Gut bacteria-host metabolic interplay during conventionalisation of the mouse germfree colon

The interplay between dietary nutrients, gut microbiota and mammalian host tissues of the gastrointestinal tract is recognised as highly relevant for host health. Combined transcriptome, metabonome and microbial profiling tools were employed to analyse the dynamic responses of germfree mouse colonic mucosa to colonisation by normal mouse microbiota (conventionalisation) at different time-points during 16 days. The colonising microbiota showed a shift from early (days 1 and 2) to later colonisers (days 8 and 16). The dynamic changes in the microbial community were rapidly reflected by the urine metabolic profiles (day 1) and at later stages (day 4 onward) by the colon mucosa transcriptome and metabolic profiles. Correlations of host transcriptomes, metabolite patterns and microbiota composition revealed associations between Bacilli and Proteobacteria, and differential expression of host genes involved in energy and anabolic metabolism. Differential gene expression correlated with scyllo- and myo-inositol, glutamine, glycine and alanine levels in colonic tissues during the time span of conventionalisation. Our combined time-resolved analyses may help to expand the understanding of host-microbe molecular interactions during the microbial establishment.

Conditional mean functions of non-linear models of US output

We compare a number of models of post War US output growth in terms of the degree and pattern of non-linearity they impart to the conditional mean, where we condition on either the previous period's growth rate, or the previous two periods' growth rates. The conditional means are estimated non-parametrically using a nearest-neighbour technique on data simulated from the models. In this way, we condense the complex, dynamic, responses that may be present in to graphical displays of the implied conditional mean.

Structure and viscoelasticity of an electrorheological fluid in oscillatory shear: computer simulation investigation

The three-dimensional molecular dynamics simulation method has been used to study the dynamic responses of an electrorheological (ER) fluid in oscillatory shear. The structure and related viscoelastic behaviour of the fluid are found to be sensitive to the amplitude of the strain. With the increase of the strain amplitude, the structure formed by the particles changes from isolated columns to sheet-like structures which may be perpendicular or parallel to the oscillating direction. Along with the structure evolution, the field-induced moduli decrease significantly with an increase in strain amplitude. The viscoelastic behaviour of the structures obtained in the cases of different strain amplitudes was examined in the linear response regime and an evident structure dependence of the moduli was found. The reason for this lies in the anisotropy of the arrangement of the particles in these structures. Short-range interactions between the particles cannot be neglected in determining the viscoelastic behaviour of ER fluids at small strain amplitude, especially for parallel sheets. The simulation results were compared with available experimental data and good agreement was reached for most of them.

Competitive strategy revisited: contested concepts and dynamic capabilities

Strategy is a contested concept. The generic literature is characterized by a diverse range of competing theories and alternative perspectives. Traditional models of the competitive strategy of construction firms have tended to focus on exogenous factors. In contrast, the resource-based view of strategic management emphasizes the importance of endogenous factors. The more recently espoused concept of dynamic capabilities extends consideration beyond static resources to focus on the ability of firms to reconfigure their operating routines to enable responses to changing environments. The relevance of the dynamics capabilities framework to the construction sector is investigated through an exploratory case study of a regional contractor. The focus on how firms continuously adapt to changing environments provides new insights into competitive strategy in the construction sector. Strong support is found for the importance of path dependency in shaping strategic choice. The case study further suggests that strategy is a collective endeavour enacted by a loosely defined group of individual actors. Dynamic capabilities are characterized by an empirical elusiveness and as such are best construed as situated practices embedded within a social and physical context.

A dynamic model of neurovascular coupling: Implications for blood vessel dilation and constriction

Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.

A dynamic causal model of the coupling between pulse stimulation and neural activity

We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.

Dynamic response times of electrorheological fluids in steady shear

Transient responses of electrorheological fluids to square-wave electric fields in steady shear are investigated by computational simulation method. The structure responses of the fluids to the field with high frequency are found to be very similar to that to the field with very low frequency or the sudden applied direct current field. The stress rise processes are also similar in both cases and can be described by an exponential expression. The characteristic time tau of the stress response is found to decrease with the increase of the shear rate (gamma) over dot and the area fraction of the particles phi(2). The relation between them can be roughly expressed as tau proportional to(gamma) over dot(-3/4)phi(2)(-3/2). The simulation results are compared with experimental measurements. The aggregation kinetics of the particles in steady shear is also discussed according to these results.

Many-body effect in electrorheological responses

The many-body effect in the kinetic responses of ER fluids is studied by a molecular-dynamic simulation method. The mutual polarization effects of the particles are considered by self-consistently calculating the dipole strength on each particle according to the external field and the dipole field due to all the other particles in the fluids. The many-body effect is found to increase with the enhancement of the particle concentration and the permittivity ratio between the solvent and the particles. The calculated response times are shorter than that predicted with the 'point-dipole' model and agree very well with experimental results. The many-body effect enhances the shear stresses of the fluids by several times. But they are not proportional to the many-body correction factor lambda as expected. This is due to the fact that larger interaction forces between the particles lead to coarsening of the fibers formed in the suspensions. The results show that the many-body and multipolar interaction between the particles must be treated comprehensively in the simulations in order to get more reliable results.

Ionospheric and geomagnetic responses to changes in IMF B_Z: a superposed epoch study

Superposed epoch studies have been carried out in order to determine the ionospheric response at mid-latitudes to southward turnings of the interplanetary magnetic field (IMF). This is compared with the geomagnetic response, as seen in the indices K p, AE and Dst. The solar wind, IMF and geomagnetic data used were hourly averages from the years 1967–1989 and thus cover a full 22-year cycle in the solar magnetic field. These data were divided into subsets, determined by the magnitudes of the southward turnings and the concomitant increase in solar wind pressure. The superposed epoch studies were carried out using the time of the southward turning as time zero. The response of the mid-latitude ionosphere is studied by looking at the F-layer critical frequencies, f o F2, from hourly soundings by the Slough ionosonde and their deviation from the monthly median values, δf o F2. For the southward turnings with a change in B z of δB z > 11.5 nT accompanied by a solar wind dynamic pressure P exceeding 5 nPa, the F region critical frequency, f o F2, shows a marked decrease, reaching a minimum value about 20 h after the southward turning. This recovers to pre-event values over the subsequent 24 h, on average. The Dst index shows the classic storm-time decrease to about −60 nT. Four days later, the index has still to fully recover and is at about −25 nT. Both the K p and AE indices show rises before the southward turnings, when the IMF is strongly northward but the solar wind dynamic pressure is enhanced. The average AE index does register a clear isolated pulse (averaging 650 nT for 2 h, compared with a background peak level of near 450 nT at these times) showing enhanced energy deposition at high latitudes in substorms but, like K p, remains somewhat enhanced for several days, even after the average IMF has returned to zero after 1 day. This AE background decays away over several days as the Dst index recovers, indicating that there is some contamination of the currents observed at the AE stations by the continuing enhanced equatorial ring current. For data averaged over all seasons, the critical frequencies are depressed at Slough by 1.3 MHz, which is close to the lower decile of the overall distribution of δf o Fl values. Taking 30-day periods around summer and winter solstice, the largest depression is 1.6 and 1.2 MHz, respectively. This seasonal dependence is confirmed by a similar study for a Southern Hemisphere station, Argentine Island, giving peak depressions of 1.8 MHz and 0.5 MHz for summer and winter. For the subset of turnings where δB z > 11.5 nT and P ≤ 5 nPa, the response of the geomagnetic indices is similar but smaller, while the change in δf o F2 has all but disappeared. This confirms that the energy deposited at high latitudes, which leads to the geomagnetic and ionospheric disturbances following a southward turning of the IMF, increases with the energy density (dynamic pressure) of the solar wind flow. The magnitude of all responses are shown to depend on δB z . At Slough, the peak depression always occurs when Slough rotates into the noon sector. The largest ionospheric response is for southward turnings seen between 15–21 UT.

Improved simulation of fire–vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1)

The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.

Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.