scholarly journals Emergence of Novel SARS-CoV-2 variants in India: second wave

2021 ◽  
Vol 15 (11) ◽  
pp. 1578-1583
Author(s):  
Rama Adiga ◽  
Varun Nayak
Keyword(s):  
Indian Subcontinent ◽  
Asian Countries ◽  
Sample Collection ◽  
High Coverage ◽  
Time Period ◽  
Indian State ◽  
Rapid Pace ◽  
Global Initiative ◽  
Second Wave

Introduction: Globally South-East Asia reported 40% of SARS-CoV-2 infected cases in the fourth week of April 2021. It continued to show an increase with India accounting for 50% of cases worldwide and 30% of global deaths. Genomic surveillance should continue at a rapid pace because of the continuously evolving nature of the virus. The time period of sample collection from the Global Initiative on Sharing All Influenza Data database was concurrent with the surge in new cases seen in the Indian subcontinent. Methodology: 7,415 sequences were downloaded from Global Initiative on Sharing All Influenza Data between January and April 2021; out of which 4,411 were high coverage genome sequences and were considered for analysis. Phylogenetic analysis were carried out using Nextstrain. Results: 21A or B.1.617 or delta was the most prevalent lineage in India accounting for 67.7% of the genomes. Next important clades were 20A, 20B and 20I accounting for 23.6%, 11.8% and 12.1% respectively collected between January 2021 and April 2021. The remaining sequences were assigned to clade 20H, 20J, 20D, 20C, 20G,20E,19A and 19B.The spike mutation frequencies of L452R, E484Q and P681R in Indian state of Maharashtra were 62.4%, 66.5% and 61.5% respectively. Two unique N-terminal domain deletion of spike protein were found at position 67 and 68. Conclusions: The phylogenomics of the delta variant or 21A emerged in neighboring Asian countries of Thailand, Bangladesh, Indonesia and Japan. We analyzed the SARS-CoV-2 genomes from India for mutation characterization of the spike glycoprotein and the nucleocapsid protein.

scholarly journals “At Least until the Second Wave Comes…”: A Twitter Analysis of the NHS and COVID-19 between March and June 2020

2021 ◽  
Vol 18 (8) ◽  
pp. 3943
Author(s):  
Kathy McKay ◽  
Sarah Wayland ◽  
David Ferguson ◽  
Jane Petty ◽  
Eilis Kennedy
Keyword(s):  
Health Care ◽  
Social Media ◽  
Content Analysis ◽  
Well Being ◽  
Profound Impact ◽  
Time Period ◽  
Twitter Analysis ◽  
The Uk ◽  
Media Narratives ◽  
Second Wave

In the UK, tweets around COVID-19 and health care have primarily focused on the NHS. Recent research has identified that the psychological well-being of NHS staff has been adversely impacted as a result of the COVID-19 pandemic. The aim of this study was to investigate narratives relating to the NHS and COVID-19 during the first lockdown (26 March–4 July 2020). A total of 123,880 tweets were collated and downloaded bound to the time period of the first lockdown in order to analyse the real-time discourse around COVID-19 and the NHS. Content analysis was undertaken and tweets were coded to positive and negative sentiments. Five main themes were identified: (1) the dichotomies of ‘clap for carers’; (2) problems with PPE and testing; (3) peaks of anger; (4) issues around hero worship; and (5) hints of a normality. Further research exploring and documenting social media narratives around COVID-19 and the NHS, in this and subsequent lockdowns, should help in tailoring suitable support for staff in the future and acknowledging the profound impact that the pandemic has had.

scholarly journals Application of artificial intelligence in pancreaticobiliary diseases

2021 ◽  
Vol 14 ◽  
pp. 263177452199305
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Zhongheng Zhang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Response To Treatment ◽  
Endoscopic Retrograde ◽  
Artificial Intelligence Techniques ◽  
Computer Aided ◽  
Rapid Pace ◽  
Cystic Pancreatic Lesions ◽  
Aided Diagnosis

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.

scholarly journals Influence of the COVID-19 Pandemic on Dental Emergency Admissions in an Urgent Dental Care Service in North Italy

2021 ◽  
Vol 18 (4) ◽  
pp. 1812 ◽  
Author(s):  
Maria Grazia Cagetti ◽  
Araxi Balian ◽  
Nicole Camoni ◽  
Guglielmo Campus
Keyword(s):  
Retrospective Study ◽  
Dental Care ◽  
Tooth Extraction ◽  
Care Service ◽  
Emergency Admissions ◽  
Exact Test ◽  
Remarkable Increase ◽  
Time Period ◽  
Dental Emergency ◽  
Second Wave

A retrospective study was performed to verify if the number of admissions for urgent dental care in the Urgent Dental Care Service of San Paolo Hospital in Milan (Italy) was directly related to the different phases of the COVID-19 pandemic. Different periods were analyzed: 25 March–5 April 2019 (pre-COVID); 23 March–3 April 2020 (lockdown); 8 June–19 June 2020 (reopening); and November 9–November 20 (second wave). Raw data regarding admissions, diagnoses, and treatments were extracted. Descriptive and bivariate analyses were performed. The survey included 901 admissions, 285 in pre-COVID, 93 during lockdown, 353 in reopening, and 170 in the second wave. In each time period, statistically significant differences were found in the prevalence of each kind of diagnoses (χ2(3) = 20.33 p = 0.01 for endodontic emergencies, χ2(3) = 29.05 p < 0.01 for cellulitis/phlegmon, χ2(3) = 28.55 p < 0.01 for periodontal emergencies, Fisher’s Exact Test p < 0.01 for trauma, and χ2(3) = 59.94 p < 0.01 for all other kinds of diagnosis). A remarkable increase in consultations (+186.36%) and other treatments (+90.63%) occurred during reopening. Tooth extraction was the most frequently delivered treatment, but suffered the largest reduction during lockdown (−79.82%). The COVID-19 pandemic has highly affected dental activity in north Italy, underling the weaknesses of a private dental system in a pandemic scenario.

scholarly journals Identification and Characterization of a Halotolerant, Cold-Active Marine Endo-β-1,4-Glucanase by Using Functional Metagenomics of Seaweed-Associated Microbiota

2014 ◽  
Vol 80 (16) ◽  
pp. 4958-4967 ◽  
Author(s):  
Marjolaine Martin ◽  
Sophie Biver ◽  
Sébastien Steels ◽  
Tristan Barbeyron ◽  
Murielle Jam ◽  
...  
Keyword(s):  
Metagenomic Library ◽  
Functional Screening ◽  
Sample Collection ◽  
Prolonged Incubation ◽  
Content Type ◽  
Cold Active ◽  
Esterase Loci ◽  
Collection Period ◽  
Identification And Characterization

ABSTRACTA metagenomic library was constructed from microorganisms associated with the brown algaAscophyllum nodosum. Functional screening of this library revealed 13 novel putative esterase loci and two glycoside hydrolase loci. Sequence and gene cluster analysis showed the wide diversity of the identified enzymes and gave an idea of the microbial populations present during the sample collection period. Lastly, an endo-β-1,4-glucanase having less than 50% identity to sequences of known cellulases was purified and partially characterized, showing activity at low temperature and after prolonged incubation in concentrated salt solutions.

scholarly journals Detection and characterization of the SARS-CoV-2 lineage B.1.526 in New York

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Anthony P. West ◽  
Joel O. Wertheim ◽  
Jade C. Wang ◽  
Tetyana I. Vasylyeva ◽  
Jennifer L. Havens ◽  
...  
Keyword(s):  
New York ◽  
Viral Evolution ◽  
Software Tool ◽  
Neutralization Titer ◽  
The Public ◽  
Wide Scale ◽  
Health Relevance ◽  
Second Wave ◽  
Variant Database

AbstractWide-scale SARS-CoV-2 genome sequencing is critical to tracking viral evolution during the ongoing pandemic. We develop the software tool, Variant Database (VDB), for quickly examining the changing landscape of spike mutations. Using VDB, we detect an emerging lineage of SARS-CoV-2 in the New York region that shares mutations with previously reported variants. The most common sets of spike mutations in this lineage (now designated as B.1.526) are L5F, T95I, D253G, E484K or S477N, D614G, and A701V. This lineage was first sequenced in late November 2020. Phylodynamic inference confirmed the rapid growth of the B.1.526 lineage. In concert with other variants, like B.1.1.7, the rise of B.1.526 appears to have extended the duration of the second wave of COVID-19 cases in NYC in early 2021. Pseudovirus neutralization experiments demonstrated that B.1.526 spike mutations adversely affect the neutralization titer of convalescent and vaccinee plasma, supporting the public health relevance of this lineage.

scholarly journals The history of introduction of the African baobab ( Adansonia digitata , Malvaceae: Bombacoideae) in the Indian subcontinent

2015 ◽  
Vol 2 (9) ◽  
pp. 150370 ◽  
Author(s):  
Karen L. Bell ◽  
Haripriya Rangan ◽  
Christian A. Kull ◽  
Daniel J. Murphy
Keyword(s):  
West Africa ◽  
Indian Subcontinent ◽  
Central India ◽  
Adansonia Digitata ◽  
Multiple Introductions ◽  
Human Interactions ◽  
Time Period ◽  
History Of ◽  
Genetic Clusters ◽  
Southeast India

To investigate the pathways of introduction of the African baobab, Adansonia digitata , to the Indian subcontinent, we examined 10 microsatellite loci in individuals from Africa, India, the Mascarenes and Malaysia, and matched this with historical evidence of human interactions between source and destination regions. Genetic analysis showed broad congruence of African clusters with biogeographic regions except along the Zambezi (Mozambique) and Kilwa (Tanzania), where populations included a mixture of individuals assigned to at least two different clusters. Individuals from West Africa, the Mascarenes, southeast India and Malaysia shared a cluster. Baobabs from western and central India clustered separately from Africa. Genetic diversity was lower in populations from the Indian subcontinent than in African populations, but the former contained private alleles. Phylogenetic analysis showed Indian populations were closest to those from the Mombasa-Dar es Salaam coast. The genetic results provide evidence of multiple introductions of African baobabs to the Indian subcontinent over a longer time period than previously assumed. Individuals belonging to different genetic clusters in Zambezi and Kilwa may reflect the history of trafficking captives from inland areas to supply the slave trade between the fifteenth and nineteenth centuries. Baobabs in the Mascarenes, southeast India and Malaysia indicate introduction from West Africa through eighteenth and nineteenth century European colonial networks.

scholarly journals Women Serial Killers in a Climate of Changing Gender Norms

2018 ◽  
Author(s):  
Elizabeth Benkart
Keyword(s):  
Multivariate Regression ◽  
Gulf Coast ◽  
Gender Norms ◽  
Serial Killer ◽  
Serial Killers ◽  
Florida Gulf Coast ◽  
Time Period ◽  
American Society ◽  
Second Wave ◽  
The Waves

Existing research suggests that patterns of both men and women serial killers are hyper-gendered. In American society, however, gender norms for women have dramatically changed over time. This study proposes that the patterns of women serial killers reflect the femininity ideals of the time period in which they operated in. The shifts in gender norms are operationalized by three time periods representative of the waves of feminism. The Radford/Florida Gulf Coast University’s serial killer database is used to establish a sample of 1,321 serial killers. Using multivariate regression analyses and controlling for age of last kill, which could potentially alter the kill method but be unrelated to gender, women serial killers do appear to be impacted by the femininity ideals of their time period but not as clearly as initially anticipated. Men serial killers were also found to be affected by changes in femininity ideals. Both women and men serial killers had more feminine kill patterns during the first wave of feminism, but men serial killers had a very violent, hyper-masculine peak during the second wave of feminism that women serial killers did not have.

scholarly journals The hydrological response of baseflow in fractured mountain areas

2009 ◽  
Vol 6 (2) ◽  
pp. 3359-3384 ◽  
Author(s):  
A. Millares ◽  
M. J. Polo ◽  
M. A. Losada
Keyword(s):  
Hydrological Model ◽  
Water System ◽  
Essential Element ◽  
Mediterranean Area ◽  
Mountainous Areas ◽  
Mountain Areas ◽  
Linear Behavior ◽  
Time Period ◽  
Recession Curves

Abstract. The study of baseflow in mountainous areas of basin headwaters, where the characteristics of the often fractured materials are very different to the standard issues concerning porous material applied in conventional hydrogeology, is an essential element in the characterization and quantification of water system resources. Their analysis through recession fragments provides information on the type of response of the sub-surface and subterranean systems and on the average relation between the storage and discharge of aquifers, starting from the joining of these fragments into a single curve, the Master Recession Curve (MRC). This paper presents the generation of the downward MRC over fragments selected after a preliminary analysis of the recession curves, using a hydrological model as the methodology for the identification and the characterization of quick sub-surface flows flowing through fractured materials. The hydrological calculation has identified recession fragments through surface runoff or snowmelt and those periods of intense evapotranspiration. The proposed methodology has been applied to three sub-basins belonging to a high altitude mountain basin in the Mediterranean area, with snow present every year, and their results were compared with those for the upward concatenation of the recession fragments. The results show the existence of two different responses, one quick (at the sub-surface, through the fractured material) and the other slow, with linear behavior which takes place in periods of 10 and 17 days, respectively and which is linked to the dimensions of the sub-basin. In addition, recesses belonging to the dry season have been selected in order to compare and validate the results corresponding to the study of recession fragments. The comparison, using these two methodologies, which differ in the time period selected, has allowed us to validate the results obtained for the slow flow.

scholarly journals A Data Driven Change-point Epidemic Model for Assessing the Impact of Large Gathering and Subsequent Movement Control Order on COVID-19 Spread in Malaysia

2020 ◽  
Author(s):  
Sarat C. Dass ◽  
Wai M. Kwok ◽  
Gavin J. Gibson ◽  
Balvinder S. Gill ◽  
Bala M. Sundram ◽  
...  
Keyword(s):  
Change Point ◽  
Movement Control ◽  
Disease Spread ◽  
Time Period ◽  
Before And After ◽  
Quantitative Understanding ◽  
Control Order ◽  
Short Time ◽  
The Impact ◽  
Second Wave

AbstractThe second wave of COVID-19 in Malaysia is largely attributed to a mass gathering held in Sri Petaling between February 27, 2020 and March 1, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model the before and after disease dynamics, and is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implemention within a short time period.

Sign in / Sign up

Export Citation Format

Share Document