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The percentage of patients requiring cerclage was 37.5%, 58.8%, 43.3%, and 10% of patients with short cervix first seen at 16-18, 18 1/7-20, 20 1/7-22, and 22 1/7-24 weeks, respectively. OC13.01: Multiple gestation and cervical shortening: serial transvaginal cervical length must begin at 16 weeks Despite progesterone use, progressive shortening triggered cerclage in 30/109 (27.5% of short cervix and 2.3% of all multiples). [Extracted from the article]

Den israelske journalisten og forfatteren Donna Rosentahl kalte sin bok om israelerne «An ordinary people in an extraordinary land». Men alle som har oppholdt seg mye i Israel oppdager at spenningene innad i nasjonen er langt større enn i de fleste andre nasjoner.

The increased use of nanoparticles (NPs) requires efficient testing of their potential toxic effects. A promising approach is to use reporter cell lines to quickly assess the activation of cellular stress response pathways. This study aimed to use the ToxTracker reporter cell lines to investigate (geno)toxicity of various metal- or metal oxide NPs and draw general conclusions on NP-induced effects, in combination with our previous findings. The NPs tested in this study ( n = 18) also included quantum dots (QDs) in different sizes. The results showed a large variation in cytotoxicity of the NPs tested. Furthermore, whereas many induced oxidative stress only few activated reporters related to DNA damage. NPs of manganese (Mn and Mn 3 O 4 ) induced the most remarkable ToxTracker response with activation of reporters for oxidative stress, DNA damage, protein unfolding and p53-related stress. The QDs (CdTe) were highly toxic showing clearly size-dependent effects and calculations suggest surface area as the most relevant dose metric. Of all NPs investigated in this and previous studies the following induce the DNA damage reporter; CuO, Co, CoO, CdTe QDs, Mn, Mn 3 O 4 , V 2 O 5 , and welding NPs. We suggest that these NPs are of particular concern when considering genotoxicity induced by metal- and metal oxide NPs.

This work focuses on kinetic aspects of stability, mobility, and dissolution of bare Cu, Al and Mn, and SiO2 NPs in synthetic freshwater (FW) with and without the presence of natural organic matter (NOM). This includes elucidation of particle and surface interactions, metal dissolution kinetics, and speciation predictions of released metals in solution. Dihydroxy benzoic acid (DHBA) and humic acid adsorbed rapidly on all metal NPs (<1 min) via multiple surface coordinations, followed in general by rapid agglomeration and concomitant sedimentation for a large fraction of the particles. In contrast, NOM did not induce agglomeration of the SiO2 NPs during the test duration (21 days). DHBA in concentrations of 0.1 and 1 mM was unable to stabilize the metal NPs for time periods longer than 6 h, whereas humic acid, at certain concentrations (20 mg/L) was more efficient (>24 h). The presence of NOM increased the amount of released metals into solution, in particular for Al and Cu, whereas the effect for Mn was minor. At least 10% of the particle mass was dissolved within 24 h and remained in solution for the metal NPs in the presence of NOM. Speciation modeling revealed that released Al and Cu predominantly formed complexes with NOM, whereas less complexation was seen for Mn. The results imply that potentially dispersed NPs of Cu, Al and Mn readily dissolve or sediment close to the source in freshwater of low salinity, whereas SiO2 NPs are more stable and therefore more mobile in solution.

Studded tyres made of tungsten carbide cobalt (WC-Co) are in the Northern countries commonly used during the winter time. Tungsten (W)-containing nano- and micron-sized particles have been detected close to busy roads in several European countries. Other typical traffic wear particles consist of copper (Cu). The aims of this study were to investigate particle stability and transformation/dissolution properties of nanoparticles (NPs) of WC-Co compared with NPs of tungsten carbide (WC), cobalt (Co), and Cu. Their physicochemical characteristics (primarily surface oxide and charge) are compared with their extent of sedimentation and metal release in synthetic surface water (SW) with and without two different model organic molecules, 2,3- and 3,4-dihydroxybenzoic acid (DHBA) mimicking certain sorption sites of humic substances, for time periods up to 22 days. The WC-Co NPs possessed a higher electrochemical and chemical reactivity in SW with and without DHBA molecules as compared with NPs of WC, Co, and Cu. Co was completely released from the WC-Co NPs within a few hours of exposure, although it remained adsorbed/bonded to the particle surface and enabled the adsorption of negatively charged DHBA molecules, in contrast with the WC NPs (no adsorption of DHBA). The DHBA molecules were found to rapidly adsorb on the Co and Cu NPs. The sedimentation of the WC and WC-Co NPs was not influenced by the presence of the 2,3- or 3,4-DHBA molecules. A slight influence (slower sedimentation) was observed for the Co NPs, and a strong influence (slower sedimentation) was observed for the Cu NPs in SW with 2,3-DHBA compared with SW alone. The extent of metal release increased in the order: WC < Cu < Co < WC-Co NPs. All NPs released more than 1 wt-% of their metal total mass. The release from the Cu NPs was most influenced by the presence of DHBA molecules., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Many countries intend to use compacted bentonite as a barrier in their deep geological repositories for nuclear waste. In order to describe and predict hydraulic conductivity or radionuclide transport through the bentonite barrier, fundamental understanding of the microstructure of compacted bentonite is needed. This study examined the interlayer swelling and overall microstructure of Wyoming Bentonite MX-80 and the corresponding homo-ionic Na(+) and Ca(2+) forms, using XRD with samples saturated under confined swelling conditions and free swelling conditions. For the samples saturated under confined conditions, the interparticle, or so-called free or external porosity was estimated by comparing the experimental interlayer distances obtained from one-dimensional XRD profile fitting against the maximum interlayer distances possible for the corresponding water content. The results showed that interlayer porosity dominated total porosity, irrespective of water content, and that the interparticle porosity was lower than previously reported in the literature. At compactions relevant for the saturated bentonite barrier (1.4-1.8 g/cm(3)), the interparticle porosity was estimated to ≤3%., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Colloid generation and sedimentation experiments were carried out on Na- and Ca-montmorillonite in order to verify whether pseudo-equilibrium concentrations are reached at the same level in both types of experiments. The size and concentration of colloidal Na- and Ca-montmorillonite particles were monitored as a function of time and distance from the colloid bed in different ionic strength solutions. A stable pseudo-equilibrium concentration was reached after time in generation and sedimentation experiments. The colloid concentration decreased sharply at distances near to the colloid source. Na-montmorillonite concentration at pseudo-equilibrium (roughly quantified at distances > or = 7 cm from the colloid source) was 5.2 +/- 0.5, 0.5 +/- 0.1, and 0.2 +/- 0.1 mg L(-1) in 0.001, 0.01, and 0.1 M NaCl solution, respectively, while the Ca-montmorillonite concentration was 0.4 +/- 0.2 mg L(-1) in 0.001 M NaCl.

The stability of the sodium and calcium forms of montmorillonite was studied at different NaCl and CaCl2 concentrations. The aggregation kinetics was determined from the decrease in particle concentration with time at different electrolyte concentrations. The DLVO theory defines the critical coagulation concentration (CCC) value as the electrolyte concentration that balances the attractive and repulsive potential energies between the particles, making aggregation diffusion-controlled. Therefore CCC values were obtained by extrapolation of the aggregation rate constants measured as a function of ionic strength to conditions where the rate constant value is determined by diffusion only. When the electrolyte was CaCl2, the CCC value was found to be approximately two orders of magnitude lower than the CCC values obtained using NaCl as electrolyte.

The stability of natural bentonite suspensions has been investigated as a function of temperature at pH 9 and ionic strength 10(-3) M. The sedimentation rate of the particles is directly related to their stability. The sedimentation kinetics was determined by examining the variation of particle concentration in solution with time. The observed kinetics for sedimentation is discussed quantitatively in terms of the potential energy between particles. The zeta-potential of the particles was measured and the DLVO theory was used to calculate attractive and repulsive potentials. Experimental observations are consistent with DLVO model predictions and show that the stability of bentonite colloids increases with temperature. Differences with other colloidal systems can be attributed to the temperature dependence of the surface charge of bentonite particles.

This article describes the applicability of multivariate projection techniques, such as principal-component analysis (PCA) and partial least-squares (PLS) projections to latent structures, to the large-volume high-density data structures obtained within genomics, proteomics, and metabonomics. PCA and PLS, and their extensions, derive their usefulness from their ability to analyze data with many, noisy, collinear, and even incomplete variables in both X and Y. Three examples are used as illustrations: the first example is a genomics data set and involves modeling of microarray data of cell cycle-regulated genes in the microorganism Saccharomyces cerevisiae. The second example contains NMR-metabonomics data, measured on urine samples of male rats treated with either of the drugs chloroquine or amiodarone. The third and last data set describes sequence-function classification studies in a set of G-protein-coupled receptors using hierarchical PCA.

Multivariate PCA- and PLS-models involving many variables are often difficult to interpret, because plots and lists of loadings, coefficients, VIPs, etc, rapidly become messy and hard to overview. There may then be a strong temptation to eliminate variables to obtain a smaller data set. Such a reduction of variables, however, often removes information and makes the modelling efforts less reliable. Model interpretation may be misleading and predictive power may deteriorate. A better alternative is usually to partition the variables into blocks of logically related variables and apply hierarchical data analysis. Such blocked data may be analyzed by PCA and PLS. This modelling forms the base-level of the hierarchical modelling set-up. On the base-level in-depth information is extracted for the different blocks. The score vectors formed on the base-level, here called 'super variables', may be linked together in new matrices on the top-level. On the top-level superficial relationships between the X- and the Y-data are investigated. In this paper the basic principles of hierarchical modelling by means of PCA and PLS are reviewed. One objective of the paper is to disseminate this concept to a broader QSAR audience. The hierarchical methods are used to analyze a set of 10 haloalkanes for which K = 30 chemical descriptors and M = 255 biological responses have been gathered. Due to the complexity of the biological data, they are sub-divided in four blocks. All the modelling steps on the base-level and the top-level are reported and the final QSAR model is interpreted thoroughly.

In vivo studies suggest that the Escherichia coli SeqA protein modulates replication initiation in two ways: by delaying initiation and by sequestering newly replicated origins from undergoing re-replication. As a first approach towards understanding the biochemical bases for these effects, we have examined the effects of purified SeqA protein on replication reactions performed in vitro on an oriC plasmid. Our results demonstrate that SeqA directly affects the biochemical events occurring at oriC. First, SeqA inhibits formation of the pre-priming complex. Secondly, SeqA can inhibit replication from an established pre-priming complex, without disrupting the complex. Thirdly, SeqA alters the dependence of the replication system on DnaA protein concentration, stimulating replication at low concentrations of DnaA. Our data suggest that SeqA participates in the assembly of initiation-competent complexes at oriC and, at a later stage, influences the behaviour of these complexes.

Three categories of molecular flexibility are defined. A novel method of aligning partly flexible molecules with each other is described. The binding mode of one of these molecules to its receptor site was already well known from previous crystallographic studies, and this known binding mode was used to predict the binding mode of the other molecules at their receptor. The predictions were checked by comparison with previous observations, and were correct. Two novel methods were combined in this research. It was necessary to take account of the conformational changes which occur when each ligand molecule binds to the protein, and a new release of programme Grid was used for this. It was also necessary to analyse the Grid results in order to distinguish the role of each chemical group at the receptor site. This was done by applying hierarchical principal component analysis (Hi-PCA) methods to the descriptors obtained from Grid.

The seqA gene negatively modulates replication initiation at the E. coli origin, oriC. seqA is also essential for sequestration, which acts at oriC and the dnaA promoter to ensure that replication initiation occurs exactly once per chromosome per cell cycle. Initiation is promoted by full methylation of GATC sites clustered in oriC; sequestration is specific to the hemimethylated forms generated by replication. SeqA protein purification and DNA binding are described. SeqA interacts with fully methylated oriC strongly and specifically. This reaction requires multiple molecules of SeqA and determinants throughout oriC, including segments involved in open complex formation. SeqA interacts more strongly with hemimethylated DNA; in this case, oriC and non-oriC sequences are bound similarly. Also, binding of hemimethylated oriC by membrane fractions is due to SeqA. Direct interaction of SeqA protein with the replication origin is likely to be involved in both replication initiation and sequestration.

The DnaC protein is required for loading the DnaB helicase at oriC. Thus DnaC promotes the formation of the pre-replication complex, but must leave the complex in order for the DnaB protein to function as a helicase. In vitro, a slight excess of DnaC inhibits the movement of replication forks by inhibiting DnaB helicase activity (Allen and Kornberg, 1991). Here we show that inhibition of DNA replication by excess DnaC also occurs in vivo. The rate of replication-fork movement was measured by flow cytometry. Initiation of replication was inhibited with rifampicin and the rate of fork movement monitored during replication runout by measuring the increase in the fraction of the cell population with fully replicated chromosomes. The replication rate was inversely related to the amount of excess DnaC protein. Initiation of replication was also inhibited. Co-overexpression of DnaB protein alleviated the inhibition of replication caused by moderate excess of DnaC. The results show that DnaC interacts with replication forks during elongation in vivo, probably by binding to DnaB and inhibiting its helicase activity. Therefore, the ratio of DnaC to DnaB and the affinity of DnaC for a helicase hexamer at an established replication fork are of great importance for the rate of replication fork movement also in vivo.

Models have been developed that allow the biological activity of a DNA segment to be altered in a desired direction. Partial least squares projections to latent structures (PLS) was used to establish a quantitative model between a numerical description of 68 bp fragments of 25 E.coli promoters and their corresponding quantitative measure of in vivo strength. This quantitative sequence-activity model (QSAM) was used to generate two 68 bp fragments predicted to be more potent promoters than any of those on which the model originally was based. The optimized structures were experimentally verified to be strong promoters in vivo.

A strategy for the systematic analysis and priority ranking of environmental chemicals has been applied to a class of 58 halogenated aliphatic hydrocarbons. A training set of ten compounds representing this class, was selected by statistical design. The training set compounds were then subjected to biological testing in the Salmonella typhimurium reverse mutation assay (Ames test). The measured biological data, recorded as dose-response curves, were analyzed to determine the mutagenic potency (slope of the initial portion) and the mutagen dose (MD 50) required to increase the number of revertants above the background by 50%. For each compound, four mutagenic potency estimates and four MD 50 values were determined, all originating from the tester strains TA 100 and TA 1535 with and without metabolic activation. The obtained responses were analyzed with multivariate techniques to give QSAR models relating the mutagenic potency data to the physico-chemical properties of the compounds. Finally, the derived QSARs were used to predict the mutagenic potencies and the MD 50S for the non-tested compounds in the class.

A new way to represent and analyze DNA sequence data is described. This approach complements methods currently used, in that it allows the systematic part of the variation between different sequences to be modeled. This can prove as informative as absence of variation (homology), which is the most widely used criterion for comparing sequence data. A multivariate sequence-activity model (SAM), for DNA-promoter sequences is presented, by which the relative promoter strength is modeled in terms of the primary DNA-sequence. The model is shown to have a good predictive capability. The coefficients from the model are interpreted, and used to design new structures predicted to be strong promoters in the system investigated. The approach described is also applicable to other kinds of sequence data, e.g. RNAs, proteins or peptides.