Binding of metals to macromolecular organic acids in natural waters

Trace metal speciation and bioavailability have become keys to current day toxicity and risk assessments. For many metals, macromolecular organic acids constitute the major ligand in fresh water and soil solution. Therefore, understanding their characteristics and behaviour is necessary for understanding trace metal behaviour. This study comprises investigations of the proton- and copper-binding properties of hydrophobic and hydrophilic dissolved organic matter fractions, and competition effects of iron(III) and aluminium. The solutions studied were a forest floor solution and a municipal solid waste incinerator bottom ash leachate. Two geochemical models (SHM and NICA-Donnan) were tested and calibrated against the experimental data. A structural analysis of the binding mode of iron(III) to fulvic acid in acid aqueous solutions was made using extended X-ray absorption fine structure (EXAFS) spectroscopy. Dissolved organic carbon (DOC) in the bottom ash leachate had fulvic acid-like properties and was dominated by the hydrophilic acid fraction. Three organic fractions (hydrophobic, transphilic and hydrophilic) were isolated from the forest floor solution using an XAD-8/XAD-4 tandem. All fractions were characterised by distinct but differing proton-binding properties, suggesting a more acidic character than 'generic' fulvic acid. The copper-binding isotherms were very similar for all three fractions and suggested strong copper binding to a small number of sites. In general, both models tested could be adjusted to obtain good fits to data on both proton- and copper-binding, but iron(III) and aluminium competition was better predicted by the SHM than the NICA-Donnan model. Only mononuclear iron(III) complexes were included in the model calculations, as the EXAFS study showed that these ¬dominated in the aqueous phase. Studies on untreated soil solution indicated that the three isolated fractions were the only contributors to the observed copper binding and together constitute the 'active' DOC fraction. Thus, combination of Leenheer fractionation data with the model parameters derived in this study is recommended for improved predictions of trace metal speciation in soil solutions. However, further studies along this research line, including other samples and trace metals, are highly recommended

e-LEARNING FISIKA BERBASIS MACROMEDIA FLASH MX

Vast amounts of knowledge about the proton- and metal-binding properties of dissolved organic matter (DOM) in natural waters have been obtained in studies on isolated humic and fulvic (hydrophobic) acids. Although macromolecular hydrophilic acids normally make up about one-third of DOM, their proton- and metal-binding properties are poorly known. Here, we investigated the acid-base and Cu-binding properties of the hydrophobic (fulvic) acid fraction and two hydrophilic fractions isolated from a soil solution. Proton titrations revealed a higher total charge for the hydrophilic acid fractions than for the hydrophobic acid fraction. The most hydrophilic fraction appeared to be dominated by weak acid sites, as evidenced by increased slope of the curve of surface charge versus pH at pH values above 6. The titration curves were poorly predicted by both Stockholm Humic Model (SHM) and NTCA-Donnan model calculations using generic parameter values, but could be modelled accurately after optimisation of the proton-binding parameters (pH &lt;= 9). Cu-binding isotherms for the three fractions were determined at pH values of 4, 6 and 9. With the optimised proton-binding parameters, the SHM model predictions for Cu binding improved, whereas the NICA-Donnan predictions deteriorated. After optimisation of Cu-binding parameters, both models described the experimental data satisfactorily. Iron(III) and aluminium competed strongly with Cu for binding sites at both pH 4 and pH 6. The SHM model predicted this competition reasonably well, but the NICA-Donnan model underestimated the effects significantly at pH 6. Overall, the Cu-binding behaviour of the two hydrophilic acid fractions was very similar to that of the hydrophobic acid fraction, despite the differences observed in proton-binding characteristics. These results show that for modelling purposes, it is essential to include the hydrophilic acid fraction in the pool of 'active' humic substances.QC 20100525</p

Skewed X-inactivation is common in the general female population

X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants

Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. Acknowledgements: We especially thank all volunteers who participated in our study. This study made use of data generated by the ‘Genome of the Netherlands’ project, which is funded by the Netherlands Organization for Scientific Research (grant no. 184021007). The data were made available as a Rainbow Project of BBMRI-NL. Samples were contributed by LifeLines (http://lifelines.nl/lifelines-research/general), the Leiden Longevity Study (http://www.healthy-ageing.nl; http://www.langleven.net), the Netherlands Twin Registry (NTR: http://www.tweelingenregister.org), the Rotterdam studies (http://www.erasmus-epidemiology.nl/rotterdamstudy) and the Genetic Research in Isolated Populations programme (http://www.epib.nl/research/geneticepi/research.html#gip). The sequencing was carried out in collaboration with the Beijing Institute for Genomics (BGI). Cardiovascular Health Study: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268200960009C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL105756 and HL103612 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The CROATIA cohorts would like to acknowledge the invaluable contributions of the recruitment teams in Vis, Korcula and Split (including those from the Institute of Anthropological Research in Zagreb and the Croatian Centre for Global Health at the University of Split), the administrative teams in Croatia and Edinburgh and the people of Vis, Korcula and Split. SNP genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh for CROATIA-Vis, by Helmholtz Zentrum München, GmbH, Neuherberg, Germany for CROATIA-Korcula and by AROS Applied Biotechnology, Aarhus, Denmark for CROATIA-Split. They would also like to thank Jared O’Connell for performing the pre-phasing for all cohorts before imputation. The ERF study as a part of EuroSPAN (European Special Populations Research Network) was supported by European Commission FP-6 STRP grant number 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme ‘Quality of Life and Management of the Living Resources’ of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by joint grant from the Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). This research was financially supported by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). Statistical analyses for the ERF study were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003 PI: Posthuma) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam. We are grateful to all study participants and their relatives, general practitioners and neurologists for their contributions and to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work and P. Snijders for his help in data collection. The FamHS is funded by a NHLBI grant 5R01HL08770003, and NIDDK grants 5R01DK06833603 and 5R01DK07568102. The Framingham Heart Study SHARe Project for GWAS scan was supported by the NHLBI Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix Inc for genotyping services (Contract No. N02-HL-6-4278). DNA isolation and biochemistry were partly supported by NHLBI HL-54776. A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at the Boston University School of Medicine and Boston Medical Center. We are grateful to Han Chen for conducting the 1000G imputation. The Family Heart Study was supported by the by grants R01-HL-087700 and R01-HL-088215 from the National Heart, Lung, and Blood Institute (NHLBI). We would like to acknowledge the invaluable contributions of the families who took part in the Generation Scotland: Scottish Family Health Study, the general practitioners and Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes academic researchers, IT staff, laboratory technicians, statisticians and research managers. SNP genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh. GS:SFHS is funded by the Scottish Executive Health Department, Chief Scientist Office, grant number CZD/16/6. SNP genotyping was funded by the Medical Research Council, United Kingdom. We wish to acknowledge the services of the LifeLines Cohort Study, the contributing research centres delivering data to LifeLines and all the study participants. MESA Whites and the MESA SHARe project are conducted and supported by contracts N01-HC-95159 through N01-HC-95169 and RR-024156 from the NHLBI. Funding for MESA SHARe genotyping was provided by NHLBI Contract N02.HL.6.4278. MESA Family is conducted and supported in collaboration with MESA investigators; support is provided by grants and contracts R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071252, R01HL071258 and R01HL071259. We thank the participants of the MESA study, the Coordinating Center, MESA investigators and study staff for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. Netherland Twin Register (NTR) and Netherlands Study of Depression and Anxiety (NESDA): Funding was obtained from the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants Middelgroot-911-09-032, Spinozapremie 56-464-14192, Geestkracht programme of the Netherlands Organization for Health Research and Development (Zon-MW, grant number 10-000-1002), Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007), VU University’s Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Program (FP7/2007-2013), ENGAGE (HEALTH-F4-2007-201413); the European Science Council (ERC Advanced, 230374); and the European Research Council (ERC-284167). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health, Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). PREVEND genetics is supported by the Dutch Kidney Foundation (Grant E033), the EU project grant GENECURE (FP-6 LSHM CT 2006 037697), the National Institutes of Health (grant 2R01LM010098), The Netherlands Organisation for Health Research and Development (NWO-Groot grant 175.010.2007.006, NWO VENI grant 916.761.70, ZonMw grant 90.700.441) and the Dutch Inter University Cardiology Institute Netherlands (ICIN). The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. J.W.J is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Genotyping was supported by the seventh framework programme of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII) and the Municipality of Rotterdam. We are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project no. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera and Marjolein Peters for their help in creating the GWAS database.Peer reviewedPublisher PD

Skewed X-inactivation is common in the general female population

X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants

Characterization of iron in floating surface films of some natural waters using EXAFS

Floating, iron bearing films have been observed in a wide range of environments, including wetlands, seep waters in ground water discharge areas, small rivers and lakes. To date, knowledge about their formation and composition is scarce. We have investigated the form of iron in floating iron-rich films of different origin, including a pond and a brook, as well as seep water pools of a groundwater discharge area. Sampling sites were located in southern (pond, brook) and central (seep pools) Sweden. Synchrotron-based X-ray absorption spectroscopy (EXAFS and XANES) allowed identification of the iron precipitates present in the films, without any pretreatment. The EXAFS data showed that the iron containing phase formed in the floating films varied in composition between the sites investigated. In the films from two ground water discharge areas, characterized by out-flowing iron(II) rich ground water being high in pH and low in DOC, the iron phase was completely dominated by ferrihydrite. In contrast, surface films sampled from the brook and the pond, the iron speciation showed a mixture of iron(III)-organic complexes and iron (hydr)oxide (most likely ferrihydrite). These waters were oxic and contained higher concentration of DOC than the seep water pools in the ground water discharge areas. The position of the pre-edge peak, which is sensitive to the oxidation state of iron, did not indicate occurrence of iron (II) in any of the films. Elemental composition of one film (seep water), suggested that films contained about one third of organic matter. Ferrihydrite is probably present as small particles with humic material sorbed onto surfaces or included in the particles, making the particles sufficiently hydrophobic to not settle without physical disturbance. The films are fragile and break easily down and become suspended upon disturbance. More studies are warranted in order to understand the mechanism of the formation of these fascinating films and their biogeochemical role.QC 20121203</p

Дипломная работа в структуре высшего медицинского образования

ОБРАЗОВАНИЕ МЕДИЦИНСКОЕ ЗАКОНЧЕННОЕПРОФЕССИОНАЛЬНАЯ КОМПЕТЕНТНОСТ

Chromium(III) Complexation to Natural Organic Matter: Mechanisms and Modeling

Chromium is a common soil contaminant, and it often exists as chromium­(III). However, limited information exists on the coordination chemistry and stability of chromium­(III) complexes with natural organic matter (NOM). Here, the complexation of chromium­(III) to mor layer material and to Suwannee River Fulvic Acid (SRFA) was investigated using EXAFS spectroscopy and batch experiments. The EXAFS results showed a predominance of monomeric chromium­(III)-NOM complexes at low pH (<5), in which only Cr···C and Cr–O–C interactions were observed in the second coordination shell. At pH > 5 there were polynuclear chromium­(III)-NOM complexes with Cr···Cr interactions at 2.98 Å and for SRFA also at 3.57 Å, indicating the presence of dimers (soil) and tetramers (SRFA). The complexation of chromium­(III) to NOM was intermediate between that of iron­(III) and aluminum­(III). Chromium­(III) complexation was slow at pH < 4: three months or longer were required to reach equilibrium. The results were used to constrain chromium-NOM complexation in the Stockholm Humic Model (SHM): a monomeric complex dominated at pH < 5, whereas a dimeric complex dominated at higher pH. The optimized constant for the monomeric chromium­(III) complex was in between those of the iron­(III) and aluminum­(III) NOM complexes. Our study suggests that chromium­(III)-NOM complexes are important for chromium speciation in many environments