1,2,3,4-Tetrahydrobenzo[h][1,6]naphthyridines as a new family of potent peripheral-to-midgorge-site inhibitors of acetylcholinesterase: synthesis, pharmacological evaluation and mechanistic studies

A series of 1,2,3,4-tetrahydrobenzo[h][1,6]naphthyridines differently substituted at positions 1, 5, and 9 have been designed from the pyrano[3,2-c]quinoline derivative 1, a weak inhibitor of acetylcholinesterase (AChE) with predicted ability to bind to the AChE peripheral anionic site (PAS), at the entrance of the catalytic gorge. Fourteen novel benzonaphthyridines have been synthesized through synthetic sequences involving as the key step a multicomponent Povarov reaction between an aldehyde, an aniline and an enamine or an enamide as the activated alkene. The novel compounds have been tested against Electrophorus electricus AChE (EeAChE), human recombinant AChE (hAChE), and human serum butyrylcholinesterase (hBChE), and their brain penetration has been assessed using the PAMPA-BBB assay. Also, the mechanism of AChE inhibition of the most potent compounds has been thoroughly studied by kinetic studies, a propidium displacement assay, and molecular modelling. We have found that a seemingly small structural change such as a double O → NH bioisosteric replacement from the hit 1 to 16a results in a dramatic increase of EeAChE and hAChE inhibitory activities (>217- and >154-fold, respectively), and in a notable increase in hBChE inhibitory activity (> 11-fold), as well. An optimized binding at the PAS besides additional interactions with AChE midgorge residues seem to account for the high hAChE inhibitory potency of 16a (IC50 = 65 nM), which emerges as an interesting anti-Alzheimer lead compound with potent dual AChE and BChE inhibitory activities.

1,2,3,4-Tetrahydrobenzo[h][1,6]naphthyridines as a new family of potent peripheral-to-midgorge-site inhibitors of acetylcholinesterase: synthesis, pharmacological evaluation and mechanistic studies

A series of 1,2,3,4-tetrahydrobenzo[h][1,6]naphthyridines differently substituted at positions 1, 5, and 9 have been designed from the pyrano[3,2-c]quinoline derivative 1, a weak inhibitor of acetylcholinesterase (AChE) with predicted ability to bind to the AChE peripheral anionic site (PAS), at the entrance of the catalytic gorge. Fourteen novel benzonaphthyridines have been synthesized through synthetic sequences involving as the key step a multicomponent Povarov reaction between an aldehyde, an aniline and an enamine or an enamide as the activated alkene. The novel compounds have been tested against Electrophorus electricus AChE (EeAChE), human recombinant AChE (hAChE), and human serum butyrylcholinesterase (hBChE), and their brain penetration has been assessed using the PAMPA-BBB assay. Also, the mechanism of AChE inhibition of the most potent compounds has been thoroughly studied by kinetic studies, a propidium displacement assay, and molecular modelling. We have found that a seemingly small structural change such as a double O → NH bioisosteric replacement from the hit 1 to 16a results in a dramatic increase of EeAChE and hAChE inhibitory activities (>217- and >154-fold, respectively), and in a notable increase in hBChE inhibitory activity (> 11-fold), as well. An optimized binding at the PAS besides additional interactions with AChE midgorge residues seem to account for the high hAChE inhibitory potency of 16a (IC50 = 65 nM), which emerges as an interesting anti-Alzheimer lead compound with potent dual AChE and BChE inhibitory activities.

Content value chains modelling using a copyright ontology

Existing digital rights management (DRM) systems, initiatives like Creative Commons or research works as some digital rights ontologies provide limited support for content value chains modelling and management. This is becoming a critical issue as content markets start to profit from the possibilities of digital networks and the World Wide Web. The objective is to support the whole copyrighted content value chain across enterprise or business niches boundaries. Our proposal provides a framework that accommodates copyright law and a rich creation model in order to cope with all the creation life cycle stages. The dynamic aspects of value chains are modelled using a hybrid approach that combines ontology-based and rule-based mechanisms. The ontology implementation is based on Web Ontology Language and Description Logic (OWL-DL) reasoners, are directly used for license checking. On the other hand, for more complex aspects of the dynamics of content value chains, rule languages are the choice.

Modelling leaf development in Oxalis latifolia

This study was carried to develop functions that could explain the growth of Oxalis latifolia, in both early stages and throughout the season, contributing to the improvement of its cultural control. Bulbs of the Cornwall form of O. latifolia were buried at 1 and 8 cm in March 1999 and 2000. Samples were destructive at fixed times, and at each time the corresponding BBCH scale codes as well as the absolute number of growing and adult leaves were noted. Using the absolute number of adult leaves (transformed to percentages), a Gaussian curve of three parameters that explains the growth during the season (R2=0.9355) was developed. The BBCH scale permitted the fit of two regression lines that were accurately adjusted for each burial depth (R2=0.9969 and R2=0.9930 respectively for 1 and 8 cm). The best moment for an early defoliation in Northern Spain could be calculated with these regression lines, and was found to be the second week of May. In addition, it was observed that a burial depth of 8 cm does not affect the growing pattern of the weed, but it affects the number of leaves they produce, which decreases to less than a half of those produced at 1 cm.

Modelling bird species richness with neural networks for forest landscape management in NE Spain

Para preservar la biodiversidad de los ecosistemas forestales de la Europa mediterránea en escenarios actuales y futuros de cambio global mediante una gestión forestal sostenible es necesario determinar cómo influye el medio ambiente y las propias características de los bosques sobre la biodiversidad que éstos albergan. Con este propósito, se analizó la influencia de diferentes factores ambientales y de estructura y composición del bosque sobre la riqueza de aves forestales a escala 1 × 1 km en Cataluña (NE de España). Se construyeron modelos univariantes y multivariantes de redes neuronales para respectivamente explorar la respuesta individual a las variables y obtener un modelo parsimonioso (ecológicamente interpretable) y preciso. La superficie de bosque (con una fracción de cabida cubierta superior a 5%), la fracción de cabida cubierta media, la temperatura anual y la precipitación estival medias fueron los mejores predictores de la riqueza de aves forestales. La red neuronal multivariante obtenida tuvo una buena capacidad de generalización salvo en las localidades con una mayor riqueza. Además, los bosques con diferentes grados de apertura del dosel arbóreo, más maduros y más diversos en cuanto a su composición de especies arbóreas se asociaron de forma positiva con una mayor riqueza de aves forestales. Finalmente, se proporcionan directrices de gestión para la planificación forestal que permitan promover la diversidad ornítica en esta región de la Europa mediterránea.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Statistical modelling of CSP solving algorithms performance

The goal of this work is to try to create a statistical model, based only on easily computable parameters from the CSP problem to predict runtime behaviour of the solving algorithms, and let us choose the best algorithm to solve the problem. Although it seems that the obvious choice should be MAC, experimental results obtained so far show, that with big numbers of variables, other algorithms perfom much better, specially for hard problems in the transition phase.

Evaluating the Performance of a Regional-Scale Photochemical Modelling System: Part I Ozone Predictions

We present a detailed evaluation of the seasonal performance of the Community Multiscale Air Quality (CMAQ) modelling system and the PSU/NCAR meteorological model coupled to a new Numerical Emission Model for Air Quality (MNEQA). The combined system simulates air quality at a fine resolution (3 km as horizontal resolution and 1 h as temporal resolution) in north-eastern Spain, where problems of ozone pollution are frequent. An extensive database compiled over two periods, from May to September 2009 and 2010, is used to evaluate meteorological simulations and chemical outputs. Our results indicate that the model accurately reproduces hourly and 1-h and 8-h maximum ozone surface concentrations measured at the air quality stations, as statistical values fall within the EPA and EU recommendations. However, to further improve forecast accuracy, three simple bias-adjustment techniques mean subtraction (MS), ratio adjustment (RA), and hybrid forecast (HF) based on 10 days of available comparisons are applied. The results show that the MS technique performed better than RA or HF, although all the bias-adjustment techniques significantly reduce the systematic errors in ozone forecasts.

Modelling the Evolution and Spread of HIV Immune Escape Mutants.

During infection with human immunodeficiency virus (HIV), immune pressure from cytotoxic T-lymphocytes (CTLs) selects for viral mutants that confer escape from CTL recognition. These escape variants can be transmitted between individuals where, depending upon their cost to viral fitness and the CTL responses made by the recipient, they may revert. The rates of within-host evolution and their concordant impact upon the rate of spread of escape mutants at the population level are uncertain. Here we present a mathematical model of within-host evolution of escape mutants, transmission of these variants between hosts and subsequent reversion in new hosts. The model is an extension of the well-known SI model of disease transmission and includes three further parameters that describe host immunogenetic heterogeneity and rates of within host viral evolution. We use the model to explain why some escape mutants appear to have stable prevalence whilst others are spreading through the population. Further, we use it to compare diverse datasets on CTL escape, highlighting where different sources agree or disagree on within-host evolutionary rates. The several dozen CTL epitopes we survey from HIV-1 gag, RT and nef reveal a relatively sedate rate of evolution with average rates of escape measured in years and reversion in decades. For many epitopes in HIV, occasional rapid within-host evolution is not reflected in fast evolution at the population level.

Modelling the disability severity score in motor insurance claims: an application to the Spanish case

Bodily injury claims have the greatest impact on the claim costs of motor insurance companies. The disability severity of motor claims is assessed in numerous European countries by means of score systems. In this paper a zero inflated generalized Poisson regression model is implemented to estimate the disability severity score of victims in-volved in motor accidents on Spanish roads. We show that the injury severity estimates may be automatically converted into financial terms by insurers at any point of the claim handling process. As such, the methodology described may be used by motor insurers operating in the Spanish market to monitor the size of bodily injury claims. By using insurance data, various applications are presented in which the score estimate of disability severity is of value to insurers, either for computing the claim compensation or for claim reserve purposes.

Modelling nitrogen and phosphorus loads in a Mediterranean river catchment (La Tordera, NE Spain)

Human activities have resulted in increased nutrient levels in many rivers all over Europe. Sustainable management of river basins demands an assessment of the causes and consequences of human alteration of nutrient flows, together with an evaluation of management options. In the context of an integrated and interdisciplinary environmental assessment (IEA) of nutrient flows, we present and discuss the application of the nutrient emission model MONERIS (MOdelling Nutrient Emissions into River Systems) to the Catalan river basin, La Tordera (north-east Spain), for the period 1996–2002. After a successful calibration and verification process (Nash-Sutcliffe efficiencies E=0.85 for phosphorus and E=0.86 for nitrogen), the application of the model MONERIS proved to be useful in estimating nutrient loads. Crucial for model calibration, in-stream retention was estimated to be about 50 % of nutrient emissions on an annual basis. Through this process, we identified the importance of point sources for phosphorus emissions (about 94% for 1996–2002), and diffuse sources, especially inputs via groundwater, for nitrogen emissions (about 31% for 1996–2002). Despite hurdles related to model structure, observed loads, and input data encountered during the modelling process, MONERIS provided a good representation of the major interannual and spatial patterns in nutrient emissions. An analysis of the model uncertainty and sensitivity to input data indicates that the model MONERIS, even in data-starved Mediterranean catchments, may be profitably used by water managers for evaluating quantitative nutrient emission scenarios for the purpose of managing river basins. As an example of scenario modelling, an analysis of the changes in nutrient emissions through two different future scenarios allowed the identification of a set of relevant measures to reduce nutrient loads.

Predicting overall service quality: a structural equation modelling approach

In this article, the results of a modified SERVQUAL questionnaire (Parasuraman et al., 1991) are reported. The modifications consisted in substituting questionnaire items particularly suited to a specific service (banking) and context (county of Girona, Spain) for the original rather general and abstract items. These modifications led to more interpretable factors which accounted for a higher percentage of item variance. The data were submitted to various structural equation models which made it possible to conclude that the questionnaire contains items with a high measurement quality with respect to five identified dimensions of service quality which differ from those specified by Parasuraman et al. And are specific to the banking service. The two dimensions relating to the behaviour of employees have the greatest predictive power on overall quality and satisfaction ratings, which enables managers to use a low-cost reduced version of the questionnaire to monitor quality on a regular basis. It was also found that satisfaction and overall quality were perfectly correlated thus showing that customers do not perceive these concepts as being distinct

Modelling syntectonic sedimentation: combining a discrete element model of tectonic. Deformation and process-based sedimentary Model in 3D.

This paper presents a new numerical program able to model syntectonic sedimentation. The new model combines a discrete element model of the tectonic deformation of a sedimentary cover and a process-based model of sedimentation in a single framework. The integration of these two methods allows us to include the simulation of both sedimentation and deformation processes in a single and more effective model. The paper describes briefly the antecedents of the program, Simsafadim-Clastic and a discrete element model, in order to introduce the methodology used to merge both programs to create the new code. To illustrate the operation and application of the program, analysis of the evolution of syntectonic geometries in an extensional environment and also associated with thrust fault propagation is undertaken. Using the new code, much more complex and realistic depositional structures can be simulated together with a more complex analysis of the evolution of the deformation within the sedimentary cover, which is seen to be affected by the presence of the new syntectonic sediments.

Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO2 and water fluxes through combined in situ measurements and ecosystem modelling

Water stress is a defining characteristic of Mediterranean ecosystems, and is likely to become more severe in the coming decades. Simulation models are key tools for making predictions, but our current understanding of how soil moisture controls ecosystem functioning is not sufficient to adequately constrain parameterisations. Canopy-scale flux data from four forest ecosystems with Mediterranean-type climates were used in order to analyse the physiological controls on carbon and water flues through the year. Significant non-stomatal limitations on photosynthesis were detected, along with lesser changes in the conductance-assimilation relationship. New model parameterisations were derived and implemented in two contrasting modelling approaches. The effectiveness of two models, one a dynamic global vegetation model ('ORCHIDEE'), and the other a forest growth model particularly developed for Mediterranean simulations ('GOTILWA+'), was assessed and modelled canopy responses to seasonal changes in soil moisture were analysed in comparison with in situ flux measurements. In contrast to commonly held assumptions, we find that changing the ratio of conductance to assimilation under natural, seasonally-developing, soil moisture stress is not sufficient to reproduce forest canopy CO2 and water fluxes. However, accurate predictions of both CO2 and water fluxes under all soil moisture levels encountered in the field are obtained if photosynthetic capacity is assumed to vary with soil moisture. This new parameterisation has important consequences for simulated responses of carbon and water fluxes to seasonal soil moisture stress, and should greatly improve our ability to anticipate future impacts of climate changes on the functioning of ecosystems in Mediterranean-type climates.

1,2,3,4-Tetrahydrobenzo[h][1,6]naphthyridines as a new family of potent peripheral-to-midgorge-site inhibitors of acetylcholinesterase: synthesis, pharmacological evaluation and mechanistic studies

A series of 1,2,3,4-tetrahydrobenzo[h][1,6]naphthyridines differently substituted at positions 1, 5, and 9 have been designed from the pyrano[3,2-c]quinoline derivative 1, a weak inhibitor of acetylcholinesterase (AChE) with predicted ability to bind to the AChE peripheral anionic site (PAS), at the entrance of the catalytic gorge. Fourteen novel benzonaphthyridines have been synthesized through synthetic sequences involving as the key step a multicomponent Povarov reaction between an aldehyde, an aniline and an enamine or an enamide as the activated alkene. The novel compounds have been tested against Electrophorus electricus AChE (EeAChE), human recombinant AChE (hAChE), and human serum butyrylcholinesterase (hBChE), and their brain penetration has been assessed using the PAMPA-BBB assay. Also, the mechanism of AChE inhibition of the most potent compounds has been thoroughly studied by kinetic studies, a propidium displacement assay, and molecular modelling. We have found that a seemingly small structural change such as a double O → NH bioisosteric replacement from the hit 1 to 16a results in a dramatic increase of EeAChE and hAChE inhibitory activities (>217- and >154-fold, respectively), and in a notable increase in hBChE inhibitory activity (> 11-fold), as well. An optimized binding at the PAS besides additional interactions with AChE midgorge residues seem to account for the high hAChE inhibitory potency of 16a (IC50 = 65 nM), which emerges as an interesting anti-Alzheimer lead compound with potent dual AChE and BChE inhibitory activities.