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1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-321265

ABSTRACT

As the whole world is witnessing what novel Coronavirus (COVID-19) can do to the mankind, it presents several unique features also. In absence of specific vaccine for COVID-19, it is essential to detect the disease at an early stage and isolate an infected patient. Till today there is a global shortage of testing labs and testing kits for COVID-19. This paper discusses about the role of machine learning techniques for getting important insights like whether lung Computed Tomography (CT) scan should be the first screening /alternative test for real-time reverse transcriptase-polymerase chain reaction (RT-PCR), Is COVID-19 pneumonia different from other viral pneumonia and if yes how to distinguish it using lung CT scan images from the carefully selected data of lung CT scan COVID-19 infected patients from the hospitals of Italy, China and India having no past medical illnesses i.e. high blood pressure, diabetes and heart disease. The reason for selecting images of the patients having no past illnesses history is that people with medical problems are already known to develop serious illness because of COVID-19 but we wanted to check and analyse condition of those patients (lung condition) which don’t have past medical history using CT scan images.

2.
Nat Commun ; 13(1): 383, 2022 01 19.
Article in English | MEDLINE | ID: covidwho-1636827

ABSTRACT

A single center open label phase 2 randomised control trial (Clinical Trial Registry of India No. CTRI/2020/05/025209) was done to assess clinical and immunological benefits of passive immunization using convalescent plasma therapy. At the Infectious Diseases and Beleghata General Hospital in Kolkata, India, 80 patients hospitalized with severe COVID-19 disease and fulfilling the inclusion criteria (aged more than 18 years, with either mild ARDS having PaO2/FiO2 200-300 or moderate ARDS having PaO2/FiO2 100-200, not on mechanical ventilation) were recruited and randomized into either standard of care (SOC) arm (N = 40) or the convalescent plasma therapy (CPT) arm (N = 40). Primary outcomes were all-cause mortality by day 30 of enrolment and immunological correlates of response to therapy if any, for which plasma abundance of a large panel of cytokines was quantitated before and after intervention to assess the effect of CPT on the systemic hyper-inflammation encountered in these patients. The secondary outcomes were recovery from ARDS and time taken to negative viral RNA PCR as well as to report any adverse reaction to plasma therapy. Transfused convalescent plasma was characterized in terms of its neutralizing antibody content as well as proteome. The trial was completed and it was found that primary outcome of all-cause mortality was not significantly different among severe COVID-19 patients with ARDS randomized to two treatment arms (Mantel-Haenszel Hazard Ratio 0.6731, 95% confidence interval 0.3010-1.505, with a P value of 0.3424 on Mantel-Cox Log-rank test). No adverse effect was reported with CPT. In severe COVID-19 patients with mild or moderate ARDS no significant clinical benefit was registered in this clinical trial with convalescent plasma therapy in terms of prespecified outcomes.


Subject(s)
COVID-19/therapy , Antibodies, Neutralizing/immunology , Antibodies, Neutralizing/therapeutic use , Antibodies, Viral/immunology , Antibodies, Viral/therapeutic use , Blood Donors , COVID-19/immunology , COVID-19/virology , Cytokines/blood , Female , Hospitals, General , Humans , Immunity, Humoral , Immunization, Passive , India , Inflammation , Male , Phylogeny , Respiratory Distress Syndrome/immunology , Respiratory Distress Syndrome/therapy , Respiratory Distress Syndrome/virology , SARS-CoV-2/classification , SARS-CoV-2/genetics , SARS-CoV-2/immunology , Survival Analysis , Treatment Outcome , Viral Load
3.
Complement Ther Clin Pract ; 46: 101509, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1506806

ABSTRACT

BACKGROUND: Among numerous changes in response to the COVID-19 pandemic, most yoga classes have repositioned online. However benefits, difficulties and satisfaction of teaching yoga online remain to be studied. With this background the present survey aimed to determine: (i) benefits, disadvantages and satisfaction of teaching yoga online and (ii) their association with characteristics related to (a) socio-demographic, (b) online yoga teaching experience and (c) yoga practice. METHODS: Three hundred and five yoga instructors were invited to take part in the online survey. Of these, 181 (m:f = 98:83) responded to the survey satisfactorily and were included. RESULTS: The three most common benefits of teaching yoga online were: (i) a sense of safety from risk of COVID-19 (93.92%), (ii) cost saving (82.87%) and (iii) wider access to trainees within India (77.90%). The three most common disadvantages were: (i) technical difficulties (74.03%), (ii) missing in-person contact (63.90%) and (iii) concern that online instructions can lead to injury (59.16%). Around 66.30% respondents were satisfied with the monitoring of trainees during online yoga classes while 70.16% respondents were satisfied with the level of attention they could pay to the topic they were teaching during online yoga class. The benefits and disadvantages of teaching yoga online varied with the characteristics of yoga instructors (p < 0.05, χ2 test). CONCLUSIONS: The benefits and disadvantages of teaching yoga online are of relevance during and beyond the pandemic. Characteristics related to (i) socio-demographics, (ii) online yoga teaching and (iii) yoga practice influence reported benefits and disadvantages of teaching yoga online.


Subject(s)
COVID-19 , Yoga , Humans , Pandemics , SARS-CoV-2 , Surveys and Questionnaires
4.
SSRN; 2021.
Preprint in English | SSRN | ID: ppcovidwho-291756

ABSTRACT

Due to the worldwide spread of SARS-CoV-2 (commonly referred to as COVID-19), the World Health Organization (WHO) declared a global pandemic in March 2020. Referring to the Terror Management Health Model for Pandemics (TMHMP), we obtained qualitative empirical findings to understand real-life experience of customer-facing frontline workers during the pandemic. Customer-facing employees encountered a new challenge in dealing with customers and safeguarding themselves from the spread of virus, while processing anxieties that a heightened state of mortality salience can provoke. Using the TMHMP, we aim to understand how essential frontline employees cope with the fear and anxiety of death during the pandemic. We leverage thematic analysis of interview transcriptions to identify salient themes. We take an interpretative approach to encompass social theories to understand the events from the perspective of the frontline workers. The practical implication of our study is to help employers craft communications for future pandemics in order to better manage employees' emotional and behavioral responses. We contribute to theory by providing the first empirical findings to support the TMHMP;along with novel insight into the nature of Terror Management Theory, including Actionable Proximal Defenses (APD) and Internal Proximal Defenses (IPD).

5.
Bioorg Chem ; 117: 105460, 2021 12.
Article in English | MEDLINE | ID: covidwho-1487614

ABSTRACT

The current pneumonia outbreak, which began in early December 2019 near Wuhan City, Hubei Province, China, is caused by a novel corona virus (CoV) known as '2019-nCoV' or '2019 novel corona virus or COVID-19' by the World Health Organization (WHO). Vaccines are available to prevent corona virus contagious infection or to reduce the viral load in body but virus is continuously mutating itself to infect people at severity. In this critical scenario this review provide a compiled study for techniques and tools that can be used to treat corona virus infections and its variants by some modern techniques and natural products such as inhibitors, siRNA technique and plant based approaches. This review focuses on healthy treatment and strategies that can be used effectively to treat the disease globally by reducing the post COVID symptoms.


Subject(s)
Biological Products/chemistry , Spike Glycoprotein, Coronavirus/antagonists & inhibitors , Angiotensin-Converting Enzyme 2/antagonists & inhibitors , Angiotensin-Converting Enzyme 2/metabolism , Biological Products/metabolism , Biological Products/therapeutic use , COVID-19/drug therapy , COVID-19/pathology , COVID-19/virology , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/metabolism , Humans , Plants/chemistry , Plants/metabolism , RNA, Small Interfering/metabolism , RNA, Small Interfering/therapeutic use , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism
6.
Front Microbiol ; 12: 653399, 2021.
Article in English | MEDLINE | ID: covidwho-1389208

ABSTRACT

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

7.
J Infect Dis ; 224(4): 565-574, 2021 08 16.
Article in English | MEDLINE | ID: covidwho-1358458

ABSTRACT

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing coronavirus disease 2019 (COVID-19), has led to significant morbidity and mortality. While most suffer from mild symptoms, some patients progress to severe disease with acute respiratory distress syndrome (ARDS) and associated systemic hyperinflammation. METHODS: First, to characterize key cytokines and their dynamics in this hyperinflammatory condition, we assessed abundance and correlative expression of a panel of 48 cytokines in patients progressing to ARDS as compared to patients with mild disease. Then, in an ongoing randomized controlled trial of convalescent plasma therapy (CPT), we analyzed rapid effects of CPT on the systemic cytokine dynamics as a correlate for the level of hypoxia experienced by the patients. RESULTS: We identified an anti-inflammatory role of CPT independent of its neutralizing antibody content. CONCLUSIONS: Neutralizing antibodies, as well as reductions in circulating interleukin-6 and interferon-γ-inducible protein 10, contributed to marked rapid reductions in hypoxia in response to CPT. CLINICAL TRIAL REGISTRY OF INDIA: CTRI/2020/05/025209. http://www.ctri.nic.in/.


Subject(s)
COVID-19/immunology , COVID-19/therapy , SARS-CoV-2/immunology , Adult , Anti-Inflammatory Agents/therapeutic use , Antibodies, Neutralizing/immunology , COVID-19/drug therapy , COVID-19/epidemiology , COVID-19/virology , Cytokines/blood , Cytokines/immunology , Female , Humans , Immunization, Passive/methods , India/epidemiology , Male , Middle Aged , Plasma , RNA, Viral/isolation & purification , Respiratory Distress Syndrome/drug therapy , Respiratory Distress Syndrome/immunology , SARS-CoV-2/isolation & purification , Viral Load
8.
Front Microbiol ; 12: 664386, 2021.
Article in English | MEDLINE | ID: covidwho-1323083

ABSTRACT

Human host and pathogen interaction is dynamic in nature and often modulated by co-pathogens with a functional role in delineating the physiological outcome of infection. Co-infection may present either as a pre-existing pathogen which is accentuated by the introduction of a new pathogen or may appear in the form of new infection acquired secondarily due to a compromised immune system. Using diverse examples of co-infecting pathogens such as Human Immunodeficiency Virus, Mycobacterium tuberculosis and Hepatitis C Virus, we have highlighted the role of co-infections in modulating disease severity and clinical outcome. This interaction happens at multiple hierarchies, which are inclusive of stress and immunological responses and together modulate the disease severity. Already published literature provides much evidence in favor of the occurrence of co-infections during SARS-CoV-2 infection, which eventually impacts the Coronavirus disease-19 outcome. The availability of biological models like 3D organoids, mice, cell lines and mathematical models provide us with an opportunity to understand the role and mechanism of specific co-infections. Exploration of multi-omics-based interactions across co-infecting pathogens may provide deeper insights into their role in disease modulation.

9.
Pathogens ; 9(11)2020 Nov 04.
Article in English | MEDLINE | ID: covidwho-909053

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has challenged the research community globally to innovate, interact, and integrate findings across hierarchies. Research on SARS-CoV-2 has produced an abundance of data spanning multiple parallels, including clinical data, SARS-CoV-2 genome architecture, host response captured through transcriptome and genetic variants, microbial co-infections (metagenome), and comorbidities. Disease phenotypes in the case of COVID-19 present an intriguing complexity that includes a broad range of symptomatic to asymptomatic individuals, further compounded by a vast heterogeneity within the spectrum of clinical symptoms displayed by the symptomatic individuals. The clinical outcome is further modulated by the presence of comorbid conditions at the point of infection. The COVID-19 pandemic has produced an expansive wealth of literature touching many aspects of SARS-CoV-2 ranging from causal to outcome, predisposition to protective (possible), co-infection to comorbidity, and differential mortality globally. As challenges provide opportunities, the current pandemic's challenge has underscored the need and opportunity to work for an integrative approach that may be able to thread together the multiple variables. Through this review, we have made an effort towards bringing together information spanning across different domains to facilitate researchers globally in pursuit of their response to SARS-CoV-2.

10.
Environ Sci Pollut Res Int ; 27(29): 37155-37163, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-662493

ABSTRACT

As the whole world is witnessing what novel coronavirus (COVID-19) can do to the mankind, it presents several unique features also. In the absence of specific vaccine for COVID-19, it is essential to detect the disease at an early stage and isolate an infected patient. Till today there is a global shortage of testing labs and testing kits for COVID-19. This paper discusses about the role of machine learning techniques for getting important insights like whether lung computed tomography (CT) scan should be the first screening/alternative test for real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is COVID-19 pneumonia different from other viral pneumonia and if yes how to distinguish it using lung CT scan images from the carefully selected data of lung CT scan COVID-19-infected patients from the hospitals of Italy, China, Moscow and India? For training and testing the proposed system, custom vision software of Microsoft azure based on machine learning techniques is used. An overall accuracy of almost 91% is achieved for COVID-19 classification using the proposed methodology.


Subject(s)
Coronavirus Infections , Machine Learning , Pandemics , Pneumonia, Viral , Tomography, X-Ray Computed , Betacoronavirus , COVID-19 , China , Humans , India , Italy , Moscow , SARS-CoV-2
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