Modeling of breath methane concentration profiles during exercise on an ergometer

We develop a simple three compartment model based on mass balance equations which quantitatively describes the dynamics of breath methane concentration profiles during exercise on an ergometer. With the help of this model it is possible to estimate the endogenous production rate of methane in the large intestine by measuring breath gas concentrations of methane.Comment: 17 pages, 4 figure

Parameterizing the microbial loop: an experiment in reducing model complexity

The structure of the plankton food web in the upper mixed layer has important implications for the export of biogenic material from the euphotic zone. While the action of the microbial loop causes material to be recycled near the surface, activity of the larger zooplankton leads to a significant downward flux of material. The balance between these pathways must be properly represented in climate models to predict carbon export. However, the number of biogeochemical compartments available to represent the food web is limited by the need to couple biogeochemical models with general circulation models. A structurally simple model is therefore sought, with a number of free parameters, which can be constrained by available observations to produce reliable estimates of export.A step towards addressing this aim is described: an attempt is made to emulate the behavior of an 11 compartment model with an explicit microbial loop, using a 4 compartment model. The latter, incorporating a basic microbial loop parameterization, is derived directly from the 'true' model. The results are compared with equivalent results for a 4 compartment model with no representation of the microbial loop. These non-identical twin experiments suggest that export estimates from 4 compartment models are prone to serious biases in regions where the action of the microbial loop is significant. The basic parameterization shows some promise in addressing the problem but a more sophisticated parameterization would be needed to produce reliable estimates. Some recommendations are made for future research

Modeling 18F−FDG^{18}F-FDG Kinetics during Acute Lung Injury: Experimental Data and Estimation Errors

Background: There is increasing interest in Positron Emission Tomography (PET) of 2-deoxy-2-[18F]flouro-D-glucose ($^{18}F-FDG$) to evaluate pulmonary inflammation during acute lung injury (ALI). We assessed the effect of extra-vascular lung water on estimates of $^{18}F-FDG$-kinetics parameters in experimental and simulated data using the Patlak and Sokoloff methods, and our recently proposed four-compartment model. Methodology/Principal Findings Eleven sheep underwent unilateral lung lavage and 4 h mechanical ventilation. Five sheep received intravenous endotoxin (10 ng/kg/min). Dynamic $^{18}F-FDG$ PET was performed at the end of the 4 h period. $^{18}F-FDG$ net uptake rate (Ki), phosphorylation rate (k3), and volume of distribution (Fe) were estimated in three isogravitational regions for each method. Simulations of normal and ALI $^{18}F-FDG$-kinetics were conducted to study the dependence of estimated parameters on the transport rate constants to (k5) and from (k6) the extra-vascular extra-cellular compartment. The four-compartment model described 85.7% of the studied $^{18}F-FDG$-kinetics better than the Sokoloff model. Relative to the four-compartment model the Sokoloff model exhibited a consistent positive bias in Ki (3.32 [1.30–5.65] 10−4/min, p<0.001) and showed inaccurate estimates of the parameters composing Ki (k3 and Fe), even when Ki was similar for those methods. In simulations, errors in estimates of Ki due to the extra-vascular extra-cellular compartment depended on both k5 and k5/k6, with errors for the Patlak and Sokoloff methods of 0.02 [−0.01–0.18] and 0.40 [0.18–0.60] 10−3/min for normal lungs and of −0.47 [−0.89–0.72] and 2.35 [0.85–3.68] 10−3/min in ALI. Conclusions/Significance: $^{18}F-FDG$ accumulation in lung extra-vascular fluid, which is commonly increased during lung injury, can result in substantial estimation errors using the traditional Patlak and Sokoloff methods. These errors depend on the extra-vascular extra-cellular compartment volume and its transport rates with other compartments. The four-compartment model provides more accurate quantification of $^{18}F-FDG$-kinetics than those methods in the presence of increased extra-vascular fluid

Results of tests OA26 and IA16 in the NASA/ARC 3.5-foot hypersonic wind tunnel on an 0.015-scale model (36-OTS) of the space shuttle configuration 140A/B to obtain pressures for venting analysis

Tests were conducted, from November 15 to December 4, 1973, to obtain surface pressure data on an 0.015-scale replica of the Space Shuttle Vehicle 4. Data were obtained at Mach numbers of 5.3, 7.4, and 10.3, to support the venting analysis for both launch and entry conditions. These tests were the final tests in a series covering a Mach number range from 0.6 to 10.3. The model was instrumented with pressure orifices in the vicinity of the cargo bay door hinge and parting lines, and on the side of the fuselage at the crew compartment, and below the orbital maneuvering system pods at the aft compartment. The model was tested at angles of attack and sideslip consistent with expected divergencies from the nominal trajectory

A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced threecompartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential that contributes to the local field potential of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the dendritic field potential around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. [Mazzoni, A., S. Panzeri, N. K. Logothetis, and N. Brunel (2008). Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons. PLoS Computational Biology 4 (12), e1000239], and conclude that our biophysically motivated approach yields substantial improvement.Comment: 31 pages, 4 figure

A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues

We model a general, hierarchically organized tissue by a multi compartment approach, allowing any number of mutations within a cell. We derive closed solutions for the deterministic clonal dynamics and the reproductive capacity of single clones. Our results hold for the average dynamics in a hierarchical tissue characterized by an arbitrary combination of proliferation parameters.Comment: 4 figures, to appear in Royal Society Interfac

Wind induced dispersion and algal growth in shallow lakes

The objectives of this paper are (1) to present experimental measurements of wind induced, vertical dispersion in Lake Brielle, The Netherlands, and (2) to examine the utility of a euphotic—dark zone model for investigation of the effects of dispersion and sedimentation on algal growth and phosphate cycling in shallow lakes. A tracer technique was used to measure dispersion (D) caused by a moderate wind of 4 m/s. The resulting values ranged between 4 and 6 cm2/s and compared well with that predicted from theory. The latter objective was accomplished by comparing the results of a simple, two compartment model with those using a more complex, but more descriptive, finite difference model which accounts for the algal concentration gradient induced by growth, dispersion and sedimentation. Simulations showed good agreement in computation of the average euphotic and dark zone algal concentrations between the two models for D ranging from 0 to 6 cm2/s and for a sedimentation rate constant, Ks, of 0.002 and 0.02 m/h.\ud \ud The results of simulations suggest that rapid algal growth occurs most readily in calm weather when wind induced dispersion in negligible. Dispersion may also influence the rate of particulate phosphate accumulation in the sediment (due to the settling out of algal cells) and the soluble phosphate profile in the overlying water column. Field data is needed to verify the relationship between algal growth and wind induced dispersion