Expression of fibroblast growth factor receptors during development and regression of the bovine corpus luteum

There is evidence that fibroblast growth factors (FGFs) are involved in the regulation of growth and regression of the corpus luteum (CL). However, the expression pattern of most FGF receptors (FGFRs) during CL lifespan is still unknown. The objective of the present study was to determine the pattern of expression of `B` and `C` splice variants of FGFRs in the bovine CL. Bovine CL were collected from an abattoir and classed as corpora hemorrhagica (Stage I), developing (Stage II), developed (Stage III) or regressed (Stage IV) CL. Expression of FGFR mRNA was measured by semiquantitative reverse transcription-polymerase chain reaction and FGFR protein was localised by immunohistochemistry. Expression of mRNA encoding the `B` and `C` spliced forms of FGFR1 and FGFR2 was readily detectable in the bovine CL and was accompanied by protein localisation. FGFR1C and FGFR2C mRNA expression did not vary throughout CL lifespan, whereas FGFR1B was upregulated in the developed (Stage III) CL. FGFR3B, FGFR3C and FGFR4 expression was inconsistent in the bovine CL. The present data indicate that FGFR1 and FGFR2 splice variants are the main receptors for FGF action in the bovine CL.

Proximal arterial vasoconstriction precedes regression of the hyaloid vasculature

Purpose: To determine whether constriction of proximal arterial vessels precedes involution of the distal hyaloid vasculature in the mouse, under normal conditions, and whether this vasoconstriction is less pronounced when the distal hyaloid network persists, as it does in oxygen-induced retinopathy (OIR). Methods: Photomicrographs of the vasa hyaloidea propria were analysed from pre-term pups (1-2 days prior to birth), and on Days 1-11 post-birth. The OIR model involved exposing pups to similar to 90% O-2 from D1-5, followed by return to ambient air. At sampling times pups were anaesthetised and perfused with india ink. Retinal flatmounts were also incubated with FITC-lectin (BS-1, G. simplicifolia,); this labels all vessels, allowing identification of vessels not patent to the perfusate. Results: Mean diameter of proximal hyaloid vessels in preterm pups was 25.44 +/- 1.98 mum; +/-1 SEM). Within 3-12 hrs of birth, significant vasoconstriction was evident (diameter:12.45 +/- 0.88 mum), and normal hyaloid regression subsequently occurred. Similar vasoconstriction occurred in the O-2-treated group, but this was reversed upon return to room air, with significant dilation of proximal vessels by D7 (diameter: 31.75 +/- 11.99 mum) and distal hyaloid vessels subsequently became enlarged and tortuous. Conclusions: Under normal conditions, vasoconstriction of proximal hyaloid vessels occurs at birth, preceding attenuation of distal hyaloid vessels. Vasoconstriction also occurs in O-2-treated pups during treatment, but upon return to room air, the remaining hyaloid vessels dilate proximally, and the distal vessels become dilated and tortuous. These observations support the contention that regression of the hyaloid network is dependent, in the first instance, on proximal arterial vasoconstriction.

Quantitative evaluation of altered hepatic spaces and membrane transport in fibrotic rat liver

Four animal models were used to quantitatively evaluate hepatic alterations in this study: (1) a carbon tetrachloride control group (phenobarbital treatment only), (2) a CCl4-treated group (phenobarbital with CCl4 treatment), (3) an alcohol-treated group (liquid diet with alcohol treatment), and (4) a pair-fed alcohol control group (liquid diet only). At the end of induction, single-pass perfused livers were used to conduct multiple indicator dilution (MID) studies. Hepatic spaces (vascular space, extravascular albumin space, extravascular sucrose space, and cellular distribution volume) and water hepatocyte permeability/surface area product were estimated from nonlinear regression of outflow concentration versus time profile data. The hepatic extraction ratio of H-3-taurocholate was determined by the nonparametric moments method. Livers were then dissected for histopathologic analyses (e.g., fibrosis index, number of fenestrae). In these 4 models, CCl4-treated rats were found to have the smallest vascular space, extravascular albumin space, H-3-taurocholate extraction, and water hepatocyte permeability/surface area product but the largest extravascular sucrose space and cellular distribution volume. In addition, a linear relationship was found to exist between histopathologic analyses (fibrosis index or number of fenestrae) and hepatic spaces. The hepatic extraction ratio of H-3-taurocholate and water hepatocyte permeability/surface area product also correlated to the severity of fibrosis as defined by the fibrosis index. In conclusion, the multiple indicator dilution data obtained from the in situ perfused rat liver can be directly related to histopathologic analyses.

Exploring complex fitness surfaces: Multiple ornamentation and polymorphism in male guppies

The sexual ornamentation used by male guppies to attract females comprises many components, each of which varies considerably among males. Although natural and sexual selection have been shown to contribute to divergence among populations in male sexual ornaments, the role of sexual selection in maintaining polymorphism within populations is less clear. We used both parametric quadratic regression and nonparametric projection pursuit regression techniques to reveal the major axes of non-linear sexual selection on male ornaments. We visualized the fitness surfaces defined by these axes using thin-plate splines to allow a direct comparison of the two methodologies. Identification of the major axes of selection and their visualization was critical in determining the form and strength of nonlinear selection. Both types of analysis revealed fitness surfaces comprising three peaks, suggesting that there is more than one way to make an attractive guppy. Disruptive selection may be an important process underlying the presence of multiple sexual ornaments and may contribute to the maintenance of the high levels of polymorphism in male sexual ornaments found in guppy populations.

An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

Survival analysis: a tool in the study of post-harvest diseases in peaches

Survival analysis is applied when the time until the occurrence of an event is of interest. Such data are routinely collected in plant diseases, although applications of the method are uncommon. The objective of this study was to use two studies on post-harvest diseases of peaches, considering two harvests together and the existence of random effect shared by fruits of a same tree, in order to describe the main techniques in survival analysis. The nonparametric Kaplan-Meier method, the log-rank test and the semi-parametric Cox's proportional hazards model were used to estimate the effect of cultivars and the number of days after full bloom on the survival to the brown rot symptom and the instantaneous risk of expressing it in two consecutive harvests. The joint analysis with baseline effect, varying between harvests, and the confirmation of the tree effect as a grouping factor with random effect were appropriate to interpret the phenomenon (disease) evaluated and can be important tools to replace or complement the conventional analysis, respecting the nature of the variable and the phenomenon.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Determinants of salivary cotinine level: a population-based study in Brazil

OBJECTIVE: A cross-sectional population-based study was conducted to assess, in active smokers, the relationship of number of cigarettes smoked and other characteristics to salivary cotinine concentrations. METHODS: A random sample of active smokers aged 15 years or older was selected using a stepwise cluster sample strategy, in the year 2000 in Rio de Janeiro, Brazil. The study included 401 subjects. Salivary cotinine concentration was determined using gas chromatography with nitrogen-phosphorus detection. A standard questionnaire was used to collect demographic and smoking behavioral data. The relation between the number of cigarettes smoked in the last 24h and cotinine level was examined by means of a nonparametric fitting technique of robust locally weighted regression. RESULTS: Significantly (p<0.05) higher adjusted mean cotinine levels were found in subjects smoking their first cigarette within five minutes after waking up, and in those smoking 1-20 cigarettes in the last 24h who reported inhaling more than ½ the time. In those smoking 1-20 cigarettes, the slope was significantly higher for those subjects waiting for more than five minutes before smoking their first cigarette after waking up, and those smoking "light" cigarettes when compared with their counterparts. These heterogeneities became negligible and non-significant when subjects with cotinine >40 ng/mL per cigarette were excluded. CONCLUSIONS: There was found a positive association between self-reporting smoking five minutes after waking up, and inhaling more than ½ the time are consistent and higher cotinine levels. These can be markers of dependence and higher nicotine intake. Salivary cotinine proved to be a useful biomarker of recent smoking and can be used in epidemiological studies and smoking cessation programs.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes

Amulti-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Predicting Xerostomia induced by IMRT treatments: A logistic regression approach

Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

Validação da antropometria e ultrassonografia do braço, para medição dos respectivos compartimentos, em lactentes nascidos pré-termo : contributo para a avaliação corporal do recem-nascido e do lactente

RESUMO: Contexto: Indicadores fidedignos da composição corporal são importantes na orientação das estratégias nutricionais de recém-nascidos e pequenos lactentes submetidos a cuidados intensivos. O braço é uma região acessível para avaliar a composição corporal regional, pela medida dos seus compartimentos. A antropometria e a ultrassonografia (US) são métodos não invasivos, relativamente económicos, que podem ser usados à cabeceira do paciente na medição desses compartimentos, embora esses métodos não tenham ainda sido validados neste subgrupo etário. A ressonância magnética (RM) pode ser usada como método de referência na validação da medição dos compartimentos do braço. Objectivo: Validar em lactentes pré-termo, as medidas do braço por antropometria e por US. Métodos: Foi estudada uma coorte de recém-nascidos admitidos consecutivamente na unidade de cuidados intensivos neonatais, com  33 semanas de idade de gestação e peso adequado para a mesma, sem anomalias congénitas major e não submetidas a diuréticos ou oxigenoterapia no momento da avaliação. Nas vésperas da alta, foram efectuadas medições do braço, com ocultação, pelos métodos antropométrico, ultrassonográfico e RM. As medidas antropométricas directas foram: peso (P), comprimento (C), perímetro cefálico (PC), perímetro braquial (PB) e prega cutânea tricipital (PT). As área braquial total, área muscular (AM) e área adiposa foram calculadas pelos métodos de Jeliffee & Jeliffee e de Rolland-Cachera. Utilizando uma sonda PSH-7DLT de 7 Hz no ecógrafo Toshiba SSH 140A foram medidos os perímetros braquial e muscular e calculadas automaticamente as áreas braquial e muscular, sendo a área adiposa obtida por subtracção. Como método de referência foi utilizada a RM – Philips Gyroscan ACS-NT, Power-Track 1000 ®, 1.5 Tesla com uma antena de quadratura do joelho. Na análise estatística foram utilizados os métodos paramétricos e não paramétricos, conforme adequado. Resultados: Foram incluídas 30 crianças, nascidas com ( ±DP) 30.7 ±1.9 semanas de gestação, pesando 1380 ±325g, as quais foram avaliadas às 35.4 ±1.1 semanas de idade corrigida, quando pesavam 1786 ±93g. Nenhuma das medidas antropométricas, individualmente, constitui um indicador aceitável (r2 <0.5) das medições por RM. A melhor e mais simples equação alternativa encontrada é a que estima a AM (r2 = 0.56), derivada dos resultados da análise de regressão múltipla: AMRM = (P x 0.17) + (PB x 5.2) – (C x 6) – 150, sendo o P expresso em g, o C e o PB em cm. Nenhuma das medidas ultrassonográficas constitui um indicador aceitável (r2 <0.4) das medições por RM. Conclusões: A antropometria e as medidas ultrassonográficas do braço não são indicadores fidedignos da composição corporal regional em lactentes pré-termo, adequados para a idade de gestação.----------ABSTRACT: Background: Accurate predictors for body composition are valuable tools guiding nutritional strategies in infants needing intensive care. The upper-arm is a part of the body that is easily accessible and convenient for assessing the regional body composition, throughout the assessment of their compartments. Anthropometry and by ultrasonography (US) are noninvasive and relatively nonexpensive methods for bedside assessment of the upper-arm compartments. However, these methods have not yet been validated in infants. Magnetic resonance imaging (MRI) may be used as gold standard to validate the measurements of the upper-arm compartments. Objective: To validate the upper-arm measurements by anthropometry and by US in preterm infants. Methods: A cohort of neonates consecutively admitted at the neonatal intensive care unit, appropriate for gestational age, with  33 weeks, without major congenital abnormalities and not subjected to diuretics or oxygen therapy, was assessed. Before the discharge, the upper-arm was blindly measured by anthropometry, US and MRI. The direct anthropometric parameters measured were: weight (W), length (L), head circumference (HC), mid-arm circumference (MAC), and tricipital skinfold thickness. The arm area (AA), arm muscle area (AMA) and arm fat area were calculated applying the methods proposed by Jeliffee & Jeliffee and by Rolland-Cachera. Using the sonolayer Toshiba SSH 140A and the probe PSH-7DLT 7Hz, the arm and muscle perimeters were measured by US, the arm and muscle areas included were automatically calculated, and the fat area was calculated by subtraction. The MR images were acquired on a 1.5-T Philips Gyroscan ACS-NT, Power-Track 1000 scanner, and a knee coil was chosen for the upper-arm measurements. For statistical analysis parametric and nonparametric methods were used as appropriate. Results: Thirty infants born with ( ±SD) 30.7 ±1.9 weeks of gestational age and weighing 1380 ±325g were included in the study; they were assessed at 35.4 ±1.1 weeks of corrected age, weighing 1786 ±93g. None of the anthropometric measurements are individually acceptable (r2 <0.5) for prediction of the measurements obtained by MRI. The best and simple alternative equation found is the equation for prediction of the AMA (r2 = 0.56), derived from the results of multiple regression analysis: AMARM = (W x 0.17) + (MAC x 5.2) – (L x 6) – 150, being the W expressed in g, and L and MAC in cm. None of the ultrasonographic measurements are acceptable (r2 <0.5) predictors for the measurements obtained by MRI. Conclusions: The measurements of the upper-arm by anthropometry and by US are not accurate predictors for the regional body composition in preterm appropriate for gestational age infants.

Double coverage and demand for health care: Evidence from quantile regression

An individual experiences double coverage when he bene ts from more than one health insurance plan at the same time. This paper examines the impact of such supplementary insurance on the demand for health care services. Its novelty is that within the context of count data modelling and without imposing restrictive parametric assumptions, the analysis is carried out for di¤erent points of the conditional distribution, not only for its mean location. Results indicate that moral hazard is present across the whole outcome distribution for both public and private second layers of health insurance coverage but with greater magnitude in the latter group. By looking at di¤erent points we unveil that stronger double coverage e¤ects are smaller for high levels of usage. We use data for Portugal, taking advantage of particular features of the public and private protection schemes on top of the statutory National Health Service. By exploring the last Portuguese Health Survey, we were able to evaluate their impacts on the consumption of doctor visi

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.