The COVID-19 pandemic has strained testing capabilities worldwide. There is an urgent need to find economical and scalable ways to test more people. We present Tapestry, a novel quantitative nonadaptive pooling scheme to test many samples using only a few tests. The underlying molecular diagnostic test is any real-time RT-PCR diagnostic panel approved for the detection of the SARS-CoV-2 virus. In cases where most samples are negative for the virus, Tapestry accurately identifies the status of each individual sample with a single round of testing in fewer tests than simple two-round pooling. We also present a companion Android application BYOM Smart Testing which guides users through the pipetting steps required to perform the combinatorial pooling. The results of the pooled tests can be fed into the application to recover the status and estimated viral load for each individual sample. NOTE: This protocol has been validated with in vitro experiments that used synthetic RNA and DNA fragments and additionally, its expected behavior has been confirmed using computer simulations. Validation with clinical samples is ongoing. We are looking for clinical collaborators with access to patient samples. Please contact the corresponding author if you wish to validate this protocol on clinical samples.
Second wave of COVID 19 pandemic in India came with unexpected quick speed and intensity, creating an acute shortage of beds, ventilators, and oxygen at the peak of occurrence. This may have been partly caused by emergence of new variant delta. Clinical experience with the cases admitted to hospitals suggested that it is not merely a steep rise in cases but also possibly the case profile is different. This study was taken up to investigate the differentials in the characteristics of the cases admitted in the second wave versus those admitted in the first wave. Records of a total of 14398 cases admitted in the first wave (2020) to our network of hospitals in north India and 5454 cases admitted in the second wave (2021) were retrieved, making it the largest study of this kind in India. Their demographic profile, clinical features, management, and outcome was studied. Age sex distribution of the cases in the second wave was not much different from those admitted in the first wave but the patients with comorbidities and those with greater severity had larger share. Level of inflammatory markers was more adverse. More patients needed oxygen and invasive ventilation. ICU admission rate remained nearly the same. On the positive side, readmissions were lower, and the duration of hospitalization was slightly less. Usage of drugs like remdesivir and IVIG was higher while that of favipiravir and tocilizumab was lower. Steroid and anticoagulant use remained high and almost same during the two waves. More patients had secondary bacterial and fungal infections in Wave 2. Mortality increased by almost 40% in Wave 2, particularly in the younger patients of age less than 45 years. Higher mortality was observed in those admitted in wards, ICU, with or without ventilator support and those who received convalescent plasma. No significant demographic differences in the cases in these two waves, indicates the role of other factors such as delta variant and late admissions in higher severity and more deaths. Comorbidity and higher secondary bacterial and fungal infections may have contributed to increased mortality.
Most endangered species exist today in small populations, many of which are isolated. Evolution in such populations is largely governed by genetic drift. Empirical evidence for drift affecting striking phenotypes based on substantial genetic data are rare. Approximately 37% of tigers (Panthera tigris) in the Similipal Tiger Reserve (in eastern India) are pseudomelanistic, characterized by wide, merged stripes. Camera trap data across the tiger range revealed the presence of pseudomelanistic tigers only in Similipal. We investigated the genetic basis for pseudomelanism and examined the role of drift in driving this phenotype's frequency. Whole-genome data and pedigree-based association analyses from captive tigers revealed that pseudomelanism cosegregates with a conserved and functionally important coding alteration in Transmembrane Aminopeptidase Q (Taqpep), a gene responsible for similar traits in other felid species. Noninvasive sampling of tigers revealed a high frequency of the Taqpep p.H454Y mutation in Similipal (12 individuals, allele frequency = 0.58) and absence from all other tiger populations (395 individuals). Population genetic analyses confirmed few (minimal number) tigers in Similipal, and its genetic isolation, with poor geneflow. Pairwise FST (0.33) at the mutation site was high but not an outlier. Similipal tigers had low diversity at 81 single nucleotide polymorphisms (mean heterozygosity = 0.28, SD = 0.27). Simulations were consistent with founding events and drift as possible drivers for the observed stark difference of allele frequency. Our results highlight the role of stochastic processes in the evolution of rare phenotypes. We highlight an unusual evolutionary trajectory in a small and isolated population of an endangered species.
Background: The COVID-19 disease caused by the SARS-CoV-2 virus, has toppled the world since first case noted in 2019, and the cases have been increasing there after. This grave effect is caused by the cytokine storm induced inflammation produced by the noxious virus. As it is an inflammatory state, various acute phase reactants are expected to raise; thus serum ferritin is contemplated to increase. Here we aim to anchor serum ferritin as a way marker for diagnosis and management of COVID-19 patients and study its role as a prognostic marker. Another aspect is the association of COVID-19 with the N: L ratio; observation has stated that higher N: L ratio results in more severe outcome. The study aimed to establish a correlation of COVID-19 severity with serum ferritin in the form of HRCT Score, N: L Ratio and Clinical Outcome in the patients admitted in Intensive Care Unit Result: Out of 200 patients who were admitted in the intensive care unit with COVID-19, the association of serum ferritin with N: L Ratio and HRCT Score was significant, and the association of serum ferritin with clinical outcome in terms of discharged and expired was found to be statistically significant Conclusion: Serum ferritin was found to be a potent marker for clinical outcome in intensive care unit patients in terms of death versus treated. HRCT Score and N:L ratio were found to be correlated with serum ferritin. Therefore, we conclude that serum ferritin may determine the severity of COVID-19 infection and it can be used as a marker for Clinical Outcome thereby making it an often neglected biomarker for predicting prognosis in COVID-19 with most of the physicians focusing mostly on interleukin 6, C Reactive protein and d dimer as a marker of severe COVID infection.
Unprecedented advances in sequencing technology in the past decade allow a better understanding of genetic variation and its partitioning in natural populations. Such inference is critical to conservation: to understand species biology and identify isolated populations. We review empirical population genetics studies of Endangered Bengal tigers within India, where 60–70% of wild tigers live. We assess how changes in marker type and sampling strategy have impacted inferences by reviewing past studies, and presenting three novel analyses including a single-nucleotide polymorphism (SNP) panel, genome-wide SNP markers, and a whole-mitochondrial genome network. At a broad spatial scale, less than 100 SNPs revealed the same patterns of population clustering as whole genomes (with the exception of one additional population sampled only in the SNP panel). Mitochondrial DNA indicates a strong structure between the northeast and other regions. Two studies with more populations sampled revealed further substructure within Central India. Overall, the comparison of studies with varied marker types and sample sets allows more rigorous inference of population structure. Yet sampling of some populations is limited across all studies, and these should be the focus of future sampling efforts. We discuss challenges in our understanding of population structure, and how to further address relevant questions in conservation genetics. This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.
Introduction: SARSCoV2 infection increases the risk of secondary bacterial and fungal infections and contributes to adverse outcomes. The present study was undertaken to get better insights into the extent of secondary bacterial and fungal infections in Indian hospitalized patients and to assess how these alter the course of COVID19 so that the control measures can be suggested. Methods: This is a retrospective multicentre study where data of all RTPCR positive COVID19 patients was accessed from Electronic Health Records (EHR) of a network of 10 hospitals across 5 North Indian states admitted during the period from March 2020 to July 2021.The data included demographic profile of patients, clinical characteristics, laboratory parameters treatment modalities and outcome in those with secondary infections (SIs) and those without SIs. Spectrum of SIS was also studied in detail. Results: Of 19852 RTPCR positive SARSCO2 patients admitted during the study period, 1940 (9.8%) patients developed SIs. Patients with SIs were 8 years older on average (median age 62.6 years versus 54.3 years P<0.001) than those without SIs. The risk of SIs was significantly (p < 0.001) associated with age, severity of disease at admission, diabetes, ICU admission, and ventilator use. The most common site of infection was urinary tract infection (UTI) (41.7%), followed by blood stream infection (BSI) (30.8%), sputum/BAL/ET fluid (24.8%), and the least was pus/wound discharge (2.6%). As many as 13.4% had infections with more than organism and 34.1% patients had positive cultures from more than one site. Gram negative bacilli (GNB) were the commonest organisms (63.2%), followed by Gram positive cocci (GPC) (19.6%) and fungus (17.3%). Most of the patients with SIs were on multiple antimicrobials the most commonly used were the BL BLI for GNBs (76.9%) followed by carbapenems (57.7%), cephalosporins (53.9%) and antibiotics carbapenem resistant entreobacteriace (47.1%). The usage of emperical antibiotics for GPCs was in 58.9% and of antifungals in 56.9% of cases, and substantially more than the results obtained by culture. The average stay in hospital for patients with SIs was twice than those without SIs (median 13 days versus 7 days). The overall mortality in the group with SIs (40.3%) was more than 8 times of that in those without SIs (4.6%). Only 1.2% of SI patients with mild COVID 19 at presentation died, while 17.5% of those with moderate disease and 58.5% of those with severe COVID 19 died (P< 0.001). The mortality was highest in those with BSI (49.8%), closely followed by those with HAP (47.9%), and then UTI and SSTI (29.4% each). The mortality rate where only one microorganism was identified was 37.8% and rose to 56.3% in those with more than one microorganism. The mortality in cases with only one site of infection was 28.8%, which steeply rose to 62.5% in cases with multiple sites of infection. The mortality in diabetic patients with SIs was 45.2% while in non-diabetics it was 34.3% (p < 0.001). Conclusions: Secondary bacterial and fungal infections can complicate the course of almost 10% of COVID19 hospitalised patients. These patients tend to not only have a much longer stay in hospital, but also a higher requirement for oxygen and ICU care. The mortality in this group rises steeply by as much as 8 times. The group most vulnerable to this complication are those with more severe COVID19 illness, elderly, and diabetic patients. Varying results in different studies suggest that a region or country specific guideline be developed for appropriate use of antibiotics and antifungals to prevent their overuse in such cases. Judicious empiric use of combination antimicrobials in this set of vulnerable COVID19 patients can save lives.
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