Relationship between Emotional Intelligence and Anxiety among Young Adults

Anxiety is not a new term in the academic and social environment for young adults. From examination anxiety to adjustment problems at higher school, university, and workplace, anxiety has many adverse effects on young adult performance and mental health. Emotional intelligence provides us the ability to deal effectively with mental abnormality and anxiety in a different environment. At the university level, there were young adults of different social, cultural, and economic strata, so the university or workplace environment has a different impact on their level of affiliation and interaction. The present study aims to find out the relationship between these two constructs among young adults. Emotional intelligence level measured by the Kumar, A. I Narain, S. Emotional Intelligence Scale EIS-SANS, National Psychological Corporation (2014). The construct of anxiety level is measured by the Hamilton M. The assessment of anxiety states by rating. Br J Med Psychol 1959; 32:50–55. Two hundred and fourteen (n = 214) young adults from different parts of India constitute the sample of this study out of 214 respondents, 127 males and 87 females respondents between the age range of 20 and 40 years. The collected data were analyzed ANOVA and correlation through SPSS (Version 26). The results revealed that there is a fragile association between emotional intelligence level and level of anxiety; results revealed that there is a negative correlation between emotional intelligence and anxiety (r = −0.061, P < 0.05). The findings of this study have established that there is a significant difference between emotional intelligence and anxiety across gender of young adults, and male respondents had a better emotional intelligence which helps them to cope up with anxiety, female respondents, slightly behind in such condition

Identification and characterization of fusarium mangiferae as pathogen of mango malformation in india

Fusarium mangiferae (=F. subglutinans) isolates collect from malformed samples from major mango-growing area of North India. Molecular identification and characterization of eleven most virulent isolates of F. mangiferae, based on pathogenicity tests used for the present study. Species-specific, genus specific ITS-PCR and PCR-RFLP performed for the accurate and easy detection of F. mangiferae. The rDNA-ITS 28S region sequences used for phylogenetic analysis of Fusarium isolates from India and other countries for homology search between them. The phylogenetic tree divided the isolates into three clades (i.e., American, Asian and African) and showed the high level of sequence based similarity (69-99%) among all Fusarium sequences from Asia. Thus, claimed Fusarium mangiferae as dominant pathogen of mango malformation. Furthermore, we conclude that exploiting the nested PCR coupled with PCR-RFLP will help in rapid and accurate detection of F. mangiferae pathogen of mango malformation

Identification and characterization of Fusarium mangiferae as pathogen of mango malformation in India

ABSTRACT Fusarium mangiferae (=F. subglutinans) isolates collect from malformed samples from major mango-growing area of North India. Molecular identification and characterization of eleven most virulent isolates of F. mangiferae, based on pathogenicity tests used for the present study. Species-specific, genus specific ITS-PCR and PCR-RFLP performed for the accurate and easy detection of F. mangiferae. The rDNA-ITS 28S region sequences used for phylogenetic analysis of Fusarium isolates from India and other countries for homology search between them. The phylogenetic tree divided the isolates into three clades (i.e., American, Asian and African) and showed the high level of sequence based similarity (69-99%) among all Fusarium sequences from Asia. Thus, claimed Fusarium mangiferae as dominant pathogen of mango malformation. Furthermore, we conclude that exploiting the nested PCR coupled with PCR-RFLP will help in rapid and accurate detection of F. mangiferae pathogen of mango malformation

Dataset for: Metabolite assignment of Ultra-Filtered Synovial Fluid extracted from knee joints of Reactive Arthritis patients using High-Resolution NMR spectroscopy

Currently, there are no reliable clinical biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Metabolic profiling of synovial fluid (SF) –obtained from joints affected in ReA- holds great promise in this regard and will further aid monitoring treatment and improving our understanding about disease mechanism. As a first step in this direction, we report here the metabolite specific assignment of 1H and 13C resonances detected in the NMR spectra of SF samples extracted from human patients with established ReA. The metabolite characterization has been carried out on both normal as well as on ultra-filtered (deproteinized) SF samples of eight ReA patients (n=8) using high resolution (800 MHz) 1H and 1H-13C NMR spectroscopy methods such as one-dimensional (1D) 1H CPMG and two-dimensional (2D) J-resolved1H NMR and homonuclear 1H-1H TOCSY and heteronuclear1H-13C HSQC correlation spectra. Compared to normal SF samples, several distinctive 1H NMR signals were identified and assigned to metabolites in the 1H NMR spectra of ultra-filtered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared to normal (un-filtered) SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metabolites will serve to guide future metabolomics studies aiming to identify/evaluate the SF based metabolic biomarkers of diagnostic/prognostic potential or seeking biochemical insights into disease mechanisms in a clinical perspective