A Multi-state model for the analysis of functional decline and mortality of frail elderly patients

L’objectiu d’aquest estudi, que correspon a un projecte de recerca sobre la pèrdua funcional i la mortalitat de persones grans fràgils, és construir un procés de supervivència predictiu que tingui en compte l’evolució funcional i nutricional dels pacients al llarg del temps. En aquest estudi ens enfrontem a l’anàlisi de dades de supervivència i mesures repetides però els mètodes estadístics habituals per al tractament conjunt d’aquest tipus de dades no són apropiats en aquest cas. Com a alternativa utilitzem els models de supervivència multi-estats per avaluar l’associació entre mortalitat i recuperació, o no, dels nivells funcionals i nutricionals considerats normals. Després d’estimar el model i d’identificar els factors pronòstics de mortalitat és possible obtenir un procés predictiu que permet fer prediccions de la supervivència dels pacients en funció de la seva història concreta fins a un determinat moment. Això permet realitzar un pronòstic més precís de cada grup de pacients, la qual cosa pot ser molt útil per als professionals sanitaris a l’hora de prendre decisions clíniques.

Nuclear magnetic resonance chemical shifts with the statistical average of orbital-dependent model potentials in Kohn-Sham density functional theory

The performance of the SAOP potential for the calculation of NMR chemical shifts was evaluated. SAOP results show considerable improvement with respect to previous potentials, like VWN or BP86, at least for the carbon, nitrogen, oxygen, and fluorine chemical shifts. Furthermore, a few NMR calculations carried out on third period atoms (S, P, and Cl) improved when using the SAOP potential

Surface structure and stability of PdZn and PtZn alloys: Density-functional slab model studies

Geometric parameters of binary (1:1) PdZn and PtZn alloys with CuAu-L10 structure were calculated with a density functional method. Based on the total energies, the alloys are predicted to feature equal formation energies. Calculated surface energies of PdZn and PtZn alloys show that (111) and (100) surfaces exposing stoichiometric layers are more stable than (001) and (110) surfaces comprising alternating Pd (Pt) and Zn layers. The surface energy values of alloys lie between the surface energies of the individual components, but they differ from their composition weighted averages. Compared with the pure metals, the valence d-band widths and the Pd or Pt partial densities of states at the Fermi level are dramatically reduced in PdZn and PtZn alloys. The local valence d-band density of states of Pd and Pt in the alloys resemble that of metallic Cu, suggesting that a similar catalytic performance of these systems can be related to this similarity in the local electronic structures.

Implication of Nerve Growth Factor in intestinal mucosal mast cell activity and colonic motor alterations in a model of ovalbumin-induced gut dysfunction in rats

We determined NGF involvement in MMCs and colonic motor alterations in an ovalbumin (OVA)-induced gut dysfunction model in rats. Animals received OVA (6 weeks), with/without simultaneous K252a (TrkA antagonist) treatment. MMCs, rat mast cell protease II (RMCPII) levels and colonic contractility in vitro were assessed. OVA increased MMC density and RMCPII concentration. Spontaneous contractility was similar in both groups and inhibited by K252a. Carbachol responses were increased by OVA in a K252a-independent manner. NO-synthase inhibition increased spontaneous activity in OVA-treated animals in a K252a-dependent manner. These observations support an involvement of NGF in the functional changes observed in this model.

Influence of the in vivo deregulation of the expression of ntrk3 (trkc) on cortical development of a murine model of panic/anxiety disorder

Alteracions durant el desenvolupament cerebral produirien canvis en la connectivitat neuronal i la bioquímica cel•lular que podrien resultar en una disfunció cognitiva i/o emocional, desembocant a trastorns psiquiàtrics. Les neurotrofines intervenen en els processos del neurodesenvolupament i en la funcionalitat del cervell adult i, conseqüentment, serien bons candidats com a factors de predisposició en diverses malalties mentals. S’ha suggerit la implicació del receptor de la neurotrofina 3, TrkC, en el trastorn de pànic. Nosaltres proposem que la sobreexpressió del gen NTRK3 (TrkC) és un mediador comú dels desencadenants genètics i ambientals d’aquest trastorn. Concretament, la seva desregulació podria produir canvis estructurals i funcionals a l’escorça cerebral dels pacients pel seu paper durant l’establiment dels circuïts corticals i la neuroplasticitat a l’adult, probablement esdevenint elements de predisposició a patir atacs de pànic. Els objectius principals d’aquest treball han estat: 1/determinar la contribució específica del gen NTRK3 a les alteracions de l’escorça cerebral observades en pacients, utilitzant un model murí modificat genèticament (TgNTRK3), i 2/analitzar l’impacte específic de la sobreexpressió de NTRK3 sobre la corticogènesi durant estadis embrionaris o postnatals estudiant la neurogènesi i la neuritogènesi. Els resultats indiquen que la sobreexpressió de NTRK3 als ratolins produeix una reducció del gruix de l’escorça frontal, recapitulant la hipofrontalitat dels pacients, que comportaria una menor inhibició dels nuclis subcorticals del sistema límbic com l’amígdala, i alteracions citoarquitectòniques a l’escorça prefrontal medial que recolzen la hipòtesi del seu mal funcionament. Tanmateix, els ratolins TgNTRK3 presenten canvis estructurals a l’escorça somatosensorial, suggerint que el processament de la informació sensorial podria estar alterat, el que encara no s’ha explorat en pacients. La sobreexpressió de NTRK3 també afecta la neuritogènesi en cultius primaris corticals i modifica la resposta de les neurones a l’estimulació amb neurotrofines. Per tant, el fenotip cortical adult dels TgNTRK3 podria dependre d’alteracions durant la corticogènesi.

Exploring chromium (VI) dioxodihalides chemistry: is density functional theory the most suitable tool?

A comparative systematic study of the CrO2F2 compound has been performed using different conventional ab initio methodologies and density functional procedures. Two points have been analyzed: first, the accuracy of results yielded by each method under study, and second, the computational cost required to reach such results. Weighing up both aspects, density functional theory has been found to be more appropriate than the Hartree-Fock (HF) and the analyzed post-HF methods. Hence, the structural characterization and spectroscopic elucidation of the full CrO2X2 series (X=F,Cl,Br,I) has been done at this level of theory. Emphasis has been given to the unknown CrO2I2 species, and specially to the UV/visible spectra of all four compounds. Furthermore, a topological analysis in terms of charge density distributions has revealed why the valence shell electron pair repulsion model fails in predicting the molecular shape of such CrO2X2 complexes

The quest for a message: budding yeast, a model organism to study the control of pre-mRNA splicing

Removal of introns during pre-mRNA splicing is a critical process in gene expression, and understanding its control at both single-gene and genomic levels is one of the great challenges in Biology. Splicing takes place in a dynamic, large ribonucleoprotein complex known as the spliceosome. Combining Genetics and Biochemistry, Saccharomyces cerevisiae provides insights into its mechanisms, including its regulation by RNA-protein interactions. Recent genome-wide analyses indicate that regulated splicing is broad and biologically relevant even in organisms with a relatively simple intronic structure, such as yeast. Furthermore, the possibility of coordination in splicing regulation at genomic level is becoming clear in this model organism. This should provide a valuable system to approach the complex problem of the role of regulated splicing in genomic expression.

From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

Structural and functional properties of genes involved in human cancer

Background: One of the main goals of cancer genetics is to identify the causative elements at the molecular level leading to cancer.Results: We have conducted an analysis of a set of genes known to be involved in cancer in order to unveil their unique features that can assist towards the identification of new candidate cancer genes. Conclusion: We have detected key patterns in this group of genes in terms of the molecular function or the biological process in which they are involved as well as sequence properties. Based on these features we have developed an accurate Bayesian classification model with which human genes have been scored for their likelihood of involvement in cancer.

A dynamic choice model of hybrid behavior in the attribute-space

This paper presents a dynamic choice model in the attributespace considering rational consumers that discount the future. In lightof the evidence of several state-dependence patterns, the model isfurther extended by considering a utility function that allows for thedifferent types of behavior described in the literature: pure inertia,pure variety seeking and hybrid. The model presents a stationaryconsumption pattern that can be inertial, where the consumer only buysone product, or a variety-seeking one, where the consumer buys severalproducts simultane-ously. Under the inverted-U marginal utilityassumption, the consumer behaves inertial among the existing brands forseveral periods, and eventually, once the stationary levels areapproached, the consumer turns to a variety-seeking behavior. An empiricalanalysis is run using a scanner database for fabric softener andsignificant evidence of hybrid behavior for most attributes is found,which supports the functional form considered in the theory.

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

Deformed-jellium model for the fission of multiply charged metal clusters

A deformed-jellium model is used to calculate the fission barrier height of positive doubly charged sodium clusters within an extended Thomas-Fermi approximation. The fissioning cluster is continuously deformed from the parent configuration until it splits into two fragments. Although the shape of the fission barrier obviously depends on the parametrization of the fission path, we have found that remarkably, the maximum of the barrier corresponds to a configuration in which the emerging fragments are already formed and rather well apart. The implication of this finding in the calculation of critical numbers for fission is illustrated in the case of multiply charged Na clusters.

Nuclear incompressibility in the quasilocal density functional theory

We explore the ability of the recently established quasilocal density functional theory for describing the isoscalar giant monopole resonance. Within this theory we use the scaling approach and perform constrained calculations for obtaining the cubic and inverse energy weighted moments (sum rules) of the RPA strength. The meaning of the sum rule approach in this case is discussed. Numerical calculations are carried out using Gogny forces and an excellent agreement is found with HF+RPA results previously reported in literature. The nuclear matter compression modulus predicted in our model lies in the range 210230 MeV which agrees with earlier findings. The information provided by the sum rule approach in the case of nuclei near the neutron drip line is also discussed.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.