Rise in plasma lactate concentrations with psychosocial stress: a possible sign of cerebral energy demand.

OBJECTIVE: It is known that exogenous lactate given as an i.v. energy infusion is able to counteract a neuroglycopenic state that developed during psychosocial stress. It is unknown, however, whether the brain under stressful conditions can induce a rise in plasma lactate to satisfy its increased needs during stress. Since lactate is i) an alternative cerebral energy substrate to glucose and ii) its plasmatic concentration is influenced by the sympathetic nervous system, the present study aimed at investigating whether plasma lactate concentrations increase with psychosocial stress in humans. METHODS: 30 healthy young men participated in two sessions (stress induced by the Trier Social Stress Test and a non-stress control session). Blood samples were frequently taken to assess plasma lactate concentrations and stress hormone profiles. RESULTS: Plasma lactate increased 47% during psychosocial stress (from 0.9 ± 0.05 to 1.4 ± 0.1 mmol/l; interaction time × stress intervention: F = 19.7, p < 0.001). This increase in lactate concentrations during stress was associated with an increase in epinephrine (R(2) = 0.221, p = 0.02) and ACTH concentrations (R(2) = 0.460, p < 0.001). CONCLUSION: Plasma lactate concentrations increase during acute psychosocial stress in humans. This finding suggests the existence of a demand mechanism that functions to allocate an additional source of energy from the body towards the brain, which we refer to as 'cerebral lactate demand'.

On the problematic of reserving and stochastic loss models

Abstract Traditionally, the common reserving methods used by the non-life actuaries are based on the assumption that future claims are going to behave in the same way as they did in the past. There are two main sources of variability in the processus of development of the claims: the variability of the speed with which the claims are settled and the variability between the severity of the claims from different accident years. High changes in these processes will generate distortions in the estimation of the claims reserves. The main objective of this thesis is to provide an indicator which firstly identifies and quantifies these two influences and secondly to determine which model is adequate for a specific situation. Two stochastic models were analysed and the predictive distributions of the future claims were obtained. The main advantage of the stochastic models is that they provide measures of variability of the reserves estimates. The first model (PDM) combines one conjugate family Dirichlet - Multinomial with the Poisson distribution. The second model (NBDM) improves the first one by combining two conjugate families Poisson -Gamma (for distribution of the ultimate amounts) and Dirichlet Multinomial (for distribution of the incremental claims payments). It was found that the second model allows to find the speed variability in the reporting process and development of the claims severity as function of two above mentioned distributions' parameters. These are the shape parameter of the Gamma distribution and the Dirichlet parameter. Depending on the relation between them we can decide on the adequacy of the claims reserve estimation method. The parameters have been estimated by the Methods of Moments and Maximum Likelihood. The results were tested using chosen simulation data and then using real data originating from the three lines of business: Property/Casualty, General Liability, and Accident Insurance. These data include different developments and specificities. The outcome of the thesis shows that when the Dirichlet parameter is greater than the shape parameter of the Gamma, resulting in a model with positive correlation between the past and future claims payments, suggests the Chain-Ladder method as appropriate for the claims reserve estimation. In terms of claims reserves, if the cumulated payments are high the positive correlation will imply high expectations for the future payments resulting in high claims reserves estimates. The negative correlation appears when the Dirichlet parameter is lower than the shape parameter of the Gamma, meaning low expected future payments for the same high observed cumulated payments. This corresponds to the situation when claims are reported rapidly and fewer claims remain expected subsequently. The extreme case appears in the situation when all claims are reported at the same time leading to expectations for the future payments of zero or equal to the aggregated amount of the ultimate paid claims. For this latter case, the Chain-Ladder is not recommended.

Essays on the treatment of cash flows under stochastic interest rates

Abstract This paper shows how to calculate recursively the moments of the accumulated and discounted value of cash flows when the instantaneous rates of return follow a conditional ARMA process with normally distributed innovations. We investigate various moment based approaches to approximate the distribution of the accumulated value of cash flows and we assess their performance through stochastic Monte-Carlo simulations. We discuss the potential use in insurance and especially in the context of Asset-Liability Management of pension funds.

Less Risk, More Effort : Demand Risk Allocation in Incomplete Contracts

This article investigates the allocation of demand risk within an incomplete contract framework. We consider an incomplete contractual relationship between a public authority and a private provider (i.e. a public-private partnership), in which the latter invests in non-verifiable cost-reducing efforts and the former invests in non-verifiable adaptation efforts to respond to changing consumer demand over time. We show that the party that bears the demand risk has fewer hold-up opportunities and that this leads the other contracting party to make more effort. Thus, in our model, bearing less risk can lead to more effort, which we describe as a new example of âeuro~counter-incentivesâeuro?. We further show that when the benefits of adaptation are important, it is socially preferable to design a contract in which the demand risk remains with the private provider, whereas when the benefits of cost-reducing efforts are important, it is socially preferable to place the demand risk on the public authority. We then apply these results to explain two well-known case studies.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

The Demand for Social Insurance: Does Culture Matter?

Does culture shape the demand for social insurance against risks to health and work? We study this issue across language groups in Switzerland where a language border sharply separates social groups at identical actual levels of publicly provided social insurance. We find substantially stronger support for expansions of social insurance among residents of French, Italian or Romansh-speaking language border municipalities compared with their German-speaking neighbours in adjacent municipalities. Informal insurance does not vary enough to explain stark differences in social insurance but differences in ideology and segmented media markets potentially contribute to the discrepancy in demand for social insurance.

Linking supply to demand: the neuronal monocarboxylate transporter MCT2 and the alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid receptor GluR2/3 subunit are associated in a common trafficking process.

MCT2 is the major neuronal monocarboxylate transporter (MCT) that allows the supply of alternative energy substrates such as lactate to neurons. Recent evidence obtained by electron microscopy has demonstrated that MCT2, like alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid (AMPA) receptors, is localized in dendritic spines of glutamatergic synapses. Using immunofluorescence, we show in this study that MCT2 colocalizes extensively with GluR2/3 subunits of AMPA receptors in neurons from various mouse brain regions as well as in cultured neurons. It also colocalizes with GluR2/3-interacting proteins, such as C-kinase-interacting protein 1, glutamate receptor-interacting protein 1 and clathrin adaptor protein. Coimmunoprecipitation of MCT2 with GluR2/3 and C-kinase-interacting protein 1 suggests their close interaction within spines. Parallel changes in the localization of both MCT2 and GluR2/3 subunits at and beneath the plasma membrane upon various stimulation paradigms were unraveled using an original immunocytochemical and transfection approach combined with three-dimensional image reconstruction. Cell culture incubation with AMPA or insulin triggered a marked intracellular accumulation of both MCT2 and GluR2/3, whereas both tumor necrosis factor alpha and glycine (with glutamate) increased their cell surface immunolabeling. Similar results were obtained using Western blots performed on membrane or cytoplasm-enriched cell fractions. Finally, an enhanced lactate flux into neurons was demonstrated after MCT2 translocation on the cell surface. These observations provide unequivocal evidence that MCT2 is linked to AMPA receptor GluR2/3 subunits and undergoes a similar translocation process in neurons upon activation. MCT2 emerges as a novel component of the synaptic machinery putatively linking neuroenergetics to synaptic transmission.

An allele-specific, stochastic gene expression process controls the expression of multiple Ly49 family genes and generates a diverse, MHC-specific NK cell receptor repertoire.

Mouse NK cells express MHC class I-specific inhibitory Ly49 receptors. Since these receptors display distinct ligand specificities and are clonally distributed, their expression generates a diverse NK cell receptor repertoire specific for MHC class I molecules. We have previously found that the Dd (or Dk)-specific Ly49A receptor is usually expressed from a single allele. However, a small fraction of short-term NK cell clones expressed both Ly49A alleles, suggesting that the two Ly49A alleles are independently and randomly expressed. Here we show that the genes for two additional Ly49 receptors (Ly49C and Ly49G2) are also expressed in a (predominantly) mono-allelic fashion. Since single NK cells can co-express multiple Ly49 receptors, we also investigated whether mono-allelic expression from within the tightly linked Ly49 gene cluster is coordinate or independent. Our clonal analysis suggests that the expression of alleles of distinct Ly49 genes is not coordinate. Thus Ly49 alleles are apparently independently and randomly chosen for stable expression, a process that directly restricts the number of Ly49 receptors expressed per single NK cell. We propose that the Ly49 receptor repertoire specific for MHC class I is generated by an allele-specific, stochastic gene expression process that acts on the entire Ly49 gene cluster.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

Cost Analysis of Long-Term Treatment of Patients with Symptomatic Gastroesophageal Reflux Disease (GERD) with Esomeprazole On-Demand Treatment or Esomeprazole Continuous Treatment: An Open, Randomized, Multicenter Study in Switzerland.

Objectives: To assess the difference in direct medical costs between on-demand (OD) treatment with esomeprazole (E) 20 mg and continuous (C) treatment with E 20 mg q.d. from a clinical practice view in patients with gastroesophageal reflux disease (GERD) symptoms. Methods: This open, randomized study (ONE: on-demand Nexium evaluation) compared two long-term management options with E 20 mg in endoscopically uninvestigated patients seeking primary care for GERD symptoms who demonstrated complete relief of symptoms after an initial treatment of 4 weeks with E 40 mg. Data on consumed quantities of all cost items were collected in the study, while data on prices during the time of study were collected separately. The analysis was done from a societal perspective. Results: Forty-nine percent (484 of 991) of patients randomized to the OD regimen and 46% (420 of 913) of the patients in the C group had at least one contact with the investigator that would have occurred nonprotocol-driven. The difference of the adjusted mean direct medical costs between the treatment groups was CHF 88.72 (95% confidence interval: CHF 41.34-153.95) in favor of the OD treatment strategy (Wilcoxon rank-sum test: P < 0.0001). Adjusted direct nonmedical costs and productivity loss were similar in both groups. Conclusions: The adjusted direct medical costs of a 6-month OD treatment with esomeprazole 20 mg in uninvestigated patients with symptoms of GERD were significantly lower compared with a continuous treatment with E 20 mg once a day. The OD therapy represents a cost-saving alternative to the continuous treatment strategy with E.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.