Long-term treatment of familial male-limited precocious puberty (testotoxicosis) with cyproterone acetate or ketoconazole

Background Familial male-limited precocious puberty (FMPP) or testotoxicosis is a rare gonadotrophin-independent form of sexual precocity caused by constitutively activating mutations of the LH receptor. Several clinical therapeutic approaches have been reported for this disorder, but with a paucity of long-term outcome data. Objective To evaluate the long-term treatment of testotoxicosis with cyproterone acetate or ketoconazole. Design A multicentric retrospective clinical study. Patients Ten boys from eight unrelated Brazilian families who carried known LH-receptor activating mutations were treated with 70 mg/m(2) cyproterone acetate (n = 5) or 10 mg/kg ketoconazole (n = 5) for a mean period of 5 and 8 years, respectively. Measurements Chronological and bone ages, bone age/chronological age ratio, target height (TH) range, adult height, basal and GnRH-stimulated gonadotrophin levels and basal testosterone levels were assessed. Results Growth velocity decreased significantly during treatment with cyproterone acetate or ketoconazole when compared to pretreatment value in each group (P < 0.05). Bone age/chronological age ratio decreased significantly after cyproterone acetate or ketoconazole therapy. Basal testosterone levels were significantly lower in patients undergoing ketoconazole compared to cyproterone acetate treatment [0.6 +/- 0.3 nmol/l (42 +/- 21 ng/dl) vs. 5.6 +/- 4.0 nmol/l (392 +/- 280 ng/dl); P < 0.05], as expected. Secondary gonadotrophin-dependent precocious puberty occurred at a similar frequency (40%) in both groups. Five patients have attained adult height and two patients have already reached 90% of their adult height. Two of them achieved their TH range and one patient, for whom TH was not available, had an adult height of 0.3 SDS. Four boys (two in each group) did not attain their TH range. Conclusion Long-term treatment with cyproterone acetate or ketoconazole resulted in similar outcomes without important side-effects in boys with testotoxicosis. However, both therapies showed limited efficacy in attaining normal adult height.

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.

The calibre of the Foramen of Panizza in Crocodylus porosus is variable and under adrenergic control

The foramen of Panizza is located within the outflow tract of the crocodilian heart, between the left and right aortas. It has been suggested that the foremen of Panizza has a variable calibre, which could explain the profound changes in the distribution of flows and pressure profiles recorded in the right and left aortas. We investigated this possibility using a modified in-situ perfused heart preparation in combination with isolated strip preparations from the outflow tract. In the perfused heart preparation, bolus injections of adrenaline increased the resistance in the foramen of Panizza, indicating a decrease in its diameter. Isolated strip preparations from the outflow tract showed a concentration-dependent increase in tension in response to adrenaline, while vasoactive intestinal polypeptide caused a relaxation in adrenaline pre-contracted strip preparations. We propose that an increase in the diameter of the foremen of Panizza may be important during pulmonary to systemic shunts to allow blood to flow from the left to right aorta (reverse foramen flow) in order to supply the carotid and coronary arteries. During non-shunting conditions, a constricted foramen may prevent excess flow from the right to left aorta during diastole.

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).

Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.

Bias-dependent photocurrent collection in p-i-n a-Si : H/SiC : H heterojunction

A series of large area single layers and glass/ZnO:AVp(SixC1-x:H)/i(Si:H)/n(SixC1-x:H)/AI (0 < x < 1) heterojunction cells were produced by plasma-enhanced chemical vapour deposition (PE-CVD) at low temperature. Junction properties, carrier transport and photogeneration are investigated from dark and illuminated current-voltage (J-V) and capacitance-voltage (C-V) characteristics. For the heterojunction cells atypical J-V characteristics under different illumination conditions are observed leading to poor fill factors. High series resistances around 106 Q are also measured. These experimental results were used as a basis for the numerical simulation of the energy band diagram, and the electrical field distribution of the structures. Further comparison with the sensor performance gave satisfactory agreement. Results show that the conduction band offset is the most limiting parameter for the optimal collection of the photogenerated carriers. As the optical gap increases and the conductivity of the doped layers decreases, the transport mechanism changes from a drift to a diffusion-limited process.

Intra-hospital organ and tissue donation coordination project: cost-effectiveness and social benefits

OBJECTIVE To evaluate the viability of a professional specialist in intra-hospital committees of organ and tissue donation for transplantation. METHODS Epidemiological, retrospective and cross-sectional study (2003-2011 and 2008-2012), which was performed using organ donation for transplants data in the state of Sao Paulo, Southeastern Brazil. Nine hospitals were evaluated (hospitals 1 to 9). Logistic regression was used to evaluate the differences in the number of brain death referrals and actual donors (dependent variables) after the professional specialist started work (independent variable) at the intra-hospital committee of organ and tissue donation for transplantation. To evaluate the hospital invoicing, the hourly wage of the doctor and registered nurse, according to the legislation of the Consolidation of Labor Laws, were calculated, as were the investment return and the time elapsed to do so. RESULTS Following the nursing specialist commencement on the committee, brain death referrals and the number of actual donors increased at hospital 2 (4.17 and 1.52, respectively). At hospital 7, the number of actual donors also increased from 0.005 to 1.54. In addition, after the nurse started working, hospital revenues increased by 190.0% (ranging 40.0% to 1.955%). The monthly cost for the nurse working 20 hours was US$397.97 while the doctor would cost US$3,526.67. The return on investment was 275% over the short term (0.36 years). CONCLUSIONS This paper showed that including a professional specialist in intra-hospital committees for organ and tissue donation for transplantation proved to be cost-effective. Further economic research in the area could contribute to the efficient public policy implementation of this organ and tissue harvesting model.

Brownian bridge and other path-dependent Gaussian processes vectorial simulation

The iterative simulation of the Brownian bridge is well known. In this article, we present a vectorial simulation alternative based on Gaussian processes for machine learning regression that is suitable for interpreted programming languages implementations. We extend the vectorial simulation of path-dependent trajectories to other Gaussian processes, namely, sequences of Brownian bridges, geometric Brownian motion, fractional Brownian motion, and Ornstein-Ulenbeck mean reversion process.

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”

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

O financiamento por capitação ajustada pelo risco em contexto de integração vertical de cuidados de saúde : a utilização dos consumos com medicamentos como proxy da carga de doença em ambulatório

RESUMO - Introdução - Com o presente projecto de investigação pretendeu-se estudar o financiamento por capitação ajustado pelo risco em contexto de integração vertical de cuidados de saúde, recorrendo particularmente a informação sobre o consumo de medicamentos em ambulatório como proxy da carga de doença. No nosso país, factores como a expansão de estruturas de oferta verticalmente integradas, inadequação histórica da sua forma de pagamento e a recente possibilidade de dispor de informação sobre o consumo de medicamentos de ambulatório em bases de dados informatizadas são três fortes motivos para o desenvolvimento de conhecimento associado a esta temática. Metodologia - Este trabalho compreende duas fases principais: i) a adaptação e aplicação de um modelo de consumo de medicamentos que permite estimar a carga de doença em ambulatório (designado de PRx). Nesta fase foi necessário realizar um trabalho de selecção, estruturação e classificação do modelo. A sua aplicação envolveu a utilização de bases de dados informatizadas de consumos com medicamentos nos anos de 2007 e 2008 para a região de Saúde do Alentejo; ii) na segunda fase foram simulados três modelos de financiamento alternativos que foram propostos para financiar as ULS em Portugal. Particularmente foram analisadas as dimensões e variáveis de ajustamento pelo risco (índices de mortalidade, morbilidade e custos per capita), sua ponderação relativa e consequente impacto financeiro. Resultados - Com o desenvolvimento do modelo PRx estima-se que 36% dos residentes na região Alentejo têm pelo menos uma doença crónica, sendo a capacidade de estimação do modelo no que respeita aos consumos de medicamentos na ordem dos 0,45 (R2). Este modelo revelou constituir uma alternativa a fontes de informação tradicionais como são os casos de outros estudos internacionais ou o Inquérito Nacional de Saúde. A consideração dos valores do PRx para efeitos de financiamento per capita introduz alterações face a outros modelos propostos neste âmbito. Após a análise dos montantes de financiamento entre os cenários alternativos, obtendo os modelos 1 e 2 níveis de concordância por percentil mais próximos entre si comparativamente ao modelo 3, seleccionou-se o modelo 1 como o mais adequado para a nossa realidade. Conclusão - A aplicação do modelo PRx numa região de saúde permitiu concluir em função dos resultados alcançados, que já existe a possibilidade de estruturação e operacionalização de um modelo que permite estimar a carga de doença em ambulatório a partir de informação relativa ao seu perfil de consumo de medicamentos dos utentes. A utilização desta informação para efeitos de financiamento de organizações de saúde verticalmente integradas provoca uma variação no seu actual nível de financiamento. Entendendo este estudo como um ponto de partida onde apenas uma parte da presente temática ficará definida, outras questões estruturantes do actual sistema de financiamento não deverão também ser olvidadas neste contexto. ------- ABSTRACT - Introduction - The main goal of this study was the development of a risk adjustment model for financing integrated delivery systems (IDS) in Portugal. The recent improvement of patient records, mainly at primary care level, the historical inadequacy of payment models and the increasing number of IDS were three important factors that drove us to develop new approaches for risk adjustment in our country. Methods - The work was divided in two steps: the development of a pharmacy-based model in Portugal and the proposal of a risk adjustment model for financing IDS. In the first step an expert panel was specially formed to classify more than 33.000 codes included in Portuguese pharmacy national codes into 33 chronic conditions. The study included population of Alentejo Region in Portugal (N=441.550 patients) during 2007 and 2008. Using pharmacy data extracted from three databases: prescription, private pharmacies and hospital ambulatory pharmacies we estimated a regression model including Potential Years of Life Lost, Complexity, Severity and PRx information as dependent variables to assess total cost as the independent variable. This healthcare financing model was compared with other two models proposed for IDS. Results - The more prevalent chronic conditions are cardiovascular (34%), psychiatric disorders (10%) and diabetes (10%). These results are also consistent with the National Health Survey. Apparently the model presents some limitations in identifying patients with rheumatic conditions, since it underestimates prevalence and future drug expenditure. We obtained a R2 value of 0,45, which constitutes a good value comparing with the state of the art. After testing three scenarios we propose a model for financing IDS in Portugal. Conclusion - Drug information is a good alternative to diagnosis in determining morbidity level in a population basis through ambulatory care data. This model offers potential benefits to estimate chronic conditions and future drug costs in the Portuguese healthcare system. This information could be important to resource allocation decision process, especially concerning risk adjustment and healthcare financing.

Prognostic Value of a New Cardiopulmonary Exercise Testing Parameter in Chronic Heart Failure: Oxygen Uptake Efficiency at Peak Exercise - Comparison with Oxygen Uptake Efficiency Slope

INTRODUCTION: A growing body of evidence shows the prognostic value of oxygen uptake efficiency slope (OUES), a cardiopulmonary exercise test (CPET) parameter derived from the logarithmic relationship between O(2) consumption (VO(2)) and minute ventilation (VE) in patients with chronic heart failure (CHF). OBJECTIVE: To evaluate the prognostic value of a new CPET parameter - peak oxygen uptake efficiency (POUE) - and to compare it with OUES in patients with CHF. METHODS: We prospectively studied 206 consecutive patients with stable CHF due to dilated cardiomyopathy - 153 male, aged 53.3±13.0 years, 35.4% of ischemic etiology, left ventricular ejection fraction 27.7±8.0%, 81.1% in sinus rhythm, 97.1% receiving ACE-Is or ARBs, 78.2% beta-blockers and 60.2% spironolactone - who performed a first maximal symptom-limited treadmill CPET, using the modified Bruce protocol. In 33% of patients an cardioverter-defibrillator (ICD) or cardiac resynchronization therapy device (CRT-D) was implanted during follow-up. Peak VO(2), percentage of predicted peak VO(2), VE/VCO(2) slope, OUES and POUE were analyzed. OUES was calculated using the formula VO(2) (l/min) = OUES (log(10)VE) + b. POUE was calculated as pVO(2) (l/min) / log(10)peakVE (l/min). Correlation coefficients between the studied parameters were obtained. The prognosis of each variable adjusted for age was evaluated through Cox proportional hazard models and R2 percent (R2%) and V index (V6) were used as measures of the predictive accuracy of events of each of these variables. Receiver operating characteristic (ROC) curves from logistic regression models were used to determine the cut-offs for OUES and POUE. RESULTS: pVO(2): 20.5±5.9; percentage of predicted peak VO(2): 68.6±18.2; VE/VCO(2) slope: 30.6±8.3; OUES: 1.85±0.61; POUE: 0.88±0.27. During a mean follow-up of 33.1±14.8 months, 45 (21.8%) patients died, 10 (4.9%) underwent urgent heart transplantation and in three patients (1.5%) a left ventricular assist device was implanted. All variables proved to be independent predictors of this combined event; however, VE/VCO2 slope was most strongly associated with events (HR 11.14). In this population, POUE was associated with a higher risk of events than OUES (HR 9.61 vs. 7.01), and was also a better predictor of events (R2: 28.91 vs. 22.37). CONCLUSION: POUE was more strongly associated with death, urgent heart transplantation and implantation of a left ventricular assist device and proved to be a better predictor of events than OUES. These results suggest that this new parameter can increase the prognostic value of CPET in patients with CHF.

Activity-Dependent Neurorehabilitation Beyond Physical Trainings: "Mental Exercise" Through Mirror Neuron Activation

The activity dependent brain repair mechanism has been widely adopted in many types of neurorehabilitation. The activity leads to target specific and non-specific beneficial effects in different brain regions, such as the releasing of neurotrophic factors, modulation of the cytokines and generation of new neurons in adult hood. However physical exercise program clinically are limited to some of the patients with preserved motor functions; while many patients suffered from paralysis cannot make such efforts. Here the authors proposed the employment of mirror neurons system in promoting brain rehabilitation by "observation based stimulation". Mirror neuron system has been considered as an important basis for action understanding and learning by mimicking others. During the action observation, mirror neuron system mediated the direct activation of the same group of motor neurons that are responsible for the observed action. The effect is clear, direct, specific and evolutionarily conserved. Moreover, recent evidences hinted for the beneficial effects on stroke patients after mirror neuron system activation therapy. Finally some music-relevant therapies were proposed to be related with mirror neuron system.

Information flow analysis using data-dependent logical propositions

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Development of a satellite based PM10 concentration product for urban areas

Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente