THREE METHODS TO INCREASE THE LIKELY TO IDENTIFY GENE INVOLVED IN COMPLEX DISEASE

The large part of human pathology is composed by complex disease, such as heart disease, obesity, cancer, diabetes, and many common psychiatric and neurological conditions. The common feature of all these conditions is the multifactorial etiology that involves both genetic and environmental factors. The common disease-common variant (CDCV) hypothesis posits that common, interacting alleles underlie most common diseases, in association with environmental factors. Furthermore, according to the thrift genotype, such alleles have been subjected to selective pressure, mainly those involved in metabolic disease such as T2DM and obesity. Although the concept of gene-environment interaction is central to ecogenetics, and has long been recognized by geneticists (Haldane 1946), there are relatively few detailed descriptions of gene–environment interaction in biomedical literature. This lacking may be explained by difficulties in collecting environmental information of enough quality and by great difficulties in analyze them. Indeed, when the number of factors to analyze is large, become overwhelming the course of dimensionality and the multiple testing problems. In the present thesis the hypothesis that knowledge-driven approaches may improve the ability to identify genes involved in complex disease was checked. Three approaches have been presented, each of them leading to the identification of a factor or of a interaction of factors. As the study a complex disease is composed by three steps: (1) selection of candidate genes, (2) collecting of genetic and non-genetic information and (3) statistical analysis of data, it is showed that each of these steps may be improved by consideration of the biological background. The first study, regarded the possibility to exploit evolutionary information to identify genes involved in type 2 diabetes. This hypothesis was based on the thrifty genotype hypothesis. A gene was identified, ACO1, and was successfully associated to the disease. In the second study, we analyses the case of a gene, PPAGγ that have been inconsistency associated with obesity. We hypothesized that the inconsistence of association may be due to its relationship with environment. Then we jointly analyzed the genotype of the gene and comprehensive nutritional information about a cohort and proved an interaction. The genotype of PPARγ modulated the response to the diet. Ala-carriers gained more weight than ProPro individuals when had the same caloric intake. In the third study, we implemented a software tool to create simulated populations based on gene-environment interactions. The system was based on genetic information to simulate realistic populations. We used these simulated populations to collect information on statistical methods more frequently used to study case-controls samples. Afterward, we built an ensemble of these methods and applied it to a real sample. We showed that ensemble had better performances of each single methods in condition of small sample size

Long-term orientation, family-intensive governance arrangements, and firm performance: an institutional economics perspective

In this study, we examine the effect of cultural long-term orientation on the likelihood of adopting more family-intensive governance arrangements (FGAs) and the impact on firm performance. FGAs may impose various costs on the firm, including the extraction of private benefits, conflicts with professional managers, paternalistic human resource management practices, and lower legitimacy. Drawing on institutional economics, we theorize that cultural long-term orientation reduces some of these costs, thereby increasing the relative efficiency of FGAs as a governance option. Thus, we expect FGAs to be adopted more frequently in countries with a more long-term orientation. We also expect FGAs to have a less negative impact on performance in these countries as a result of these lower costs. The results of mixed-effects regressions on a cross-sectional sample of 3221 listed family and nonfamily firms in 19 countries confirm that FGAs are more likely to be adopted in more long-term oriented countries. We also find that FGAs have a negative effect on firm performance, but not that cultural long-term orientation weakens this relationship. However, an interesting mediating effect emerges whereby cultural long-term orientation increases the likelihood of adopting FGAs but negatively affects firm performance.Family firms are embedded in institutional frameworks that inevitably shape their governance structures and performance. In this study, we examine the impact of cultural long-term orientation on the likelihood of adopting more family-intensive governance structures and their effect on performance. Specifically, drawing on institutional theory, we hypothesize that (a) a country's long-term orientation increases the likelihood of adopting more family-intensive governance structures; (b) family-intensive governance negatively affects performance; (c) a country's long-term orientation plays a moderating role in the relationship between family-intensive governance and performance. Our statistical analysis using mixed-effects regressions on a cross-sectional dataset of 3221 publicly listed family and nonfamily firms in 19 countries validates the first two hypotheses. Although we do not find that cultural long-term orientation weakens the negative effect of family-intensive governance and performance, our results reveal an intriguing mediating effect suggesting that cultural long-term orientation negatively affects firm performance by increasing the intensity of family involvement in firm governance

Gas Turbine Health State Determination: Methodology Approach and Field Application

A reduction of gas turbine maintenance costs, together with the increase in machine availability and the reduction of management costs, is usually expected when gas turbine preventive maintenance is performed in parallel to on-condition maintenance. However, on-condition maintenance requires up-to-date knowledge of the machine health state. The gas turbine health state can be determined by means of Gas Path Analysis (GPA) techniques, which allow the calculation of machine health state indices, starting from measurements taken on the machine. Since the GPA technique makes use of field measurements, the reliability of the diagnostic process also depends on measurement reliability. In this paper, a comprehensive approach for both the measurement validation and health state determination of gas turbines is discussed, and its application to a 5 MW gas turbine working in a natural gas compression plant is presented

reducing pressure valve with real gases an integrated approach for the design

Abstract In the pursuit of an increasing cleaner fuel, methane represents a widely-employed solution for vehicles. The lower emissions, if compared to gasoline or diesel fuel, makes it an attractive opportunity in tackling transport-related pollution. Methane-powered vehicles are indeed often excluded from driving bans, pushing the demand for such kind of car. Methane is usually stored on board in tanks filled with pressure up to 20 MPa. The fuel injection systems for methane feeding usually work at pressure lower than 1 MPa (around 0.7 MPa). This difference demands a pressure-reducing valve to be installed to adjust the pressure and the fuel flow rate as required by the driver. This component and its design in hostile condition is the object of this study. Particularly, in automotive applications, the fluid operates not far from the critical point and therefore the behavior should be modelled with a real gas approach. In such light, it is immediate to note that, by the throttling procedure, the temperature of the gas drops. In addition to the acceleration of the flow, the Joule-Thomson effect related to the non-ideality of the fluid lowers the static temperature of the gas itself during the expansion. If this is combined with particularly cold environmental conditions, the material of the seals may fail entailing gas leakage. In this work, an integrated numerical and experimental study of methane fluid and thermodynamic conditions when passing through the valve orifice is reported. Extreme environmental conditions have been numerically tested, comparing and validating the results with experiments. The numerical simulations have been carried out with the open-source software suite OpenFOAM-v1712. The capability of real gas modelling has been extended by implementing a new thermophysical strategy based on the CoolProp set of libraries

Pro12Ala polymorphism in the PPARG gene contributes to the development of diabetic nephropathy in Chinese type 2 diabetic patients: comment on the study by Liu et al.

We read with interest the article by Liu et al. (1) showing that the Pro/Pro genotype of the peroxisome proliferator–activated receptor (PPAR)-γ2 is a significant independent predictor of the development of diabetic nephropathy in a large population of Chinese type 2 diabetic patients. The study confirms, in a different ethnic group, what has already been shown in relatively small studies conducted in Caucasian diabetic patients (i.e., a population with lower prevalence of diabetic nephropathy and higher frequency of Pro12Ala genotype than the Chinese population), although none of these studies provides a complete evaluation of renal function (2–4). We report data that confirm the association between the Pro12Ala polymorphism of PPAR-γ2 and urinary albumin excretion rate (AER) in

real gas expansion with dynamic mesh in common positive displacement machines

Abstract Fluids processed by the machinery involved in ORC cycles undergo several transformations among which the expansion in positive displacement machines. The fluid path inside this component is very complicated and gaps play a crucial role. Due to the importance of this technical detail, gap design and optimization is a decisive step in achieving an high efficiency both of the expander and the whole cycle. In this work the fluid dynamics of several fluids commonly used in ORC cycles is investigated. Particularly, their behaviour during the expansion through the gap in operation is numerically investigated. The effects of the gap formation and its evolution on the processed fluid is studied thanks to a dynamic mesh approach. A typical application has been considered in this work: the variable gap between the fixed and mobile spirals of a scroll expander is analysed. The relative motion and in turn, the variation of the gaps during the machine operation, implies the use of particular numerical strategies able to well represent these localized geometrical features. On the top of that, the modelling of the processed fluids as a real gas determines an extra effort in the way of representing the actual behavior involved in the positive displacement machine operation. This analysis shows the local fluid dynamic phenomena due to the variable clearances. R134a and its replacements R152a and R1234ze(E), fluids widespread in the ORC cycles, are used in this work. The fluids are investigated under the same conditions and effects like separation and shock wave are highlighted. This analysis allows the comprehension of how local phenomena could affect the overall machine operation and efficiency. Gaps are the responsible of the volumetric efficiency of the machine and, coupled with (i) time-variable geometry modification, (ii) relative velocities and (iii) fluid characteristics characterize the global ORC system performance

Validation of an URANS approach for direct and indirect noise assessment in a high pressure turbine stage

Abstract In response to the continuous increase in aircraft noise pollution, computational aeroacoustic analyses are mandatory during the aero-engine design loop. In order to investigate the acoustic generation and propagation phenomena within a multi-stage turbomachinery, an experimental campaign on direct and indirect noise coming from a high pressure axial turbine stage has been carried out by Politecnico di Milano in the context of the European research project RECORD. The purpose of this work is to numerically predict both the direct noise produced by stator/rotor interactions and the indirect noise generated by the non-acoustic fluctuations coming from an annular combustor that impinge on the HPT stage by using URANS analyses. The computational results are in good agreement with experimental measures, confirming the possibility to include the numerical method during the engine design loop to assess noise emissions and suggest low noise design solutions