Etiology of ovarian failure in blepharophimosis ptosis epicanthus inversus syndrome: FOXL2 is a conserved, early-acting gene in vertebrate ovarian development

Blepharophimosis ptosis epicanthus inversus syndrome (BPES) is a human disorder caused by mutations in the forkhead transcription factor gene FOXL2 and is characterized by facial dysmorphology combined in some cases with ovarian failure. To better understand the role of FOXL2 in the etiology of ovarian failure in BPES, we examined its expression in embryonic ovaries of mice, chickens, and red-eared slider turtles, representatives of three phylogenetically distant vertebrate groups that have different mechanisms of sex determination. Expression of Foxl2 was detected in early ovaries of all three species around the time of sex determination and was associated with both somatic and germ cell populations in mice. Expression was sexually dimorphic in all cases. Sequence analysis of turtle and chicken FoxL2 orthologues indicated an unusually high degree of structural conservation during evolution. FoxL2 was found to be autosomal in chickens, and therefore unlikely to represent the dominant ovarian-determining gene that has been postulated to exist as a possible explanation for female heterogamety in birds. Our observations suggest that BPES may result from early abnormalities in regulating the development of the fetal ovary, rather than premature degeneration of the postnatal or adult ovary. Further, our results suggest that FOXL2 is a highly conserved early regulator of vertebrate ovarian development.

Acute liver failure in children: A regional experience

Objective: To review the outcome of acute liver failure (ALF) and the effect of liver transplantation in children in Australia. Methodology: A retrospective review was conducted of all paediatric patients referred with acute liver failure between 1985 and 2000 to the Queensland Liver Transplant Service, a paediatric liver transplant centre based at the Royal Children's Hospital, Brisbane, that is one of three paediatric transplant centres in Australia. Results: Twenty-six patients were referred with ALF. Four patients did not require transplantation and recovered with medical therapy while two were excluded because of irreversible neurological changes and died. Of the 20 patients considered for transplant, three refused for social and/or religious reasons, with 17 patients listed for transplantation. One patient recovered spontaneously and one died before receiving a transplant. There were 15 transplants of which 40% (6/15) were < 2 years old. Sixty-seven per cent (10/15) survived > 1 month after transplantation. Forty per cent (6/15) survived more than 6 months after transplant. There were only four long-term survivors after transplant for ALF (27%). Overall, 27% (6/22) of patients referred with ALF survived. Of the 16 patients that died, 44% (7/16) were from neurological causes. Most of these were from cerebral oedema but two patients transplanted for valproate hepatotoxicity died from neurological disease despite good graft function. Conclusions: Irreversible neurological disease remains a major cause of death in children with ALF. We recommend better patient selection and early referral and transfer to a transplant centre before onset of irreversible neurological disease to optimize outcome of children transplanted for ALF.

Biaxial failure model for fiber reinforced concrete

Steel fiber reinforced concrete (SFRC) is widely applied in the construction industry. Numerical elastoplastic analysis of the macroscopic behavior is complex. This typically involves a piecewise linear failure curve including corner singularities. This paper presents a single smooth biaxial failure curve for SFRC based on a semianalytical approximation. Convexity of the proposed model is guaranteed so that numerical problems are avoided. The model has sufficient flexibility to closely match experimental results. The failure curve is also suitable for modeling plain concrete under biaxial loading. Since this model is capable of simulating the failure states in all stress regimes with a single envelope, the elastoplastic formulation is very concise and simple. The finite element implementation is developed to demonstrate the conciseness and the effectiveness of the model. The computed results display good agreement with published experimental data.

Left ventricular dyssynchrony predicts benefit of cardiac resynchronization therapy in patients with end-stage heart failure before pacemaker implantation

We evaluated patients with end-stage heart failure who have a high likelihood of response to cardiac resynchronization therapy (biventricular pacing). It appears that 20% of patients do not respond to this expensive therapy despite the use of selection criteria (dilated cardiomyopathy, heart failure, New York Heart Association class II or IV, left ventricular election fraction 120 ms). The presence of left ventricular dys-synchrony is needed to result in improvement after cardiac resynchronization therapy. (C)2003 by Excerpta Medica, Inc.

Mechanisms of exercise training in patients with heart failure

Background The reduction of exercise capacity because of fatigue and dyspnea in patients with heart failure can be improved with exercise training. We sought to examine the mechanisms of exercise training, as an adjunctive treatment strategy for patients with heart failure. Methods a reviewed the published data on the possible mechanisms of effect of exercise training in heart failure. Results Symptoms of heart failure may be explained on the basis of abnormal skeletal muscle perfusion and structure and endothelial function. Exercise training has been shown to engender changes in muscle structure and biochemistry and vascular function, although effects on cardiac function have not been detected uniformly and may require longer training periods. Conclusions A suitable, long-term program of exercise training may reverse unfavorable interactions among the heart, vessels, and skeletal muscles. These improvements may be preserved with an ongoing maintenance program.

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.

Survival Analysis Employed in Predicting Corporate Failure: A Forecasting Model Proposal

In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.

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.

How logrolling can explain the failure of the government coalition in Brazil

This article presents an analysis of the behavior of federal representatives in the Brazilian House of Representatives between 1995 and 1998, when a series of constitutional amendments were presented by the president to be voted on by Congress. The objective is to show that the lack of a stable government coalition resulted in costs to society that were not anticipated by the government. The study argues that a logroll - a trade of votes - was the strategy used by the government in order to guarantee the number of votes necessary to approve the amendments. This strategy created a vicious system in which representatives would only vote with the government if they had benefits in return.

Health related quality of life in patients with refractory chronic heart failure undergoing cardiac resynchronization: type of therapeutic response

The benefits of cardiac resynchronization therapy (CRT) in the health-related quality of life (HRQL) are largely demonstrated in selected patients with severe congestive heart failure (CHF). However, the differences between responders and non-responders, with regard to the effect of CRT in the various dimensions that constitute HRQL are still a matter of discussion. Objective: To evaluate the impact of CRT on the HRQL of patients with CHF refractory to optimal pharmacological therapy, within 6 months after CRT. Methods: 43 patients, submitted to successful implantation of CRT, were evaluated in hospital just before intervention and in the outpatient clinic within 6 months after CRT. HRQL was analyzed based on the Kansas City Cardiomyopathy Questionnaire (KCCQ). Patients were classified as super-responders (ejection fraction of left ventricle - LVEF - ≥45% post-CRT), n=15, responders (sustained improvement in functional class and LVEF increased by 15%), n=19, and non-responders (no clinical or LVEF improvement), n=9. Results: In the group of super-responders, CRT was associated with an improvement in HRQL for the various fields and sums assessed (ρ<0.05); in responders, CRT has been associated with an improvement of HRQL in the various fields and sums, except in the self-efficacy dimension (ρ<0.05); in non-responders, CRT was not associated with improvement of HRQL. Conclusion: In a population with severe CHF undergoing CRT, the patients with clinical and echocardiographic positive response, obtained a favorable impact in all dimensions of HRQL, while the group without response to CRT showed no improvement. These data reinforces the importance of HRQL as a multidimensional tool for assessment of benefits in clinical practice.

Evaluating the quality of life in patients with refractory chronic heart failure undergoing cardiac resynchronization regarding the type of therapeutic response

The benefits of cardiac resynchronization therapy (CRT) in the quality of life have been largely demonstrated in selected patients with severe congestive heart failure (CHF). However, the differences between responders and non-responders, with regard to the effect of CRT in the various dimensions of quality of life is still a matter of discussion. Objective: to evaluate the impact of CRT on the quality of life of patients with CHF refractory to optimal pharmacological therapy, within 6 months after CRT.

Relation of happiness, hope and affection with quality of life in patients with heart failure

Introduction: Meeting the actual role of positive psychology, begins to be recognized the relation of positive variables with health. Objective: To know the relation of happiness, hope and affection with quality of life in individuals with heart failure. Population and Methodology: 128 individuals with heart failure, 98 men and 30 women, 61.9±12,1 years of age, 6,6±3,9 years in school and 74,2% retired because of this disease. 56,3% were in Class III of New York Heart Association, with poor left ventricular ejection fraction (25,3±6,2%). The clinical history was of 9,4±8,5 years for this heart disease and had at least one hospitalization due to heart failure with 51,6% having ischemic heart disease.

Happiness, hope and affection as predictors of quality of life and functionality of individuals with heart failure at 3 month follow up

Introduction: Meeting the actual role of positive psychology, begins to be recognized the contribution of positive variables in health outcomes. Objective: To know the contribution of happiness, hope and affection individually and as a whole in the quality of life and functionality of individuals with heart failure. Population and Methodology: 128 individuals with heart failure, 98 men and 30 women, 61.9±12,1 years of age, 6,6±3,9 years of school and 74,2% retired because of this disease. 56,3% were in Class III of New York Heart Association, with poor left ventricular ejection fraction (25,3±6,2%). The clinical history was of 9,4±8,5 years for this heart disease and had at least one hospitalization due to heart failure with 51,6% having ischemic heart disease.

A model to forecast financial failure, in non financial galician SMES

We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly.