145 research outputs found

    Subtidal macrozoobenthos communities from northern Chile during and post El Niño 1997–1998

    No full text
    Despite a large amount of climatic and oceanographic information dealing with the recurring climate phenomenon El Niño (EN) and its well known impact on diversity of marine benthic communities, most published data are rather descriptive and consequently our understanding of the underlying mechanisms and processes that drive community structure during EN are still very scarce. In this study, we address two questions on the effects of EN on macrozoobenthic communities: (1) how does EN affect species diversity of the communities in northern Chile? and (2) is EN a phenomenon that restarts community assembling processes by affecting species interactions in northern Chile? To answer these questions, we compared species diversity and co-occurrence patterns of soft-bottoms macrozoobenthos communities from the continental shelf off northern Chile during (March 1998) and after (September 1998) the strong EN event 1997–1998. The methods used varied from species diversity and species co-occurrence analyses to multivariate ordination methods. Our results indicate that EN positively affects diversity of macrozoobenthos communities in the study area, increasing the species richness and diversity and decreasing the species dominance. EN represents a strong disturbance that affects species interactions that rule the species assembling processes in shallow-water, sea-bottom environments

    Recent developments of the Hierarchical Reference Theory of Fluids and its relation to the Renormalization Group

    Full text link
    The Hierarchical Reference Theory (HRT) of fluids is a general framework for the description of phase transitions in microscopic models of classical and quantum statistical physics. The foundations of HRT are briefly reviewed in a self-consistent formulation which includes both the original sharp cut-off procedure and the smooth cut-off implementation, which has been recently investigated. The critical properties of HRT are summarized, together with the behavior of the theory at first order phase transitions. However, the emphasis of this presentation is on the close relationship between HRT and non perturbative renormalization group methods, as well as on recent generalizations of HRT to microscopic models of interest in soft matter and quantum many body physics.Comment: 17 pages, 5 figures. Review paper to appear in Molecular Physic

    Endomicroscopic and transcriptomic analysis of impaired barrier function and malabsorption in environmental enteropathy

    Get PDF
    Introduction: Environmental enteropathy (EE) is associated with growth failure, micronutrient malabsorption and impaired responses to oral vaccines. We set out to define cellular mechanisms of impaired barrier function in EE and explore protective mechanisms. Methods: We studied 49 adults with environmental enteropathy in Lusaka, Zambia using confocal laser endomicroscopy (CLE); histology, immunohistochemistry and mRNA sequencing of small intestinal biopsies; and correlated these with plasma lipopolysaccharide (LPS) and a zinc uptake test. Results: CLE images (median 134 for each study) showed virtually ubiquitous small intestinal damage. Epithelial defects, imaged by histology and claudin 4 immunostaining, were predominantly seen at the tips of villi and corresponded with leakage imaged in vivo by CLE. In multivariate analysis, circulating log-transformed LPS was correlated with cell shedding events (β = 0.83; P = 0.035) and with serum glucagon-like peptide-2 (β = -0.13; P = 0.007). Zinc uptake from a test dose of 25mg was attenuated in 30/47 (64%) individuals and in multivariate analysis was reduced by HIV, but positively correlated with GLP-2 (β = 2.72; P = 0.03). There was a U-shaped relationship between circulating LPS and villus surface area. Transcriptomic analysis identified 23 differentially expressed genes in severe enteropathy, including protective peptides and proteins. Conclusions: Confocal endomicroscopy, claudin 4 immunostaining and histology identify epithelial defects which are probably sites of bacterial translocation, in the presence of which increased epithelial surface area increases the burden of translocation. GLP 2 and other protective peptides may play an important role in mucosal protection in EE

    Biochemical, physiological, and performance response of a functional watermelon juice enriched in L-citrulline during a half-marathon race

    Get PDF
    Background: Watermelon is a rich natural source of l-citrulline. This non-essential amino acid increases exercise performance. Objective: Evaluate the effect of Fashion watermelon juice enriched in l-citrulline (CWJ) (3.45 g per 500 mL) in physical performance and biochemical markers after a half-marathon race. Design: A randomised, double blind, crossover design where 2 h after drinking 500 mL of CWJ or placebo (PLA, beverage without l-citrulline) amateur male runners performed two half-marathon races. Jump height, heart rate and rating of perceived exertion were evaluated before and after the races. Moreover, muscle soreness and plasma markers of muscle damage and metabolism were evaluated for 72 h after the races. Results: Muscle soreness perception was significantly lower from 24 to 72 h after the race with CWJ beverage. Immediately after the races, runners under CWJ condition showed plasma lactate and glucose concentrations significantly lower and higher lactate dehydrogenase and l-arginine concentration than runners under PLA. A maintenance of jump heights after the races under CWJ supplementation was found, decreasing significantly with PLA. Conclusion: A single Fashion watermelon juice enriched in l-citrulline dose diminished muscle soreness perception from 24 to 72 h after the race and maintained lower concentrations of plasma lactate after an exhausting exercise.Actividad Física y Deport

    Functional Polymorphisms in IL13 Are Protective against High Schistosoma mansoni Infection Intensity in a Brazilian Population

    Get PDF
    IL-13 is a signature cytokine of the helper T cell type 2 (TH2) pathway which underlies host defense to helminthic infection and activates production of IgE in both parasitized populations and in urban settings after allergen exposure.Two functional polymorphisms in IL13, rs1800925 (or c.1-1111C>T) and rs20541 (or R130Q) were previously found to be associated with Schistosoma hematobium infection intensity. They have not been thoroughly explored in S. mansoni-endemic populations, however, and were selected along with 5 tagging SNPs for genotyping in 812 individuals in 318 nuclear families from a schistosomiasis-endemic area of Conde, Bahia, in Brazil. Regression models using GEE to account for family membership and family-based quantitative transmission disequilibrium tests (QTDT) were used to evaluate associations with total serum IgE (tIgE) levels and S. mansoni fecal egg counts adjusted for non-genetic covariates. We identified a protective effect for the T allele at rs20541 (P = 0.005) against high S. mansoni egg counts, corroborated by QTDT (P = 0.014). Our findings also suggested evidence for protective effects for the T allele at rs1800925 and A allele at rs2066960 after GEE analysis only (P = 0.050, 0.0002).The two functional variants in IL13 are protective against high S. mansoni egg counts. These markers showed no evidence of association with tIgE levels, unlike tIgE levels previously studied in non-parasitized or atopic study populations

    A cost and performance comparison of Public Private Partnership and public hospitals in Spain

    Full text link
    © 2016 Caballer-Tarazona and Vivas-Consuelo. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The Erratum to this article has been published in Health Economics Review 2016 6:20[EN] Public-private partnership (PPP) initiatives are extending around the world, especially in Europe, as an innovation to traditional public health systems, with the intention of making them more efficient. There is a varied range of PPP models with different degrees of responsibility from simple public sector contracts with the private, up to the complete privatisation of the service. As such, we may say the involvement of the private sector embraces the development, financing and provision of public infrastructures and delivery services. In this paper, one of the oldest PPP initiatives developed in Spain and transferred to other European and Latin American countries is evaluated for first time: the integrated healthcare delivery Alzira model. Through a comparison of public and PPP hospital performance, cost and quality indicators, the efficiency of the PPP experience in five hospitals is evaluated to identify the influence of private management in the results. Regarding the performance and efficiency analysis, it is seen that the PPP group obtains good results, above the average, but not always better than those directly managed. It is necessary to conduct studies with a greater number of PPP hospitals to obtain conclusive results.Caballer Tarazona, M.; Vivas Consuelo, DJJ. (2016). A cost and performance comparison of Public Private Partnership and public hospitals in Spain. Health Economics Review. 6(17):1-7. doi:10.1186/s13561-016-0095-5S17617La Forgia GM, Harding A. Public-Private Partnerships and Public Hospital Performance in Sao Paulo, Brazil. Health Aff. 2009;28(4):1114–26.Vecchi V, Hellowell M, Longo F. Are Italian healthcare organizations paying too much for their public-private partnerships? Public Money Manage. 2010;30(2):125–32.Hellowell M, Pollock AM. The private financing of NHS hospitals: politics, policy and practice. Econ Aff. 2009;29(1):13–9.McIntosh N, Grabowski A, Jack B, Nkabane-Nkholongo EL, Vian T. A public-private partnership improves clinical performance in a hospital network in Lesotho. Health Aff. 2015;34(6):954–62.Roehrich JK, Lewis MA, George G. Are public–private partnerships a healthy option? A systematic literature review. Soc Sci Med. 2014;113:110–9.Barlow J, Roehrich J, Wright S. Europe sees mixed results from public-private partnerships for building and managing health care facilities and services. Health Aff. 2013;32(1):146–54.Hoppe EI, Kusterer DJ, Schmitz PW. Public-private partnerships versus traditional procurement: an experimental investigation. J Econ Behav Organ. 2013;89:145–66.Vivas-Consuelo D, Uso-Talamantes R, Trillo-Mata JL, Caballer-Tarazona M, Barrachina-Martinez I, Buigues-Pastor L. Predictability of pharmaceutical spending in primary health services using Clinical Risk Groups. Health Policy. 2014;116(2-3):188–95.Lopez-Casasnovas G, Costa-Font J, Planas I. Diversity and regional inequalities in the Spanish ‘system of health care services’. Health Econ. 2005;14 Suppl 1:S221–S35.Spain NHSo. National Health System of Spain. National Health System of Spain; 2010.McKee M, Edwards N, Atun R. Public-private partnerships for hospitals. Bull World Health Organ. 2006;84(11):890–6.Caballer-Tarazona M, Moya-Clemente I, Vivas-Consuelo D, Barrachina-Martínez I. A model to measure the efficiency of hospital performance. Math Comput Model. 2010;52(7-8):1095–102.Barlow J, Roehrich JK, Wright S. De facto privatization or a renewed role for the EU? Paying for Europe’s healthcare infrastructure in a recession. J R Soc Med. 2010;103(2):51–5.Herr A, Schmitz H, Augurzky B. Profit efficiency and ownership of German hospitals. Health Econ. 2011;20(6):660–74.Alonso JM, Clifton J, Díaz-Fuentes D. The impact of New Public Management on efficiency: an analysis of Madrid’s hospitals. Health Policy. 2015;119(3):333–40.IASIST. Desarrollo metodológico de los indicadores ajustados 2009 [cited 2015 July 26]. Available from: ( http://www.iasist.com/archivos/top20-2009-metodologia_161215235006.pdf ). Accessed Sept 2015.Hollingsworth B. The measurement of efficiency and productivity of health care delivery. Health Econ. 2008;17(10):1107–28.Ozgen H, Ozcan YA. A national study of efficiency for dialysis centers: an examination of market competition and facility characteristics for production of multiple dialysis outputs. Health Serv Res. 2002;37(3):711–32.Valdmanis VG, Rosko MD, Mutter RL. Hospital quality, efficiency, and input slack differentials. Health Serv Res. 2008;43(5):1830–48.Acerete B, Stafford A, Stapleton P. Spanish healthcare public private partnerships: The ‘Alzira model’. Crit Perspect Account. 2011;22(6):533–49.Allard G, Trabant A. Public-private partnerships in Spain: lessons and opportunities. Int Business Econ Res J. 2008;7(2):1–24.Shaoul J, Stafford A, Stapleton P. The cost of using private finance to build, finance and operate hospitals. Public Money Manage. 2008;28(2):101–8

    Measurement of health-related quality by multimorbidity groups in primary health care

    Full text link
    [EN] Background: Increased life expectancy in Western societies does not necessarily mean better quality of life. To improve resources management, management systems have been set up in health systems to stratify patients according to morbidity, such as Clinical Risk Groups (CRG). The main objective of this study was to evaluate the effect of multimorbidity on health-related quality of life (HRQL) in primary care. Methods: An observational cross-sectional study, based on a representative random sample (n = 306) of adults from a health district (N = 32,667) in east Spain (Valencian Community), was conducted in 2013. Multimorbidity was measured by stratifying the population with the CRG system into nine mean health statuses (MHS). HRQL was assessed by EQ-5D dimensions and the EQ Visual Analogue Scale (EQ VAS). The effect of the CRG system, age and gender on the utility value and VAS was analysed by multiple linear regression. A predictive analysis was run by binary logistic regression with all the sample groups classified according to the CRG system into the five HRQL dimensions by taking the ¿healthy¿ group as a reference. Multivariate logistic regression studied the joint influence of the nine CRG system MHS, age and gender on the five EQ-5D dimensions. Results: Of the 306 subjects, 165 were female (mean age of 53). The most affected dimension was pain/discomfort (53%), followed by anxiety/depression (42%). The EQ-5D utility value and EQ VAS progressively lowered for the MHS with higher morbidity, except for MHS 6, more affected in the five dimensions, save self-care, which exceeded MHS 7 patients who were older, and MHS 8 and 9 patients, whose condition was more serious. The CRG system alone was the variable that best explained health problems in HRQL with 17%, which rose to 21% when associated with female gender. Age explained only 4%. Conclusions: This work demonstrates that the multimorbidity groups obtained by the CRG classification system can be used as an overall indicator of HRQL. These utility values can be employed for health policy decisions based on cost-effectiveness to estimate incremental quality-adjusted life years (QALY) with routinely e-health data. Patients under 65 years with multimorbidity perceived worse HRQL than older patients or disease severity. Knowledge of multimorbidity with a stronger impact can help primary healthcare doctors to pay attention to these population groups.The authors would like to thank the Conselleria de Sanitat Universal i Sanitat Pública of the Generalitat Valenciana (the Regional Valencian Health Government) for providing the study data. We would also like to thank Helen Warbuton for editing the English.Milá-Perseguer, M.; Guadalajara Olmeda, MN.; Vivas-Consuelo, D.; Usó-Talamantes, R. (2019). Measurement of health-related quality by multimorbidity groups in primary health care. Health and Quality of Life Outcomes. 17(8):1-10. https://doi.org/10.1186/s12955-018-1063-zS110178Ministerio de Sanidad SS, Igualdad e. Indicadores de Salud 2013. Evolución de los indicadores del estado de salud en España y su magnitud en el contexto de la Unión Europea. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad; 2014.OECD/EU: Health at a Glance: Europe 2016 – State of Health in the EU Cycle, OECD Publishing, Paris. In.; 2016.WHO: Disability and health. In. Edited by WHO; 2017.Nicholson K, Makovski TT, Griffith LE, Raina P, Stranges S, van den Akker M. Multimorbidity and comorbidity revisited: refining the concepts for international health research. J Clin Epidemiol. 2018.Palmer K, Marengoni A, Forjaz MJ, Jureviciene E, Laatikainen T, Mammarella F, Muth C, Navickas R, Prados-Torres A, Rijken M, et al. Multimorbidity care model: recommendations from the consensus meeting of the joint action on chronic diseases and promoting healthy ageing across the life cycle (JA-CHRODIS). Health Policy. 2018;122(1):4–11.WHO: Innovative Care for Chronic Conditions. Building blocks for action. In.: WHO; 2014.Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3(3):223–8.Inoriza JM, Coderch J, Carreras M, Vall-Llosera L, Garcia-Goni M, Lisbona JM, Ibern P. Measurement of morbidity attended in an integrated health care organization. Gac Sanit. 2009;23(1):29–37.Hunger M, Thorand B, Schunk M, Döring A, Menn P, Peters A, Holle R. Multimorbidity and health-related quality of life in the older population: results from the German KORA-age study. Health Qual Life Outcomes. 2011;9:53.de Miguel P, Caballero I, Rivas FJ, Manera J, de Vicente MA, Gómez Á. Morbidity observed in a health area: impact on professionals and funding. Aten Primaria. 2015;47(5):301–7.Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health. 2012;12:201.Orueta JF, García-Álvarez A, García-Goñi M, Paolucci F, Nuño-Solinís R. Prevalence and costs of multimorbidity by deprivation levels in the Basque Country: a population based study using health administrative databases. PLoS One. 2014;9(2):e89787.Mujica-Mota RE, Roberts M, Abel G, Elliott M, Lyratzopoulos G, Roland M, Campbell J. Common patterns of morbidity and multi-morbidity and their impact on health-related quality of life: evidence from a national survey. Qual Life Res. 2015;24(4):909–18.Caballer Tarazona V, Guadalajara Olmeda N, Vivas Consuelo D, Clemente Collado A. Impact of morbidity on health care costs of a Department of Health through clinical risk groups. Valencian Community, Spain. Rev Esp Salud Publica. 2016;90:e1–e15.Calderon-Larranaga A, Abrams C, Poblador-Plou B, Weiner JP, Prados-Torres A. Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: the impact of a local calibration. BMC Health Serv Res. 2010;10:22.Hughes JS, Averill RF, Eisenhandler J, Goldfield NI, Muldoon J, Neff JM, Gay JC. Clinical risk groups (CRGs): a classification system for risk-adjusted capitation-based payment and health care management. Med Care. 2004;42(1):81–90.Vivas-Consuelo D, Uso-Talamantes R, Trillo-Mata JL, Caballer-Tarazona M, Barrachina-Martinez I, Buigues-Pastor L. Predictability of pharmaceutical spending in primary health services using clinical risk groups. Health Policy. 2014;116(2–3):188–95.Milla Perseguer M, Guadalajara Olmeda N, Vivas Consuelo D. Impact of cardiovascular risk factors on the consumption of resources in primary care according to clinical risk groups. Aten Primaria. 2018.WHOQOL. The World Health Organization quality of life assessment (WHOQOL): development and general psychometric properties. Soc Sci Med. 1998;46(12):1569–85.Badia X, Carne X. The evaluation of quality of life in clinical trials. Medicina Clinica. 1998;110(14):550–6.Revicki DA. Health-related quality of life in the evaluation of medical therapy for chronic illness. J Fam Pract. 1989;29(4):377–80.Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Health-related quality of life and healthcare utilization in multimorbidity: results of a cross-sectional survey. Qual Life Res. 2013;22(4):791–9.Romero M, Vivas-Consuelo D, Alvis-Guzman N. Is health related quality of life (HRQoL) a valid indicator for health systems evaluation? Springerplus. 2013;2:664.Hanmer J, Feeny D, Fischhoff B, Hays RD, Hess R, Pilkonis PA, Revicki DA, Roberts MS, Tsevat J, Yu L. The PROMIS of QALYs. Health Qual Life Outcomes. 2015;13.Herdman M, Badia X, Berra S. EuroQol-5D: a simple alternative for measuring health-related quality of life in primary care. Atencion primaria / Sociedad Espanola de Medicina de Familia y Comunitaria. 2001;28(6):425–30.EuroQol G. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(199–208).Agborsangaya CB, Lahtinen M, Cooke T, Johnson JA. Comparing the EQ-5D 3L and 5L: measurement properties and association with chronic conditions and multimorbidity in the general population. Health Qual Life Outcomes. 2014;12:7.Real Decreto Legislativo 8/2015, de 30 de octubre, por el que se aprueba el texto refundido de la Ley General de la Seguridad Social. In. «BOE» núm. 261, de 31/10/2015.: Ministerio de Empleo y Seguridad Social.; 2015.Ministry of Health and Social Policy:. Estudios sobre la calidad de vida de pacientes afectados por determinadas patologías. [ http://www.mscbs.gob.es/organizacion/sns/planCalidadSNS/ ].Ministry of Health and Social Policy: Encuesta Nacional de Salud. España 2011/12. Calidad de vida relacionada con la salud en adultos: EQ-5D-5L. Serie Informes monográficos n° 3. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad; 2014.Fortin M, Bravo G, Hudon C, Lapointe L, Almirall J, Dubois MF, Vanasse A. Relationship between multimorbidity and health-related quality of life of patients in primary care. Qual Life Res. 2006;15(1):83–91.Fortin M, Dubois MF, Hudon C, Soubhi H, Almirall J. Multimorbidity and quality of life: a closer look. Health Qual Life Outcomes. 2007;5:52.Brazier JE, Yang Y, Tsuchiya A, Rowen DL. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ. 2010;11.Peak J, Goranitis I, Day E, Copello A, Freemantle N, Frew E. Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP. Health Qual Life Outcomes. 2018;16(1):106.Rivero-Arias O, Ouellet M, Gray A, Wolstenholme J, Rothwell PM, Luengo-Fernandez R. Mapping the modified Rankin scale (mRS) measurement into the generic EuroQol (EQ-5D) health outcome. Med Decis Mak. 2010;30.Argimon Pallás JM, Jiménez Villa J: Métodos de investigación clínica y epidemiológica, vol. Capítulo 15. Tamaño de la muestra; 2013.Yepes-Núñez JJ, García García HI: Preferencias de estados de salud y medidas de utilidad. In., vol. 24. Iatreia; 2011: 365–377.Attema AE, Edelaar-Peeters Y, Versteegh MM, Stolk EA. Time trade-off: one methodology, different methods. Eur J Health Econ. 2013;14(Suppl 1):S53–64.Badia X, Roset M, Herdman M, Kind P. A comparison of United Kingdom and Spanish general population time trade-off values for EQ-5D health states. Med Decis Mak. 2001;21(1):7–16.Garin N, Olaya B, Moneta MV, Miret M, Lobo A, Ayuso-Mateos JL, Haro JM. Impact of multimorbidity on disability and quality of life in the Spanish older population. PLoS One. 2014;9(11):e111498.Mielck A, Vogelmann M, Leidl R. Health-related quality of life and socioeconomic status: inequalities among adults with a chronic disease. Health Qual Life Outcomes. 2014;12:58.Usó Talamantes R: Análisis y desarrollo de un modelo predictivo del gasto farmacéutico ambulatorio ajustado a morbilidad y riesgo clínico [tesis doctoral]. Universidad Politécnica de Valencia; 2015. https://www.educacion.gob.es/teseo/mostrarRef.do?ref=1183638 .Sánchez Mollá M, Candela García I, Gómez-Romero FJ, Orozco Beltrán D, Ollero Baturone M. Concordance between stratification systems and identification of patients with multiple chronic diseases in primary care. Rev Calid Asist. 2017;32(1):10–6.Vivas-Consuelo D, Uso-Talamantes R, Guadalajara-Olmeda N, Trillo-Mata J-L, Sancho-Mestre C, Buigues-Pastor L. Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool. BMC Health Serv Res. 2014;14:462.Coderch J, Sánchez-Pérez I, Ibern P, Carreras M, Pérez-Berruezo X, Inoriza JM. Predicting individual risk of high healthcare cost to identify complex chronic patients. Gac Sanit. 2014;28(4):292–300.Osca Guadalajara M, Guadalajara Olmeda N, Escartín Martínez R. Impact of Teriparatide on quality of life in osteoporotic patients. Rev Esp Salud Publica. 2015;89(2):215–25.Prazeres F, Santiago L. Relationship between health-related quality of life, perceived family support and unmet health needs in adult patients with multimorbidity attending primary care in Portugal: a multicentre cross-sectional study. Health Qual Life Outcomes. 2016;14(1):156.Brettschneider C, Leicht H, Bickel H, Dahlhaus A, Fuchs A, Gensichen J, Maier W, Group MS. Relative impact of multimorbid chronic conditions on health-related quality of life--results from the MultiCare cohort study. PLoS One. 2013;8(6):e66742

    Sequential solvent extraction for the modes of occurrence of selenium in coals of different ranks from the Huaibei Coalfield, China

    Get PDF
    Forms of selenium in bituminous coal, anthracite, and cokeite (natural coke) from Huaibei Coalfield, Anhui, China, have been determined by sequential solvent extraction. The selenium content in bulk samples is 4.0, 2.4, and 2.0 μg/g in bituminous coal, anthracite, and cokeite, respectively. The six forms of selenium determined by six-step solvent extraction are water-leachable, ion-exchangeable, organic matter-associated, carbonate-associated, silicate-associated, and sulfide-associated. The predominant forms of selenium in bituminous coal are organic matter-associated (39.0%), sulfide-associated (21.1%), and silicate bound (31.8%); these three forms account for 92% of the total. The organic matter bound-selenium decrease dramatically from bituminous coal (39.0%) to anthracite (11.6%) and to cokeite (0%), indicating that organic matter bound selenium is converted to other forms during metamorphism of the coal, most likely sulfide-form. The sulfide-associated form increased remarkably from bituminous coal (21.1%) to anthracite (50.4%) and cokeite (54.5%), indicating the formation of selenium sulfide, possibly in pyrite during the transformation of bituminous coal to anthracite and cokeite. The silicate-associated selenium in bituminous coal (31.8%) is much higher than that in anthracite (16.4%) and cokeite (15.8%), indicating that silicate-associated selenium is partly converted to sulfide during metamorphism

    Population Genetics of GYPB and Association Study between GYPB*S/s Polymorphism and Susceptibility to P. falciparum Infection in the Brazilian Amazon

    Get PDF
    Merozoites of Plasmodium falciparum invade through several pathways using different RBC receptors. Field isolates appear to use a greater variability of these receptors than laboratory isolates. Brazilian field isolates were shown to mostly utilize glycophorin A-independent invasion pathways via glycophorin B (GPB) and/or other receptors. The Brazilian population exhibits extensive polymorphism in blood group antigens, however, no studies have been done to relate the prevalence of the antigens that function as receptors for P. falciparum and the ability of the parasite to invade. Our study aimed to establish whether variation in the GYPB*S/s alleles influences susceptibility to infection with P. falciparum in the admixed population of Brazil.Two groups of Brazilian Amazonians from Porto Velho were studied: P. falciparum infected individuals (cases); and uninfected individuals who were born and/or have lived in the same endemic region for over ten years, were exposed to infection but have not had malaria over the study period (controls). The GPB Ss phenotype and GYPB*S/s alleles were determined by standard methods. Sixty two Ancestry Informative Markers were genotyped on each individual to estimate admixture and control its potential effect on the association between frequency of GYPB*S and malaria infection.GYPB*S is associated with host susceptibility to infection with P. falciparum; GYPB*S/GYPB*S and GYPB*S/GYPB*s were significantly more prevalent in the in the P. falciparum infected individuals than in the controls (69.87% vs. 49.75%; P<0.02). Moreover, population genetics tests applied on the GYPB exon sequencing data suggest that natural selection shaped the observed pattern of nucleotide diversity.Epidemiological and evolutionary approaches suggest an important role for the GPB receptor in RBC invasion by P. falciparum in Brazilian Amazons. Moreover, an increased susceptibility to infection by this parasite is associated with the GPB S+ variant in this population
    corecore