Enalapril treatment corrects the reduced response to bradykinin in diabetes increasing the B2 protein expression

Considering the growing importance of the interaction between components of kallikreinkinin and renin-angiotensin systems in physiological and pathological processes, particularly in diabetes mellitus, the aim of the present study was to investigate the effect of enalapril on the reduced response of bradykinin and on the interaction between angiotensin-(1-7) (Ang-(1-7)) and bradykinin (BK), important components of these systems, in an insulin-resistance model of diabetes. For the above purpose, the response of mesenteric arterioles of anesthetized neonatal streptozotocin-induced (n-STZ) diabetic and control rats was evaluated using intravital microscopy. In n-STZ diabetic rats, enalapril treatment restored the reduced response to BK but not the potentiation of BK by Ang-(1-7) present in non-diabetic rats. The restorative effect of enalapril was observed at a dose that did not correct the altered parameters induced by diabetes such as hyperglycernia, glicosuria, insulin resistance but did reduce the high blood pressure levels of n-SZT diabetic rats. There was no difference in mRNA and protein expressions of B1 and B2 kinin receptor subtypes between n-STZ diabetic and control rats. Enalapril treatment increased the B2 kinin receptor expression. From our data, we conclude that in diabetes enalapril corrects the impaired BK response probably by increasing the expression of B2 receptors. The lack of potentiation of BK by Ang-(1-7) is not corrected by this agent. (c) 2008 Elsevier Inc. All rights reserved.

The importance of hormone receptor analysis in osteosarcoma cells growth submitted to treatment with estrogen in association with thyroid hormone

Bone tumor incidence in women peaks at age 50-60, coinciding with the menopause. That estrogen (E2) and triiodothyronine (T3) interact in bone metabolism has been well established. However, few data on the action of these hormones are available. Our purpose was to determine the role of E2 and T3 in the expression of bone activity markers, namely alkaline phosphatase (AP) and receptor activator of nuclear factor kappa B ligand (RANKL). Two osteosarcoma cell lines: MG-63 (which has both estrogen (ER) and thyroid hormone (TR) receptors) and SaOs-29 (ER receptors only) were treated with infraphysiological E2 associated with T3 at infraphysiological, physiological, and supraphysiological concentrations. Real-time RT-PCR was used for expression analysis. Our results show that, in MG-63 cells, infraphysiological E2 associated with supraphysiological T3 increases AP expression and decreases RANKL expression, while infraphysiological E2 associated with either physiological or supraphysiological T3 decreases both AP and RANKL expression. On the other hand, in SaOs-2 cells, the same hormone combinations had no significant effect on the markers` expression. Thus, the analysis of hormone receptors was shown to be crucial for the assessment of tumor potential growth in the face of hormonal changes. Special care should be provided to patients with T3 and E2 hormone receptors that may increase tumor growth. Copyright (C) 2007 John Wiley & Sons, Ltd.

Perturbation treatment of symmetry breaking within random matrix theory

We discuss the applicability, within the random matrix theory, of perturbative treatment of symmetry breaking to the experimental data on the flip symmetry breaking in quartz crystal. We found that the values of the parameter that measures this breaking are different for the spacing distribution as compared to those for the spectral rigidity. We consider both two-fold and three-fold symmetries. The latter was found to account better for the spectral rigidity than the former. Both cases, however, underestimate the experimental spectral rigidity at large L. This discrepancy can be resolved if an appropriate number of eigenfrequencies is considered to be missing in the sample. Our findings are relevant for symmetry violation studies in general. (C) 2008 Elsevier B.V. All rights reserved.

Application of chemometric methods in the evaluation of chemical and spectroscopic data on organic matter from Oxisols in sewage sludge applications

Chemometric methods can contribute to soil research by permitting the extraction of more information from the data. The aim of this work was to use Principal Component Analysis to evaluate data obtained through chemical and spectroscopic methods on the changes in the humification process of soil organic matter from two tropical soils after sewage sludge application. In this case, humic acids extracted from Typic Eutrorthox and Typic Haplorthox soils with and without sewage sludge application for 7 consecutive years were studied. The results obtained for all of the samples and methods showed two clusters: samples extracted from the two soil types. These expected results indicated the textural difference between the two soils was more significant than the differences between treatments (control and sewage sludge application) or between depths. In this case, an individual chemometric treatment was made for each type of soil. It was noted that the characterization of the humic acids extracted from soils with and without sewage sludge application after 7 consecutive years using several methods supplies important results about changes in the humification degree of soil organic matter, These important result obtained by Principal Component Analysis justify further research using these methods to characterize the changes in the humic acids extracted from sewage sludge-amended soils. (C) 2009 Elsevier B.V. All rights reserved.

Clustering Lab value working with medical data

Data mining is a relatively new field of research that its objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available [27]. On the one hand, practitioners are expected to use all this data in their work but, at the same time, such a large amount of data cannot be processed by humans in a short time to make diagnosis, prognosis and treatment schedules. A major objective of this thesis is to evaluate data mining tools in medical and health care applications to develop a tool that can help make rather accurate decisions. In this thesis, the goal is finding a pattern among patients who got pneumonia by clustering of lab data values which have been recorded every day. By this pattern we can generalize it to the patients who did not have been diagnosed by this disease whose lab values shows the same trend as pneumonia patients does. There are 10 tables which have been extracted from a big data base of a hospital in Jena for my work .In ICU (intensive care unit), COPRA system which is a patient management system has been used. All the tables and data stored in German Language database.

A fuzzy rule-based decision support system for Duodopa treatment in Parkinson

A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

The program and treatment effect of summer jobs on girls’ post-schooling incomes

Public programs (of disputed effect) offering summer jobs or work while in high school to smooth the transition from school to work is commonplace. In this paper, 1447 girls in their first grade of high school between 1997-2003 and randomly allotted summer jobs via a program in Falun (Sweden) are followed 5-12 years after graduation. The program led to a substantially larger accumulation of income while in high school. The causal effect of the high school income on post-schooling incomes was substantial and statistically significant. The implied elasticity of 0.4 is however potentially inflated dueto heterogeneous effects.

Likelihood estimate of treatment effects under selection bias

We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

Conditional treatment and its effect on recidivism

The objective of this paper is to evaluate the effect of the 1985 ”Employment Services for Ex-Offenders” (ESEO) program on recidivism. Initially, the sample has been split randomly in a control group and a treatment group. However, the actual treatment (mainly being job related counseling) only takes place conditional on finding a job, and not having been arrested, for those selected in the treatment group. We use a multiple proportional hazard model with unobserved heterogeneity for job seach and recidivism time which incorporates the conditional treatment effect. We find that the program helps to reduce criminal activity, contrary to the result of the previous analysis of this data set. This finding is important for crime prevention policy.

Life expectancy and human capital investment: the arrival of AIDS treatment in Brazil

This paper provides microevidence on the relationship between life expectancy and educational investment decisions. Human capital theory predicts an increase in life expectancy should lead to an augmenting in schooling investment. This paper uses an unique data set on AIDS patients among Brazilian inhabitants in an attempt to estimate the impact of the arrival of Antiretroviral therapy (ART) on educational outcomes. The availability of ART offsets the negative relationship between vertical HIV-transmission and schooling, around 68% and 57% for elementary and high school completion, respectively. Robustness tests indicate the results are not driven by convergence effects.

Knowledge of the patients regarding leprosy and adherence to treatment

Leprosy is a chronic infectious disease caused by Mycobacterium leprae. It is known for its great disfiguring capacity and is considered an extremely serious disease to public health worldwide. The state of Ceará ranks 13th in number of cases of leprosy in Brazil, and fourth in Northeastern region, with an average of 2,149 new cases diagnosed every year. This study aimed to evaluate the knowledge of leprosy patients regarding treatment, and to assess the level of treatment adherence and its possible barriers. The study was conducted in the reference center for dermatology, from September 2010 to October 2010, in Fortaleza, Ceará. The study data were collected by means of a structured interview, along with the Morisky-Green test, in order to assess treatment adherence and barriers to adherence. A total of 70 patients were interviewed, out of whom 66 were new cases. The majority of patients were between 42 and 50 years old, and 37 (52.9%) were male. Most patients were clinically classified as presentingmultibacillary leprosy (80%), and 78.6% of them were from Fortaleza, Brazil. The Morisky-Green test indicated that 62.9% of patients presented a low level of adherence (p < 0.005), despite claiming to aware of the disease risks. However, it was observed that 57.1% of the patients had no difficulty adhering to treatment, while 38.6% reported little difficulty. This study shows that despite the patients claiming to be familiar with leprosy and its treatment, the Morisky-Green test clearly demonstrated that they actually were not aware of the principles of therapy, which is evidenced by the low degree of treatment adherence

Computational analysis and physico-chemical characterization of an inclusion compound between praziquantel and methyl-beta-cyclodextrin for use as an alternative in the treatment of schistosomiasis

Schistosomiasis is still an endemic disease in many regions, with 250 million people infected with Schistosoma and about 500,000 deaths per year. Praziquantel (PZQ) is the drug of choice for schistosomiasis treatment, however it is classified as Class II in the Biopharmaceutics Classification System, as its low solubility hinders its performance in biological systems. The use of cyclodextrins is a useful tool to increase the solubility and bioavailability of drugs. The aim of this work was to prepare an inclusion compound of PZQ and methyl-beta-cyclodextrin (MeCD), perform its physico-chemical characterization, and explore its in vitro cytotoxicity. SEM showed a change of the morphological characteristics of PZQ:MeCD crystals, and IR data supported this finding, with changes after interaction with MeCD including effects on the C-H of the aromatic ring, observed at 758 cm(-1). Differential scanning calorimetry measurements revealed that complexation occurred in a 1:1 molar ratio, as evidenced by the lack of a PZQ transition temperature after inclusion into the MeCD cavity. In solution, the PZQ UV spectrum profile in the presence of MeCD was comparable to the PZQ spectrum in a hydrophobic solvent. Phase solubility diagrams showed that there was a 5.5-fold increase in PZQ solubility, and were indicative of a type A(L) isotherm, that was used to determine an association constant (K(a)) of 140.8 M(-1). No cytotoxicity of the PZQ:MeCD inclusion compound was observed in tests using 3T3 cells. The results suggest that the association of PZQ with MeCD could be a good alternative for the treatment of schistosomiasis.

Intralesional polysulphated glycosaminoglycan as treatment of equine collagenase induced tendinitis: clinical, ultrasonographic and histopathologic evaluation

Estudou-se o efeito de aplicações intratendíneas do polissulfato de glicosaminoglicanas (PSGAG) no tratamento de tendinite induzida pela colagenase. Dois grupos (GI e GII) de cinco eqüinos da raça Puro-Sangue Árabe, machos e fêmeas, com idades entre dois e seis anos, foram submetidos à tendinite do tendão flexor digital superficial do membro torácico esquerdo por aplicação intratendínea de 1,0ml de colagenase (2,5mg/ml). Decorridos sete dias da indução da lesão, os eqüinos do GI receberam cinco aplicações intralesionais de 1,0ml (125mg) de PSGAG, a intervalos de quatro dias, enquanto que os do GII receberam aplicações de solução fisiológica em igual volume e freqüência. Efetuaram-se avaliações clínicas e ultra-sonográficas, periodicamente, durante 150 dias. Todos os animais apresentaram claudicação e aumento local de sensibilidade, de temperatura e de volume 24 horas após a indução da lesão. Com exceção do aumento de volume, que permaneceu visível até o final do experimento, observou-se regressão de todos os sinais em todos os animais. A avaliação ultra-sonográfica evidenciou lesões de tamanho, forma e posição variados, de maior severidade entre o sétimo e 23º dia. Ao término do experimento, o grau de ecogenicidade encontrava-se entre 1 e 2, e o grau de paralelismo entre 0 e 2. A análise histopatológica evidenciou áreas cicatriciais com intensa fibroplasia e neovascularização, fibras colágenas pouco organizadas e endotendão hipercelular e espessado. Não se observou diferenças significativas entre os grupos quanto ao processo de reparação das lesões, concluindo-se que a aplicação intralesional de PSGAG não produziu efeito benéfico para tratar tendinite induzida por colagenase.

Efficiency of a constructed wetland for wastewaters treatment

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)