75 research outputs found

    Relaxation effect of abacavir on rat basilar arteries

    Get PDF
    Background The use of abacavir has been linked with increased cardiovascular risk in patients with human immunodeficiency virus infection; however, the mechanism involved remains unclear. We hypothesize that abacavir may impair endothelial function. In addition, based on the structural similarity between abacavir and adenosine, we propose that abacavir may affect vascular contractility through endogenous adenosine release or adenosine receptors in blood vessels. Methods The relaxation effect of abacavir on rat basilar arteries was studied using the myograph technique. Cyclic GMP and AMP levels were measured by immunoassay. The effects of abacavir on nucleoside transporters were studied using radiolabeled nucleoside uptake experiments. Ecto-5′ nucleotidase activity was determined by measuring the generation of inorganic phosphate using adenosine monophosphate as the substrate. Results Abacavir induced the relaxation of rat basilar arteries in a concentration-dependent manner. This relaxation was abolished when endothelium was removed. In addition, the relaxation was diminished by the nitric oxide synthase inhibitor, L-NAME, the guanylyl cyclase inhibitor, ODQ, and the protein kinase G inhibitor, KT5820. Abacavir also increased the cGMP level in rat basilar arteries. Abacavir-induced relaxation was also abolished by adenosine A2 receptor blockers. However, abacavir had no effect on ecto-5’ nucleotidase and nucleoside transporters. Short-term and long-term treatment of abacavir did not affect acetylcholine-induced relaxation in rat basilar arteries. Conclusion Abacavir induces acute endothelium-dependent relaxation of rat basilar arteries, probably through the activation of adenosine A2 receptors in endothelial cells, which subsequently leads to the release of nitric oxide, resulting in activation of the cyclic guanosine monophosphate/protein kinase G-dependent pathway in vascular smooth muscle cells. It is speculated that abacavir-induced cardiovascular risk may not be related to endothelial dysfunction as abacavir does not impair relaxation of blood vessels. The most likely explanation of increased cardiovascular risk may be increased platelet aggregation as suggested by other studies

    From Omics to Drug Metabolism and High Content Screen of Natural Product in Zebrafish: A New Model for Discovery of Neuroactive Compound

    Get PDF
    The zebrafish (Danio rerio) has recently become a common model in the fields of genetics, environmental science, toxicology, and especially drug screening. Zebrafish has emerged as a biomedically relevant model for in vivo high content drug screening and the simultaneous determination of multiple efficacy parameters, including behaviour, selectivity, and toxicity in the content of the whole organism. A zebrafish behavioural assay has been demonstrated as a novel, rapid, and high-throughput approach to the discovery of neuroactive, psychoactive, and memory-modulating compounds. Recent studies found a functional similarity of drug metabolism systems in zebrafish and mammals, providing a clue with why some compounds are active in zebrafish in vivo but not in vitro, as well as providing grounds for the rationales supporting the use of a zebrafish screen to identify prodrugs. Here, we discuss the advantages of the zebrafish model for evaluating drug metabolism and the mode of pharmacological action with the emerging omics approaches. Why this model is suitable for identifying lead compounds from natural products for therapy of disorders with multifactorial etiopathogenesis and imbalance of angiogenesis, such as Parkinson's disease, epilepsy, cardiotoxicity, cerebral hemorrhage, dyslipidemia, and hyperlipidemia, is addressed

    Quality of life among people living with hypertension in a rural Vietnam community

    Get PDF
    Background - To respond to growing prevalence of hypertension in Vietnam, it is critical to have an in-depth understanding about quality of life (QOL) among people living with hypertension and related factors. This study aimed to measure QOL among hypertensive people in a rural community in Vietnam, and its association with socio-demographic characteristics and factors related to treatment. Methods - This study was conducted in a rural community located 60 km from Ho Chi Minh City. Face-to-face interviews were conducted among 275 hypertensive people aged 50 years and above using WHOQOL-BREF questionnaire. Descriptive statistics were used to examine mean scores of quality of life. Cronbach’s alpha coefficient and Pearson’s correlation coefficient were applied to estimate the internal consistency, and the level of agreement between different domains of WHOQOL-BREF, respectively. Independent T-test and ANOVA test followed by multiple linear regression analyses were used to measure the association between QOL domains and independent variables. Results - Both overall WHOQOL-BREF and each domain had a good internal consistency, ranging from 0.65 to 0.88. The QOL among hypertensive patients was found moderate in all domains, except for psychological domain that was fairly low (mean = 49.4). Backward multiple linear regressions revealed that being men, married, attainment of higher education, having physical activities at moderate level, and adherence to treatment were positively associated with QOL. However, older age and presence of co-morbidity were negatively associated with QOL. Conclusion - WHOQOL-BREF is a reliable instrument to measure QOL among hypertensive patients. The results revealed low QOL in psychological domain and inequality in QOL across socio-demographic characteristics. Given the results, encouraging physical activities and strengthening treatment adherence should be considered to improve QOL of hypertensive people, especially for psychological aspect. Actions to improve QOL among hypertensive patients targeted towards women, lower educated and unmarried patients are needed in the setting

    High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

    Get PDF
    Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions

    Is Health Related Quality of Life (HRQoL) a valid indicator for health systems evaluation?

    Get PDF
    This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The purpose of this review is to do a discussion about the use of the HRQoL as a health measure of the populations that enable to analyze its potential use as a measure of development and efficiency of health systems. The principal use of the HRQoL is in health technologies economics evaluation; however this measure can be use in public health when need to know the health state of population. The WHO recognizes its potential use but its necessary to do a discussion about your difficulties for its application and restrictions for its use as a performance indicator for the health systems. The review show the different aspects about the use of HRQoL how a measure of efficiency ot the health system, each aspect identified in the literature is analyzed and discussed, developing the pros and cons of their possible use, especially when it comes as a cardinal measure. The analysis allows recognize that measuring HRQoL in countries could serve as a useful indicator, especially when it seeks to measure the level of health and disease, as do most of the indicators of current use. However, the methodological constraints that do not allow comparability between countries especially when you have large socioeconomic differences have yet to be resolved to allow comparison between different regions.Romero, D.; Vivas Consuelo, DJJ.; Alvis Guzman, NR. (2013). Is Health Related Quality of Life (HRQoL) a valid indicator for health systems evaluation?. SpringerPlus. 2:664-674. doi:10.1186/2193-1801-2-664S6646742Acemoglu D, Johnson S: Disease and development: The effect of life expectancy on economic growth. J Polit Econ 2007, 115(6):925-985. 10.1086/529000Anderson J, Sayles H, Curtis JR, Wolfe F, Michaud K: Converting modified health assessment questionnaire (HAQ), multidimensional HAQ, and HAQII scores into original HAQ scores using models developed with a large cohort of rheumatoid arthritis patients. Arthritis care & research 2010, 62(10):1481-1488. Epub 2010/05/25 10.1002/acr.20265Aristotles : Nicomachean Ethics: Batoche Books Kitchener. 1999. Available from: http://www.efm.bris.ac.uk/het/aristotle/ethics.pdfAugustovski FA, Irazola VE, Velazquez AP, Gibbons L, Craig BM: Argentine valuation of the EQ-5D health states. Value in health 2009, 12(4):587-596. Epub 2009/11/11 10.1111/j.1524-4733.2008.00468.xBernert S, Fernandez A, Haro JM, Konig HH, Alonso J, Vilagut G, et al.: Comparison of different valuation methods for population health status measured by the EQ-5D in three European countries. Value in health 2009, 12(5):750-758. Epub 2009/06/06 10.1111/j.1524-4733.2009.00509.xCervellati M, Sunde U: Life expectancy and economic growth: The role of the demographic transition. Discussion Paper No 2 St. Gallen. Switzerland: Research Center for Ageing, Welfare and Labour Analysis (SCALA); 2009.Cervellati M, Sunde U: Disease and development: The role of life expectancy reconsidered. Econ Lett 2011, 113(3):269-272. 10.1016/j.econlet.2011.08.008Chatters LM: Religion and health: public health research and practice. Annual review of public health 2000, 21: 335-367. Epub 2000/07/08 10.1146/annurev.publhealth.21.1.335Chen B, Mahal A: Measuring the health of the Indian elderly: evidence from National Sample Survey data. Population health metrics 2010, 8: 30. Epub 2010/11/18 10.1186/1478-7954-8-30Cleland JA, Lee AJ, Hall S: Associations of depression and anxiety with gender, age, health-related quality of life and symptoms in primary care COPD patients. Family practice 2007, 24(3):217-223. Epub 2007/05/17 10.1093/fampra/cmm009Cook EL, Harman JS: A comparison of health-related quality of life for individuals with mental health disorders and common chronic medical conditions. Public Health Rep 2008, 123(1):45-51. Epub 2008/03/20Dolan P, Gudex C, Kind P, Williams A: Valuing health states: a comparison of methods. Journal of health economics 1996, 15(2):209-231. Epub 1996/03/08 10.1016/0167-6296(95)00038-0Evans DB, Lauer JA, Tandon A, Murray CJ: Determinants of Health System Performance: Second-Stage Efficiency Analysis. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:693-698.Fayers PM, Machin D: Quality of life The assessment, analysis and interpretation of patient-reported outcomes. 2nd edition. John Wiley & Sons Ltda: West Sussex; 2007.Gulis G: Life expectancy as an indicator of environmental health. European Journal of Epidemiolog 2000, 16(2):161-165. 10.1023/A:1007629306606Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al.: Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5 L). Quality of life research 2011, 20(10):1727-1736. Epub 2011/04/12 10.1007/s11136-011-9903-xHorsman J, Furlong W, Feeny D, Torrance G: The Health Utilities Index (HUI): concepts, measurement properties and applications. Health and quality of life outcomes 2003, 1: 54. Epub 2003/11/14 10.1186/1477-7525-1-54Institute of Medicine, National Academy of Science: Summarizing population health directions for the development and application of population metrics. Washington, D.C: Committee on Summary Measures of Population Health; 1998.Jeremic V, Seke V, Radojicic Z, Jeremic D, Markovic A, Slovic D, et al.: Measuring health of countries: a novel approach. HealthMED 2011, 5(6):1762-1766.Jia H, Moriarty DG, Kanarek N: County-level social environment determinants of health-related quality of life among US adults: a multilevel analysis. Journal of community health 2009, 34(5):430-439. Epub 2009/06/26 10.1007/s10900-009-9173-5Konerding U, Moock J, Kohlmann T: The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common? Quality of life research 2009, 18(9):1249-1261. Epub 2009/09/04 10.1007/s11136-009-9525-8Krabbe PF, Peerenboom L, Langenhoff BS, Ruers TJ: Responsiveness of the generic EQ-5D summary measure compared to the disease-specific EORTC QLQ C-30. Quality of life research 2004, 13(7):1247-1253. Epub 2004/10/12le Hoi V, Chuc NT, Lindholm L: Health-related quality of life, and its determinants, among older people in rural Vietnam. BMC public health 2010, 10: 549. Epub 2010/09/14 10.1186/1471-2458-10-549McDonough CM, Tosteson AN: Measuring preferences for cost-utility analysis: how choice of method may influence decision-making. PharmacoEconomics 2007, 25(2):93-106. Epub 2007/01/26 10.2165/00019053-200725020-00003McHorney CA, Ware JE Jr, Raczek AE: The MOS 36-Item Short-Form Health Survey (SF-36): II Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical care 1993, 31(3):247-263. Epub 1993/03/01 10.1097/00005650-199303000-00006McHorney CA, Ware JE Jr, Lu JF, SCD : The MOS, 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Medical care 1994, 32(1):40-66. 10.1097/00005650-199401000-00004Molla M, Madans J, Wagener D, Crimmins E: Summary measures of population health: Report of findings on methodologic and data issues. Hyattsville, MD: National Center for Health Statics; 2003. [cited 2013. Available from: http://www.cdc.gov/nchs/data/misc/pophealth.pdfMolla M, Madans J, Wagener D, Crimmins E: Summary measures of population health: Report of findings on methodologic and data issues. Hyattsville, MD: National Center for Health Statics; 2003.Murray CJ, Frenk J: A framework for assessing the performance of health systems. Bull World Health Organ 2000, 78(6):717-731. Epub 2000/08/05Mykletun A, Stordal E, Dahl AA: Hospital Anxiety and Depression (HAD) scale: factor structure, item analyses and internal consistency in a large population. The British journal of psychiatry 2001, 179: 540-544. Epub 2001/12/04 10.1192/bjp.179.6.540NAUGHTON MJ, Shumaker SA, Anderson RT, Czajkowski SM: Psychological Aspects of Health-Related Quality of Life Measurement: Tests and Scales. In Quality of Life and Pharmaco economics in Clinical Trials. Edited by: Spilker B. New York: Lippincott-Raven; 1996:117-131.Neumann PJ, Jacobson PD, Palmer JA: Measuring the value of public health systems: the disconnect between health economists and public health practitioners. American journal of public health 2008, 98(12):2173-2180. Epub 2008/10/17 10.2105/AJPH.2007.127134OMS: Official records of the world health organization. Geneva: World Health Organization; 1948. Ginebra: Organización Mundial de la Salud; 1948 [cited 2013 Abril]; Available from: http://www.who.int/library/collections/historical/es/index3.html Ginebra: Organización Mundial de la Salud; 1948 [cited 2013 Abril]; Available from:Paternina D, Melguizo E: Calidad de vida en adultos mayores. Revisión sistemática. V encuentro institucional semilleros de investigación. Cartagena, Colombia: Universidad de Cartagena; 2010.PATRICK D, Erickson P: Health Policy, Quality of Life: Health Care Evaluation and Resource Allocation. New York: Oxford University Press; 1993.Pereira CC, Palta M, Mullahy J, Fryback DG: Race and preference-based health-related quality of life measures in the United States. Quality of life research 2011, 20(6):969-978. Epub 2010/12/25 10.1007/s11136-010-9813-3Poole JL, Steen VD: The use of the Health Assessment Questionnaire (HAQ) to determine physical disability in systemic sclerosis. Arthritis care and research 1991, 4(1):27-31. Epub 1991/03/01 10.1002/art.1790040106Prause W, Saletu B, Tribl GG, Rieder A, Rosenberger A, Bolitschek J, et al.: Effects of socio-demographic variables on health-related quality of life determined by the quality of life index–German version. Human psychopharmacology 2005, 20(5):359-365. Epub 2005/06/28 10.1002/hup.699Prieto L, Sacristan JA: Problems and solutions in calculating quality-adjusted life years (QALYs). Health and quality of life outcomes 2003, 1: 80. Epub 2003/12/23 10.1186/1477-7525-1-80Pyne JM, Sieber WJ, David K, Kaplan RM, Hyman Rapaport M, Keith WD: Use of the quality of well-being self-administered version (QWB-SA) in assessing health-related quality of life in depressed patients. Journal of affective disorders 2003, 76(1–3):237-247. Epub 2003/08/29Roset M, Badia X, Mayo NE: Sample size calculations in studies using the EuroQol 5D. Quality of life research 1999, 8(6):539-549. Epub 1999/11/05 10.1023/A:1008973731515Salomon JA, Murray CJ, Ustün TB, Chatterji S: Health state valuations in summary measures of population health. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:693-698.Sanders BS: Measuring Community Health Levels. American journal of public health and the nation's health 1964, 54: 1063-1070. Epub 1964/07/01 10.2105/AJPH.54.7.1063Tajvar M, Arab M, Montazeri A: Determinants of health-related quality of life in elderly in Tehran Iran. BMC public health 2008, 8: 323. Epub 2008/09/24 10.1186/1471-2458-8-323Tandon A, Lauer JA, Evans DB, Murray CJ: Health system efficiency: Concepts. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:683-692.Thacker SB, Stroup DF, Carande-Kulis V, Marks JS, Roy K, Gerberding JL: Measuring the public's health. Public Health Rep 2006, 121(1):14-22. Epub 2006/01/19Torrance GW: Toward a utility theory foundation for health status index models. Health services research 1976, 11(4):349-369.Vogels T, Verrips GH, Verloove-Vanhorick SP, Fekkes M, Kamphuis RP, Koopman HM, et al.: Measuring health-related quality of life in children: the development of the TACQOL parent form. Quality of life research 1998, 7(5):457-465. Epub 1998/08/06Von Neumann J, Morgenstern O: Theory of games and economic behavior. 3rd edition. New York: Jhon Wiley and Sons; 1967.Wang H, Kindig DA, Mullahy J: Variation in Chinese population health related quality of life: results from a EuroQol study in Beijing, China. Quality of life research 2005, 14(1):119-132. Epub 2005/03/26 10.1007/s11136-004-0612-6Ware JE Jr, Sherbourne CD: The MOS 36-item short-form health survey (SF-36) I. Conceptual framework and item selection. Medical care 1992, 30(6):473-483. Epub 1992/06/11 10.1097/00005650-199206000-00002WHO: WHOQOL: measuring quality of life. 1997. Available from: http://www.who.int/mental_health/media/68.pdfWHO: Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003.Wright DR, Wittenberg E, Swan JS, Miksad RA, Prosser LA: Methods for measuring temporary health States for cost-utility analyses. PharmacoEconomics 2009, 27(9):713-723. Epub 2009/09/18 10.2165/11317060-000000000-00000Zarate V, Kind P, Valenzuela P, Vignau A, Olivares-Tirado P, Munoz A: Social valuation of EQ-5D health states: the Chilean case. Value in health 2011, 14(8):1135-1141. Epub 2011/12/14 10.1016/j.jval.2011.09.00
    corecore