Leave-one-out prediction error of systolic arterial pressure time series under paced breathing

In this paper we show that different physiological states and pathological conditions may be characterized in terms of predictability of time series signals from the underlying biological system. In particular we consider systolic arterial pressure time series from healthy subjects and Chronic Heart Failure patients, undergoing paced respiration. We model time series by the regularized least squares approach and quantify predictability by the leave-one-out error. We find that the entrainment mechanism connected to paced breath, that renders the arterial blood pressure signal more regular, thus more predictable, is less effective in patients, and this effect correlates with the seriousness of the heart failure. The leave-one-out error separates controls from patients and, when all orders of nonlinearity are taken into account, alive patients from patients for which cardiac death occurred

Visualising 2-simplex formation in metabolic reactions

Understanding in silico the dynamics of metabolic reactions made by a large number of molecules has led to the development of different tools for visualising molecular interactions. However, most of them are mainly focused on quantitative aspects. We investigate the potentiality of the topological interpretation of the interaction-as-perception at the basis of a multiagent system, to tackle the complexity of visualising the emerging behaviour of a complex system. We model and simulate the glycolysis process as a multiagent system, and we perform topological data analysis of the molecular perceptions graphs, gained during the formation of the enzymatic complexes, to visualise the set of emerging patterns. Identifying expected patterns in terms of simplicial structures allows us to characterise metabolic reactions from a qualitative point of view and conceivably reveal the simulation reactivity trend

Agent-based models for detecting the driving forces of biomolecular interactions

Agent-based modelling and simulation have been effectively applied to the study of complex biological systems, especially when composed of many interacting entities. Representing biomolecules as autonomous agents allows this approach to bring out the global behaviour of biochemical processes as resulting from local molecular interactions. In this paper, we leverage the capabilities of the agent paradigm to construct an in silico replica of the glycolytic pathway; the aim is to detect the role that long-range electrodynamic forces might have on the rate of glucose oxidation. Experimental evidences have shown that random encounters and short-range potentials might not be sufficient to explain the high efficiency of biochemical reactions in living cells. However, while the latest in vitro studies are limited by present-day technology, agent-based simulations provide an in silico support to the outcomes hitherto obtained and shed light on behaviours not yet well understood. Our results grasp properties hard to uncover through other computational methods, such as the effect of electromagnetic potentials on glycolytic oscillations

Predictive-Quality Surface Reaction Chemistry in Real Reactor Models: Integrating First-Principles Kinetic Monte Carlo Simulations into Computational Fluid Dynamics

We present a numerical framework to integrate first-principles kinetic Monte Carlo (1p-kMC) based microkinetic models into the powerful computational fluid dynamics (CFD) package CatalyticFoam. This allows for the simultaneous account of a predictive-quality surface reaction kinetics inside an explicitly described catalytic reactor geometry. Crucial means toward an efficient and stable implementation are the exploitation of the disparate time scales of surface chemistry and gas-phase transport, as well as the reliable interpolation of irregularly gridded 1p-kMC data by means of an error-based modified Shepard approach. We illustrate the capabilities of the framework using the CO oxidation at Pd(100) and RuO2(110) model catalysts in different reactor configurations and fluid dynamic conditions as showcases. These showcases underscore both the necessity and value of having reliable treatments of the surface chemistry and flow inside integrated multiscale catalysis simulations when aiming at an atomic-scale understanding of the catalytic function in near-ambient environments. Our examples highlight how intricately this function is affected by specifics of the reactor geometry and heat dissipation channels on the one end, and on the other end by characteristics of the intrinsic catalytic activity that are only captured by treatments beyond prevalent mean-field rate equations

Terragni sono io!

Testo ufficiale letto prima della cerimonia della consegna del Diploma Honoris Causa all'architetto americano Peter Eisenman

Total orthotopic small bowel transplantation in swine under FK 506

Previous experimental studies in rodents and in dogs have established the efficacy of FK 506 in controlling the immunologic events following small bowel or multivisceral transplantation.1–5 To complete the assessment of FK 506 in experimental small bowel transplantation, we present here our experience with the frequently used swine model

From Fossils to Living Canids:Two Contrasting Perspectives on Biogeographic Diversification

he Canidae are an ecologically important group of dog-like carnivores that arose in North America and spread across the planet around 10 million years ago. The current distribution patterns of species, coupled with their phylogenetic structure, suggest that Canidae diversification may have occurred at varying rates across different biogeographic areas. However, such extant-only analyses undervalued the group’s rich fossil history because of a limitation in method’s development. Current State-dependent Speciation and Extinction (SSE) models are (i) often parameter-rich which hinders reliable application to relatively small clades such as the Caninae (the only extant subclade of the Canidae consisting of 36 extant species); and (ii) often assume as possible states only the states that extant species present. Here we extend the SSE method SecSSE to apply to phylogenies with extinct species as well (111 Caninae species) and compare the results to those of analyses with the extant-species-only phylogeny. The results on the extant-species tree suggest that distinct diversification patterns are related to geographic areas, but the results on the complete tree do not support this conclusion. Furthermore, our extant-species analysis yielded an unrealistically low estimate of the extinction rate. These contrasting findings suggest that information from extinct species is different from information from extant species. A possible explanation for our results is that extinct species may have characteristics (causing their extinction), which may be different from the characteristics of extant species that caused them to be extant. Hence, we conclude that differences in biogeographic areas probably did not contribute much to the variation in diversification rates in Caninae

Constitutive expression of the barley dehydrin gene aba2 enhances Arabidopsis germination in response to salt stress

Dehydrins (DHNs) are a sub-family of the late embryogenesis abundant proteins generally induced during development of desiccation tolerance in seeds and water deficit or salinity stress in plants. Nevertheless, a detailed understanding of the DHNs function is still lacking. In this work we investigated the possible protective role during salt stress of a Dhn from Hordeum vulgare (L.), aba2. The coding sequence of the aba2 gene was constitutively expressed in transgenic lines of Arabidopsis thaliana (L.). During salt stress conditions germination rate, cotyledon expansion and greening were greatly improved in the transgenic lines as compared to the wild type. Between 98 and 100% of the transgenic seeds germinated after two weeks in media containing up to 250 mM NaCl, and 90% after 22 days at 300 mM NaCl. In conditions of 200 mM NaCl 93% of the transgenic cotyledons had greened after two weeks, outperforming the wild type by 45%. Our study provides further evidence that DHNs have an important role in salt stress tolerance. The production of plants constitutively expressing DHNs could be an effective strategy to improve plant breeding programs