Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer

Over the recent years chirped-pulse, Fourier-transform microwave (CP-FTMW) spectrometers have changed the scope of rotational spectroscopy. The broad frequency and large dynamic range make possible structural determinations in molecular systems of increasingly larger size from measurements of heavy atom (C-13, N-15, O-18) isotopes recorded in natural abundance in the same spectrum as that of the parent isotopic species. The design of a broadband spectrometer operating in the 2-8 GHz frequency range with further improvements in sensitivity is presented. The current CP-FTMW spectrometer performance is benchmarked in the analyses of the rotational spectrum of the water heptamer, (H2O)(7), in both 2-8 GHz and 6-18 GHz frequency ranges. Two isomers of the water heptamer have been observed in a pulsed supersonic molecular expansion. High level ab initio structural searches were performed to provide plausible low-energy candidates which were directly compared with accurate structures provided from broadband rotational spectra. The full substitution structure of the most stable species has been obtained through the analysis of all possible singly-substituted isotopologues ((H2O)-O-18 and HDO), and a least-squares r(m)((1)) geometry of the oxygen framework determined from 16 different isotopic species compares with the calculated O-O equilibrium distances at the 0.01 angstrom level. (C) 2013 Elsevier B.V. All rights reserved.

Spatial and temporal analysis of land cover and landscape structure change in Zagros Forests

The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

Investigating within-canopy variation of functional traits and cellular structure of sugar maple (Acer saccharum) leaves

Patterns of increasing leaf mass per area (LMA), area-based leaf nitrogen (Narea), and carbon isotope composition (δ13C) with increasing height in the canopy have been attributed to light gradients or hydraulic limitation in tall trees. Theoretical optimal distributions of LMA and Narea that scale with light maximize canopy photosynthesis; however, sub-optimal distributions are often observed due to hydraulic constraints on leaf development. Using observational, experimental, and modeling approaches, we investigated the response of leaf functional traits (LMA, density, thickness, and leaf nitrogen), leaf carbon isotope composition (δ13C), and cellular structure to light availability, height, and leaf water potential (Ψl) in an Acer saccharum forest to tease apart the influence of light and hydraulic limitations. LMA, leaf and palisade layer thickness, and leaf density were greater at greater light availability but similar heights, highlighting the strong control of light on leaf morphology and cellular structure. Experimental shading decreased both LMA and area-based leaf nitrogen (Narea) and revealed that LMA and Narea were more strongly correlated with height earlier in the growing season and with light later in the growing season. The supply of CO2 to leaves at higher heights appeared to be constrained by stomatal sensitivity to vapor pressure deficit (VPD) or midday leaf water potential, as indicated by increasing δ13C and VPD and decreasing midday Ψl with height. Model simulations showed that daily canopy photosynthesis was biased during the early growing season when seasonality was not accounted for, and was biased throughout the growing season when vertical gradients in LMA and Narea were not accounted for. Overall, our results suggest that leaves acclimate to light soon after leaf expansion, through an accumulation of leaf carbon, thickening of palisade layers and increased LMA, and reduction in stomatal sensitivity to Ψl or VPD. This period of light acclimation in leaves appears to optimize leaf function over time, despite height-related constraints early in the growing season. Our results imply that vertical gradients in leaf functional traits and leaf acclimation to light should be incorporated in canopy function models in order to refine estimates of canopy photosynthesis.

Effects of anticancer drug docetaxel on the structure and function of the rabbit olfactory mucosa

Docetaxel (DCT) is an anticancer drug which acts by disrupting microtubule dynamics in the highly mitotic cancer cells. Thus, this drug has a potential to affect function and organization of tissues exhibiting high cellular turnover. We investigated, in the rabbit, the effects of a single human equivalent dose (6.26mg/kg, i.v.) of DCT on the olfactory mucosa (OM) through light and electron microscopy, morphometry, Ki-67 immunostaining, TUNEL assay and the buried food test for olfactory sensitivity. On post-exposure days (PED) 5 and 10, there was disarrangement of the normal cell layering in the olfactory epithelium (OE), apoptotic death of cells of the OE, Bowman's glands and axon bundles, and the presence (including on PED 3) of blood vessels in the bundle cores. A decrease in bundle diameters, olfactory cell densities and cilia numbers, which was most significant on PED 10 (49.3%, 63.4% and 50%, respectively), was also evident. Surprisingly by PED 15, the OM regained normal morphology. Furthermore, olfactory sensitivity decreased progressively until PED 10 when olfaction was markedly impaired, and with recovery from the impairment by PED 15. These observations show that DCT transiently alters the structure and function of the OM suggesting a high regenerative potential for this tissue.

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Estimating Diagnostic Test Accuracies for Brachyspira hyodysenteriae Accounting for the Complexities of Population Structure in Food Animals

For swine dysentery, which is caused by Brachyspira hyodysenteriae infection and is an economically important disease in intensive pig production systems worldwide, a perfect or error-free diagnostic test ("gold standard") is not available. In the absence of a gold standard, Bayesian latent class modelling is a well-established methodology for robust diagnostic test evaluation. In contrast to risk factor studies in food animals, where adjustment for within group correlations is both usual and required for good statistical practice, diagnostic test evaluation studies rarely take such clustering aspects into account, which can result in misleading results. The aim of the present study was to estimate test accuracies of a PCR originally designed for use as a confirmatory test, displaying a high diagnostic specificity, and cultural examination for B. hyodysenteriae. This estimation was conducted based on results of 239 samples from 103 herds originating from routine diagnostic sampling. Using Bayesian latent class modelling comprising of a hierarchical beta-binomial approach (which allowed prevalence across individual herds to vary as herd level random effect), robust estimates for the sensitivities of PCR and culture, as well as for the specificity of PCR, were obtained. The estimated diagnostic sensitivity of PCR (95% CI) and culture were 73.2% (62.3; 82.9) and 88.6% (74.9; 99.3), respectively. The estimated specificity of the PCR was 96.2% (90.9; 99.8). For test evaluation studies, a Bayesian latent class approach is well suited for addressing the considerable complexities of population structure in food animals.

An in situ surface electrochemistry approach towards whole-cell studies: the structure and reactivity of a Geobacter sulfurreducens submonolayer on electrified metal/electrolyte interfaces

A direct electron transfer process between bacterial cells of electrogenic species Geobacter sulfurreducens (Gs) and electrified electrode surfaces was studied to exploit the reactivity of Gs submonolayers on gold and silver surfaces. A submonolayer of Gs was prepared and studied to explore specifically the heterogeneous electron transfer properties at the bacteria/electrode interface. In situ microscopic techniques characterised the morphology of the Gs submonolayers under the operating conditions. In addition, complementary in situ spectroscopic techniques that allowed us to access in situ molecular information of the Gs with high surface selectivity and sensitivity were employed. The results provided clear evidence that the outermost cytochrome C in Gs is responsible for the heterogeneous electron transfer, which is in direct contact with the metal electrode. Feasibility of single cell in situ studies under operating conditions was demonstrated where the combination of surface-electrochemical tools at the nano- and micro-scale with microbiological approaches can offer unique opportunities for the emerging field of electro-microbiology to explore processes and interactions between microorganisms and electrical devices.

Physiological time structure of the tibialis anterior motor activity during sleep in mice, rats and humans

The validation of rodent models for restless legs syndrome (Willis-Ekbom disease) and periodic limb movements during sleep requires knowledge of physiological limb motor activity during sleep in rodents. This study aimed to determine the physiological time structure of tibialis anterior activity during sleep in mice and rats, and compare it with that of healthy humans. Wild-type mice (n = 9) and rats (n = 8) were instrumented with electrodes for recording the electroencephalogram and electromyogram of neck muscles and both tibialis anterior muscles. Healthy human subjects (31 ± 1 years, n = 21) underwent overnight polysomnography. An algorithm for automatic scoring of tibialis anterior electromyogram events of mice and rats during non-rapid eye movement sleep was developed and validated. Visual scoring assisted by this algorithm had inter-rater sensitivity of 92-95% and false-positive rates of 13-19% in mice and rats. The distribution of the time intervals between consecutive tibialis anterior electromyogram events during non-rapid eye movement sleep had a single peak extending up to 10 s in mice, rats and human subjects. The tibialis anterior electromyogram events separated by intervals <10 s mainly occurred in series of two-three events, their occurrence rate in humans being lower than in mice and similar to that in rats. In conclusion, this study proposes reliable rules for scoring tibialis anterior electromyogram events during non-rapid eye movement sleep in mice and rats, demonstrating that their physiological time structure is similar to that of healthy young human subjects. These results strengthen the basis for translational rodent models of periodic limb movements during sleep and restless legs syndrome/Willis-Ekbom disease.

Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain

Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a set-up of the Weather Research and Forecasting Model (WRF) model that minimises system- atic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable set-up: the horizontal resolution, the planetary boundary layer (PBL) parameterisation scheme and the way the WRF is nested to the driving data set. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model set-ups, but sharing the same driving data set. The results show that the lack of representation of the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis nudging, spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model performance is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

MECHANISMS OF SPECIES DIFFERENCES IN BRAIN ACETYLCHOLINESTERASE SENSITIVITY TO ORGANOPHOSPHATE INHIBITION

In vitro incubation of acetylcholinesterase from brain tissue of several species with organophosphate compounds indicated that the concentrations required to inhibit 50% of acetylcholinesterase activity (IC(,50)) differed from species to species for the same compound (Murphy, et al., 1968; Andersen, et al., 1972, 1977 and 1978).^ The hypothesis that non-specific binding proteins (Lauwerys and Murphy, 1969a,b) exerts a protective effect on acetylcholinesterase, and thus cause the differences observed in IC(,50) studies was tested by a ('3)H-DFP binding experiment. It was found that differences in the amount of non-specific binding protein cannot explain the observed differences observed in IC(,50) studies.^ An alternative hypothesis, that acetylcholinesterase from different species have different affinities for binding and/or different rates of phosphorylation by organophosphate insecticides was tested by determining the apparent affinity constant (k(,a)) and apparent rate of phosphorylation (k(,p)). Kinetic studies indicated that acetylcholinesterases from different species have different sensitivities to inhibition by organophosphate insecticides, and the differences are due to different affinities for binding and/or different rates of phosphorylation by the same organophosphate compound.^ Studies of the spontaneous reactivation of acetylcholinesterase after inhibition by organophosphate insecticides also indicated that acetylcholinesterases from different species have different rates and extents of spontaneous reactivation. This further substantiates the hypothesis that acetylcholinesterases from different species have different kinetic characteristics with respect to organophosphate insecticides inhibition.^ Eleven paraoxon analogs were synthesized for a quantitative structure-activity relationship study. It was found that the electron-withdrawing power ((sigma)) and hydrophobicity ((PARAGR)) of the substituent are important in determining the anti-cholinesterase activity of paraoxon analogs. Thus, predictions of species differences in acetylcholinesterase sensitivities to paraoxon analogs can be made if the physicochemical parameters ((sigma) and (PARAGR)) of the substituents are known.^ In another approach, i.e. enzyme modeling, the sensitivity of rat brain acetylcholinesterase to organophosphate insecticides was used as the independent variable to predict the sensitivities of acetylcholinesterases from other species to the same compound. Regression equations were derived for each species based on nineteen organophosphate insecticides studied. It was found, that in addition to paraoxon analogs, this method is also applicable to other organophosphate compounds with wide variations in structure. Thus, the sensitivities of acetylcholinesterases from other species can also be predicted from the sensitivity of rat brain acetylcholinesterase. ^

Climate sensitivity across marine domains of life: limits to evolutionary adaptation shape species interactions, supplementary material

Organisms in all domains, Archaea, Bacteria, and Eukarya will respond to climate change with differential vulnerabilities resulting in shifts in species distribution, coexistence, and interactions. The identification of unifying principles of organism functioning across all domains would facilitate a cause and effect understanding of such changes and their implications for ecosystem shifts. For example, the functional specialization of all organisms in limited temperature ranges leads us to ask for unifying functional reasons. Organisms also specialize in either anoxic or various oxygen ranges, with animals and plants depending on high oxygen levels. Here, we identify thermal ranges, heat limits of growth, and critically low (hypoxic) oxygen concentrations as proxies of tolerance in a meta-analysis of data available for marine organisms, with special reference to domain-specific limits. For an explanation of the patterns and differences observed, we define and quantify a proxy for organismic complexity across species from all domains. Rising complexity causes heat (and hypoxia) tolerances to decrease from Archaea to Bacteria to uni- and then multicellular Eukarya. Within and across domains, taxon-specific tolerance limits likely reflect ultimate evolutionary limits of its species to acclimatization and adaptation. We hypothesize that rising taxon-specific complexities in structure and function constrain organisms to narrower environmental ranges. Low complexity as in Archaea and some Bacteria provide life options in extreme environments. In the warmest oceans, temperature maxima reach and will surpass the permanent limits to the existence of multicellular animals, plants and unicellular phytoplankter. Smaller, less complex unicellular Eukarya, Bacteria, and Archaea will thus benefit and predominate even more in a future, warmer, and hypoxic ocean.

Relative sensitivity of soft-bottom intertidal macrofauna to increased CO2 and experimental stress

We used a controlled CO2 perturbation experiment to test hypotheses about changes in diversity, composition and structure of soft-bottom intertidal macrobenthic assemblages, under realistic and locally relevant scenarios of seawater acidification. Patches of undisturbed sediment were collected from 2 types of intertidal sedimentary habitat in the Ria Formosa coastal lagoon (South Portugal) and exposed to 2 levels of seawater acidification (pH reduced by 0.3 and 0.6 units) and 1 unmanipulated (control) level. After 75 d the assemblages differed significantly between the 2 types of sediment and between field controls and the ex situ treatments, but not among the 3 pH levels tested. The naturally high values of total alkalinity buffered seawater from the changes imposed on carbonate chemistry and may have contributed to offsetting acidification at the local scale. Observed differences on biota were strongly related to the organic matter content and grain-size of the sediments, particularly to the fractions of medium and coarse sand. Soft-bottom intertidal macrofauna was significantly affected by the stress of being held in an artificial environment, but not by CO2-induced seawater acidification. Given the previously observed variations in the sensitivities of marine organisms to seawater acidification, direct extrapolations of the present findings to different regions or other types of assemblages do not seem advisable. However, the contribution of ex situ studies to the assessment of ecosystem-level responses to environmental disturbances could generally be improved by incorporating adequate field controls in the experimental design.

Analysis of the railway track as a spatially periodic structure

This article presents a new and computationally efficient method of analysis of a railway track modelled as a continuous beam of 2N spans supported by elastic vertical springs. The main feature of this method is its important reduction in computational effort with respect to standard matrix methods of structural analysis. In this article, the whole structure is considered to be a repetition of a single one. The analysis presented is applied to a simple railway track model, i.e. to a repetitive beam supported on vertical springs (sleepers). The proposed method of analysis is based on the general theory of spatially periodic structures. The main feature of this theory is the possibility to apply Discrete Fourier Transform (DFT) in order to reduce a large system of q(2N + 1) linear stiffness equilibrium equations to a set of 2N + 1 uncoupled systems of q equations each. In this way, a dramatic reduction of the computational effort of solving the large system of equations is achieved. This fact is particularly important in the analysis of railway track structures, in which N is a very large number (around several thousands), and q = 2, the vertical displacement and rotation, is very small. The proposed method allows us to easily obtain the exact solution given by Samartín [1], i.e. the continuous beam railway track response. The comparison between the proposed method and other methods of analysis of railway tracks, such as Lorente de Nó and Zimmermann-Timoshenko, clearly shows the accuracy of the obtained results for the proposed method, even for low values of N. In addition, identical results between the proposed and the Lorente methods have been found, although the proposed method seems to be of simpler application and computationally more efficient than the Lorente one. Small but significative differences occur between these two methods and the one developed by Zimmermann-Timoshenko. This article also presents a detailed sensitivity analysis of the vertical displacement of the sleepers. Although standard matrix methods of structural analysis can handle this railway model, one of the objectives of this article is to show the efficiency of DFT method with respect to standard matrix structural analysis. A comparative analysis between standard matrix structural analysis and the proposed method (DFT), in terms of computational time, input, output and also software programming, will be carried out. Finally, a URL link to a MatLab computer program list, based on the proposed method, is given

Liquid crystal temperature sensor based on a micrometric structure and a metallic nanometric layer

This letter presents a novel temperature sensor, which consists of an interdigitated comb electrode structure with a micrometric-scale size, nanometric metallic layer, and nematic liquid crystal (NLC) film. This sensor exploits the permittivity dependence of the NLC with temperature and principle of electrical conductivity above the percolation threshold in thin film metallic layers. The latter has been demonstrated to increase the temperature sensitivity considerably. The high impedance input reduces the power dissipation, and the high enough voltage output makes it easy to measure the output signal with high precision. The operation principle and fabrication process as well as the characterization of the temperature sensor are presented. Experimental results show that the device offers a sensitivity of 9 mV/°C and is dependent on the applied voltage. This is six times greater than the same structure without the use of a nanometric layer.

A novel high-sensitivity, low-power, liquid crystal temperature sensor

A novel temperature sensor based on nematic liquid crystal permittivity as a sensing magnitude, is presented. This sensor consists of a specific micrometric structure that gives considerable advantages from other previous related liquid crystal (LC) sensors. The analytical study reveals that permittivity change with temperature is introduced in a hyperbolic cosine function, increasing the sensitivity term considerably. The experimental data has been obtained for ranges from −6 °C to 100 °C. Despite this, following the LC datasheet, theoretical ranges from −40 °C to 109 °C could be achieved. These results have revealed maximum sensitivities of 33 mVrms/°C for certain temperature ranges; three times more than of most silicon temperature sensors. As it was predicted by the analytical study, the micrometric size of the proposed structure produces a high output voltage. Moreover the voltage’s sensitivity to temperature response can be controlled by the applied voltage. This response allows temperature measurements to be carried out without any amplification or conditioning circuitry, with very low power consumption.