Estimation of total body water from bioelectrical impedance analysis in patients with pancreatic cancer - agreement between three methods of prediction

Introduction Bioelectrical impedance analysis (BIA) is a useful field measure to estimate total body water (TBW). No prediction formulae have been developed or validated against a reference method in patients with pancreatic cancer. The aim of this study was to assess the agreement between three prediction equations for the estimation of TBW in cachectic patients with pancreatic cancer. Methods Resistance was measured at frequencies of 50 and 200 kHz in 18 outpatients (10 males and eight females, age 70.2 +/- 11.8 years) with pancreatic cancer from two tertiary Australian hospitals. Three published prediction formulae were used to calculate TBW - TBWs developed in surgical patients, TBWca-uw and TBWca-nw developed in underweight and normal weight patients with end-stage cancer. Results There was no significant difference in the TBW estimated by the three prediction equations - TBWs 32.9 +/- 8.3 L, TBWca-nw 36.3 +/- 7.4 L, TBWca-uw 34.6 +/- 7.6 L. At a population level, there is agreement between prediction of TBW in patients with pancreatic cancer estimated from the three equations. The best combination of low bias and narrow limits of agreement was observed when TBW was estimated from the equation developed in the underweight cancer patients relative to the normal weight cancer patients. When no established BIA prediction equation exists, practitioners should utilize an equation developed in a population with similar critical characteristics such as diagnosis, weight loss, body mass index and/or age. Conclusions Further research is required to determine the accuracy of the BIA prediction technique against a reference method in patients with pancreatic cancer.

Polyethylene flow prediction with a differential multi-mode Pom-Pom model

We report the first steps of a collaborative project between the University of Queensland, Polyflow, Michelin, SK Chemicals, and RMIT University; on simulation, validation and application of a recently introduced constitutive model designed to describe branched polymers. Whereas much progress has been made on predicting the complex flow behaviour of many - in particular linear - polymers, it sometimes appears difficult to predict simultaneously shear thinning and extensional strain hardening behaviour using traditional constitutive models. Recently a new viscoelastic model based on molecular topology, was proposed by McLeish and Larson (1998). We explore the predictive power of a differential multi-mode version of the pom-pom model for the flow behaviour of two commercial polymer melts: a (long-chain branched) low-density polyethylene (LDPE) and a (linear) high-density polyethylene (HDPE). The model responses are compared to elongational recovery experiments published by Langouche and Debbaut (1999), and start-up of simple shear flow, stress relaxation after simple and reverse step strain experiments carried out in our laboratory.

Parallel simulation system for earthquake generation: Fault analysis modules and parallel coupling analysis

Solid earth simulations have recently been developed to address issues such as natural disasters, global environmental destruction and the conservation of natural resources. The simulation of solid earth phenomena involves the analysis of complex structures including strata, faults, and heterogeneous material properties. Simulation of the generation and cycle of earthquakes is particularly important, but such simulations require the analysis of complex fault dynamics. GeoFEM is a parallel finite-element analysis system intended for solid earth field phenomena problems. This paper describes recent development in the GeoFEM project for the simulation of earthquake generation and cycles.

Prediction of Golgi Type II membrane proteins based on their transmembrane domains

Motivation: A major issue in cell biology today is how distinct intracellular regions of the cell, like the Golgi Apparatus, maintain their unique composition of proteins and lipids. The cell differentially separates Golgi resident proteins from proteins that move through the organelle to other subcellular destinations. We set out to determine if we could distinguish these two types of transmembrane proteins using computational approaches. Results: A new method has been developed to predict Golgi membrane proteins based on their transmembrane domains. To establish the prediction procedure, we took the hydrophobicity values and frequencies of different residues within the transmembrane domains into consideration. A simple linear discriminant function was developed with a small number of parameters derived from a dataset of Type II transmembrane proteins of known localization. This can discriminate between proteins destined for Golgi apparatus or other locations (post-Golgi) with a success rate of 89.3% or 85.2%, respectively on our redundancy-reduced data sets.

Assessment of bioelectrical impedance analysis for the prediction of total body water in cystic fibrosis

The aim of this study was to compare the measurement of total body water (TBW) by deuterium ((H2O)-H-2) dilution and bioelectrical impedance analysis (BIA) in patients with cystic fibrosis (CF) and healthy controls. Thirty-six clinically stable patients with CF (age 25.4 +/- 5.6 yrs) and 42 healthy controls (age 25.4 +/- 4.8) were recruited into this study. TBW was measured by (H2O)-H-2 dilution and predicted by BIA in patients and controls. The TBW predicted from BIA was significantly different from TBW as measured using (H2O)-H-2 in patients (P

Prediction of mortality in patients without angina: Use of an exercise score and exercise echocardiography

Background Exercise testing has limited efficacy for identifying coronary artery disease (CAD) in the absence of anginal. symptoms. Exercise echocardiography is more accurate than standard exercise testing, but its efficacy in this situation has not been defined. We sought to identify whether the Duke treadmill. score or exercise echocardiography (ExE) could be used to identify risk in patients without anginal symptoms. Methods We studied 1859 patients without typical or atypical angina, heart failure, or a history or ECG evidence of infarction or CAD, who were referred for ExE, of whom 1832 (age 51 15 years, 944 men) were followed for up to 10 years. The presence and extent of ischaemia and scar were interpreted by expert reviewers at the time of the original study. Results Exercise provoked significant (>0.1 mV) ST segment depression in 215 patients (12%), and wall motion abnormalities in 137 (8%). Seventy-eight patients (4%) died before revascularization, only 17 from known cardiac causes. The independent predictors of death were age (RR 1.1, p

Prediction of multilayer adsorption and capillary condensation phenomena in cylindrical mesopores

MCM-41 periodic mesoporous silicates with a high degree of structural ordering are synthesized and used as model adsorbents to study the isotherm prediction of nitrogen adsorption. The nitrogen adsorption isotherm at 77 K for a macroporous silica is measured and used in high-resolution alpha(s)-plot comparative analysis to determine the external surface area, total surface area and primary mesopore volume of the MCM-41 materials. Adsorption equilibrium data of nitrogen on the different pore size MCM-41 samples (pore diameters from 2.40 to 4.92 nm) are also obtained. Based on the Broekhoff and de Boer' thermodynamic analysis, the nitrogen adsorption isotherms for the different pore size MCM-41 samples are interpreted using a novel strategy, in which the parameters of an empirical expression, used to represent the potential of interaction between the adsorbate and adsorbent, are obtained by fitting only the multilayer region prior to capillary condensation for C-16 MCM-41. Subsequently the entire isotherm, including the phase transition, is predicted for all the different pore size MCM-41 samples without any fitting. The results show that the prediction of multilayer adsorption and total adsorbed amount are in good agreement with the experimental isotherms. The predictions of the relative pressure corresponding to capillary equilibrium (coexistence) transition agree remarkably with experimental data on the adsorption branch even for hysteretic isotherms, confirming that this is the branch appropriate for pore size distribution analysis. The impact of pore radius on the adsorption film thickness and capillary coexistence pressure is also investigated, and found to agree with the experimental data. (C) 2003 Elsevier Inc. All rights reserved.

Fatigue Prediction on Fibrin Poly-ε-caprolactone Macroporous Scaffolds

Tissue engineering applications rely on scaffolds that during its service life, either for in-vivo or in vitro applications, are under mechanical solicitations. The variation of the mechanical condition of the scaffold is strongly relevant for cell culture and has been scarcely addressed. Fatigue life cycle of poly-ε-caprolactone, PCL, scaffolds with and without fibrin as filler of the pore structure were characterized both dry and immersed in liquid water. It is observed that the there is a strong increase from 100 to 500 in the number of loading cycles before collapse in the samples tested in immersed conditions due to the more uniform stress distributions within the samples, the fibrin loading playing a minor role in the mechanical performance of the scaffolds

Prediction of genetic gain from selection indices for disease resistance in papaya hybrids

In order to select superior hybrids for the concentration of favorable alleles for resistance to papaya black spot, powdery mildew and phoma spot, 67 hybrids were evaluated in two seasons, in 2007, in a randomized block design with two replications. Genetic gains were estimated from the selection indices of Smith & Hazel, Pesek & Baker, Williams, Mulamba & Mock, with selection intensity of 22.39%, corresponding to 15 hybrids. The index of Mulamba & Mock showed gains more suitable for the five traits assessed when it was used the criterion of economic weight tentatively assigned. Together, severity of black spot on leaves and on fruits, characteristics considered most relevant to the selection of resistant materials, expressed percentage gain of -44.15%. In addition, there were gains for other characteristics, with negative predicted selective percentage gain. The results showed that the index of Mulamba & Mock is the most efficient procedure for simultaneous selection of papaya hybrid resistant to black spot, powdery mildew and phoma spot.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Assessment and prediction of asthma and its severity in the pediatric community

Seventy four asthmatic children aged 7 to 11 years were examined along with controls matched by age and sex. Clinical and laboratory investigations preceded a 28-day follow-up where data about morning and evening peak expiratory flow rate (PEF), symptoms and treatment were recorded. The coefficient of variation of PEF was found to be an objective measurement of asthma severity that has statistically significant correlation with both symptoms (r s= .36) and treatment (r s= .60). Moreover, it separates mild and severe asthmatics, as confirmed by statistically significant differences (p= .008 or less) in symptoms, treatment, skin allergy and airways response to exercise. Skin allergy and airways responsiveness to exercise were found to be predictors of both disease and severity. By means of logistic regression analysis it was possible to establish the probabilities for both asthma and severe asthma when children presenting and not presenting these characteristics are compared. One single positive skin test represent a probability of 88% for the development of asthma and a probability of 70% for severe disease. A PEF reduction of 10% after an exercise test implies a probability of 73% for disease and a probability of 64% for severe disease. Increases in these variables imply geometrically increased risks and their presence together have a multiplicative effect in the final risk.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

The source of the 1722 Algarve earthquake: evidence from MCS and tsunami data

The 27 December 1722 Algarve earthquake destroyed a large area in southern Portugal generating a local tsunami that inundated the shallow areas of Tavira. It is unclear whether its source was located onshore or offshore and, in any case, what was the tectonic source responsible for the event. We analyze available historical information concerning macroseismicity and the tsunami to discuss the most probable location of the source. We also review available seismotectonic knowledge of the offshore region close to the probable epicenter, selecting a set of four candidate sources. We simulate tsunamis produced by these candidate sources assuming that the sea bottom displacement is caused by a compressive dislocation over a rectangular fault, as given by the half-space homogeneous elastic approach, and we use numerical modeling to study wave propagation and run-up. We conclude that the 27 December 1722 Tavira earthquake and tsunami was probably generated offshore, close to 37 degrees 01'N, 7 degrees 49'W.