Role of atmospheric stability over the Arabian Sea and the unprecedented failure of monsoon 2002

The anomalous behaviour of the monsoon 2002 has been studied. We have made an attempt to combine satellite and other data sources to characterize the thermal stratification over the Arabian Sea during different phases of monsoon 2002. Using NOAA-ATOVSderived atmospheric temperature and moisture profiles, we have calculated a daily stability index (SI) over the entire Indian region and surrounding oceans. The time series of SI clearly brings out the three major significant epochs of monsoon 2002. The relatively dry atmosphere west of 65° E, signifying lack of convection and an unstable atmosphere over the southeast Arabian Sea with west-to-east gradients in water vapour, SI and cloud liquid water content are noted. The unfavourable stratification during July over the entire Arabian Sea has been investigated in detail. The dominant modes of instability oscillations have been seen to be ~ 30 days both over the western and eastern Arabian Sea, while for the high-frequency modes preference was seen over the eastern part. Using the analysed fields of the National Centre for Medium Range Weather Forecasts, the relative contributions of advective and subsidence components in the maintenance of stratification have been investigated. The latter has been found to have played a more dominant role in the deficit monsoon 200

A Review on Ashwagandha Ghrita

Ashwagandha (Withania somnifera (L) Family - Solanaceae) known as Indian ginseng is an effective immunomodulator, aphrodisiac, sedative and adaptogen. Ashwagandha Ghrita is a ghee based Ayurvedic formulation which is available in the market, but Ashwagandha Ghrita containing Rasasindura and Tamra Bhasma along with Ashwagandha and Musta Churna is also mentioned in classical text which many of us are not aware of. As we all know that the action of Rasaushadhis are quick and require very less dose the one mentioned by Vagbhatacharya (author of Rasaratnasamuchaya) is the need of the hour for the immunomodulation

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence.Comment: 8 pages plus references, 3 figures, 2 tables. Submission to the ABCD Neurocognitive Prediction Challenge at MICCAI 201

Pre-processing and differential expression analysis of Agilent microRNA arrays using the AgiMicroRna Bioconductor library

<p>Abstract</p> <p>Background</p> <p>The main research tool for identifying microRNAs involved in specific cellular processes is gene expression profiling using microarray technology. Agilent is one of the major producers of microRNA arrays, and microarray data are commonly analyzed by using R and the functions and packages collected in the Bioconductor project. However, an analytical package that integrates the specific characteristics of microRNA Agilent arrays has been lacking.</p> <p>Results</p> <p>This report presents the new bioinformatic tool <it>AgiMicroRNA </it>for the pre-processing and differential expression analysis of Agilent microRNA array data. The software is implemented in the open-source statistical scripting language R and is integrated in the Bioconductor project (<url>http://www.bioconductor.org</url>) under the GPL license. For the pre-processing of the microRNA signal, <it>AgiMicroRNA </it>incorporates the <it>robust multiarray average algorithm</it>, a method that produces a summary measure of the microRNA expression using a linear model that takes into account the probe affinity effect. To obtain a normalized microRNA signal useful for the statistical analysis, <it>AgiMicroRna </it>offers the possibility of employing either the processed signal estimated by the <it>robust multiarray average algorithm </it>or the processed signal produced by the Agilent image analysis software. The <it>AgiMicroRNA </it>package also incorporates different graphical utilities to assess the quality of the data. <it>AgiMicroRna </it>uses the linear model features implemented in the <it>limma </it>package to assess the differential expression between different experimental conditions and provides links to the <it>miRBase </it>for those microRNAs that have been declared as significant in the statistical analysis.</p> <p>Conclusions</p> <p><it>AgiMicroRna </it>is a rational collection of Bioconductor functions that have been wrapped into specific functions in order to ease and systematize the pre-processing and statistical analysis of Agilent microRNA data. The development of this package contributes to the Bioconductor project filling the gap in microRNA array data analysis.</p

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci.

Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases and 882 controls, and the follow-up investigation of the top GWA results was performed in independent Danish (1396 cases and 1803 controls) and German-Dutch (1169 cases, 3714 controls) samples. The SNPs most strongly associated in the single-marker analysis of the combined Danish samples were rs4757144 in ARNTL (P=3.78 × 10(-6)) and rs8057927 in CDH13 (P=1.39 × 10(-5)). Both genes have previously been linked to schizophrenia or other psychiatric disorders. The strongest associated SNP in the combined analysis, including Danish and German-Dutch samples, was rs12922317 in RUNDC2A (P=9.04 × 10(-7)). A region-based analysis summarizing independent signals in segments of 100 kb identified a new region-based genome-wide significant locus overlapping the gene ZEB1 (P=7.0 × 10(-7)). This signal was replicated in the follow-up analysis (P=2.3 × 10(-2)). Significant interaction with maternal CMV infection was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies

Mechanistic model of natural killer cell proliferative response to IL-15 receptor stimulation

Natural killer (NK) cells are innate lymphocytes that provide early host defense against intracellular pathogens, such as viruses. Although NK cell development, homeostasis, and proliferation are regulated by IL-15, the influence of IL-15 receptor (IL-15R)-mediated signaling at the cellular level has not been quantitatively characterized. We developed a mathematical model to analyze the kinetic interactions that control the formation and localization of IL-15/IL-15R complexes. Our computational results demonstrated that IL-15/IL-15R complexes on the cell surface were a key determinant of the magnitude of the IL-15 proliferative signal and that IL-15R occupancy functioned as an effective surrogate measure of receptor signaling. Ligand binding and receptor internalization modulated IL-15R occupancy. Our work supports the hypothesis that the total number and duration of IL-15/IL-15R complexes on the cell surface crosses a quantitative threshold prior to the initiation of NK cell division. Furthermore, our model predicted that the upregulation of IL-15Rα on NK cells substantially increased IL-15R complex formation and accelerated the expansion of dividing NK cells with the greatest impact at low IL-15 concentrations. Model predictions of the threshold requirement for NK cell recruitment to the cell cycle and the subsequent exponential proliferation correlated well with experimental data. In summary, our modeling analysis provides quantitative insight into the regulation of NK cell proliferation at the receptor level and provides a framework for the development of IL-15 based immunotherapies to modulate NK cell proliferation

Pathogenesis of HIV in the Central Nervous System

HIV can infect the brain and impair central nervous system (CNS) function. Combination antiretroviral therapy (cART) has not eradicated CNS complications. HIV-associated neurocognitive disorders (HAND) remain common despite cART, although attenuated in severity. This may result from a combination of factors including inadequate treatment of HIV reservoirs such as circulating monocytes and glia, decreased effectiveness of cART in CNS, concurrent illnesses, stimulant use, and factors associated with prescribed drugs, including antiretrovirals. This review highlights recent investigations of HIV-related CNS injury with emphasis on cART-era neuropathological mechanisms in the context of both US and international settings

Consumer perceptions of co-branding alliances: Organizational dissimilarity signals and brand fit

This study explores how consumers evaluate co-branding alliances between dissimilar partner firms. Customers are well aware that different firms are behind a co-branded product and observe the partner firms’ characteristics. Drawing on signaling theory, we assert that consumers use organizational characteristics as signals in their assessment of brand fit and for their purchasing decisions. Some organizational signals are beyond the control of the co-branding partners or at least they cannot alter them on short notice. We use a quasi-experimental design and test how co-branding partner dissimilarity affects brand fit perception. The results show that co-branding partner dissimilarity in terms of firm size, industry scope, and country-of-origin image negatively affects brand fit perception. Firm age dissimilarity does not exert significant influence. Because brand fit generally fosters a benevolent consumer attitude towards a co-branding alliance, the findings suggest that high partner dissimilarity may reduce overall co-branding alliance performance

Multiancestry Study of Gene-Lifestyle Interactions for Cardiovascular Traits in 610 475 Individuals From 124 Cohorts Design and Rationale

Background— Several consortia have pursued genome-wide association studies for identifying novel genetic loci for blood pressure, lipids, hypertension, etc. They demonstrated the power of collaborative research through meta-analysis of study-specific results. Methods and Results— The Gene-Lifestyle Interactions Working Group was formed to facilitate the first large, concerted, multiancestry study to systematically evaluate gene–lifestyle interactions. In stage 1, genome-wide interaction analysis is performed in 53 cohorts with a total of 149 684 individuals from multiple ancestries. In stage 2 involving an additional 71 cohorts with 460 791 individuals from multiple ancestries, focused analysis is performed for a subset of the most promising variants from stage 1. In all, the study involves up to 610 475 individuals. Current focus is on cardiovascular traits including blood pressure and lipids, and lifestyle factors including smoking, alcohol, education (as a surrogate for socioeconomic status), physical activity, psychosocial variables, and sleep. The total sample sizes vary among projects because of missing data. Large-scale gene–lifestyle or more generally gene–environment interaction (G×E) meta-analysis studies can be cumbersome and challenging. This article describes the design and some of the approaches pursued in the interaction projects. Conclusions— The Gene-Lifestyle Interactions Working Group provides an excellent framework for understanding the lifestyle context of genetic effects and to identify novel trait loci through analysis of interactions. An important and novel feature of our study is that the gene–lifestyle interaction (G×E) results may improve our knowledge about the underlying mechanisms for novel and already known trait loci