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2.
Biosensors (Basel) ; 13(2)2023 Jan 29.
Article in English | MEDLINE | ID: covidwho-2309398

ABSTRACT

With the move of molecular tests from diagnostic labs to on-site testing becoming more common, there is a sudden rise in demand for nucleic acid-based diagnostic tools that are selective, sensitive, flexible to terrain changes, and cost-effective to assist in point-of-care systems for large-scale screening and to be used in remote locations in cases of outbreaks and pandemics. CRISPR-based biosensors comprise a promising new approach to nucleic acid detection, which uses Cas effector proteins (Cas9, Cas12, and Cas13) as extremely specialized identification components that may be used in conjunction with a variety of readout approaches (such as fluorescence, colorimetry, potentiometry, lateral flow assay, etc.) for onsite analysis. In this review, we cover some technical aspects of integrating the CRISPR Cas system with traditional biosensing readout methods and amplification technologies such as polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and recombinase polymerase amplification (RPA) and continue to elaborate on the prospects of the developed biosensor in the detection of some major viral and bacterial diseases. Within the scope of this article, we also discuss the recent COVID pandemic and the numerous CRISPR biosensors that have undergone development since its advent. Finally, we discuss some challenges and future prospects of CRISPR Cas systems in point-of-care testing.


Subject(s)
Biosensing Techniques , COVID-19 , Nucleic Acids , Humans , Point-of-Care Systems , Point-of-Care Testing , Biological Assay , Nucleic Acid Amplification Techniques , COVID-19 Testing
3.
Luminescence ; 2022 Dec 28.
Article in English | MEDLINE | ID: covidwho-2284289

ABSTRACT

The review discusses the diagnostic application of biosensors as point-of-care devices in the COVID-19 pandemic. Biosensors are important analytical tools that can be used for the robust and effective detection of infectious diseases in real-time. In this current scenario, the utilization of smart, efficient biosensors for COVID-19 detection is increasing and we have included a few smart biosensors such as smart and intelligent based biosensors, plasmonic biosensors, field effect transistor (FET) biosensors, smart optical biosensors, surface enhanced Raman scattering (SERS) biosensor, screen printed electrode (SPE)-based biosensor, molecular imprinted polymer (MIP)-based biosensor, MXene-based biosensor and metal-organic frame smart sensor. Their significance as well as the benefits and drawbacks of each kind of smart sensor are mentioned in depth. Furthermore, we have compiled a list of various biosensors which have been developed across the globe for COVID-19 and have shown promise as commercial detection devices. Significant challenges in the development of effective diagnostic methods are discussed and recommendations have been made for better diagnostic outcomes to manage the ongoing pandemic effectively.

4.
Microbes Infect ; : 105059, 2022 Oct 11.
Article in English | MEDLINE | ID: covidwho-2230619

ABSTRACT

The present cross-sectional study aims to explore the fungal community composition of the nasopharyngeal region of SARS-CoV-2 infected individuals and how the infection influences the mycobiome therein. The infection significantly (p<0.05) influenced the alpha diversity. Interestingly, a higher abundance of Cladosporium and Alternaria was noted in the infected individuals and inter-individual variation in mycobiome composition was well supported by beta dispersion analysis (p < 0.05). Moreover, decrease in Aspergillus abundance was observed in infected patients across the four age groups. This study provides insight into the alteration in mycobiome during the viral disease progression and demands continuous investigation to monitor fungal infections.

6.
Mater Today Proc ; 2020 Sep 22.
Article in English | MEDLINE | ID: covidwho-2095742

ABSTRACT

COVID-19 pandemic has become the most devastating disease of the current century and spread over 216 countries around the world. The disease is spreading through outbreaks despite the availability of modern sophisticated medical treatment. Machine Learning and Image Analysis research has been making great progress in many directions in the healthcare field for providing support to subsequent medical diagnosis. In this paper, we have propose three research directions with methodologies in the fight against the pandemic namely: Chest X-Ray (CXR) images classification using deep convolution neural networks with transfer learning to assist diagnosis; Patient Risk prediction of pandemic based on risk factors such as patient characteristics, comorbidities, initial symptoms, vital signs for prognosis of disease; and forecasting of disease spread & case fatality rate using deep neural networks. Further, some of the challenges, open datasets and opportunities are discussed for researchers.

8.
Microbes and infection ; 2022.
Article in English | EuropePMC | ID: covidwho-2057878

ABSTRACT

The present cross-sectional study aims to explore the fungal community composition of the nasopharyngeal region of SARS-CoV-2 infected individuals and how the infection influences the mycobiome therein. The infection significantly (p<0.05) influenced the alpha diversity. Interestingly, a higher abundance of Cladosporium and Alternaria was noted in the infected individuals and inter-individual variation in mycobiome composition was well supported by beta dispersion analysis (p < 0.05). Moreover, decrease in Aspergillus abundance was observed in infected patients across the four age groups. This study provides insight into the alteration in mycobiome during the viral disease progression and demands continuous investigation to monitor fungal infections.

10.
J Med Virol ; 94(10): 4628-4643, 2022 10.
Article in English | MEDLINE | ID: covidwho-1888758

ABSTRACT

The global pandemic of COVID-19 began in December 2019 and is still continuing. The past 2 years have seen the emergence of several variants that were more vicious than each other. The emergence of Omicron (B.1.1.529) proved to be a huge epidemiological concern as the rate of infection of this particular strain was enormous. The strain was identified in South Africa on November 24, 2021 and was classified as a "Variant of Concern" on November 26, 2021. The Omicron variant possessed mutations in the key RBD region, the S region, thereby increasing the affinity of ACE2 for better transmission of the virus. Antibody resistance was found in this variant and it was able to reduce vaccine efficiency of vaccines. The need for a booster vaccine was brought forth due to the prevalence of the Omicron variant and, subsequently, this led to targeted research and development of variant-specific vaccines and booster dosage. This review discusses broadly the genomic characters and features of Omicron along with its specific mutations, evolution, antibody resistance, and evasion, utilization of CRISPR-Cas12a assay for Omicron detection, T-cell immunity elicited by vaccines against Omicron, and strategies to decrease Omicron infection along with COVID-19 and it also discusses on XE recombinant variant and on infectivity of BA.2 subvariant of Omicron.


Subject(s)
COVID-19 , COVID-19/prevention & control , Humans , Pandemics , SARS-CoV-2/genetics , Vaccine Development
11.
Microbiol Res ; 261: 127055, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1819572

ABSTRACT

The human oral cavity harbours complex microbial communities with various commensal microorganisms that play pivotal roles in maintaining host health and immunity but can elicit local and systemic diseases. The role of commensal microorganisms in SARS-CoV-2 infection and disease susceptibility and enrichment of opportunistic pathobionts in the oral cavity is poorly understood. The present study aims to understand the altered landscape of the oral microbiome and mycobiome in SARS-CoV-2 infected patients (n = 30) and its correlation with risk factors compared to non-infected individuals (n = 24) using targeted amplicon sequencing. Diminution of species richness, an elevated abundance of opportunistic pathogens (Veillonella, Acinetobacter, Klebsiella, Prevotella, Gemella, and Streptococcus) and impaired metabolic pathways were observed in the COVID-19 patients. Similarly, altered oral mycobiome with enrichment of known respiratory disease causing pathogenic fungi were observed in the infected individuals. The data further suggested that reduction in immunomodulatory microorganisms lowers the protection of individuals from SARS-CoV-2. Linear discriminant analysis identified several differentially abundant taxa associated with risk factors (ageing and co-morbidities). We also observed distinct bacterial and fungal community structures of elderly infected patients compared to the younger age group members making them highly vulnerable to SARS-CoV-2 infection and disease severity. Furthermore, we also assessed the dynamics of the oral microbiome and mycobiome in symptomatic and asymptomatic patients, host types, co-morbidities, and viral load in the augmentation of specific pathobionts. Overall, the present study demonstrates the microbiome and mycobiome profiling of the COVID-19 infected individuals, the data further suggests that the SARS-CoV-2 infection triggers the prevalence of specific pathobiont.


Subject(s)
COVID-19 , Mycobiome , Aged , Dysbiosis/microbiology , Fungi , Humans , SARS-CoV-2
12.
Microbes Infect ; 24(1): 104880, 2022 02.
Article in English | MEDLINE | ID: covidwho-1364363

ABSTRACT

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is causing a severe global health emergency owing to its highly infectious nature. Although the symptoms of SARS-CoV-2 are well known but its impact on nasopharyngeal microbiome is poorly studied. The present cross-sectional study was intended to understand the perturbation in the nasopharyngeal microbiome composition within the infected (n = 63) and non-infected (n = 26) individuals using 16S rRNA gene based targeted amplicon sequencing and their association with host types and the prevalence of opportunistic pathogens at the stage of infection. The results confirmed that number of OTUs were significantly (p < 0.05) decreased in the SARS-CoV-2 infected individuals in comparison to non-infected individuals. Pairwise Wilcoxon test showed a significant (p < 0.05) increase in the abundance of Proteobacteria in infected individuals compared to non-infected ones and vice-versa for Fusobacteria and Bacteroidetes. Similarity percentage (SIMPER) analysis showed the increment in the abundance of opportunistic pathogens (Haemophilus, Stenotrophomonas, Acinetobacter, Moraxella, Corynebacterium 1, Gemella, Ralstonia, and Pseudomonas) involved in secondary infection. Furthermore, this study highlighted the microbial community structure of individuals within and across the families. In this study, we also performed the assesment of microbiome associated with host types (age and genders) and COVID-19 conditions (symptomatic and asymptomatic). The data suggested that the host types/conditions during the COVID-19 infection are potential factors in enrichment of specific bacterial communities in upper respiratory tract.


Subject(s)
COVID-19 , Microbiota , Cross-Sectional Studies , Female , Humans , Male , Prevalence , RNA, Ribosomal, 16S/genetics , SARS-CoV-2
13.
Indian J Psychiatry ; 63(4): 335-347, 2021.
Article in English | MEDLINE | ID: covidwho-1360852

ABSTRACT

INTRODUCTION: The psychological impact of COVID-19 on health-care workers (HCWs) has received attention from researchers to understand the extent of the effects of the ongoing pandemic on this population. The aim of this systematic review and meta-analysis was to synthesize the currently available literature on the topic to determine the prevalence of mental health problems in HCWs. MATERIALS AND METHODS: We conducted a systematic review and meta-analysis, searching PubMed, PsycINFO, Scopus, and Cochrane Library databases for articles published from December 2019 to August 15, 2020. We identified studies reporting the prevalence of any mental health condition in HCWs involved directly or indirectly in providing services during the COVID-19 pandemic. The prevalence proportion for individual outcome was extracted as an estimate of interest. We performed random-effects meta-analyses evaluated using Q statistic, I 2 statistic, subgroup analyses, and sensitivity analyses and assessed study quality. This review was done in adherence to the Reporting Items for Systematic Reviews and Meta-Analysis and Meta-analysis of Observational Studies in Epidemiology guidelines. The study protocol was registered prospectively at PROSPERO (CRD42020182005). RESULTS: We identified 1958 studies, of which 33 studies including 39703 participants (with a median = 393; range = 88-14825) were finally included for analysis. The estimated overall prevalence were as follows: depression 32.4% (95% confidence interval [CI]: 25.9-39.3, I 2 = 99%), anxiety 32.5% (95% CI: 26.4-39.0, I 2 = 99%), insomnia or sleep disturbance 36.6% (95% CI: 36.6-48.3, I 2 = 99%), and stress 37.7% (95% CI: 24.0-52.3, I 2 = 100%). CONCLUSION: HCWs who are dealing with the COVID-19 pandemic have a significant prevalence of depression, anxiety, insomnia and poor sleep quality, and stress. The health-care workforce needs to practice self-care now more than ever, while health-care managers and policymakers need to factor in the mental health consequences of COVID-19 on their workforce.

14.
Microb Ecol ; 82(2): 365-376, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1293356

ABSTRACT

The unprecedented COVID-19 pandemic has had major impact on human health worldwide. Whilst national and international COVID-19 lockdown and travel restriction measures have had widespread negative impact on economies and mental health, they may have beneficial effect on the environment, reducing air and water pollution. Mass bathing events (MBE) also known as Kumbh Mela are known to cause perturbations of the ecosystem affecting resilient bacterial populations within water of rivers in India. Lockdowns and travel restrictions provide a unique opportunity to evaluate the impact of minimum anthropogenic activity on the river water ecosystem and changes in bacterial populations including antibiotic-resistant strains. We performed a spatiotemporal meta-analysis of bacterial communities of the Godavari River, India. Targeted metagenomics revealed a 0.87-fold increase in the bacterial diversity during the restricted activity of lockdown. A significant increase in the resilient phyla, viz. Proteobacteria (70.6%), Bacteroidetes (22.5%), Verrucomicrobia (1.8%), Actinobacteria (1.2%) and Cyanobacteria (1.1%), was observed. There was minimal incorporation of allochthonous bacterial communities of human origin. Functional profiling using imputed metagenomics showed reduction in infection and drug resistance genes by - 0.71-fold and - 0.64-fold, respectively. These observations may collectively indicate the positive implications of COVID-19 lockdown measures which restrict MBE, allowing restoration of the river ecosystem and minimise the associated public health risk.


Subject(s)
Bacteria/isolation & purification , Communicable Disease Control/legislation & jurisprudence , Ecosystem , Rivers/microbiology , Bacteria/classification , COVID-19/epidemiology , COVID-19/prevention & control , Drug Resistance, Bacterial , Environmental Monitoring , Hinduism , Human Activities , India/epidemiology , Principal Component Analysis
15.
Med Mycol Case Rep ; 31: 6-10, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-611686

ABSTRACT

As the COVID-19 pandemic has developed, concern for invasive fungal infections in critically ill COVID-19 patients with acute respiratory distress syndrome (ARDS) has emerged. We describe a clinical case of coronavirus disease (COVID-19) associated pulmonary aspergillus (CAPA) infection and acute respiratory distress syndrome (ARDS) with a good clinical outcome, in a previously well, non-immunocompromised Australian woman.

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