A real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations

In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.

Changes in the use of broad-spectrum antibiotics after cefepime shortage: a time series analysis

The original cefepime product was withdrawn from the Swiss market in January 2007 and replaced by a generic 10 months later. The goals of the study were to assess the impact of this cefepime shortage on the use and costs of alternative broad-spectrum antibiotics, on antibiotic policy, and on resistance of Pseudomonas aeruginosa toward carbapenems, ceftazidime, and piperacillin-tazobactam. A generalized regression-based interrupted time series model assessed how much the shortage changed the monthly use and costs of cefepime and of selected alternative broad-spectrum antibiotics (ceftazidime, imipenem-cilastatin, meropenem, piperacillin-tazobactam) in 15 Swiss acute care hospitals from January 2005 to December 2008. Resistance of P. aeruginosa was compared before and after the cefepime shortage. There was a statistically significant increase in the consumption of piperacillin-tazobactam in hospitals with definitive interruption of cefepime supply and of meropenem in hospitals with transient interruption of cefepime supply. Consumption of each alternative antibiotic tended to increase during the cefepime shortage and to decrease when the cefepime generic was released. These shifts were associated with significantly higher overall costs. There was no significant change in hospitals with uninterrupted cefepime supply. The alternative antibiotics for which an increase in consumption showed the strongest association with a progression of resistance were the carbapenems. The use of alternative antibiotics after cefepime withdrawal was associated with a significant increase in piperacillin-tazobactam and meropenem use and in overall costs and with a decrease in susceptibility of P. aeruginosa in hospitals. This warrants caution with regard to shortages and withdrawals of antibiotics.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

Heterogeneity in vaccination coverage explains the size and occurrence of measles epidemics in German surveillance data

The objective of this study was to characterize empirically the association between vaccination coverage and the size and occurrence of measles epidemics in Germany. In order to achieve this we analysed data routinely collected by the Robert Koch Institute, which comprise the weekly number of reported measles cases at all ages as well as estimates of vaccination coverage at the average age of entry into the school system. Coverage levels within each federal state of Germany are incorporated into a multivariate time-series model for infectious disease counts, which captures occasional outbreaks by means of an autoregressive component. The observed incidence pattern of measles for all ages is best described by using the log proportion of unvaccinated school starters in the autoregressive component of the model.

Prognostic importance of anaemia in patients with acute pulmonary embolism

Although associated with adverse outcomes in other cardiopulmonary diseases, limited evidence exists on the prognostic value of anaemia in patients with acute pulmonary embolism (PE). We sought to examine the associations between anaemia and mortality and length of hospital stay in patients with PE. We evaluated 14,276 patients with a primary diagnosis of PE from 186 hospitals in Pennsylvania, USA. We used random-intercept logistic regression to assess the association between anaemia at the time of presentation and 30-day mortality and discrete-time logistic hazard models to assess the association between anaemia and time to hospital discharge, adjusting for patient (age, gender, race, insurance type, clinical and laboratory variables) and hospital (region, size, teaching status) factors. Anaemia was present in 38.7% of patients at admission. Patients with anaemia had a higher 30-day mortality (13.7% vs. 6.3%; p <0.001) and a longer length of stay (geometric mean, 6.9 vs. 6.6 days; p <0.001) compared to patients without anaemia. In multivariable analyses, anaemia remained associated with an increased odds of death (OR 1.82, 95% CI: 1.60-2.06) and a decreased odds of discharge (OR 0.85, 95% CI: 0.82-0.89). Anaemia is very common in patients presenting with PE and is independently associated with an increased short-term mortality and length of stay.

Groundwater age distributions at a public drinking water supply well field derived from multiple age tracers (⁸⁵Kr, ³H/³He, and ³⁹Ar)

Groundwater age is a key aspect of production well vulnerability. Public drinking water supply wells typically have long screens and are expected to produce a mixture of groundwater ages. The groundwater age distributions of seven production wells of the Holten well field (Netherlands) were estimated from tritium-helium (3H/3He), krypton-85 (85Kr), and argon-39 (39Ar), using a new application of a discrete age distribution model and existing mathematical models, by minimizing the uncertainty-weighted squared differences of modeled and measured tracer concentrations. The observed tracer concentrations fitted well to a 4-bin discrete age distribution model or a dispersion model with a fraction of old groundwater. Our results show that more than 75 of the water pumped by four shallow production wells has a groundwater age of less than 20 years and these wells are very vulnerable to recent surface contamination. More than 50 of the water pumped by three deep production wells is older than 60 years. 3H/3He samples from short screened monitoring wells surrounding the well field constrained the age stratification in the aquifer. The discrepancy between the age stratification with depth and the groundwater age distribution of the production wells showed that the well field preferentially pumps from the shallow part of the aquifer. The discrete groundwater age distribution model appears to be a suitable approach in settings where the shape of the age distribution cannot be assumed to follow a simple mathematical model, such as a production well field where wells compete for capture area.

Impact of anti-inflammatory treatment on the onset of uveitis in juvenile idiopathic arthritis: Longitudinal analysis from a nation-wide paediatric rheumatological database

PURPOSE Based on a nation-wide database, this study analysed the influence of methotrexate (MTX), TNF inhibitors and a combination of the two on uveitis occurrence in JIA patients. METHODS Data from the National Paediatric Rheumatological Database in Germany were used in this study. Between 2002 and 2013, data from JIA patients were annually documented at the participating paediatric rheumatological sites. Patients with JIA disease duration of less than 12 months at initial documentation and ≥2 years of follow-up were included in this study. The impact of anti-inflammatory treatment on the occurrence of uveitis was evaluated by discrete-time survival analysis. RESULTS A total of 3,512 JIA patients (mean age 8.3±4.8 years, female 65.7%, ANA-positive 53.2%, mean age at arthritis onset 7.8±4.8 years) fulfilled the inclusion criteria. Mean total follow-up time was 3.6±2.4 years. Uveitis developed in a total of 180 patients (5.1%) within one year after arthritis onset. Uveitis onset after the first year was observed in another 251 patients (7.1%). DMARD treatment in the year before uveitis onset significantly reduced the risk for uveitis: MTX (HR 0.63, p=0.022), TNF inhibitors (HR 0.56, p<0.001) and a combination of the two (HR 0.10, p<0.001). Patients treated with MTX within the first year of JIA had an even a lower uveitis risk (HR 0.29, p<0.001). CONCLUSION The use of DMARDs in JIA patients significantly reduced the risk for uveitis onset. Early MTX use within the first year of disease and the combination of MTX with a TNF inhibitor had the highest protective effect. This article is protected by copyright. All rights reserved.

Evolutionary demography of long-lived monocarpic perennials: a time-lagged integral projection model

1. The evolution of flowering strategies (when and at what size to flower) in monocarpic perennials is determined by balancing current reproduction with expected future reproduction, and these are largely determined by size-specific patterns of growth and survival. However, because of the difficulty in following long-lived individuals throughout their lives, this theory has largely been tested using short-lived species (< 5 years). 2. Here, we tested this theory using the long-lived monocarpic perennial Campanula thyrsoides which can live up to 16 years. We used a novel approach that combined permanent plot and herb chronology data from a 3-year field study to parameterize and validate integral projection models (IPMs). 3. Similar to other monocarpic species, the rosette leaves of C. thyrsoides wither over winter and so size cannot be measured in the year of flowering. We therefore extended the existing IPM framework to incorporate an additional time delay that arises because flowering demography must be predicted from rosette size in the year before flowering. 4. We found that all main demographic functions (growth, survival probability, flowering probability and fecundity) were strongly size-dependent and there was a pronounced threshold size of flowering. There was good agreement between the predicted distribution of flowering ages obtained from the IPMs and that estimated in the field. Mostly, there was good agreement between the IPM predictions and the direct quantitative field measurements regarding the demographic parameters lambda, R-0 and T. We therefore conclude that the model captures the main demographic features of the field populations. 5. Elasticity analysis indicated that changes in the survival and growth function had the largest effect (c. 80%) on lambda and this was considerably larger than in short-lived monocarps. We found only weak selection pressure operating on the observed flowering strategy which was close to the predicted evolutionary stable strategy. 6. Synthesis. The extended IPM accurately described the demography of a long-lived monocarpic perennial using data collected over a relatively short period. We could show that the evolution of flowering strategies in short- and long-lived monocarps seem to follow the same general rules but with a longevity-related emphasis on survival over fecundity.

Time-dependent and somatically acquired mitochondrial DNA mutagenesis and respiratory chain dysfunction in a scleroderma model of lung fibrosis.

Reactive oxygen species (ROS) have been implemented in the etiology of pulmonary fibrosis (PF) in systemic sclerosis. In the bleomycin model, we evaluated the role of acquired mutations in mitochondrial DNA (mtDNA) and respiratory chain defects as a trigger of ROS formation and fibrogenesis. Adult male Wistar rats received a single intratracheal instillation of bleomycin and their lungs were examined at different time points. Ashcroft scores, collagen and TGFβ1 levels documented a delayed onset of PF by day 14. In contrast, increased malon dialdehyde as a marker of ROS formation was detectable as early as 24 hours after bleomycin instillation and continued to increase. At day 7, lung tissue acquired significant amounts of mtDNA deletions, translating into a significant dysfunction of mtDNA-encoded, but not nucleus-encoded respiratory chain subunits. mtDNA deletions and markers of mtDNA-encoded respiratory chain dysfunction significantly correlated with pulmonary TGFβ1 concentrations and predicted PF in a multivariate model.

From quantum to classical dynamics: The relativistic O ( N ) model in the framework of the real-time functional renormalization group

We investigate the transition from unitary to dissipative dynamics in the relativistic O(N) vector model with the λ(φ2)2 interaction using the nonperturbative functional renormalization group in the real-time formalism. In thermal equilibrium, the theory is characterized by two scales, the interaction range for coherent scattering of particles and the mean free path determined by the rate of incoherent collisions with excitations in the thermal medium. Their competition determines the renormalization group flow and the effective dynamics of the model. Here we quantify the dynamic properties of the model in terms of the scale-dependent dynamic critical exponent z in the limit of large temperatures and in 2≤d≤4 spatial dimensions. We contrast our results to the behavior expected at vanishing temperature and address the question of the appropriate dynamic universality class for the given microscopic theory.