVID-19, but the methodological deficiencies of SRs should be taken into consideration. Therefore, to better guide clinical practice in the future, the methodological quality of SRs should still be improved, and high-quality randomized controlled trials (RCTs) and observational studies should also be carried out.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325005

ABSTRACT

Background: At present, the epidemic of the novel coronavirus disease 2019 (COVID-19) has quickly engulfed the world. Inflammatory cytokines are associated with the severity and outcomes of patients with COVID-19. However, the effects of pro-inflammatory factors in cancer patients with COVID-19 are unknown. Methods: A multi-center, retrospective, cross-sectional study, based on 5 designated tertiary hospitals for the treatment of COVID-19 in Hubei Province, China. 112 cancer patients with COVID-19, and 105 COVID-19 patients without cancer were enrolled in the study between January 1 st , 2020 and April 30 th , 2020. The risk assessment of pro-inflammatory factors for disease severity and clinical adverse outcomes was identified by univariable and multivariable logistic regression models. Results: Of the 112 cancer patients with COVID-19, 40 (35.7%) patients were in critical condition and 18 (16.1%) patients died unfortunately. Univariate and multivariate analysis demonstrated that hemoglobin count and pro-inflammatory neutrophil and C-reactive protein, can be used as independent factors affecting the severity of COVID-19;Meanwhile, pro-inflammatory neutrophils and C-reactive protein can be used as an independent influencing factor for adverse clinical outcome. Moreover, the dynamic changes of neutrophils and C-reactive protein were also presented, and compared with COVID-19 patients without cancer, cancer patients with COVID-19 showed higher neutrophil counts and C-reactive protein levels. Conclusions: In cancer patients with COVID-19, the significant increase in pro-inflammatory neutrophil and C-reactive protein indicated a more critical illness and adverse clinical outcome, and pro-inflammatory neutrophils and C-reactive protein played a more adverse effect compare with COVID-19 patients without cancer, which may be the cause of critical illness and adverse clinical outcomes of cancer patients with COVID-19.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324440

ABSTRACT

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts;in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321364

ABSTRACT

Background: Previous studies on the impact of COVID-19 on the mental health of the patients has been limited by the lack of relevant data. With the rapid and sustained growth of the publications on COVID-19 research, we will perform a living systematic review (LSR) to provide comprehensive and continuously updated data to explore the prevalence of depression, anxiety, delirium, and post-traumatic stress disorder (PTSD) among COVID-19 patients. Methods: We will perform a comprehensive search of the following databases: Cochrane Library, PubMed, Web of Science, Embase, and Chinese Biomedicine Literature to identify relevant studies. We will utilize different tools to examine the bias risks (quality) regarding studies of varying design types, such as the revised Cochrane risk-of-bias tool (RoB 2) for randomized controlled trials (RCT), the Newcastle-Ottawa Scale (NOS) for cohort and case-control studies, etc. The literature searches would be updated every month. We will perform meta-analysis if any new eligible studies or data are obtained and resubmit an updated systematic review if any change in outcomes and heterogeneity is determined after the addition of the new studies. There will be no restrictions on language or year of publication. Discussion: This LSR would provide an in-depth and up-to-date summary of the psychological impact of COVID-19 diagnosis and treatment on the patients. Systematic review registration PROSPERO CRD42020196610

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321362

ABSTRACT

Background: Previous studies on the impact of corona virus disease 2019 (COVID-19) on the mental health of the patients has been limited by the lack of relevant data. With the rapid and sustained growth of the publications on COVID-19 research, we will perform a living systematic review (LSR) to provide comprehensive and continuously updated data to explore the prevalence of delirium, depression, anxiety, and post-traumatic stress disorder (PTSD) among COVID-19 patients. Methods: We will perform a comprehensive search of the following databases: Cochrane Library, PubMed, Web of Science, Embase, and Chinese Biomedicine Literature to identify relevant studies. We will include peer-reviewed cross-sectional studies published in English and Chinese. Two reviewers will independently assess the methodological quality of included studies using the Joanna Briggs Institute Prevalence Critical Appraisal tool and perform data extraction. In the absence of clinical heterogeneity, the prevalence estimates with a 95% confidence interval (CI) of delirium, depression, anxiety, and post-traumatic stress disorder (PTSD) will be calculated by using random-effects model to minimize the effect of between-study heterogeneity separately. The literature searches will be updated every three months. We will perform meta-analysis if any new eligible studies or data are obtained. We will resubmit an updated review when there were relevant changes in the results, i.e. when outcomes became statistically significant (or not statistically significant anymore) or when heterogeneity became substantial (or not substantial anymore). Discussion: This LSR will provide an in-depth and up-to-date summary of whether the common neuropsychiatric conditions observed in patients hospitalized for severe acute respiratory syndrome (SARS-CoV) and Middle East respiratory syndrome (MERS) are also prevalent in a different stage of COVID-19 patients. Systematic review registration PROSPERO CRD42020196610

15.
Neural Comput Appl ; : 1-14, 2021 Jul 04.
Article in English | MEDLINE | ID: covidwho-1296938

ABSTRACT

Patients with deaths from COVID-19 often have co-morbid cardiovascular disease. Real-time cardiovascular disease monitoring based on wearable medical devices may effectively reduce COVID-19 mortality rates. However, due to technical limitations, there are three main issues. First, the traditional wireless communication technology for wearable medical devices is difficult to satisfy the real-time requirements fully. Second, current monitoring platforms lack efficient streaming data processing mechanisms to cope with the large amount of cardiovascular data generated in real time. Third, the diagnosis of the monitoring platform is usually manual, which is challenging to ensure that enough doctors online to provide a timely, efficient, and accurate diagnosis. To address these issues, this paper proposes a 5G-enabled real-time cardiovascular monitoring system for COVID-19 patients using deep learning. Firstly, we employ 5G to send and receive data from wearable medical devices. Secondly, Flink streaming data processing framework is applied to access electrocardiogram data. Finally, we use convolutional neural networks and long short-term memory networks model to obtain automatically predict the COVID-19 patient's cardiovascular health. Theoretical analysis and experimental results show that our proposal can well solve the above issues and improve the prediction accuracy of cardiovascular disease to 99.29%.

16.
Journal of Environmental Engineering ; 147(8), 2021.
Article in English | ProQuest Central | ID: covidwho-1254130

ABSTRACT

This study focuses on using wastewater-based epidemiology to provide early warnings of the second COVID-19 wave in the Detroit metropolitan area of Michigan. SARS-CoV-2 RNA from untreated wastewater samples was compared to reported public health records. Untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) Water Resource Recovery Facility (WRRF), located in southeast Michigan, between August 6, 2020 and December 14, 2020. The WRRF receives wastewater from its service area via three main interceptors: the Detroit River Interceptor (DRI), the North Interceptor-East Arm (NIEA), and the Oakwood-Northwest-Wayne County Interceptor (ONWI). A total of 144 untreated wastewater samples were collected (45, 48, and 51 for ONWI, NIEA, and DRI, respectively) at the point of intake into the WRRF. Virus-selective sampling was conducted, and viruses were isolated from wastewater using electropositive NanoCeram column filters. For each sample, an average of 33 L of wastewater was passed through NanoCeram electropositive cartridge filters at an average rate of 11  L/min. Viruses were eluted and concentrated, and the SARS-CoV-2 RNA concentrations were quantified with RT-qPCR. SARS-CoV-2 RNA was detected in 98% of the samples, and measured concentrations were in the range of 4.45×104 to 5.30×106 genomic copies/L. Early warnings of COVID-19 peaks were observed approximately 4 weeks prior to reported publicly available clinical data.

17.
Front Public Health ; 9: 646780, 2021.
Article in English | MEDLINE | ID: covidwho-1256408

ABSTRACT

Background: The COVID-19 pandemic is a significant health threat. Health care worker (HCWs) are at a significant risk of infection which may cause high levels of psychological distress. The aim of this study was to investigate the psychological impact of the COVID-19 on HCWs and factors which were associated with these stresses during the first outbreak in Shanghai. Methods: Between February 9 and 21, 2020, a total of 3,114 frontline HCWs from 26 hospitals in Shanghai completed an online survey. The questionnaire included questions on their sociodemographic characteristics, 15 stress-related questions, and General Health Questionnaire-12 (GHQ-12). Exploratory factor analysis was applied to the 15 stress-related questions which produced four distinct factors for evaluation. Multiple linear regression models were performed to explore the association of personal characteristics with each score of the four factors. Binary logistic analysis was used to explain the association of personal characteristics and these four factors with the GHQ-12. Results: There were 2,691 valid surveys received. The prevalence of emotional distress (defined as GHQ-12 ≥ 12) was noted in 47.7% (95%CI:45.7-49.6%) HCWs. Females (OR = 1.43, 95%CI:1.09-1.86) were more likely to have a psychological distress than males. However, HCWs who work in secondary hospitals (OR = 0.71, 95% CI:0.58-0.87) or had a no contact history (OR = 0.45, 95%CI: 0.35-0.58) were less likely to suffer psychological distress. HCWs who were nurses, married, and had a known contact history were highly likely to have anxiety. HCWs working at tertiary hospitals felt an elevated anxiety regarding the infection, a lack of knowledge, and less protected compared to those who worked at secondary hospitals. Conclusions: Our study shows that the frontline HCWs had a significant psychosocial distress during the COVID-19 outbreak in Shanghai. HCWs felt a lack of knowledge and had feelings of being not protected. It is necessary for hospitals and governments to provide additional trainings and psychological counseling to support the first-line HCWs.


Subject(s)
COVID-19 , Pandemics , China/epidemiology , Cross-Sectional Studies , Disease Outbreaks , Female , Health Personnel , Humans , Male , SARS-CoV-2
18.
Clin Transl Sci ; 14(3): 1123-1132, 2021 05.
Article in English | MEDLINE | ID: covidwho-1091057

ABSTRACT

The outbreak of the novel coronavirus severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) respiratory disease, led to a global pandemic with high morbidity and mortality. Despite frenzied efforts in therapeutic development, there are currently no effective drugs for treatment, nor are there vaccines for its prevention. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, is one of the most practical treatment options against the outbreak. In this study, we present a novel strategy for in silico molecular modeling screening for potential drugs that may interact with multiple main proteins of SARS-CoV-2. Targeting multiple viral proteins is a novel drug discovery concept in that it enables the potential drugs to act on different stages of the virus' life cycle, thereby potentially maximizing the drug potency. We screened 2631 US Food and Drug Administration (FDA)-approved small molecules against 4 key proteins of SARS-CoV-2 that are known as attractive targets for antiviral drug development. In total, we identified 29 drugs that could actively interact with 2 or more target proteins, with 5 drugs (avapritinib, bictegravir, ziprasidone, capmatinib, and pexidartinib) being common candidates for all 4 key host proteins and 3 of them possessing the desirable molecular properties. By overlaying docked positions of drug candidates onto individual host proteins, it has been further confirmed that the binding site conformations are conserved. The drugs identified in our screening provide potential guidance for experimental confirmation, such as in vitro molecular assays and in vivo animal testing, as well as incorporation into ongoing clinical studies.


Subject(s)
COVID-19/drug therapy , Drug Evaluation, Preclinical/methods , Drug Repositioning , SARS-CoV-2/drug effects , Drug Approval , Drug Discovery , Humans , Hydrogen-Ion Concentration , Models, Molecular , Molecular Docking Simulation
20.
Front Pharmacol ; 11: 576994, 2020.
Article in English | MEDLINE | ID: covidwho-1067659

ABSTRACT

Background: At present, the epidemic of the novel coronavirus disease 2019 (COVID-19) has quickly engulfed the world. Inflammatory cytokines are associated with the severity and outcomes of patients with COVID-19. However, the prognostic value of pro-inflammatory factors in cancer patients with COVID-19 are unknown. Methods: A multi-center, retrospective, cross-sectional study, based on five designated tertiary hospitals for the treatment of COVID-19 in Hubei Province, China. 112 cancer patients with COVID-19, and 105 COVID-19 patients without cancer were enrolled in the study between January 1st, 2020 and April 30th, 2020. The risk assessment of pro-inflammatory factors for disease severity and clinical adverse outcomes was identified by univariable and multivariable logistic regression models. Results: Of the 112 cancer patients with COVID-19, 40 (35.7%) patients were in critical condition and 18 (16.1%) patients died unfortunately. Univariate and multivariate analysis demonstrated that hemoglobin level and pro-inflammatory neutrophils and C-reactive protein (CRP), can be used as independent factors affecting the severity of COVID-19; Meanwhile, pro-inflammatory neutrophils and CRP can be used as an independent influencing factor for adverse clinical outcome of death. Moreover, the dynamic changes of neutrophils and CRP were also presented, and compared with COVID-19 patients without cancer, cancer patients with COVID-19 showed higher neutrophil counts and CRP levels. Conclusion: In cancer patients with COVID-19, the significant increase in pro-inflammatory neutrophils and CRP indicated a more critical illness and adverse clinical outcome, and pro-inflammatory neutrophils and CRP played a greater adverse role compare with COVID-19 patients without cancer, which may be the cause of critical illness and adverse clinical outcomes of cancer patients with COVID-19.

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