A partition method for the solution of coupled liquid-structure interaction problem

A numerical code is presented to study the motion of an incompressible inviscid flow in a deformable tank. It is based on a method belonging to the partition treatment class, as the fluid and structural fields are solved by coupling two distinct models. The fluid field is modeled by the Laplace equation and numerically solved by a Finite Volume technique. The computational grid is updated at each time step to take into account the movements of the free surface and the deformations of the vertical walls. An unsteady finite element formulation is used for modeling the tank on a grid discretized by triangular elements and linear shape functions. Results are presented for two different cases: a flow induced by a perturbation on the free surface in a tank motionless; a flow in a tank forced to oscillate periodically in the horizontal direction

STAT3, a hub protein of cellular signaling pathways, is triggered by β-hexaclorocyclohexane

Background: Organochlorine pesticides (OCPs) are widely distributed in the environment and their toxicity is mostly associated with the molecular mechanisms of endocrine disruption. Among OCPs, particular attention was focused on the effects of β-hexaclorocyclohexane (β-HCH), a widely common pollutant. A detailed epidemiological study carried out on exposed population in the “Valle del Sacco” found correlations between the incidence of a wide range of diseases and the occurrence of β-HCH contamination. Taking into account the pleiotropic role of the protein signal transducer and activator of transcription 3 (STAT3), its function as a hub protein in cellular signaling pathways triggered by β-HCH was investigated in different cell lines corresponding to tissues that are especially vulnerable to damage by environmental pollutants. Materials and Methods: Human prostate cancer (LNCaP), human breast cancer (MCF-7 and MDA-MB 468), and human hepatoma (HepG2) cell lines were treated with 10 µM β-HCH in the presence or absence of specific inhibitors for different receptors. All samples were subjected to analysis by immunoblotting and RT-qPCR. Results and Conclusions: The preliminary results allow us to hypothesize the involvement of STAT3, through both its canonical and non-canonical pathways, in response to β-HCH. Moreover, we ascertained the role of STAT3 as a master regulator of energy metabolism via the altered expression and localization of HIF-1α and PKM2, respectively, resulting in a Warburg-like effect

Systems biology of stored blood cells: can it help to extend the expiration date?

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinnWith increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics.info:eu-repo/grantAgreement/EC/FP7/23281

A methodology for track geometry estimation using inertial measurements: compensation of bogie filtering

In this paper, a methodology for the estimation of track longitudinal level based on the double integration of acceleration measurements is presented. The method is meant to be implemented on vehicles in-service along main line, where trains run at various speed depending on the line characteristics. The system relies on the information coming from a single sensor, mounted at the centre of the bogie frame. A suitable strategy to account for the filtering action introduced by the bogie, that makes the system blind to specific wavelengths, is proposed. To monitor the track conditions, the standard deviation and the peak value of the longitudinal level computed over a 100 m windows are adopted as synthetic indicators. Linear regression models relating the indicators sampled from the direct measurements taken by a diagnostic vehicle and those computed by double integration of the acceleration signals are realized. Both regression models, fed with the data gathered during a long-term monitoring, are finally adopted to estimate the track longitudinal level from the instrumented commercial vehicle, showing satisfactory results

Acceleration-based condition monitoring of track longitudinal level using multiple regression models

In this paper, a condition monitoring system for railway track geometry is presented. The methodology has been designed for high-speed application, where the train travels at the maximum allowed speed for most of the trip. The system is designed to rely on acceleration data recorded by in-service vehicles to provide estimations of the track longitudinal level, based on pre-built regression models. It exploits synthetic indicators sampled over predefined track sections 100 m long. Different predictors are considered, computed both from acceleration data and from track geometry measured by the diagnostic train. The proposed modelling strategy allows distinguishing between isolated and distributed defects that populate the railway track as well as reproducing the evolution over time of the maximum longitudinal level registered in the considered track section; moreover, also accurate predictions of the defect amplitude are made. The results have been validated against track geometry data recorded by the diagnostic train during a monitoring period of 2 years. It is proven that the proposed system could support current maintenance strategies, providing a continuous flow of data to monitor the track infrastructure

An application of the Unknown Input Observer algorithm for the identification of vertical railway track irregularity

In this paper, a model-based solution for the identification of the railway track irregularity from simulation data is presented. The proposed methodology relies on the application of the Unknown Input Observer algorithm. A Simpack railway vehicle model is adopted to simulate the acceleration levels that vehicle-mounted sensors (for instance on the bogies and carbody) would measure during operation. A vehicle running at constant speed on a straight track is considered, considering different type of track irregularity (longitudinal level, cross-level) to test the algorithm capability to identify the input irregularity. In the analysed cases, satisfactory results are achieved both in terms of signal histories and corresponding frequency content, proving the methodology suitable for the identification of the track irregularity for monitoring purposes, adopting an instrumented vehicle

The rna-binding ubiquitin ligase mex3a affects glioblastoma tumorigenesis by inducing ubiquitylation and degradation of rig-i

Glioblastoma multiforme (GB) is the most malignant primary brain tumor in humans, with an overall survival of approximatively 15 months. The molecular heterogeneity of GB, as well as its rapid progression, invasiveness and the occurrence of drug-resistant cancer stem cells, limits the efficacy of the current treatments. In order to develop an innovative therapeutic strategy, it is mandatory to identify and characterize new molecular players responsible for the GB malignant phenotype. In this study, the RNA-binding ubiquitin ligase MEX3A was selected from a gene expression analysis performed on publicly available datasets, to assess its biological and still-unknown activity in GB tumorigenesis. We find that MEX3A is strongly up-regulated in GB specimens, and this correlates with very low protein levels of RIG-I, a tumor suppressor involved in differentiation, apoptosis and innate immune response. We demonstrate that MEX3A binds RIG-I and induces its ubiquitylation and proteasome-dependent degradation. Further, the genetic depletion of MEX3A leads to an increase of RIG-I protein levels and results in the suppression of GB cell growth. Our findings unveil a novel molecular mechanism involved in GB tumorigenesis and suggest MEX3A and RIG-I as promising therapeutic targets in GB

β-Hexachlorocyclohexane Drives Carcinogenesis in the Human Normal Bronchial Epithelium Cell Line BEAS-2B

Organochlorine pesticides constitute the majority of the total environmental pollutants, and a wide range of compounds have been found to be carcinogenic to humans. Among all, growing interest has been focused on β-hexachlorocyclohexane (β-HCH), virtually the most hazardous and, at the same time, the most poorly investigated member of the hexachlorocyclohexane family. Considering the multifaceted biochemical activities of β-HCH, already established in our previous studies, the aim of this work is to assess whether β-HCH could also trigger cellular malignant transformation toward cancer development. For this purpose, experiments were performed on the human normal bronchial epithelium cell line BEAS-2B exposed to 10 µM β-HCH. The obtained results strongly support the carcinogenic potential of β-HCH, which is achieved through both non-genotoxic (activation of oncogenic signaling pathways and proliferative activity) and indirect genotoxic (ROS production and DNA damage) mechanisms that significantly affect cellular macroscopic characteristics and functions such as cell morphology, cell cycle profile, and apoptosis. Taking all these elements into account, the presented study provides important elements to further characterize β-HCH, which appears to be a full-fledged carcinogenic agent

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics.

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.The increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed "unsteady-state flux balance analysis" (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBA predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through (13)C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.National Heart Lung and Blood Institute European Research Council U.S. Department of Energ