Biosynthetic Chlorination of the Piperazate Residue in Kutzneride Biosynthesis by KthP

Kutznerides 2 and 8 of the cyclic hexadepsipeptide family of antifungal natural products from the soil actinomycete Kutzneria sp. 744 contain two sets of chlorinated residues, a 6,7-dichlorohexahydropyrroloindole moiety derived from dichlorotryptophan and a 5-chloropiperazate moiety, as well as a methylcyclopropylglycine residue that may arise from isoleucine via a cryptic chlorination pathway. Previous studies identified KtzD, KtzQ and KtzR as three halogenases in the kutzneride pathway but left no candidate for installing the CS chlorine on piperazate. On the basis of analysis of the complete genome sequence of Kutzneria, we now identify a fourth halogenase in the pathway whose gene is separated from the defined kutzneride cluster by 12 open reading frames. KthP (kutzneride halogenase for piperazate) is a mononuclear nonheme iron halogenase that acts on the piperazyl ring tethered by a thioester linkage to the holo forms of thiolation domains. MS analysis of the protein-bound product confirmed chlorination of the piperazate framework from the (3S)- but not the (3R)-piperazyl-S-pantetheinyl thiolation proteins. After thioesterase-mediated release, nuclear magnetic resonance was used to assign the free imino acid as (3S,5S)-5-chloropiperazate, distinct from the 3S,5R stereoisomer reported in the mature kutznerides. These results demonstrate that a fourth halogenase, KthP, is active in the kutzneride biosynthetic pathway and suggest further processing of the (3S,5S)-5-chloropiperazate during subsequent incorporation into the kutzneride depsipeptide frameworks.

Children’s Reasoning About the Temporal Order of Past and Future Events

Four- and five-year-olds completed two sets of tasks that involved reasoning about the temporal order in which events had occurred in the past or were to occur in the future. Four-year-olds succeeded on the tasks that involved reasoning about the order of past events but not those that involved reasoning about the order of future events, whereas 5-year-olds passed both types of tasks. Individual children who failed the past-event tasks were not particularly likely to fail the more difficult future-event tasks. However, children's performance on the reasoning tasks was predictive of their performance on a task assessing their comprehension of the terms “before” and “after.” Our results suggest that there may be a developmental change over this age range in the ability to flexibly represent and reason about the before-and-after relationships between events.

Energy Dependence of Gold Nanoparticle Radiosensitization in Plasmid DNA

Gold nanoparticles (GNPs) are of considerable interest for use as a radiosensitizer, because of their biocompatibility and their ability to increase dose deposited because of their high mass energy absorption coefficient. Their sensitizing properties have been verified experimentally, but a discrepancy between the experimental results and theoretical predictions suggests that the sensitizing effect does not depend solely on gold's superior absorption of energetic photons. This work presents the results of three sets of experiments that independently mapped out the energy dependence of the radiosensitizing effects of GNPs on plasmid DNA suspended in water. Incident photon energy was varied from 11.8 to 80 keV through the use of monochromatic synchrotron and broadband X-rays. These results depart significantly from the theoretical predictions in two ways: First, the sensitization is significantly larger than would be predicted; second, it does not vary with energy as would be predicted from energy absorption coefficients. These results clearly demonstrate that the effects of GNP-enhanced therapies cannot be predicted by considering additional dose alone and that a greater understanding of the processes involved is necessary for the development of future therapeutics.

Determining the parametric effectiveness of a CAD model

The motivation for this paper is to present an approach for rating the quality of the parameters in a computer-aided design model for use as optimization variables. Parametric Effectiveness is computed as the ratio of change in performance achieved by perturbing the parameters in the optimum way, to the change in performance that would be achieved by allowing the boundary of the model to move without the constraint on shape change enforced by the CAD parameterization. The approach is applied in this paper to optimization based on adjoint shape sensitivity analyses. The derivation of parametric effectiveness is presented for optimization both with and without the constraint of constant volume. In both cases, the movement of the boundary is normalized with respect to a small root mean squared movement of the boundary. The approach can be used to select an initial search direction in parameter space, or to select sets of model parameters which have the greatest ability to improve model performance. The approach is applied to a number of example 2D and 3D FEA and CFD problems.

Approximating the Set of Local Minima in Partial RNA Folding Landscapes

Motivation: We study a stochastic method for approximating the set of local minima in partial RNA folding landscapes associated with a bounded-distance neighbourhood of folding conformations. The conformations are limited to RNA secondary structures without pseudoknots. The method aims at exploring partial energy landscapes pL induced by folding simulations and their underlying neighbourhood relations. It combines an approximation of the number of local optima devised by Garnier and Kallel (2002) with a run-time estimation for identifying sets of local optima established by Reeves and Eremeev (2004).

Results: The method is tested on nine sequences of length between 50 nt and 400 nt, which allows us to compare the results with data generated by RNAsubopt and subsequent barrier tree calculations. On the nine sequences, the method captures on average 92% of local minima with settings designed for a target of 95%. The run-time of the heuristic can be estimated by O(n2D?ln?), where n is the sequence length, ? is the number of local minima in the partial landscape pL under consideration and D is the maximum number of steepest descent steps in attraction basins associated with pL.

Design of a thick-walled screen for flow equalization in microstructured reactors

A systematic computational fluid dynamics (CFD) approach has been applied to design the geometry of the channels of a three-dimensional (thick-walled) screen comprising upstream and downstream sets of elongated channels positioned at an angle of 90 degrees with respect to each other. Such a geometry of the thick-wall screen can effectively drop the ratio of the maximum flow velocity to mean flow velocity below 1.005 in a downstream microstructured reactor at low Reynolds numbers. In this approach the problem of flow equalization reduces to that of flow equalization in the first and second downstream channels of the thick-walled screen. In turn, this requires flow equalization in the corresponding cross-sections of the upstream channels. The validity of the proposed design method was assessed through a case study. The effect of different design parameters on the flow non-uniformity in the downstream channels has been established. The design equation is proposed to calculate the optimum values of the screen parameters. The CFD results on flow distribution were experimentally validated by Laser Doppler Anemometry measurements in the range of Reynolds numbers from 6 to 113. The measured flow non-uniformity in the separate reactor channels was below 2%.

KINETICS OF REDUCTION OF HEXACYANOFERRATE(III) BY THIOSULFATE IONS MEDIATED BY RUTHENIUM DIOXIDE HYDRATE

The kinetics of reduction of hexacyanoferrate(III) by excess thiosulfate, mediated by RuO2.xH2O, are investigated. At high concentrations of S2O32- (0.1 mol dm-3) the kinetics of Fe(CN)63- reduction are first order with respect to [Fe(CN)63-] and [RuO2.xH2O] and independent of [Fe(CN)64-], [S2O32-] and [S4O62-]. At relatively low concentrations Of S2O32- (0.01 mol dm-3) and in the presence of appreciable concentrations of Fe(CN)64- and S4O62- (0.01 mol dm-3) the kinetics depend directly upon [Fe(CN)63-] and [RuO2.xH2O] and inversely upon [Fe(CN)64-]. Both sets of kinetics can be rationalised using an electrochemical model of redox catalysts in which a reversible reduction reaction [Fe(CN)63- + e- --> Fe(CN)64-] is coupled to an irreversible oxidation reaction (s2O32- - e- --> 1/2S4O62-), by a dispersion of RuO2.xH2O microelectrodes. At high concentrations Of S2O32- this model predicts that the kinetics of Fe(CN)63- reduction are controlled by the rate of diffusion of the Fe(CN)63- ions to the RuO2.xH2O particles. The kinetics observed at low concentrations of S2O32- are predicted by the electrochemical model, assuming that the Tafel slope for the oxidation Of S2O32- to S4O62- on the RuO2.xH2O particles is 56.4 mV decade-1.

Screening and confirmatory determination of ractopamine residues in calves treated with growth promoting doses of the beta-agonist

Ractopamine (RCT) is a phenethanolamine member of the family of beta-adrenergic agonists (beta-agonists), This class of compounds have become notable for their properties of enhancing the growth rates of farm animal species but are not licensed for use in Europe. An ELISA procedure employing a polyclonal antibody raised in a goat was developed to detect RCT residues in bovine urine samples, The assay had a high sensitivity (calibration curve mid-point of 22 pg per well), allowing the analysis of urine samples without the need for sample clean-up. In addition, an LC-MS-MS confirmatory procedure was developed which was able to act as a confirmatory procedure for the ELISA results. Four calves were orally treated with RCT (0.1 mg kg(-1) body mass for 17 d) and urine samples collected were assayed by both analytical procedures. It was observed that RCT residues were excreted mainly in the form of glucuronides and deconjugation could be achieved using two different sources of the enzyme beta-glucuronidase (Helix pomatia and Escherichia coli), High concentrations of RCT residues were found throughout the medication period (44-473 ng ml(-1); LC-MS-MS data) and remained present for several days following removal of the drug from the diet, RCT residues were no longer detectable 2 weeks after withdrawal, Good agreement (r(2) = 0.73) was achieved between the ELISA and LC-MS-MS results, especially when sample deconjugation was applied to the urine samples for both sets of analyses, The results show that an effective screening and confirmatory system was devised to detect RCT residues in urine samples taken during treatment and close to withdrawal, However, alternative matrices may have to be selected to allow the illegal use of the substance to be detected following prolonged withdrawal times.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

The nervous system of Amphilina foliacea (Platyhelminthes, Amphilinidea). An immunocytochemical, ultrastructural and spectrofluorometrical study

The nervous system of young and adult Amphilina foliacea was studied with immunocytochemical, electron microscopical and spectrofluorometrical methods. The general neuroanatomy is described in detail. New data on the structure and development of the brain were obtained. The 5-HT and GYIRFamide-immunoreactivities occur in separate sets of neurones. The innervation of the reproductive organs is described. The fine structure of 2 types of neurones in the CNS, a sensory neurone, a 'glial' cell type, the neuropile and the synapses are described. The level of 5-HT varies between 0.074 and 0.461 mug/g wet weight. This is the first detailed study of the nervous system of A. foliacea. Earlier data on the structure of the nervous system in A. foliacea published in Russian are introduced into the discussion. The study provides data that can be used when considering the phylogenetic position of Amphilinidea.

Cryptic plasmid pKA22 isolated from the naphthalene degrading derivative of Rhodococcus rhodochrous NCIMB13064

Cryptic plasmids were found in Rhodococcus rhodochrous NCIMB13064 derivatives which had lost the ability to utilize short-chain 1-chloroalkanes (chain length C-3-C-10) and had acquired the ability to degrade naphthalene. The reversions of these derivatives to the original phenotype were accompanied by the loss of the cryptic plasmids. The 4969-bp pKA22 plasmid was cloned in Escherichia coli and sequenced. This plasmid encodes a putative 33,200-Da protein which contains motifs typical of theta replicase proteins and shows a high degree of similarity to a putative theta replicase from Brevibacterium linens plasmid pRBL1 and to a putative protein encoded by ORF1 of the plasmid pAL5000 from Mycobacterium fortuitum. Two sets of long direct repeats were found in pKA22 which may be involved in the replication of the plasmid and recombination processes. (C) 1997 Academic Press.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.

Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with different groups of growth-promoting hormones (dexamethasone, prednisolone, oestradiol) based on recorded metabolite profiles. Two methods of NMR analysis were investigated—a Carr–Purcell–Meiboom–Gill (CPMG)-pulse sequence technique and a conventional 1H NMR method using pre-extracted plasma. Using the CPMG method, 17 distinct metabolites could be identified from the spectra. 1H NMR analysis of extracted plasma facilitated identification of 23 metabolites—six more than the alternative method and all within the aromatic region. Multivariate statistical analysis of acquired data from both forms of NMR analysis separated the plasma metabolite profiles into distinct sample cluster sets representative of the different animal study groups. Samples from both sets of corticosteroid-treated animals—dexamethasone and prednisolone—were found to be clustered relatively closely and had similar alterations to identified metabolite panels. Distinctive metabolite profiles, different from those observed within plasma from corticosteroid-treated animal plasma, were observed in oestradiol-treated animals and samples from these animals formed a cluster spatially isolated from control animal plasma samples. These findings suggest the potential use of NMR methodologies of plasma metabolite analysis as a high-throughput screening technique to aid detection of growth promoter use.

Analysis of the 3D zone of flow establishment from a ship’s propeller

In the present study an experimental investigation of the time-averaged velocity and turbulence intensity distributions from a ship’s propeller, in “bollard pull” condition (zero speed of advance), is reported. Previous studies have focused mainly on the velocity profile of not a rotating ship propeller but a plain jet. The velocity profile of a propeller is investigated experimentally in this study.
The velocity measurements were performed in laboratory by using a Laser Doppler Anemometry (LDA). The measurements demonstrated two-peaked ridges velocity profile with a low velocity core at the centre within the near wake. The two-peaked ridges combined to be one-peaked ridge at 3.68 diameters downstream indicating the end of the zone of flow establishment. The study
provides useful information from a rotating ship’s propeller rather than a simplified plain jet to researchers investigating flow velocity generated from a propeller and probably resulting local scouring.

Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.