Stable isotope composition of atmospheric carbon monoxide : a modelling study

Stable isotope composition of atmospheric carbon monoxide: A modelling study.rnrnThis study aims at an improved understanding of the stable carbon and oxygen isotope composition of the carbon monoxide (CO) in the global atmosphere by means of numerical simulations. At first, a new kinetic chemistry tagging technique for the most complete parameterisation of isotope effects has been introduced into the Modular Earth Submodel System (MESSy) framework. Incorporated into the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model, an explicit treatment of the isotope effects on the global scale is now possible. The expanded model system has been applied to simulate the chemical system containing up to five isotopologues of all carbon- and oxygen-bearing species, which ultimately determine the δ13C, δ18O and Δ17O isotopic signatures of atmospheric CO. As model input, a new stable isotope-inclusive emission inventory for the relevant trace gases has been compiled. The uncertainties of the emission estimates and of the resulting simulated mixing and isotope ratios have been analysed. The simulated CO mixing and stable isotope ratios have been compared to in-situ measurements from ground-based observatories and from the civil-aircraft-mounted CARIBIC−1 measurement platform.rnrnThe systematically underestimated 13CO/12CO ratios of earlier, simplified modelling studies can now be partly explained. The EMAC simulations do not support the inferences of those studies, which suggest for CO a reduced input of the highly depleted in 13C methane oxidation source. In particular, a high average yield of 0.94 CO per reacted methane (CH4) molecule is simulated in the troposphere, to a large extent due to the competition between the deposition and convective transport processes affecting the CH4 to CO reaction chain intermediates. None of the other factors, assumed or disregarded in previous studies, however hypothesised to have the potential in enriching tropospheric CO in 13C, were found significant when explicitly simulated. The inaccurate surface emissions, likely underestimated over East Asia, are responsible for roughly half of the discrepancies between the simulated and observed 13CO in the northern hemisphere (NH), whereas the remote southern hemisphere (SH) compositions suggest an underestimated fractionation during the oxidation of CO by the hydroxyl radical (OH). A reanalysis of the kinetic isotope effect (KIE) in this reaction contrasts the conventional assumption of a mere pressure dependence, and instead suggests an additional temperature dependence of the 13C KIE, which is driven by changes in the partitioning of the reaction exit channels. This result is yet to be confirmed in the laboratory.rnrnApart from 13CO, for the first time the atmospheric distribution of the oxygen mass-independent fractionation (MIF) in CO, Δ17O, has been consistently simulated on the global scale with EMAC. The applicability of Δ17O(CO) observations to unravelling changes in the tropospheric CH4-CO-OH system has been scrutinised, as well as the implications of the ozone (O3) input to the CO isotope oxygen budget. The Δ17O(CO) is confirmed to be the principal signal for the CO photochemical age, thus providing a measure for the OH chiefly involved in the sink of CO. The highly mass-independently fractionated O3 oxygen is estimated to comprise around 2% of the overall tropospheric CO source, which has implications for the δ18O, but less likely for the Δ17O CO budgets. Finally, additional sensitivity simulations with EMAC corroborate the nearly equal net effects of the present-day CH4 and CO burdens in removing tropospheric OH, as well as the large turnover and stability of the abundance of the latter. The simulated CO isotopologues nonetheless hint at a likely insufficient OH regeneration in the NH high latitudes and the upper troposphere / lower stratosphere (UTLS).rn

Chemical interaction between ocean and atmosphere

The exchange of chemical constituents between ocean and atmosphere provides potentially important feedback mechanisms in the climate system. The aim of this study is to develop and evaluate a chemically coupled global atmosphere-ocean model. For this, an atmosphere-ocean general circulation model with atmospheric chemistry has been expanded to include oceanic biogeochemistry and the process of air-sea gas exchange. The calculation of seawater concentrations in the oceanic biogeochemistry submodel has been expanded from DMS, CO₂

Alterations of white matter integrity related to motor activity in schizophrenia

Altered structural connectivity is a key finding in schizophrenia, but the meaning of white matter alterations for behavior is rarely studied. In healthy subjects, motor activity correlated with white matter integrity in motor tracts. To explore the relation of motor activity and fractional anisotropy (FA) in schizophrenia, we investigated 19 schizophrenia patients and 24 healthy control subjects using Diffusion Tensor Imaging (DTI) and actigraphy on the same day. Schizophrenia patients had lower activity levels (AL). In both groups linear relations of AL and FA were detected in several brain regions. Schizophrenia patients had lower FA values in prefrontal and left temporal clusters. Furthermore, using a general linear model, we found linear negative associations of FA and AL underneath the right supplemental motor area (SMA), the right precentral gyrus and posterior cingulum in patients. This effect within the SMA was not seen in controls. This association in schizophrenia patients may contribute to the well known dysfunctions of motor control. Thus, structural disconnectivity could lead to disturbed motor behavior in schizophrenia.

The link between visual exploration and neuronal activity: A multi-modal study combining eye tracking, functional magnetic resonance imaging and transcranial magnetic stimulation

In the present multi-modal study we aimed to investigate the role of visual exploration in relation to the neuronal activity and performance during visuospatial processing. To this end, event related functional magnetic resonance imaging er-fMRI was combined with simultaneous eye tracking recording and transcranial magnetic stimulation (TMS). Two groups of twenty healthy subjects each performed an angle discrimination task with different levels of difficulty during er-fMRI. The number of fixations as a measure of visual exploration effort was chosen to predict blood oxygen level-dependent (BOLD) signal changes using the general linear model (GLM). Without TMS, a positive linear relationship between the visual exploration effort and the BOLD signal was found in a bilateral fronto-parietal cortical network, indicating that these regions reflect the increased number of fixations and the higher brain activity due to higher task demands. Furthermore, the relationship found between the number of fixations and the performance demonstrates the relevance of visual exploration for visuospatial task solving. In the TMS group, offline theta bursts TMS (TBS) was applied over the right posterior parietal cortex (PPC) before the fMRI experiment started. Compared to controls, TBS led to a reduced correlation between visual exploration and BOLD signal change in regions of the fronto-parietal network of the right hemisphere, indicating a disruption of the network. In contrast, an increased correlation was found in regions of the left hemisphere, suggesting an intent to compensate functionality of the disturbed areas. TBS led to fewer fixations and faster response time while keeping accuracy at the same level, indicating that subjects explored more than actually needed.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Segregation analysis of overweight body condition in an experimental cat population

The goal of this study was to analyze the mode of inheritance of an overweight body condition in an experimental cat population. The cat population consisted of 95 cats of which 81 cats could be clearly classified into lean or overweight using the body condition scoring system according to Laflamme. The lean or overweight classification was then used for segregation analyses. Complex segregation analyses were employed to test for the significance of one environmental and 4 genetic models (general, mixed inheritance, major gene, and polygene). The general genetic model fit the data significantly better than the environmental model (P models employed, the major gene model explained the segregation of the overweight phenotype best. This is the first study in which a genetic component could be shown to be responsible for the development of overweight in cats.

Regional mRNA expression of key gluconeogenic enzymes in the liver of dairy cows

Liver tissue was collected from eight random dairy cows at a slaughterhouse to test if gene expression of pyruvate carboxylase (PC), mitochondrial phosphoenolpyruvate carboxykinase (PEPCKm) and cytosolic phosphoenolpyruvate carboxykinase (PEPCKc) is different at different locations in the liver. Obtained liver samples were analysed for mRNA expression levels of PC, PEPCKc and PEPCKm and subjected to the MIXED procedure of SAS to test for the sampled locations with cow liver as repeated subject. Additionally, the general linear model procedure (GLM) for analysis of variance was applied to test for significant differences for mRNA abundance of PEPCKm, PEPCKc and bPC between the livers. In conclusion, this study demonstrated that mRNA abundance of PC, PEPCKc and PEPCKm is not different between locations in the liver but may differ between individual cows.

The impact of different glacial boundary conditions on atmospheric dynamics and precipitation in the North Atlantic region

Using a highly resolved atmospheric general circulation model, the impact of different glacial boundary conditions on precipitation and atmospheric dynamics in the North Atlantic region is investigated. Six 30-yr time slice experiments of the Last Glacial Maximum at 21 thousand years before the present (ka BP) and of a less pronounced glacial state – the Middle Weichselian (65 ka BP) – are compared to analyse the sensitivity to changes in the ice sheet distribution, in the radiative forcing and in the prescribed time-varying sea surface temperature and sea ice, which are taken from a lower-resolved, but fully coupled atmosphere-ocean general circulation model. The strongest differences are found for simulations with different heights of the Laurentide ice sheet. A high surface elevation of the Laurentide ice sheet leads to a southward displacement of the jet stream and the storm track in the North Atlantic region. These changes in the atmospheric dynamics generate a band of increased precipitation in the mid-latitudes across the Atlantic to southern Europe in winter, while the precipitation pattern in summer is only marginally affected. The impact of the radiative forcing differences between the two glacial periods and of the prescribed time-varying sea surface temperatures and sea ice are of second order importance compared to the one of the Laurentide ice sheet. They affect the atmospheric dynamics and precipitation in a similar but less pronounced manner compared with the topographic changes.

Simulated winter circulation types in the North Atlantic and European region for preindustrial and glacial conditions

[1] Winter circulation types under preindustrial and glacial conditions are investigated and used to quantify their impact on precipitation. The analysis is based on daily mean sea level pressure fields of a highly resolved atmospheric general circulation model and focuses on the North Atlantic and European region. We find that glacial circulation types are dominated by patterns with an east-west pressure gradient, which clearly differs from the predominantly zonal patterns for the recent past. This is also evident in the frequency of occurrence of circulation types when projecting preindustrial circulation types onto the glacial simulations. The elevation of the Laurentide ice sheet is identified as a major cause for these differences. In areas of strong precipitation signals in glacial times, the changes in the frequencies of occurrence of the circulation types explain up to 60% of the total difference between preindustrial and glacial simulations.

Climate variability of the mid- and high-latitudes of the Southern Hemisphere in ensemble simulations from 1500 to 2000 AD

To increase the sparse knowledge of long-term Southern Hemisphere (SH) climate variability, we assess an ensemble of 4 transient simulations over the last 500 yr performed with a state-of-the-art atmosphere ocean general circulation model. The model is forced with reconstructions of solar irradiance, greenhouse gas (GHG) and volcanic aerosol concentrations. A 1990 control simulation shows that the model is able to represent the Southern Annular Mode (SAM), and to some extent the South Pacific Dipole (SPD) and the Zonal Wave 3 (ZW3). During the past 500 yr we find that SPD and ZW3 variability remain stable, whereas SAM shows a significant shift towards its positive state during the 20th century. Regional temperatures over South America are strongly influenced by changing both GHG concentrations and volcanic eruptions, whereas precipitation shows no significant response to the varying external forcing. For temperature this stands in contrast to proxy records, suggesting that SH climate is dominated by internal variability rather than external forcing. The underlying dynamics of the temperature changes generally point to a combination of several modes, thus, hampering the possibilities of regional reconstructing the modes from proxy records. The linear imprint of the external forcing is as expected, i.e. a warming for increase in the combined solar and GHG forcing and a cooling after volcanic eruptions. Dynamically, only the increase in SAM with increased combined forcing is simulated.

Estimating the number of motor units using random sums with independently thinned terms

The problem of estimating the numbers of motor units N in a muscle is embedded in a general stochastic model using the notion of thinning from point process theory. In the paper a new moment type estimator for the numbers of motor units in a muscle is denned, which is derived using random sums with independently thinned terms. Asymptotic normality of the estimator is shown and its practical value is demonstrated with bootstrap and approximative confidence intervals for a data set from a 31-year-old healthy right-handed, female volunteer. Moreover simulation results are presented and Monte-Carlo based quantiles, means, and variances are calculated for N in{300,600,1000}.

Increased sensitivity in mapping task demand in visuospatial processing using reaction-time-dependent hemodynamic response predictors in rapid event-related fMRI

Searching for the neural correlates of visuospatial processing using functional magnetic resonance imaging (fMRI) is usually done in an event-related framework of cognitive subtraction, applying a paradigm comprising visuospatial cognitive components and a corresponding control task. Besides methodological caveats of the cognitive subtraction approach, the standard general linear model with fixed hemodynamic response predictors bears the risk of being underspecified. It does not take into account the variability of the blood oxygen level-dependent signal response due to variable task demand and performance on the level of each single trial. This underspecification may result in reduced sensitivity regarding the identification of task-related brain regions. In a rapid event-related fMRI study, we used an extended general linear model including single-trial reaction-time-dependent hemodynamic response predictors for the analysis of an angle discrimination task. In addition to the already known regions in superior and inferior parietal lobule, mapping the reaction-time-dependent hemodynamic response predictor revealed a more specific network including task demand-dependent regions not being detectable using the cognitive subtraction method, such as bilateral caudate nucleus and insula, right inferior frontal gyrus and left precentral gyrus.

Multiple Testing With an Empirical Alternative Hypothesis

An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for use of an empirical alternative hypothesis to increase by 50% or more the number of true positives identified at a given significance level.

Mixture Cure Survival Models with Dependent Censoring

A number of authors have studies the mixture survival model to analyze survival data with nonnegligible cure fractions. A key assumption made by these authors is the independence between the survival time and the censoring time. To our knowledge, no one has studies the mixture cure model in the presence of dependent censoring. To account for such dependence, we propose a more general cure model which allows for dependent censoring. In particular, we derive the cure models from the perspective of competing risks and model the dependence between the censoring time and the survival time using a class of Archimedean copula models. Within this framework, we consider the parameter estimation, the cure detection, and the two-sample comparison of latency distribution in the presence of dependent censoring when a proportion of patients is deemed cured. Large sample results using the martingale theory are obtained. We applied the proposed methodologies to the SEER prostate cancer data.

Perceptual Learning via Modification of Cortical Top-Down Signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.