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9 results on '"Mandaviya P"'

1. An Empirical Study on Financial Performance Analysis of selected Equity stocks of Indian Pharmaceutical Industry.

Author

Raval, Navjyot, Mandaviya, Meeta, and Gajera, Alpesh

Subjects
FINANCIAL performance, CORPORATE finance, PHARMACEUTICAL industry, DRUG factories, PERFORMANCE theory
Abstract

The Indian pharmaceutical industry currently tops India’s science-based industries with wide-ranging capabilities in the complex field of drug manufacture and technology. The pharmaceutical industry in India is the world’s third-largest in terms of volume and stands 14th in terms of value. India’s pharmaceutical market grew at 11.7 percent during December 2018. The Indian pharmaceutical industry is expected to grow at a rate of 9.9 percent till 2010 and after that 13.5 percent till 2019. The presentation of the organization can be estimated by its monetary adequacy, i.e., by its size of income Riskiness and productivity are two fundamental variables that mutually direct the estimation of the worry. The drug business in India meets around 70% of the nation's interest in mass medications, drug intermediates, drug definitions, synthetics, tablets, cases, orals, and injectables. There has been a huge conversation about a definitive target of the organization's exhibition, regardless of whether it should be a benefit boost or it should be abundance amplification. It is seen that while seeing the organization's exhibition, the benefit and abundance boost are connected and are influenced by each other. This examination pointed toward inspecting the monetary exhibition of chose value supplies of the Indian drug industry for the investigation time of a long time from 2009 to 2019. The Indian drug market is required to contact US$ 74 billion deals by 2020 from US$ 11 billion. [ABSTRACT FROM AUTHOR]

Published
2021
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2. Does Gender Matter? Job Stress, Work-Life Balance, Health and Job Satisfaction among University Teachers in India.

Author

Solanki, Sandip and Mandaviya, Meeta

Subjects
JOB stress, WORK-life balance, JOB satisfaction, PSYCHOLOGY of college teachers, INDIAN women (Asians)
Abstract

This study investigates gender differences in the perceived level of stress of university instructors in India. An online cross-sectional survey was completed with 86 respondents comprised of 51 males and 35 females in the state of Gujarat. Results indicate that job stress on work-life balance is significantly stronger for females. Additionally, male respondents scored higher in managing anger at work compared with female respondents and reveal a stronger detachment with work. Further, male respondents have more health-related issues compared with females due to job stress and imbalance in work life, while females exhibit lower career resilience due to family characteristics and responsibilities. This research contributes to the research on work-life balance specific to the teaching profession. Originality/value: To the best of the author's knowledge this study is unique and different from other studies as this is the first study concerning India. [ABSTRACT FROM AUTHOR]

Published
2021

3. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Author

Min, Josine L., Hemani, Gibran, Hannon, Eilis, Dekkers, Koen F., Castillo-Fernandez, Juan, Luijk, René, Carnero-Montoro, Elena, Lawson, Daniel J., Burrows, Kimberley, Suderman, Matthew, Bretherick, Andrew D., Richardson, Tom G., Klughammer, Johanna, Iotchkova, Valentina, Sharp, Gemma, Al Khleifat, Ahmad, Shatunov, Aleksey, Iacoangeli, Alfredo, McArdle, Wendy L., Ho, Karen M., Kumar, Ashish, Söderhäll, Cilla, Soriano-Tárraga, Carolina, Giralt-Steinhauer, Eva, Kazmi, Nabila, Mason, Dan, McRae, Allan F., Corcoran, David L., Sugden, Karen, Kasela, Silva, Cardona, Alexia, Day, Felix R., Cugliari, Giovanni, Viberti, Clara, Guarrera, Simonetta, Lerro, Michael, Gupta, Richa, Bollepalli, Sailalitha, Mandaviya, Pooja, Zeng, Yanni, Clarke, Toni-Kim, Walker, Rosie M., Schmoll, Vanessa, Czamara, Darina, Ruiz-Arenas, Carlos, Rezwan, Faisal I., Marioni, Riccardo E., Lin, Tian, Awaloff, Yvonne, Germain, Marine, Aïssi, Dylan, Zwamborn, Ramona, van Eijk, Kristel, Dekker, Annelot, van Dongen, Jenny, Hottenga, Jouke-Jan, Willemsen, Gonneke, Xu, Cheng-Jian, Barturen, Guillermo, Català-Moll, Francesc, Kerick, Martin, Wang, Carol, Melton, Phillip, Elliott, Hannah R., Shin, Jean, Bernard, Manon, Yet, Idil, Smart, Melissa, Gorrie-Stone, Tyler, Shaw, Chris, Al Chalabi, Ammar, Ring, Susan M., Pershagen, Göran, Melén, Erik, Jiménez-Conde, Jordi, Roquer, Jaume, Lawlor, Deborah A., Wright, John, Martin, Nicholas G., Montgomery, Grant W., Moffitt, Terrie E., Poulton, Richie, Esko, Tõnu, Milani, Lili, Metspalu, Andres, Perry, John R. B., Ong, Ken K., Wareham, Nicholas J., Matullo, Giuseppe, Sacerdote, Carlotta, Panico, Salvatore, Caspi, Avshalom, Arseneault, Louise, Gagnon, France, Ollikainen, Miina, Kaprio, Jaakko, Felix, Janine F., Rivadeneira, Fernando, Tiemeier, Henning, van IJzendoorn, Marinus H., Uitterlinden, André G., Jaddoe, Vincent W. V., Haley, Chris, McIntosh, Andrew M., Evans, Kathryn L., Murray, Alison, Räikkönen, Katri, Lahti, Jari, Nohr, Ellen A., Sørensen, Thorkild I. A., Hansen, Torben, Morgen, Camilla S., Binder, Elisabeth B., Lucae, Susanne, Gonzalez, Juan Ramon, Bustamante, Mariona, Sunyer, Jordi, Holloway, John W., Karmaus, Wilfried, Zhang, Hongmei, Deary, Ian J., Wray, Naomi R., Starr, John M., Beekman, Marian, van Heemst, Diana, Slagboom, P. Eline, Morange, Pierre-Emmanuel, Trégouët, David-Alexandre, Veldink, Jan H., Davies, Gareth E., de Geus, Eco J. C., Boomsma, Dorret I., Vonk, Judith M., Brunekreef, Bert, Koppelman, Gerard H., Alarcón-Riquelme, Marta E., Huang, Rae-Chi, Pennell, Craig E., van Meurs, Joyce, Ikram, M. Arfan, Hughes, Alun D., Tillin, Therese, Chaturvedi, Nish, Pausova, Zdenka, Paus, Tomas, Spector, Timothy D., Kumari, Meena, Schalkwyk, Leonard C., Visscher, Peter M., Davey Smith, George, Bock, Christoph, Gaunt, Tom R., Bell, Jordana T., Heijmans, Bastiaan T., Mill, Jonathan, and Relton, Caroline L.

Abstract

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15–17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype–phenotype map than previously anticipated.

Published
2021
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4. Epigenetic Signatures of Cigarette Smoking.

Author

Joehanes, Roby, Just, Allan C., Marioni, Riccardo E., Pilling, Luke C., Reynolds, Lindsay M., Mandaviya, Pooja R., Weihua Guan, Tao Xu, Elks, Cathy E., Aslibekyan, Stella, Moreno-Macias, Hortensia, Smith, Jennifer A., Brody, Jennifer A., Dhingra, Radhika, Yousefi, Paul, Pankow, James S., Kunze, Sonja, Shah, Sonia H., McRae, Allan F., and Lohman, Kurt

Subjects
SMOKING, SMOKING cessation, DNA methylation, GENETICS
Abstract

Background--DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. Methods and Results--To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA samples from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine-phosphate-guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P<1?10-7 (18 760 CpGs at false discovery rate <0.05). Genes annotated to these CpGs were enriched for associations with several smokingrelated traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P<1?10-7 (2623 CpGs at false discovery rate <0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs. Conclusions--Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke. [ABSTRACT FROM AUTHOR]

Published
2016
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5. An epigenome-wide association study meta-analysis of educational attainment

Author

Karlsson Linnér, R, Marioni, R E, Rietveld, C A, Simpkin, A J, Davies, N M, Watanabe, K, Armstrong, N J, Auro, K, Baumbach, C, Bonder, M J, Buchwald, J, Fiorito, G, Ismail, K, Iurato, S, Joensuu, A, Karell, P, Kasela, S, Lahti, J, McRae, A F, Mandaviya, P R, Seppälä, I, Wang, Y, Baglietto, L, Binder, E B, Harris, S E, Hodge, A M, Horvath, S, Hurme, M, Johannesson, M, Latvala, A, Mather, K A, Medland, S E, Metspalu, A, Milani, L, Milne, R L, Pattie, A, Pedersen, N L, Peters, A, Polidoro, S, Räikkönen, K, Severi, G, Starr, J M, Stolk, L, Waldenberger, M, Eriksson, J G, Esko, T, Franke, L, Gieger, C, Giles, G G, Hägg, S, Jousilahti, P, Kaprio, J, Kähönen, M, Lehtimäki, T, Martin, N G, van Meurs, J B C, Ollikainen, M, Perola, M, Posthuma, D, Raitakari, O T, Sachdev, P S, Taskesen, E, Uitterlinden, A G, Vineis, P, Wijmenga, C, Wright, M J, Relton, C, Davey Smith, G, Deary, I J, Koellinger, P D, and Benjamin, D J

Abstract

The epigenome is associated with biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here we provide evidence on the associations between epigenetic modifications—in our case, CpG methylation—and educational attainment (EA), a biologically distal environmental factor that is arguably among the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10 767 individuals. We find nine CpG probes significantly associated with EA. However, robustness analyses show that all nine probes have previously been found to be associated with smoking. Only two associations remain when we perform a sensitivity analysis in the subset of never-smokers, and these two probes are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, the effect sizes of the associations with EA are far smaller than the known associations with the biologically proximal environmental factors alcohol consumption, body mass index, smoking and maternal smoking during pregnancy. Follow-up analyses that combine the effects of many probes also point to small methylation associations with EA that are highly correlated with the combined effects of smoking. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

Published
2017
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6. Epigenetic Signatures of Cigarette Smoking

Author

Joehanes, Roby, Just, Allan C., Marioni, Riccardo E., Pilling, Luke C., Reynolds, Lindsay M., Mandaviya, Pooja R., Guan, Weihua, Xu, Tao, Elks, Cathy E., Aslibekyan, Stella, Moreno-Macias, Hortensia, Smith, Jennifer A., Brody, Jennifer A., Dhingra, Radhika, Yousefi, Paul, Pankow, James S., Kunze, Sonja, Shah, Sonia H., McRae, Allan F., Lohman, Kurt, Sha, Jin, Absher, Devin M., Ferrucci, Luigi, Zhao, Wei, Demerath, Ellen W., Bressler, Jan, Grove, Megan L., Huan, Tianxiao, Liu, Chunyu, Mendelson, Michael M., Yao, Chen, Kiel, Douglas P., Peters, Annette, Wang-Sattler, Rui, Visscher, Peter M., Wray, Naomi R., Starr, John M., Ding, Jingzhong, Rodriguez, Carlos J., Wareham, Nicholas J., Irvin, Marguerite R., Zhi, Degui, Barrdahl, Myrto, Vineis, Paolo, Ambatipudi, Srikant, Uitterlinden, André G., Hofman, Albert, Schwartz, Joel, Colicino, Elena, Hou, Lifang, Vokonas, Pantel S., Hernandez, Dena G., Singleton, Andrew B., Bandinelli, Stefania, Turner, Stephen T., Ware, Erin B., Smith, Alicia K., Klengel, Torsten, Binder, Elisabeth B., Psaty, Bruce M., Taylor, Kent D., Gharib, Sina A., Swenson, Brenton R., Liang, Liming, DeMeo, Dawn L., O’Connor, George T., Herceg, Zdenko, Ressler, Kerry J., Conneely, Karen N., Sotoodehnia, Nona, Kardia, Sharon L. R., Melzer, David, Baccarelli, Andrea A., van Meurs, Joyce B. J., Romieu, Isabelle, Arnett, Donna K., Ong, Ken K., Liu, Yongmei, Waldenberger, Melanie, Deary, Ian J., Fornage, Myriam, Levy, Daniel, and London, Stephanie J.

Abstract

Supplemental Digital Content is available in the text.

Published
2016
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9. Evaluation of commonly used analysis strategies for epigenome- and transcriptome-wide association studies through replication of large-scale population studies

Author

van Rooij, Jeroen, Mandaviya, Pooja R., Claringbould, Annique, Felix, Janine F., van Dongen, Jenny, Jansen, Rick, Franke, Lude, ’t Hoen, Peter A. C., Heijmans, Bas, and van Meurs, Joyce B. J.

Abstract

Background: A large number of analysis strategies are available for DNA methylation (DNAm) array and RNA-seq datasets, but it is unclear which strategies are best to use. We compare commonly used strategies and report how they influence results in large cohort studies. Results: We tested the associations of DNAm and RNA expression with age, BMI, and smoking in four different cohorts (n= ~ 2900). By comparing strategies against the base model on the number and percentage of replicated CpGs for DNAm analyses or genes for RNA-seq analyses in a leave-one-out cohort replication approach, we find the choice of the normalization method and statistical test does not strongly influence the results for DNAm array data. However, adjusting for cell counts or hidden confounders substantially decreases the number of replicated CpGs for age and increases the number of replicated CpGs for BMI and smoking. For RNA-seq data, the choice of the normalization method, gene expression inclusion threshold, and statistical test does not strongly influence the results. Including five principal components or excluding correction of technical covariates or cell counts decreases the number of replicated genes. Conclusions: Results were not influenced by the normalization method or statistical test. However, the correction method for cell counts, technical covariates, principal components, and/or hidden confounders does influence the results.

Published
2019
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