Unveiling the microbial diversity and functional dynamics of Shiv Kund, Sohna hot spring, India through a shotgun metagenomics approach.

In this research, we examined the microbial diversity in Sohna hot spring, Haryana, India using shotgun metagenome sequencing based on the Illumina Hiseq 4000 sequencing technology. The raw sequence data from metagenomic paired-end libraries were analysed for taxonomic classification, diversity, and functional annotation using MG-RAST online server. The results showed the presence of total of 57 phyla, 931 genera, and 2068 species, predominantly occupied by Moraxellaceae (Gammaproteobacteria). However, at the species level, we reported the presence of some representative pathogenic taxa, such as Acinetobacter baumannii and Moraxella osloensis. The functional annotation predicted at various levels based on SEED-based subsystem, KEGG ortholog identity (KO), Cluster of Orthologous Groups (COGs) database identified the predominance of genes associated with primary and secondary metabolism along with a crucial role in environmental and genetic signals, cellular communication, and cell signalling. Comparative Genome Analysis (CGA) using The Pathosystem Resource Integration Centre (PATRIC) tool based on genome annotation and assembly of the metagenomic libraries for representative taxon Acinetobacter baumannii (NCBI tax id:470) characterized the reads with a unique genome identifier of 470.20380 (A. baumannii DDLJ4) which is evolutionary closer to A. baumannii ATCC 470.17978 400667.7. In addition, the CARD database results about the presence of potential AMR pathotypes and the prevalence of adeABC, adeIJK, abeM gene-specific clusters that function as multidrug efflux pumps. Overall, the results provided a comprehensive insight into virulence and anti-microbial resistance mechanism and could be useful for developing potential drug targets against the possible AMR pathotypes.

Impact of ABO blood group antigens on residual factor VIII levels and risk of inhibitor development in hemophilia A

Background@#The clinical phenotype of hemophilia A (HA) does not always correlate with severity.Similarly, the presence of inhibitors does not necessarily increase the risk of bleeding.This paradox between clinical and laboratory findings may be partially attributed to non-modifiable factors, such as blood group, which is known to influence FVIII levels in healthy individuals. Our aim was to assess the effect of ABO blood group antigens on FVIII levels across the severity spectrum of HA and risk of inhibitor development. @*Methods@#Data of consecutive patients with HA who visited the coagulation unit of a northern Indian tertiary care hospital between 2010‒2021 were reviewed. Patients with missing blood group data, transfusion histories, or baseline FVIII levels were excluded. @*Results@#Mild, moderate, and severe HA was present in 41 (6.9%), 72 (12.2%), and 479 (80.9%) patients, respectively. There were no differences in the FVIII levels among the various blood groups across the HA severity spectrum. Inhibitors were administered to 35 patients (5.9%). In the multivariate analysis, blood group A was an independent risk factor for the development of inhibitors (adjusted odds ratio 2.70, P =0.04) after adjusting for age at onset of bleeding, FVIII transfusion, age at first FVIII transfusion, and severity of HA. @*Conclusion@#Unlike what is observed in healthy individuals, blood group did not influence residual FVIII levels across the severity spectrum of HA. Patients in group A had a higher risk of developing inhibitors.

A machine learning-based approach to determine infection status in recipients of BBV152 whole virion inactivated SARS-CoV-2 vaccine for serological surveys

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.

Towards sustainable agriculture with carbon sequestration, and greenhouse gas mitigation using algal biochar.

With the increase in the world's population, demand for food and other products is continuously rising. This has put a lot of pressure on the agricultural sector. To fulfill these demands, the utilization of chemical fertilizers and pesticides has also increased. Consequently, to overcome the adverse effects of agrochemicals on our environment and health, there has been a shift towards organic fertilizers or other substitutes, which are ecofriendly and help to maintain a sustainable environment. Microalgae have a very high potential of carbon dioxide (CO2) capturing and thus, help in mitigating the greenhouse effect. It is the most productive biological system for generating biomass. The high growth rate and higher photosynthetic efficiency of the algal species compared to the terrestrial plants make them a wonderful alternative towards a sustainable environment. Moreover, they could be cultivated in photobioreactors or open ponds, which in turn reduce the demand for arable land. Biochar derived from algae is high in nutrients and exhibits the property of ion exchange. Therefore, it can be utilized for sustainable agriculture by partial substituting the chemical fertilizers that degrade the fertility of the soil in the long run. This review provides a detailed insight on the properties of algal biochar as a potential fertilizer for sustainable agriculture. Application of algal biochar in bio-refinery and its economic aspects, challenges faced and future perspective are also discusses in this study.

A comparative study between light transmission aggregometry and flow cytometric platelet aggregation test for the identification of platelet function defects in patients with bleeding

Background@#Platelet aggregation studies using conventional light transmission aggregometry (LTA) have several disadvantages and require strict pre-analytical measures for reliable results.We aimed to examine the utility of flow cytometric platelet aggregation (FCA) assay in detecting platelet function defects (PFDs) in patients with a history of bleeding symptoms. @*Methods@#Sixty-four participants (24 patients and 40 healthy controls) were included in this study.LTA and FCA assay were performed simultaneously in patients and healthy controls. In the FCA assay, two portions of platelets from the same individual were labeled separately with CD31-FITC and CD31-PE. After mixing and stimulation with agonists, the double-colored platelet aggregates were visualized using a flow cytometer. The results generated using the two techniques were compared and correlated. @*Results@#The patients’ median age was 17 years (range, 3‒72 yr) with a male-to-female ratio of 1:1.7. There was substantial agreement between LTA and FCA assay in detecting a PFD (κ=0.792). Four patients showing a Glanzmann thrombasthenia-like pattern on LTA exhibited an abnormal FCA. A functional defect in collagen binding was detected on the FCA assay conducted in two immune thrombocytopenic patients with severe bleeding. @*Conclusion@#FCA assay can be used to identify functional defects in platelets, with potential applications in thrombocytopenic individuals. It also facilitates the diagnosis of inherited bleeding disorders with platelet defects.

A comparative study between light transmission aggregometry and flow cytometric platelet aggregation test for the identification of platelet function defects in patients with bleeding

Background@#Platelet aggregation studies using conventional light transmission aggregometry (LTA) have several disadvantages and require strict pre-analytical measures for reliable results.We aimed to examine the utility of flow cytometric platelet aggregation (FCA) assay in detecting platelet function defects (PFDs) in patients with a history of bleeding symptoms. @*Methods@#Sixty-four participants (24 patients and 40 healthy controls) were included in this study.LTA and FCA assay were performed simultaneously in patients and healthy controls. In the FCA assay, two portions of platelets from the same individual were labeled separately with CD31-FITC and CD31-PE. After mixing and stimulation with agonists, the double-colored platelet aggregates were visualized using a flow cytometer. The results generated using the two techniques were compared and correlated. @*Results@#The patients’ median age was 17 years (range, 3‒72 yr) with a male-to-female ratio of 1:1.7. There was substantial agreement between LTA and FCA assay in detecting a PFD (κ=0.792). Four patients showing a Glanzmann thrombasthenia-like pattern on LTA exhibited an abnormal FCA. A functional defect in collagen binding was detected on the FCA assay conducted in two immune thrombocytopenic patients with severe bleeding. @*Conclusion@#FCA assay can be used to identify functional defects in platelets, with potential applications in thrombocytopenic individuals. It also facilitates the diagnosis of inherited bleeding disorders with platelet defects.

Green technology for sustainable biohydrogen production (waste to energy): A review.

Perceiving and detecting a sustainable source of energy is very critical issue for current modern society. Hydrogen on combustion releases energy and water as a byproduct and has been considered as an environmental pollution free energy carrier. From the last decade, most of the researchers have recommended hydrogen as one of the cleanest fuels and its demand is rising ever since. Hydrogen having the highest energy density is more advantageous than any other fuel. Hydrogen obtained from the fossil fuels produces carbon dioxide as a byproduct and creates environment negative effect. Therefore, biohydrogen production from green algae and cyanobacteria is an attractive option that generates a benign renewable energy carrier. Microalgal feedstocks show a high potential for the generation of fuel such as biohydrogen, bioethanol and biodiesel. This article has reviewed the different methods of biohydrogen production while also trying to find out the most economical and ecofriendly method for its production. A thorough review process has been carried out to study the methods, enzymes involved, factors affecting the rate of hydrogen production, dual nature of algae, challenges and commercialization potential of algal biohydrogen.