Modeling of red blood cell life-spans in hematologically normal populations

Despite the impact of red blood cell (RBC) Life-spans in some disease areas such as diabetes or anemia of chronic kidney disease, there is no consensus on how to quantitatively best describe the process. Several models have been proposed to explain the elimination process of RBCs: random destruction process, homogeneous life-span model, or a series of 4-transit compartment model. The aim of this work was to explore the different models that have been proposed in literature, and modifications to those. The impact of choosing the right model on future outcomes prediction--in the above mentioned areas--was also investigated. Both data from indirect (clinical data) and direct life-span measurement (biotin-labeled data) methods were analyzed using non-linear mixed effects models. Analysis showed that: (1) predictions from non-steady state data will depend on the RBC model chosen; (2) the transit compartment model, which considers variation in life-span in the RBC population, better describes RBC survival data than the random destruction or homogenous life-span models; and (3) the additional incorporation of random destruction patterns, although improving the description of the RBC survival data, does not appear to provide a marked improvement when describing clinical data.

Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

Modeling of electroosmotic and electrophoretic mobilization in capillary and microchip isoelectric focusing

Our dynamic capillary electrophoresis model which uses material specific input data for estimation of electroosmosis was applied to investigate fundamental aspects of isoelectric focusing (IEF) in capillaries or microchannels made from bare fused-silica (FS), FS coated with a sulfonated polymer, polymethylmethacrylate (PMMA) and poly(dimethylsiloxane) (PDMS). Input data were generated via determination of the electroosmotic flow (EOF) using buffers with varying pH and ionic strength. Two models are distinguished, one that neglects changes of ionic strength and one that includes the dependence between electroosmotic mobility and ionic strength. For each configuration, the models provide insight into the magnitude and dynamics of electroosmosis. The contribution of each electrophoretic zone to the net EOF is thereby visualized and the amount of EOF required for the detection of the zone structures at a particular location along the capillary, including at its end for MS detection, is predicted. For bare FS, PDMS and PMMA, simulations reveal that EOF is decreasing with time and that the entire IEF process is characterized by the asymptotic formation of a stationary steady-state zone configuration in which electrophoretic transport and electroosmotic zone displacement are opposite and of equal magnitude. The location of immobilization of the boundary between anolyte and most acidic carrier ampholyte is dependent on EOF, i.e. capillary material and anolyte. Overall time intervals for reaching this state in microchannels produced by PDMS and PMMA are predicted to be similar and about twice as long compared to uncoated FS. Additional mobilization for the detection of the entire pH gradient at the capillary end is required. Using concomitant electrophoretic mobilization with an acid as coanion in the catholyte is shown to provide sufficient additional cathodic transport for that purpose. FS capillaries dynamically double coated with polybrene and poly(vinylsulfonate) are predicted to provide sufficient electroosmotic pumping for detection of the entire IEF gradient at the cathodic column end.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

Modeling of transfer kinetics at the serum-cerebrospinal fluid barrier in rabbits with experimental meningitis: application to grepafloxacin

The goals of the present study were to model the population kinetics of in vivo influx and efflux processes of grepafloxacin at the serum-cerebrospinal fluid (CSF) barrier and to propose a simulation-based approach to optimize the design of dose-finding trials in the meningitis rabbit model. Twenty-nine rabbits with pneumococcal meningitis receiving grepafloxacin at 15 mg/kg of body weight (intravenous administration at 0 h), 30 mg/kg (at 0 h), or 50 mg/kg twice (at 0 and 4 h) were studied. A three-compartment population pharmacokinetic model was fit to the data with the program NONMEM (Nonlinear Mixed Effects Modeling). Passive diffusion clearance (CL(diff)) and active efflux clearance (CL(active)) are transfer kinetic modeling parameters. Influx clearance is assumed to be equal to CL(diff), and efflux clearance is the sum of CL(diff), CL(active), and bulk flow clearance (CL(bulk)). The average influx clearance for the population was 0.0055 ml/min (interindividual variability, 17%). Passive diffusion clearance was greater in rabbits receiving grepafloxacin at 15 mg/kg than in those treated with higher doses (0.0088 versus 0.0034 ml/min). Assuming a CL(bulk) of 0.01 ml/min, CL(active) was estimated to be 0.017 ml/min (11%), and clearance by total efflux was estimated to be 0.032 ml/min. The population kinetic model allows not only to quantify in vivo efflux and influx mechanisms at the serum-CSF barrier but also to analyze the effects of different dose regimens on transfer kinetic parameters in the rabbit meningitis model. The modeling-based approach also provides a tool for the simulation and prediction of various outcomes in which researchers might be interested, which is of great potential in designing dose-finding trials.

On the modeling of drug induced respiratory depression in the non-steady-state

The ability of anesthetic agents to provide adequate analgesia and sedation is limited by the ventilatory depression associated with overdosing in spontaneously breathing patients. Therefore, quantitation of drug induced ventilatory depression is a pharmacokinetic-pharmacodynamic problem relevant to the practice of anesthesia. Although several studies describe the effect of respiratory depressant drugs on isolated endpoints, an integrated description of drug induced respiratory depression with parameters identifiable from clinically available data is not available. This study proposes a physiological model of CO2 disposition, ventilatory regulation, and the effects of anesthetic agents on the control of breathing. The predictive performance of the model is evaluated through simulations aimed at reproducing experimental observations of drug induced hypercarbia and hypoventilation associated with intravenous administration of a fast-onset, highly potent anesthetic mu agonist (including previously unpublished experimental data determined after administration of 1 mg alfentanil bolus). The proposed model structure has substantial descriptive capability and can provide clinically relevant predictions of respiratory inhibition in the non-steady-state to enhance safety of drug delivery in the anesthetic practice.

Response surface modeling of the interaction between propofol and sevoflurane

BACKGROUND: Propofol and sevoflurane display additivity for gamma-aminobutyric acid receptor activation, loss of consciousness, and tolerance of skin incision. Information about their interaction regarding electroencephalographic suppression is unavailable. This study examined this interaction as well as the interaction on the probability of tolerance of shake and shout and three noxious stimulations by using a response surface methodology. METHODS: Sixty patients preoperatively received different combined concentrations of propofol (0-12 microg/ml) and sevoflurane (0-3.5 vol.%) according to a crisscross design (274 concentration pairs, 3 to 6 per patient). After having reached pseudo-steady state, the authors recorded bispectral index, state and response entropy and the response to shake and shout, tetanic stimulation, laryngeal mask airway insertion, and laryngoscopy. For the analysis of the probability of tolerance by logistic regression, a Greco interaction model was used. For the separate analysis of bispectral index, state and response entropy suppression, a fractional Emax Greco model was used. All calculations were performed with NONMEM V (GloboMax LLC, Hanover, MD). RESULTS: Additivity was found for all endpoints, the Ce(50, PROP)/Ce(50, SEVO) for bispectral index suppression was 3.68 microg. ml(-1)/ 1.53 vol.%, for tolerance of shake and shout 2.34 microg . ml(-1)/ 1.03 vol.%, tetanic stimulation 5.34 microg . ml(-1)/ 2.11 vol.%, laryngeal mask airway insertion 5.92 microg. ml(-1) / 2.55 vol.%, and laryngoscopy 6.55 microg. ml(-1)/2.83 vol.%. CONCLUSION: For both electroencephalographic suppression and tolerance to stimulation, the interaction of propofol and sevoflurane was identified as additive. The response surface data can be used for more rational dose finding in case of sequential and coadministration of propofol and sevoflurane.

Age modeling of young non-varved lake sediments: methods and limits. Examples from two lakes in Central Chile

High-resolution and highly precise age models for recent lake sediments (last 100–150 years) are essential for quantitative paleoclimate research. These are particularly important for sedimentological and geochemical proxies, where transfer functions cannot be established and calibration must be based upon the relation of sedimentary records to instrumental data. High-precision dating for the calibration period is most critical as it determines directly the quality of the calibration statistics. Here, as an example, we compare radionuclide age models obtained on two high-elevation glacial lakes in the Central Chilean Andes (Laguna Negra: 33°38′S/70°08′W, 2,680 m a.s.l. and Laguna El Ocho: 34°02′S/70°19′W, 3,250 m a.s.l.). We show the different numerical models that produce accurate age-depth chronologies based on 210Pb profiles, and we explain how to obtain reduced age-error bars at the bottom part of the profiles, i.e., typically around the end of the 19th century. In order to constrain the age models, we propose a method with five steps: (i) sampling at irregularly-spaced intervals for 226Ra, 210Pb and 137Cs depending on the stratigraphy and microfacies, (ii) a systematic comparison of numerical models for the calculation of 210Pb-based age models: constant flux constant sedimentation (CFCS), constant initial concentration (CIC), constant rate of supply (CRS) and sediment isotope tomography (SIT), (iii) numerical constraining of the CRS and SIT models with the 137Cs chronomarker of AD 1964 and, (iv) step-wise cross-validation with independent diagnostic environmental stratigraphic markers of known age (e.g., volcanic ash layer, historical flood and earthquakes). In both examples, we also use airborne pollutants such as spheroidal carbonaceous particles (reflecting the history of fossil fuel emissions), excess atmospheric Cu deposition (reflecting the production history of a large local Cu mine), and turbidites related to historical earthquakes. Our results show that the SIT model constrained with the 137Cs AD 1964 peak performs best over the entire chronological profile (last 100–150 years) and yields the smallest standard deviations for the sediment ages. Such precision is critical for the calibration statistics, and ultimately, for the quality of the quantitative paleoclimate reconstruction. The systematic comparison of CRS and SIT models also helps to validate the robustness of the chronologies in different sections of the profile. Although surprisingly poorly known and under-explored in paleolimnological research, the SIT model has a great potential in paleoclimatological reconstructions based on lake sediments

Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

Impacts of changing climate and land use on vegetation dynamics in a Mediterranean ecosystem: insights from paleoecology and dynamic modeling

Forests near the Mediterranean coast have been shaped by millennia of human disturbance. Consequently, ecological studies relying on modern observations or historical records may have difficulty assessing natural vegetation dynamics under current and future climate. We combined a sedimentary pollen record from Lago di Massacciucoli, Tuscany, Italy with simulations from the LandClim dynamic vegetation model to determine what vegetation preceded intense human disturbance, how past changes in vegetation relate to fire and browsing, and the potential of an extinct vegetation type under present climate. We simulated vegetation dynamics near Lago di Massaciucoli for the last 7,000 years using a local chironomid-inferred temperature reconstruction with combinations of three fire regimes (small infrequent, large infrequent, small frequent) and three browsing intensities (no browsing, light browsing, and moderate browsing), and compared model output to pollen data. Simulations with low disturbance support pollen-inferred evidence for a mixed forest dominated by Quercus ilex (a Mediterranean species) and Abies alba (a montane species). Whereas pollen data record the collapse of A. alba after 6000 cal yr bp, simulated populations expanded with declining summer temperatures during the late Holocene. Simulations with increased fire and browsing are consistent with evidence for expansion by deciduous species after A. alba collapsed. According to our combined paleo-environmental and modeling evidence, mixed Q. ilex and A. alba forests remain possible with current climate and limited disturbance, and provide a viable management objective for ecosystems near the Mediterranean coast and in regions that are expected to experience a mediterranean-type climate in the future.

Modeling the stratospheric warming following the Mt. Pinatubo eruption: uncertainties in aerosol extinctions

In terms of atmospheric impact, the volcanic eruption of Mt. Pinatubo (1991) is the best characterized large eruption on record. We investigate here the model-derived stratospheric warming following the Pinatubo eruption as derived from SAGE II extinction data including recent improvements in the processing algorithm. This method, termed SAGE_4λ, makes use of the four wavelengths (385, 452, 525 and 1024 nm) of the SAGE II data when available, and uses a data-filling procedure in the opacity-induced "gap" regions. Using SAGE_4λ, we derived aerosol size distributions that properly reproduce extinction coefficients also at much longer wavelengths. This provides a good basis for calculating the absorption of terrestrial infrared radiation and the resulting stratospheric heating. However, we also show that the use of this data set in a global chemistry–climate model (CCM) still leads to stronger aerosol-induced stratospheric heating than observed, with temperatures partly even higher than the already too high values found by many models in recent general circulation model (GCM) and CCM intercomparisons. This suggests that the overestimation of the stratospheric warming after the Pinatubo eruption may not be ascribed to an insufficient observational database but instead to using outdated data sets, to deficiencies in the implementation of the forcing data, or to radiative or dynamical model artifacts. Conversely, the SAGE_4λ approach reduces the infrared absorption in the tropical tropopause region, resulting in a significantly better agreement with the post-volcanic temperature record at these altitudes.

The Advantages of Parametric Modeling for the Reconstruction of Historic Buildings

Consecrated in 1297 as the monastery church of the four years earlier founded St. Catherine’s monastery, the Gothic Church of St. Catherine was largely destroyed in a devastating bombing raid on January 2nd 1945. To counteract the process of disintegration, the departments of geo-information and lower monument protection authority of the City of Nuremburg decided to getting done a three dimensional building model of the Church of St. Catherine’s. A heterogeneous set of data was used for preparation of a parametric architectural model. In effect the modeling of historic buildings can profit from the so called BIM method (Building Information Modeling), as the necessary structuring of the basic data renders it into very sustainable information. The resulting model is perfectly suited to deliver a vivid impression of the interior and exterior of this former mendicant orders’ church to present observers.

Precise Orbit Determination of Low Earth Satellites at AIUB using GPS and SLR data

An ever increasing number of low Earth orbiting (LEO) satellites is, or will be, equipped with retro-reflectors for Satellite Laser Ranging (SLR) and on-board receivers to collect observations from Global Navigation Satellite Systems (GNSS) such as the Global Positioning Sys- tem (GPS) and the Russian GLONASS and the European Galileo systems in the future. At the Astronomical Insti- tute of the University of Bern (AIUB) LEO precise or- bit determination (POD) using either GPS or SLR data is performed for a wide range of applications for satellites at different altitudes. For this purpose the classical numeri- cal integration techniques, as also used for dynamic orbit determination of satellites at high altitudes, are extended by pseudo-stochastic orbit modeling techniques to effi- ciently cope with potential force model deficiencies for satellites at low altitudes. Accuracies of better than 2 cm may be achieved by pseudo-stochastic orbit modeling for satellites at very low altitudes such as for the GPS-based POD of the Gravity field and steady-state Ocean Circula- tion Explorer (GOCE).

Potentials and constraints of modeling for transdisciplinary co-producing strategies for sustainable water governance

Both climate change and socio-economic development will significantly modify the supply and consumption of water in future. Consequently, regional development has to face aggravation of existing or emergence of new conflicts of interest. In this context, transdisciplinary co-production of knowledge is considered as an important means for coping with these challenges. Accordingly, the MontanAqua project aims at developing strategies for more sustainable water management in the study area Crans-Montana-Sierre (Switzerland) in a transdisciplinary way. It strives for co-producing system, target and transformation knowledge among researchers, policy makers, public administration and civil society organizations. The research process basically consisted of the following steps: First, the current water situation in the study region was investigated. How much water is available? How much water is being used? How are decisions on water distribution and use taken? Second, participatory scenario workshops were conducted in order to identify the stakeholders’ visions of regional development. Third, the water situation in 2050 was simulated by modeling the evolution of water resources and water use and by reflecting on the institutional aspects. These steps laid ground for jointly assessing the consequences of the stakeholders’ visions of development in view of scientific data regarding governance, availability and use of water in the region as well as developing necessary transformation knowledge. During all of these steps researchers have collaborated with stakeholders in the support group RegiEau. The RegiEau group consists of key representatives of owners, managers, users, and pressure groups related to water and landscape: representatives of the communes (mostly the presidents), the canton (administration and parliament), water management associations, agriculture, viticulture, hydropower, tourism, and landscape protection. The aim of the talk is to explore potentials and constraints of scientific modeling of water availability and use within the process of transdisciplinary co-producing strategies for more sustainable water governance.