Kinetics of coupled Fe(II)-catalysed ferrihydrite transformation and U(VI) reduction

Antimony is released into the environment in some natural and man-induced processes. [1]. Yet, its impact on the transformation processes of heavy metal-adsorbing minerals remains poorly understood. In acid-mine drainage systems and shooting ranges, the adsorption of antimony by iron oxides such as ferrihydrite can play a major role. The poorly crystalline 2-line ferrihydrite represents one of the most common Fe oxides in these settings and can transform to goethite (,-FeOOH) or hematite (,-Fe2O3) with time [2]. The rate of transformation depends on the pH, temperature, and on the ions and molecules present during the transformation process [3]. This study focuses on the transformation of synthetic ferrihydrite to crystalline iron oxides in the presence of Sb(V). Transformations were carried out for 1-16 days at 70 ºC and at pH 4, 7 and 12, with different concentrations of Sb(V) (0.00, 0.23, 0.75, 2.25 and 6.00 mM Sb). Samples taken from aqueous suspensions were washed, dried, and characterized by X-ray diffraction (XRD) and atomic absorption spectroscopy (AAS). At pH 12, goethite (Sb concentrations up to 3.7 mg Sb/g) is favored and the transformation is completed after one day. Only a concentration of 6 mM Sb retarded the transformation, where even after 8 days only 50 % of the ferrihydrite was transformed into goethite. Transformations at pH 7 led to a mixture of 75 % hematite and 25 % goethite (4.3 mg Sb/g). However, at concentrations of 6 mM Sb, feroxyhyte (!- FeOOH) (9.1 mg Sb/g) was favored instead. At pH 4, hematite (32.3 mg Sb/g) was favored except for concentrations of 6 mM Sb, were again feroxyhyte (141.1 mg Sb/g) occurred. We assume that increased Sb concentrations favor feroxyhyte and indicate the incorporation of Sb into the structure of feroxyhyte. © The Author

Ferric iron geometry and coordination during hydrolysis and ferrihydrite precipitation

Definitive structural characterisation of ferrihydrite has challenged scientists primarily due to its nanosized particles and inherent long-range structural disorder which challenges analytical methodology (and modelling) typically employed to determine the structure of minerals. Here we report on the application of a synchrotron quick-scanning X-ray absorption spectroscopy (XAS) approach, which allows the collection of Extended X-ray Absorption Fine Structure (EXAFS) spectral data to k = 15 Å-1 in < 1 minute, to obtain unparalleled iron Kedge data on the hydrolysis of FeIII(H2O)6 and ferrihydrite precipitation. Modelling of the pre-edge and EXAFS data: 1) supports theoretical studies which have suggested the existence of a monomeric penta-coordinated FeIII hydrolysis species and; 2) corroborates recently proposed structural models of ferrihydrite that contain tetrahedral FeIII. Modelling results indicate that ferrihydrite consists of 15 to 25 % tetrahedral FeIII and suggest that this geometry must be included in any comprehensive structural model of ferrihydrite and, furthermore, should be considered when evaluating the reactivity, stability and other structure-property relationships of this mineral. © The Authors

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

A comparison of SNP and STR loci for delineating population structure and performing individual genetic assignment

<p>Abstract</p> <p>Background</p> <p>Technological advances have lead to the rapid increase in availability of single nucleotide polymorphisms (SNPs) in a range of organisms, and there is a general optimism that SNPs will become the marker of choice for a range of evolutionary applications. Here, comparisons between 300 polymorphic SNPs and 14 short tandem repeats (STRs) were conducted on a data set consisting of approximately 500 Atlantic salmon arranged in 10 samples/populations.</p> <p>Results</p> <p>Global F_STranged from 0.033-0.115 and -0.002-0.316 for the 14 STR and 300 SNP loci respectively. Global F_STwas similar among 28 linkage groups when averaging data from mapped SNPs. With the exception of selecting a panel of SNPs taking the locus displaying the highest global F_STfor each of the 28 linkage groups, which inflated estimation of genetic differentiation among the samples, inferred genetic relationships were highly similar between SNP and STR data sets and variants thereof. The best 15 SNPs (30 alleles) gave a similar level of self-assignment to the best 4 STR loci (83 alleles), however, addition of further STR loci did not lead to a notable increase assignment whereas addition of up to 100 SNP loci increased assignment.</p> <p>Conclusion</p> <p>Whilst the optimal combinations of SNPs identified in this study are linked to the samples from which they were selected, this study demonstrates that identification of highly informative SNP loci from larger panels will provide researchers with a powerful approach to delineate genetic relationships at the individual and population levels.</p

Exposure to Non-Steroidal Anti-Inflammatory Drugs during Pregnancy and the Risk of Selected Birth Defects: A Prospective Cohort Study

Contains fulltext : 97906.pdf (publisher's version ) (Open Access)BACKGROUND: Since use of non-steroidal anti-inflammatory drugs (NSAIDs) during pregnancy is common, small increases in the risk of birth defects may have significant implications for public health. Results of human studies on the teratogenic risks of NSAIDs are inconsistent. Therefore, we evaluated the risk of selected birth defects after prenatal exposure to prescribed and over-the-counter NSAIDs. METHODS AND FINDINGS: We used data on 69,929 women enrolled in the Norwegian Mother and Child Cohort Study between 1999 and 2006. Data on NSAID exposure were available from a self-administered questionnaire completed around gestational week 17. Information on pregnancy outcome was obtained from the Medical Birth Registry of Norway. Only birth defects suspected to be associated with NSAID exposure based upon proposed teratogenic mechanisms and previous studies were included in the multivariable logistic regression analyses. A total of 3,023 women used NSAIDs in gestational weeks 0-12 and 64,074 women did not report NSAID use in early pregnancy. No associations were observed between overall exposure to NSAIDs during pregnancy and the selected birth defects separately or as a group (adjusted odds ratio 0.7, 95% confidence interval 0.4-1.1). Associations between maternal use of specific types of NSAIDs and the selected birth defects were not found either, although an increased risk was seen for septal defects and exposure to multiple NSAIDs based on small numbers (2 exposed cases; crude odds ratio 3.9, 95% confidence interval 0.9-15.7). CONCLUSIONS: Exposure to NSAIDs during the first 12 weeks of gestation does not seem to be associated with an increased risk of the selected birth defects. However, due to the small numbers of NSAID-exposed infants for the individual birth defect categories, increases in the risks of specific birth defects could not be excluded

The Role of Pre- and Postnatal Timing of Family Risk Factors on Child Behavior at 36 months

Children growing up in disharmonious families with anxious/depressed mothers are at risk for emotional and behavioral difficulties, however whether these associations reflect postnatal environment, prenatal exposure, or an overall liability is still unclear. This study used prospectively collected data from 24,259 participants of the Norwegian Mother and Child Cohort Study (MoBa). Mothers reported on anxiety/depression and family disharmony twice in pregnancy and twice post pregnancy, as well as on their child’s physical aggression and crying behavior at age 36 months. First, results from an autoregressive cross-lagged model showed a substantial stability in both maternal anxiety/depression and family disharmony from pregnancy to 18 months postnatal, but there was no indication that family disharmony led to maternal anxiety/depression, or the other way around. Second, structural equation models further suggests that the main risk derived from an overall liability, that is, a lasting effect of family risks that spanned the two time periods

AglH, a thermophilic UDP‑<i>N</i>‑acetylglucosamine‑1‑phosphate:dolichyl phosphate GlcNAc‑1‑phosphotransferase initiating protein<i> N</i>‑glycosylation pathway in <i>Sulfolobus acidocaldarius</i>, is capable of complementing the eukaryal Alg7

AglH, a predicted UDP-GlcNAc-1-phosphate:dolichyl phosphate GlcNAc-1-phosphotransferase, is initiating the protein N-glycosylation pathway in the thermoacidophilic crenarchaeon Sulfolobus acidocaldarius. AglH successfully replaced the endogenous GlcNAc-1-phosphotransferase activity of Alg7 in a conditional lethal Saccharomyces cerevisiae strain, in which the first step of the eukaryal protein N-glycosylation process was repressed. This study is one of the few examples of cross-domain complementation demonstrating a conserved polyprenyl phosphate transferase reaction within the eukaryal and archaeal domain like it was demonstrated for Methanococcus voltae (Shams-Eldin et al. 2008). The topology prediction and the alignment of the AglH membrane protein with GlcNAc-1-phosphotransferases from the three domains of life show significant conservation of amino acids within the different proposed cytoplasmic loops. Alanine mutations of selected conserved amino acids in the putative cytoplasmic loops II (D(100)), IV (F(220)) and V (F(264)) demonstrated the importance of these amino acids for cross-domain AlgH activity in in vitro complementation assays in S. cerevisiae. Furthermore, antibiotic treatment interfering directly with the activity of dolichyl phosphate GlcNAc-1-phosphotransferases confirmed the essentiality of N-glycosylation for cell survival

Effects of attention and perceptual uncertainty on cerebellar activity during visual motion perception

Recent clinical and neuroimaging studies have revealed that the human cerebellum plays a role in visual motion perception, but the nature of its contribution to this function is not understood. Some reports suggest that the cerebellum might facilitate motion perception by aiding attentive tracking of visual objects. Others have identified a particular role for the cerebellum in discriminating motion signals in perceptually uncertain conditions. Here, we used functional magnetic resonance imaging to determine the degree to which cerebellar involvement in visual motion perception can be explained by a role in sustained attentive tracking of moving stimuli in contrast to a role in visual motion discrimination. While holding the visual displays constant, we manipulated attention by having participants attend covertly to a field of random-dot motion or a colored spot at fixation. Perceptual uncertainty was manipulated by varying the percentage of signal dots contained within the random-dot arrays. We found that attention to motion under high perceptual uncertainty was associated with strong activity in left cerebellar lobules VI and VII. By contrast, attending to motion under low perceptual uncertainty did not cause differential activation in the cerebellum. We found no evidence to support the suggestion that the cerebellum is involved in simple attentive tracking of salient moving objects. Instead, our results indicate that specific subregions of the cerebellum are involved in facilitating the detection and discrimination of task-relevant moving objects under conditions of high perceptual uncertainty. We conclude that the cerebellum aids motion perception under conditions of high perceptual demand

Towards a Physiology-Based Measure of Pain: Patterns of Human Brain Activity Distinguish Painful from Non-Painful Thermal Stimulation

Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessment has long been self-report. Because the inability to verbally communicate can prevent effective pain management, research efforts have focused on the development of a tool that accurately assesses pain without depending on self-report. Those previous efforts have not proven successful at substituting self-report with a clinically valid, physiology-based measure of pain. Recent neuroimaging data suggest that functional magnetic resonance imaging (fMRI) and support vector machine (SVM) learning can be jointly used to accurately assess cognitive states. Therefore, we hypothesized that an SVM trained on fMRI data can assess pain in the absence of self-report. In fMRI experiments, 24 individuals were presented painful and nonpainful thermal stimuli. Using eight individuals, we trained a linear SVM to distinguish these stimuli using whole-brain patterns of activity. We assessed the performance of this trained SVM model by testing it on 16 individuals whose data were not used for training. The whole-brain SVM was 81% accurate at distinguishing painful from non-painful stimuli (p<0.0000001). Using distance from the SVM hyperplane as a confidence measure, accuracy was further increased to 84%, albeit at the expense of excluding 15% of the stimuli that were the most difficult to classify. Overall performance of the SVM was primarily affected by activity in pain-processing regions of the brain including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex. Region of interest (ROI) analyses revealed that whole-brain patterns of activity led to more accurate classification than localized activity from individual brain regions. Our findings demonstrate that fMRI with SVM learning can assess pain without requiring any communication from the person being tested. We outline tasks that should be completed to advance this approach toward use in clinical settings