SARS-CoV-2: comparison of IgG levels at 9 months post second dose of vaccination in COVID-survivor and COVID-naïve healthcare workers

Background: Natural (asymptomatic/symptomatic COVID-19 infection) and artificial (vaccination) exposure to the pathogen represent two modes of acquiring active immunity. No definitive guidelines exist regarding whether COVID-survivors (with infection/re-infection/re-re-infection in the three COVID-19 waves) require a modified vaccination schedule. Most countries are offering a third vaccine dose and many are contemplating a fourth dose. Our aim was to gauge the IgG-antibody levels 9m post second vaccination in healthcare workers (HCW) and compare these with IgG-levels 1m post-vaccination in the same cohort for any decline, and to compare the post-vaccination IgG-levels in COVID-survivors and COVID-naïve HCW at 9m.Methods: This prospective observational single-centric cohort study included 63 HCW of either sex, aged 18-70y who completed 9m post-vaccination. The IgG-titre was tested at 9-10m post second vaccination in COVID-survivors and COVID-naïve HCW.Results: At 1m and 9m post-vaccination IgG-levels in COVID-survivors (23.097±4.58 and 15.103±4.367 respectively; p<0.0001) and COVID-naïve HCW (16.277±6.36 and 9.793±6.928 respectively; p=0.0013) had unequal variance (Welsch test; p=0.0022 at 9m). 9/31 COVID-naïve HCW but none of the 32 COVID-survivors tested COVID-positive in the second wave post second vaccination. 11/31 and 3/32 HCW belonging to the former and latter groups developed COVID-19 in the third wave consequently deferring their third/precautionary vaccination.Conclusions: Although HCW with IgG-levels in all brackets developed COVID-19, the severity of symptoms corresponded with the IgG-levels. COVID-19 is here to stay, but in peaceful co-existence in endemic proportions. Considering evidence that immunity acquired by vaccination/natural infection is ephemeral, re-invention of vaccines to match the ever-mutating virus is foreseen.

Discovery of miRNAs and Development of Heat-Responsive miRNA-SSR Markers for Characterization of Wheat Germplasm for Terminal Heat Tolerance Breeding

A large proportion of the Asian population fulfills their energy requirements from wheat (Triticum aestivum L.). Wheat quality and yield are critically affected by the terminal heat stress across the globe. It affects approximately 40% of the wheat-cultivating regions of the world. Therefore, there is a critical need to develop improved terminal heat-tolerant wheat varieties. Marker-assisted breeding with genic simple sequence repeats (SSR) markers have been used for developing terminal heat-tolerant wheat varieties; however, only few studies involved the use of microRNA (miRNA)-based SSR markers (miRNASSRs) in wheat, which were found as key players in various abiotic stresses. In the present study, we identified 104 heat-stress-responsive miRNAs reported in various crops. Out of these, 70 miRNA-SSR markers have been validated on a set of 20 terminal heat-tolerant and heat-susceptible wheat genotypes. Among these, only 19 miRNA-SSR markers were found to be polymorphic, which were further used to study the genetic diversity and population structure. The polymorphic miRNA-SSRs amplified 61 SSR loci with an average of 2.9 alleles per locus. The polymorphic information content (PIC) value of polymorphic miRNA-SSRs ranged from 0.10 to 0.87 with a mean value of 0.48. The dendrogram constructed using unweighted neighbor-joining method and population structure analysis clustered these 20 wheat genotypes into 3 clusters. The target genes of these miRNAs are involved either directly or indirectly in providing tolerance to heat stress. Furthermore, two polymorphic markers miR159c and miR165b were declared as very promising diagnostic markers, since these markers showed specific alleles and discriminated terminal heat-tolerant genotypes from the susceptible genotypes. Thus, these identified miRNA-SSR markers will prove useful in the characterization of wheat germplasm through the study of genetic diversity and population structural analysis and in wheat molecular breeding programs aimed at terminal heat tolerance of wheat varieties

Metabolic effects of obesity: A review

With the many recent advances in the biomedical world, vast changes are taking place in our growing knowledge of the physiological aspects of almost all the tissues and organs of the human body. One of the most prevalent topics of discussion is the question of obesity and its effect on the metabolic changes in the human body. The original classical role of adipose tissue as an energy storage organ has been greatly modified. We now know that it is an endocrine organ, producing adipokines like leptin, adiponectin, visfatin, resistin, apelin, etc, which modulate metabolic processes in the body. Since obesity is associated with an increase in the adipose tissue mass, these hormones may be expected to be produced in increased concentrations and may thus have a significant impact on the macronutrient metabolism. Further, these adipokines may interact with long term energy modulators like insulin. Even though the scientific community has started unravelling the mysteries of the close linkage between obesity, its hormones and their physiological effects, a lot still remains to be discovered. The present discussion makes an attempt to trace the basic modern day concepts of the role of obesity in various metabolic processes

International Journal of Pharma and Bio Sciences RESEARCH ARTICLE BIO CHEMISTRY STUDY OF SERUM TOTAL SIALIC ACID LEVEL AND ITS CORRELATION WITH ATHEROGENIC INDEX IN CASES OF ACUTE MYOCARDIAL INFARCTION

Sialic acid, an acylated derivative of nine carbon sugar neuraminic acid. Serum total sialic acid is a cardiovascular risk factor and associated with increased cardiovascular mortality. The present study was planned to explore the role of serum total sialic acid levels and its correlation with atherogenic index in acute myocardial infarction. It was a case controlled study conducted in the Department of Biochemistry, Pt B D Sharma PGIMS, Rohtak. 35 patients of myocardial infarction were placed in study group and 35 healthy volunteers in the control group. Serum Sialic acid was analyzed by Warren’s TBA method. Serum total sialic acid levels were found to be significantly high in study group. A strong positive correlation was observed between atherogenic index and sialic acid levels in study group. Elevation in serum total sialic acid level might result either due to the cell damage after acute myocardial infarction or increase in sialidase activity. This article can be downloaded from www.ijpbs.net B- 8KEY WORDS Sialic acid, acute myocardial infarction, LDL cholesterol, atherogenic index

ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with Pseudo K-Tuple Nucleotide Compositional Features

MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational method for prediction of miRNAs associated with abiotic stresses. Three types of datasets were used for prediction, i.e., miRNA, Pre-miRNA, and Pre-miRNA + miRNA. The pseudo K-tuple nucleotide compositional features were generated for each sequence to transform the sequence data into numeric feature vectors. Support vector machine (SVM) was employed for prediction. The area under receiver operating characteristics curve (auROC) of 70.21, 69.71, 77.94 and area under precision-recall curve (auPRC) of 69.96, 65.64, 77.32 percentages were obtained for miRNA, Pre-miRNA, and Pre-miRNA + miRNA datasets, respectively. Overall prediction accuracies for the independent test set were 62.33, 64.85, 69.21 percentages, respectively, for the three datasets. The SVM also achieved higher accuracy than other learning methods such as random forest, extreme gradient boosting, and adaptive boosting. To implement our method with ease, an online prediction server &ldquo;ASRmiRNA&rdquo; has been developed. The proposed approach is believed to supplement the existing effort for identification of abiotic stress-responsive miRNAs and Pre-miRNAs