On discrimination between carbonate and silicate inputs to Himalayan rivers

We review new and published analyses of river waters, bedloads and their constituent minerals from the Dhauli Ganga and Alaknanda, headwaters of the Ganges in Garhwal, and the Marsyandi in Nepal and their tributaries. These data are used to discriminate between the inputs of major cations and Sr from silicate and carbonate sources. Methods of estimating the proportion of the carbonate and silicate inputs to river waters using mixing arrays in Sr-Ca-Mg-Na-K 87Sr/86Sr space are shown to suffer from systematic correlations between the magnitude of the precipitation of secondary calcite and the fraction of the silicate component. This results in factor-of two overestimates of the fractions of silicate-derived Ca, Mg and Sr. To correct for this the magnitude of secondary calcite precipitated and relative fractions of silicate and carbonate-derived cations are instead calculated by modeling the displacement of water compositions from the compositions of the carbonate and silicate components of the bedload in subsets of Sr-Ca-Mg-Na-K 87Sr/86Sr space. The compositions of the carbonate and silicate end-members in the bedload are determined by sequential leaching. The results of this modeling are compared with modeling of the modal mineral inputs to waters where mineral compositions are derived from electronmicroprobe analyses of the minerals in the bedload. In the upper Marsyandi catchment, which drains low-grade Tethyan Sedimentary Series formations, a set of mainstem samples collected over a two-year period define tight correlations in Sr-Ca-Mg-Na-K- 87Sr/86Sr space. Modeling of the magnitude of secondary carbonate precipitation and fractions of silicate-derived Ca, Mg and Sr in Sr-Ca-Mg 87Sr/86Sr space gives selfconsistent results that are compatible with both the calculations of mineral modes and published Mg-isotopic compositions, if the ratio of chlorite to biotite weathering is high or if there is another silicate source of Mg. These calculations imply that between 12 and 31 percent of the Sr and 44 and 72 percent of the Mg is derived from silicate minerals where the range reflects the seasonal change in the ratio of silicate-derived to carbonate-derived cations. Modeling in Sr-Ca-Na and/or K space is inconsistent with the Sr-isotopic and Mg-isotopic constraints and we conclude that in this catchment dissolution of Na and K are incongruent relative to Sr-Ca-Mg. Potassium is preferentially retained in micas whereas the controls on Na are unclear. Modeling of the catchments underlain by High Himalayan Crystalline and Lesser Himalayan Series in Garhwal is complicated by the presence of dolomite as well as calcite in the carbonate and the results imply that dolomite dissolves faster in the acetic acid leaches than in nature. Up to 60 percent of the Sr in the catchment on High Himalayan Crystalline Series and 20 to 30 percent of Sr in the catchments on Lesser Himalayan Series are estimated to be derived from silicates. However it should be noted that the element budgets are not all self-consistent and the use of bedrock-element ratios to model the sources of chemical inputs to river waters remains subject to uncertainties

Association of the tumour necrosis factor alpha -308 but not the interleukin 10 -627 promoter polymorphism with genetic susceptibility to primary sclerosing cholangitis

BACKGROUND AND AIMS Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease of unknown aetiology. Abnormalities in immune regulation and genetic associations suggest that PSC is an immune mediated disease. Several polymorphisms within the tumour necrosis factor α (TNF-α) and interleukin 10 (IL-10) promoter genes have been described which influence expression of these cytokines. This study examines the possible association between polymorphisms at the −308 and −627 positions in the TNF-α and IL-10 promoter genes, respectively, and susceptibility to PSC. METHODS TNF-α −308 genotypes were studied by polymerase chain reaction (PCR) in 160 PSC patients from Norway and the UK compared with 145 ethnically matched controls. IL-10 −627 genotypes were studied by PCR in 90 PSC patients compared with 84 ethnically matched controls. RESULTS A total of 16% of Norwegian PSC patients and 12% of British PSC patients were homozygous for the TNF2 allele compared with 3% and 6% of respective controls. The TNF2 allele was present in 60% of PSC patients versus 30% of controls (ORcombined data=3.2 (95% confidence intervals (CI) 1.8–4.5); pcorr=10−5). The association between the TNF2 allele and susceptibility to PSC was independent of the presence of concurrent inflammatory bowel disease (IBD) in the PSC patients; 61% of PSC patients without IBD had TNF2 compared with 30% of controls (ORcombined data=3.2 (95% CI 1.2–9.0); pcorr=0.006 ). There was no difference in the −627 IL-10 polymorphism distributions between patients and controls in either population. The increase in TNF2 allele in PSC patients only occurs in the presence of DRB1*0301 (DR3) and B8. In the combined population data, DRB1*0301 showed a stronger association with susceptibility to PSC than both the TNF2 and B8 alleles (ORcombined data=3.8, pcorr=10−6 v ORcombined data=3.2, pcorr=10−5 vORcombined data =3.41, pcorr=10−4, respectively). CONCLUSIONS This study identified a significant association between possession of the TNF2 allele, a G→A substitution at position −308 in the TNF-α promoter, and susceptibility to PSC. This association was secondary to the association of PSC with the A1-B8-DRB1*0301-DQA1*0501-DQB1*0201 haplotype. No association was found between the IL-10 −627 promoter polymorphism and PSC

Laser-Plasma Interactions Enabled by Emerging Technologies

An overview from the past and an outlook for the future of fundamental laser-plasma interactions research enabled by emerging laser systems

Multilocus Sequence Typing Methods for the Emerging Campylobacter Species C. hyointestinalis, C. lanienae, C. sputorum, C. concisus, and C. curvus

Multilocus sequence typing (MLST) systems have been reported previously for multiple food- and food animal-associated Campylobacter species (e.g., C. jejuni, C. coli, C. lari, and C. fetus) to both differentiate strains and identify clonal lineages. These MLST methods focused primarily on campylobacters of human clinical (e.g., C. jejuni) or veterinary (e.g., C. fetus) relevance. However, other, emerging, Campylobacter species have been isolated increasingly from environmental, food animal, or human clinical samples. We describe herein four MLST methods for five emerging Campylobacter species: C. hyointestinalis, C. lanienae, C. sputorum, C. concisus, and C. curvus. The concisus/curvus method uses the loci aspA, atpA, glnA, gltA, glyA, ilvD, and pgm, whereas the other methods use the seven loci defined for C. jejuni (i.e., aspA, atpA, glnA, gltA, glyA, pgm, and tkt). Multiple food animal and human clinical C. hyointestinalis (n = 48), C. lanienae (n = 34), and C. sputorum (n = 24) isolates were typed, along with 86 human clinical C. concisus and C. curvus isolates. A large number of sequence types were identified using all four MLST methods. Additionally, these methods speciated unequivocally isolates that had been typed ambiguously using other molecular-based speciation methods, such as 16S rDNA sequencing. Finally, the design of degenerate primer pairs for some methods permitted the typing of related species; for example, the C. hyointestinalis primer pairs could be used to type C. fetus strains. Therefore, these novel Campylobacter MLST methods will prove useful in differentiating strains of multiple, emerging Campylobacter species

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013

In vivo emergence of HIV-1 highly sensitive to neutralizing antibodies.

BACKGROUND: The rapid and continual viral escape from neutralizing antibodies is well documented in HIV-1 infection. Here we report in vivo emergence of viruses with heightened sensitivity to neutralizing antibodies, sometimes paralleling the development of neutralization escape. METHODOLOGY/PRINCIPAL FINDINGS: Sequential viral envs were amplified from seven HIV-1 infected men monitored from seroconversion up to 5 years after infection. Env-recombinant infectious molecular clones were generated and tested for coreceptor use, macrophage tropism and neutralization sensitivity to homologous and heterologous serum, soluble CD4 and monoclonal antibodies IgG1b12, 2G12 and 17b. We found that HIV-1 evolves sensitivity to contemporaneous neutralizing antibodies during infection. Neutralization sensitive viruses grow out even when potent autologous neutralizing antibodies are present in patient serum. Increased sensitivity to neutralization was associated with susceptibility of the CD4 binding site or epitopes induced after CD4 binding, and mediated by complex envelope determinants including V3 and V4 residues. The development of neutralization sensitive viruses occurred without clinical progression, coreceptor switch or change in tropism for primary macrophages. CONCLUSIONS: We propose that an interplay of selective forces for greater virus replication efficiency without the need to resist neutralizing antibodies in a compartment protected from immune surveillance may explain the temporal course described here for the in vivo emergence of HIV-1 isolates with high sensitivity to neutralizing antibodies

Assessment of osteoarthritis candidate genes in a meta-analysis of nine genome-wide association studies

OBJECTIVE: To assess candidate genes for association with osteoarthritis (OA) and identify promising genetic factors and, secondarily, to assess the candidate gene approach in OA. METHODS: A total of 199 candidate genes for association with OA were identified using Human Genome Epidemiology (HuGE) Navigator. All of their single-nucleotide polymorphisms (SNPs) with an allele frequency of >5% were assessed by fixed-effects meta-analysis of 9 genome-wide association studies (GWAS) that included 5,636 patients with knee OA and 16,972 control subjects and 4,349 patients with hip OA and 17,836 control subjects of European ancestry. An additional 5,921 individuals were genotyped for significantly associated SNPs in the meta-analysis. After correction for the number of independent tests, P values less than 1.58 × 10(-5) were considered significant. RESULTS: SNPs at only 2 of the 199 candidate genes (COL11A1 and VEGF) were associated with OA in the meta-analysis. Two SNPs in COL11A1 showed association with hip OA in the combined analysis: rs4907986 (P = 1.29 × 10(-5) , odds ratio [OR] 1.12, 95% confidence interval [95% CI] 1.06-1.17) and rs1241164 (P = 1.47 × 10(-5) , OR 0.82, 95% CI 0.74-0.89). The sex-stratified analysis also showed association of COL11A1 SNP rs4908291 in women (P = 1.29 × 10(-5) , OR 0.87, 95% CI 0.82-0.92); this SNP showed linkage disequilibrium with rs4907986. A single SNP of VEGF, rs833058, showed association with hip OA in men (P = 1.35 × 10(-5) , OR 0.85, 95% CI 0.79-0.91). After additional samples were genotyped, association at one of the COL11A1 signals was reinforced, whereas association at VEGF was slightly weakened. CONCLUSION: Two candidate genes, COL11A1 and VEGF, were significantly associated with OA in this focused meta-analysis. The remaining candidate genes were not associated

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011