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.

Model specification tests in nonparametric stochastic regression models

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example. (C) 2002 Elsevier Science (USA).

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.

Análise do risco de insolvência pelo modelo de cox: uma aplicação prática

A previsão de insolvência é um fator importante para o sistema bancário e, por esse motivo, vem sendo estudada por vários autores. Com o intuito de corroborar esses estudos, este trabalho avaliou a situação financeira das cooperativas de crédito rural do Estado de Minas Gerais entre 1998 e 2001, buscando verificar se as mudanças que afetaram o sistema bancário após o Plano Real também atingiram as cooperativas analisadas. Para avaliar o risco de insolvência, utilizou-se o modelo de risco proporcional de Cox (Cox, 1972). Empregou-se o conceito de insolvência como o de encerramento da cooperativa, patrimônio líquido negativo e/ou 40% de resultados finais negativos. Como resultado, verificou-se que, nas cooperativas analisadas, os indicadores importantes para avaliar o risco relativo de insolvência foram os índices de "liquidez geral", "encaixe" e "despesa com pessoal". Apenas 1 cooperativa, entre as 107 pesquisadas, encontrava-se na faixa de risco de insolvência determinada pelo modelo.

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.

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.

Síntese de uma biblioteca de derivados de indole com potencial actividade antioxidante e inibição selectiva da COX‐2

Os compostos indólicos constituem uma extensa e larga família de compostos presentes em bactérias, plantas e animais, sendo alvo de especial interesse nas áreas tanto da química biológica como na da química medicinal. O triptofano, aminoácido essencial para o Homem, constitui um importante exemplo de derivados de indole. Outros exemplos, derivados desta importante estrutura, são o ácido indole‐3‐acético (hormona presente nas plantas) e a melatonina (hormona segregada pela glândula pineal). Uma importante característica dos compostos derivados do indole é que estes podem ser úteis como fármacos usados no tratamento da inflamação (por exemplo,indometacina, acemetacina, etodolac), assim como no tratamento de doenças associadas ao stress oxidativo, como o cancro e doenças neurodegenerativas. Com o intuito de estudar a relação estrutura‐actividade sintetizou‐se uma biblioteca de derivados de indole e, posteriormente, avaliou‐se a actividade antioxidante dos compostos preparados usando como espécie reactiva de oxigénio o radical peroxilo. Todos os compostos testados, à excepção de um, revelaram actividade. Os resultados obtidos contribuirão para o design racional de futuras gerações de bibliotecas. Foram, ainda, desenvolvidos estudos sintéticos para a preparação de um potencial inibidor selectivo da COX‐2.

Impact of long-stay beds on the performance of a tertiary hospital in emergencies

ABSTRACT OBJECTIVE To assess the impact of implementing long-stay beds for patients of low complexity and high dependency in small hospitals on the performance of an emergency referral tertiary hospital. METHODS For this longitudinal study, we identified hospitals in three municipalities of a regional department of health covered by tertiary care that supplied 10 long-stay beds each. Patients were transferred to hospitals in those municipalities based on a specific protocol. The outcome of transferred patients was obtained by daily monitoring. Confounding factors were adjusted by Cox logistic and semiparametric regression. RESULTS Between September 1, 2013 and September 30, 2014, 97 patients were transferred, 72.1% male, with a mean age of 60.5 years (SD = 1.9), for which 108 transfers were performed. Of these patients, 41.7% died, 33.3% were discharged, 15.7% returned to tertiary care, and only 9.3% tertiary remained hospitalized until the end of the analysis period. We estimated the Charlson comorbidity index – 0 (n = 28 [25.9%]), 1 (n = 31 [56.5%]) and ≥ 2 (n = 19 [17.5%]) – the only variable that increased the chance of death or return to the tertiary hospital (Odds Ratio = 2.4; 95%CI 1.3;4.4). The length of stay in long-stay beds was 4,253 patient days, which would represent 607 patients at the tertiary hospital, considering the average hospital stay of seven days. The tertiary hospital increased the number of patients treated in 50.0% for Intensive Care, 66.0% for Neurology and 9.3% in total. Patients stayed in long-stay beds mainly in the first 30 (50.0%) and 60 (75.0%) days. CONCLUSIONS Implementing long-stay beds increased the number of patients treated in tertiary care, both in general and in system bottleneck areas such as Neurology and Intensive Care. The Charlson index of comorbidity is associated with the chance of patient death or return to tertiary care, even when adjusted for possible confounding factors.

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”

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

Morbidity and survival in advanced AIDS in Rio de Janeiro, Brazil

Opportunistic diseases (OD) are the most common cause of death in AIDS patients. To access the incidence of OD and survival in advanced immunodeficiency, we included 79 patients with AIDS treated at Hospital Evandro Chagas (FIOCRUZ) from September 1997 to December 1999 with at least one CD4 count <=100 cells/mm³. The incidence of OD was analyzed by Poisson's regression, and survival by Kaplan Meier and Cox analysis, considering a retrospective (before CD4 <=100 cells/mm³) and a prospective (after CD4 <=100 cells/mm³) period, and controlling for demographic, clinical and laboratory characteristics. The confidence interval estipulated was 95%. Mean follow-up period was 733 days (CI = 683-782). During the study 9 (11.4%) patients died. Survival from AIDS diagnosis was a mean of 2589 days (CI = 2363-2816) and from the date of the CD4 count CD4 <=100 cells/mm³ was a mean of 1376 (CI = 1181-1572) days. Incidence of OD was 0.51 pp/y before CD4 <= 100 cells/mm³ and 0.29 pp/y after CD4 <= 100 cells/mm³. A lower number of ODs before CD4 < 100 cells/mm³ was associated with lower incidence rates after CD4 <= 100 cells/mm³. AIDS diagnosis based on CD4+ counts <= 200 cells/mm³ was associated with lower incidence rates after CD4 <= 100 cells/mm³. Baseline CD4 counts above 50 cells/mm³ (HR = 0.13) and restoration of baseline CD4+ counts above 100 cells/mm³ (HR = 0.16) were associated with a lower risk of death. Controling both variables, only restoration of baseline counts was statistically significant (HR = 0.22, p = 0.04). We found a very low incidence of OD and long survival after CD4 < 100 cells/mm³. Survival was significantly associated with restoration of baseline CD4 counts above 100 cells/mm³.