SIMSAFADIM-CLASTIC: A new approach to mathematical 3D forward simulation modelling for terrigenous and carbonate marine sedimentation

Most sedimentary modelling programs developed in recent years focus on either terrigenous or carbonate marine sedimentation. Nevertheless, only a few programs have attempted to consider mixed terrigenous-carbonate sedimentation, and most of these are two-dimensional, which is a major restriction since geological processes take place in 3D. This paper presents the basic concepts of a new 3D mathematical forward simulation model for clastic sediments, which was developed from SIMSAFADIM, a previous 3D carbonate sedimentation model. The new extended model, SIMSAFADIM-CLASTIC, simulates processes of autochthonous marine carbonate production and accumulation, together with clastic transport and sedimentation in three dimensions of both carbonate and terrigenous sediments. Other models and modelling strategies may also provide realistic and efficient tools for prediction of stratigraphic architecture and facies distribution of sedimentary deposits. However, SIMSAFADIM-CLASTIC becomes an innovative model that attempts to simulate different sediment types using a process-based approach, therefore being a useful tool for 3D prediction of stratigraphic architecture and facies distribution in sedimentary basins. This model is applied to the neogene Vallès-Penedès half-graben (western Mediterranean, NE Spain) to show the capacity of the program when applied to a realistic geologic situation involving interactions between terrigenous clastics and carbonate sediments.

Evidence for different expression profiles for c-Met, EGFR, PTEN and the mTOR pathway in low and high grade endometrial carcinomas in a cohort of consecutive women. Occurrence of PIK3CA and K-Ras mutations and microsatellite instability.

Molecular and genetic investigations in endometrial carcinogenesis may have prognostic and therapeutic implications. We studied the expression of EGFR, c-Met, PTEN and the mTOR signalling pathway (phospho-AKT/phospho-mTOR/phospho-RPS6) in 69 consecutive tumours and 16 tissue microarrays. We also analysed PIK3CA, K-Ras mutations and microsatellite instability (MSI). We distinguished two groups: group 1 (grade 1 and 2 endometrioid cancers) and group 2 (grade 3 endometrioid and type II clear and serous cell cancers). We hypothesised that these histological groups might have different features. We found that a) survival was higher in group 1 with less aggressive tumours (P⟨0.03); b) EGFR (P=0.01), PTEN and the AKT/mTOR/RPS6 signalling pathway were increased in group 1 versus group 2 (P=0.05 for phospho-mTOR); c) conversely, c-Met was higher (P⟨0.03) in group 2 than in group 1; d) In group 1, EGFR was correlated with c-Met, phospho-mTOR, phospho-RPS6 and the global activity of the phospho-AKT/phospho-mTOR/phospho-RPS6 pathway. In group 2, EGFR was correlated only with the phospho-AKT/phospho-mTOR/phospho-RPS6 pathway, whereas c-Met was correlated with PTEN; e) survival was higher for tumours with more than 50% PTEN-positive cells; f) K-RAS and PIK3CA mutations occurred in 10-12% of the available tumours and MSI in 40.4%, with a loss of MLH1 and PMS2 expression. Our results for endometrial cancers provide the first evidence for a difference in status between groups 1 and 2. The patients may benefit from different targeted treatments, anti-EGFR agents and rapamycin derivatives (anti-mTOR) for group 1 and an anti c-MET/ligand complex for group 2.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

MMPBSA decomposition of the binding energy throughout a molecular dynamics simulation of Amyloid-Beta (Aß10-35) aggregation

Recent experiments with amyloid-beta (Aß) peptides indicate that the formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Aß oligomers depend on their structure, which is governed by assembly dynamics. However, a detailed knowledge of the structure of at the atomic level has not been achieved yet due to limitations of current experimental techniques. In this study, replica exchange molecular dynamics simulations are used to identify the expected diversity of dimer conformations of Aß10-35 monomers. The most representative dimer conformation has been used to track the dimer formation process between both monomers. The process has been characterized by means of the evolution of the decomposition of the binding free energy, which provides an energetic profile of the interaction. Dimers undergo a process of reorganization driven basically by inter-chain hydrophobic and hydrophilic interactions and also solvation/desolvation processes.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Comparing simulation methods for modelling the errors of stand inventory data

Abstract

Simulation of spring wheat responses to elevated CO‚́‚ and temperature by using CERES-wheat crop model

Selostus: Kohotettujen CO‚́‚:n ja lämpötilan vaikutukset kevätvehnän fenologiseen kehitykseen ja sadontuottomahdollisuuksiin

Simulation of growth and development of irrigated cowpea in Piauí State by CROPGRO model

The objective of this work was to adapt the CROPGRO model, which is part of the DSSAT system, for simulating the cowpea (Vigna unguiculata) growth and development under soil and climate conditions of the Baixo Parnaíba region, Piauí State, Brazil. In the CROPGRO, only input parameters that define crop species, cultivars, and ecotype were changed in order to characterize the cowpea crop. Soil and climate files were created for the considered site. Field experiments without water deficit were used to calibrate the model. In these experiments, dry matter (DM), leaf area index (LAI), yield components and grain yield of cowpea (cv. BR 14 Mulato) were evaluated. The results showed good fit for DM and LAI estimates. The medium values of R² and medium absolute error (MAE) were, respectively, 0.95 and 264.9 kg ha-1 for DM, and 0.97 and 0.22 for LAI. The difference between observed and simulated values of plant phenology varied from 0 to 3 days. The model also presented good performance for yield components simulation, excluding 100-grain weight, for which the error ranged from 20.9% to 34.3%. Considering the medium values of crop yield in two years, the model presented an error from 5.6%.