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1.
MedComm (2020) ; 4(3): e295, 2023 Jun.
Article in English | MEDLINE | ID: covidwho-20245098
2.
Biosens Bioelectron ; 222: 114989, 2023 Feb 15.
Article in English | MEDLINE | ID: covidwho-2306553

ABSTRACT

For point-of-care testing (POCT), coupling isothermal nucleic acid amplification schemes (e.g., recombinase polymerase amplification, RPA) with lateral flow assay (LFA) readout is an ideal platform, since such integration offers both high sensitivity and deployability. However, isothermal schemes typically suffers from non-specific amplification, which is difficult to be differentiated by LFA and thus results in false-positives. Here, we proposed an accurate POCT platform by specific recognition of target amplicons with peptide nucleic acid (PNA, assisted by T7 Exonuclease), which could be directly plugged into the existing RPA kits and commercial LFA test strips. With SARS-CoV-2 as the model, the proposed method (RPA-TeaPNA-LFA) efficiently eliminated the false-positives, exhibiting a lowest detection concentration of 6.7 copies/µL of RNA and 90 copies/µL of virus. Using dual-gene (orf1ab and N genes of SARS-CoV-2) as the targets, RPA-TeaPNA-LFA offered a high specificity (100%) and sensitivity (RT-PCR Ct < 31, 100%; Ct < 40, 71.4%), and is valuable for on-site screening or self-testing during isolation. In addition, the dual test lines in the test strips were successfully explored for simultaneous detection of SARS-CoV-2 and H1N1, showing great potential in response to future pathogen-based pandemics.


Subject(s)
Biosensing Techniques , COVID-19 , Influenza A Virus, H1N1 Subtype , Nucleic Acids , Humans , Influenza A Virus, H1N1 Subtype/genetics , SARS-CoV-2/genetics , COVID-19/diagnosis , Nucleic Acid Amplification Techniques/methods , Point-of-Care Testing , Sensitivity and Specificity , Recombinases/genetics
3.
Small ; 19(23): e2301146, 2023 06.
Article in English | MEDLINE | ID: covidwho-2269972

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-caused COVID-19 pandemic has rapidly escalated into the largest global health emergency, which pushes to develop detection kits for the detection of COVID-19 with high sensitivity, specificity, and fast analysis. Here, aptamer-functionalized MXene nanosheet is demonstrated as a novel bionanosensor that detects COVID-19. Upon binding to the spike receptor binding domain of SARS-CoV-2, the aptamer probe is released from MXene surface restoring the quenched fluorescence. The performances of the fluorosensor are evaluated using antigen protein, cultured virus, and swab specimens from COVID-19 patients. It is evidenced that this sensor can detect SARS-CoV-2 spike protein at final concentration of 38.9 fg mL-1 and SARS-CoV-2 pseudovirus (limit of detection: 7.2 copies) within 30 min. Its application for clinical samples analysis is also demonstrated successfully. This work offers an effective sensing platform for sensitive and rapid detection of COVID-19 with high specificity.


Subject(s)
COVID-19 , Humans , COVID-19/diagnosis , SARS-CoV-2 , Pandemics , Oligonucleotides
4.
Biomolecules ; 13(1)2022 12 20.
Article in English | MEDLINE | ID: covidwho-2237631

ABSTRACT

This study was conducted to investigate oropharyngeal microbiota alterations during the progression of coronavirus disease 2019 (COVID-19) by analyzing these alterations during the infection and clearance processes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The diagnosis of COVID-19 was confirmed by using positive SARS-CoV-2 quantitative reverse transcription polymerase chain reaction (RT-qPCR). The alterations in abundance, diversity, and potential function of the oropharyngeal microbiome were identified using metatranscriptomic sequencing analyses of oropharyngeal swab specimens from 47 patients with COVID-19 (within a week after diagnosis and within two months after recovery from COVID-19) and 40 healthy individuals. As a result, in the infection process of SARS-CoV-2, compared to the healthy individuals, the relative abundances of Prevotella, Aspergillus, and Epstein-Barr virus were elevated; the alpha diversity was decreased; the beta diversity was disordered; the relative abundance of Gram-negative bacteria was increased; and the relative abundance of Gram-positive bacteria was decreased. After the clearance of SARS-CoV-2, compared to the healthy individuals and patients with COVID-19, the above disordered alterations persisted in the patients who had recovered from COVID-19 and did not return to the normal level observed in the healthy individuals. Additionally, the expressions of several antibiotic resistance genes (especially multi-drug resistance, glycopeptide, and tetracycline) in the patients with COVID-19 were higher than those in the healthy individuals. After SARS-CoV-2 was cleared, the expressions of these genes in the patients who had recovered from COVID-19 were lower than those in the patients with COVID-19, and they were different from those in the healthy individuals. In conclusion, our findings provide evidence that potential secondary infections with oropharyngeal bacteria, fungi, and viruses in patients who have recovered from COVID-19 should not be ignored; this evidence also highlights the clinical significance of the oropharyngeal microbiome in the early prevention of potential secondary infections of COVID-19 and suggests that it is imperative to choose appropriate antibiotics for subsequent bacterial secondary infection in patients with COVID-19.


Subject(s)
COVID-19 , Coinfection , Epstein-Barr Virus Infections , Microbiota , Humans , SARS-CoV-2/genetics , Herpesvirus 4, Human , Microbiota/genetics , Bacteria
6.
Sens Actuators B Chem ; 362: 131765, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-1757833

ABSTRACT

SARS-CoV-2 is one of the greatest threats to global human health. Point-of-care diagnostic tools for SARS-CoV-2 could facilitate rapid therapeutic intervention and mitigate transmission. In this work, we report CRISPR-Cas13a cascade-based viral RNA (Cas13C) assay for label-free and isothermal determination of SARS-CoV-2 and its mutations in clinical samples. Cas13a/crRNA was utilized to directly recognize the target of SARS-CoV-2 RNA, and the recognition events sequentially initiate the transcription amplification to produce light-up RNA aptamers for output fluorescence signal. The recognition of viral RNA via Cas13a-guide RNA ensures a high specificity to distinguish SARS-CoV-2 from MERS-CoV and SARS-CoV, as well as viral mutations. A post transcription amplification strategy was triggered after CRISPR-Cas13a recognition contributes to an amplification cascade that achieves high sensitivity for detecting SARS-CoV-2 RNA, with a limit of detection of 0.216 fM. In addition, the Cas13C assay could be able to discriminate single-nucleotide mutation, which was proven with N501Y in SARS-Cov-2 variant. This method was validated by a 100% agreement with RT-qPCR results from 12 clinical throat swab specimens. The Cas13C assay has the potential to be used as a routine nucleic acid test of SARS-CoV-2 virus in resource-limited regions.

7.
Signal Transduct Target Ther ; 6(1): 316, 2021 08 25.
Article in English | MEDLINE | ID: covidwho-1442753

ABSTRACT

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.


Subject(s)
COVID-19 Drug Treatment , COVID-19 Testing , COVID-19/prevention & control , Epidemics/prevention & control , SARS-CoV-2/metabolism , COVID-19/metabolism , Humans
8.
Front Med (Lausanne) ; 8: 663145, 2021.
Article in English | MEDLINE | ID: covidwho-1266666

ABSTRACT

Background: Predicting the risk of progression to severe coronavirus disease 2019 (COVID-19) could facilitate personalized diagnosis and treatment options, thus optimizing the use of medical resources. Methods: In this prospective study, 206 patients with COVID-19 were enrolled from regional medical institutions between December 20, 2019, and April 10, 2020. We collated a range of data to derive and validate a predictive model for COVID-19 progression, including demographics, clinical characteristics, laboratory findings, and cytokine levels. Variation analysis, along with the least absolute shrinkage and selection operator (LASSO) and Boruta algorithms, was used for modeling. The performance of the derived models was evaluated by specificity, sensitivity, area under the receiver operating characteristic (ROC) curve (AUC), Akaike information criterion (AIC), calibration plots, decision curve analysis (DCA), and Hosmer-Lemeshow test. Results: We used the LASSO algorithm and logistic regression to develop a model that can accurately predict the risk of progression to severe COVID-19. The model incorporated alanine aminotransferase (ALT), interleukin (IL)-6, expectoration, fatigue, lymphocyte ratio (LYMR), aspartate transaminase (AST), and creatinine (CREA). The model yielded a satisfactory predictive performance with an AUC of 0.9104 and 0.8792 in the derivation and validation cohorts, respectively. The final model was then used to create a nomogram that was packaged into an open-source and predictive calculator for clinical use. The model is freely available online at https://severeconid-19predction.shinyapps.io/SHINY/. Conclusion: In this study, we developed an open-source and free predictive calculator for COVID-19 progression based on ALT, IL-6, expectoration, fatigue, LYMR, AST, and CREA. The validated model can effectively predict progression to severe COVID-19, thus providing an efficient option for early and personalized management and the allocation of appropriate medical resources.

9.
Research (Wash D C) ; 2021: 2813643, 2021.
Article in English | MEDLINE | ID: covidwho-1160985

ABSTRACT

Sensitive detection of SARS-CoV-2 is of great importance for inhibiting the current pandemic of COVID-19. Here, we report a simple yet efficient platform integrating a portable and low-cost custom-made detector and a novel microwell array biochip for rapid and accurate detection of SARS-CoV-2. The instrument exhibits expedited amplification speed that enables colorimetric read-out within 25 minutes. A polymeric chip with a laser-engraved microwell array was developed to process the reaction between the primers and the respiratory swab RNA extracts, based on reverse transcriptase loop-mediated isothermal amplification (RT-LAMP). To achieve clinically acceptable performance, we synthesized a group of six primers to identify the conserved regions of the ORF1ab gene of SARS-CoV-2. Clinical trials were conducted with 87 PCR-positive and 43 PCR-negative patient samples. The platform demonstrated both high sensitivity (95.40%) and high specificity (95.35%), showing potentials for rapid and user-friendly diagnosis of COVID-19 among many other infectious pathogens.

10.
BMC Infect Dis ; 20(1): 688, 2020 Sep 21.
Article in English | MEDLINE | ID: covidwho-781448

ABSTRACT

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the peak season of common respiratory viral infections. However, the clinical symptoms of most SARS-CoV-2 infected patients are not significantly different from those of common respiratory viral infections. Therefore, knowing the epidemiological patterns of common respiratory viruses may be valuable to improve the diagnostic and therapeutic efficacy of patients with suspected COVID-19, especially in Southwest China (a mild epidemic area). METHODS: A total of 2188 patients with clinically suspected of COVID-19 in Southwest China were recruited from January 21 to February 29, 2020. Nasopharyngeal swabs, throat swabs and sputum specimens were collected to detect SARS-CoV-2 by using real-time reverse transcription-polymerase chain reaction (RT-PCR) and other 12 viruses via PCR fragment analysis combined with capillary electrophoresis. Clinical characteristics and laboratory test findings were acquired from electronic medical records. All data were analyzed to unravel the epidemiological patterns. RESULTS: Only 1.1% (24/2188) patients with suspected COVID-19 were eventually confirmed to have SARS-CoV-2 infection, and the most frequently observed symptoms were fever (75.0%, 18/24) and cough (20.8%, 5/24). The overall detection rate of other respiratory pathogens was 10.3% (226/2188). Among them, human rhinovirus (3.2%, 71/2188), human parainfluenza viruses (1.6%, 35/2188), influenza B virus (1.2%, 26/2188) and mycoplasma pneumonia (1.2%, 26/2188) were the predominantly detected pathogens in this study. Moreover, the co-infection was observed in 22 specimens. Notably, one COVID-19 case had a coexisting infection with human parainfluenza virus (4.2%, 1/24) and bocavirus was the most common virus tending to occur in co-infection with other respiratory pathogens. CONCLUSIONS: This study reveals the epidemiological features of common respiratory viruses and their clinical impact during the ongoing outbreak of COVID-19 in a mild epidemic area. The findings highlight the importance of understanding the transmission patterns of the common respiratory virus in COVID-19 regions, which can provide information support for the development of appropriate treatment plans and health policies, while eliminating unnecessary fear and tension.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Respiratory System/virology , Respiratory Tract Infections/virology , Adult , COVID-19 , China/epidemiology , Coinfection/epidemiology , Cough/virology , Female , Humans , Male , Middle Aged , Pandemics , Real-Time Polymerase Chain Reaction , Retrospective Studies , SARS-CoV-2 , Young Adult
11.
Clin Chim Acta ; 510: 186-190, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-651781

ABSTRACT

OBJECTIVE: The aim of this study was to systematically and comprehensively evaluate the diagnostic and prognostic value of myocardial injury biomarkers in COVID-19 patients. METHODS: This is a retrospective cohort study of confirmed COVID-19 patients that were admitted to the Renmin Hospital of Wuhan University from January 30, 2020 to February 15, 2020. RESULTS: Receiver operating characteristic (ROC) curve analysis demonstrated that cTnI-ultra had the highest area under the curve (AUC) at 0.855, with a sensitivity of 67.3% and a specificity of 88.7% for the prediction of in-hospital mortality. Patients with higher troponin I-ultra (cTnI-ultra), creatinine kinase-myocardial band (CK-MB), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were associated with higher mortality, compared to those who lower levels. The multivariable cox regression indicated that age (hazard ratio (HR) 3.450, 95% confidence interval (CI) 1.627-7.314, P = 0.001), coronary heart disease (HR 1.855, 95% CI 1.006-3.421; P = 0.048), elevated cTnI-ultra (HR 3.083, 95% CI 1.616-5.883, P = 0.001), elevated CK-MB (HR 2.907, 95% CI 1.233-6.854; P = 0.015), and elevated NT-proBNP (HR 5.776, 95% CI 2.272-14.682; P < 0.001) were associated with in-hospital mortality. CONCLUSIONS: cTnI-ultra might be the best predictor of in-hospital mortality among myocardial injury biomarkers. Elevated cTnI-ultra, CK-MB, and NT-proBNP were independent biomarkers of the mortality in COVID-19 patients.


Subject(s)
Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Heart Injuries/complications , Heart Injuries/metabolism , Hospitalization , Pneumonia, Viral/complications , Pneumonia, Viral/diagnosis , Aged , Biomarkers/metabolism , COVID-19 , Cohort Studies , Coronavirus Infections/metabolism , Coronavirus Infections/mortality , Female , Hospital Mortality , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/metabolism , Pneumonia, Viral/mortality , ROC Curve , Retrospective Studies
12.
Precis Clin Med ; 3(1): 14-21, 2020 Feb 04.
Article in English | MEDLINE | ID: covidwho-101596

ABSTRACT

In December 2019, several patients with pneumonia of an unknown cause were detected in Wuhan, China. On 7 January 2020, the causal organism was identified as a new coronavirus, later named as the 2019 novel coronavirus (2019-nCoV). Genome sequencing found the genetic sequence of 2019-nCoV homologous to that of severe acute respiratory syndrome-associated coronavirus. As of 29 January 2020, the virus had been diagnosed in more than 7000 patients in China and 77 patients in other countries. It is reported that both symptomatic and asymptomatic patients with 2019-nCoV can play a role in disease transmission via airborne and contact. This finding has caused a great concern about the prevention of illness spread. The clinical features of the infection are not specific and are often indistinguishable from those of other respiratory infections, making it difficult to diagnose. Given that the virus has a strong ability to spread between individuals, it is of top priority to identify potential or suspected patients as soon as possible-or the virus may cause a serious pandemic. Therefore, a precision medicine approach to managing this disease is urgently needed for detecting and controlling the spread of the virus. In this article, we present such an approach to managing 2019-nCoV-related pneumonia based on the unique traits of the virus recently revealed and on our experience with coronaviruses at West China Hospital in Chengdu, China.

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