Trigeminal pain and quantitative sensory testing in painful peripheral diabetic neuropathy

Objective: To evaluate patients with Diabetes Mellitus type 2 and painful peripheral neuropathy in order to investigate oral complaints and facial somatosensory findings. Research design and methods: Case-control study; 29 patients (12 women, mean age 57.86 yo) with Diabetes Mellitus type 2 and 31 age-gender-matched controls were evaluated with a standardized protocol for general characteristics, orofacial pain, research diagnostic criteria for temporomandibular disorders, visual analogue scale and McGill Pain questionnaire, and a systematic protocol of quantitative sensory testing for bilateral facial sensitivity at the areas innervated by the trigeminal branches, which included the thermal detection by ThermoSensi 2, tactile evaluation with vonFrey filaments, and superficial pain thresholds with a superficial algometer (Micromar). Statistical analysis was performed with Wilcoxon, chi-square, confidence intervals and Spearman (p < 0.05). Results: Orofacial pain was reported by 55.2% of patients, and the most common descriptor was fatigue (50%); 17.2% had burning mouth. Myofascial temporomandibular disorders were diagnosed in 9(31%) patients. The study group showed higher sensory thresholds of pain at the right maxillary branch (p = 0.017) but sensorial differences were not associated with pain (p = 0.608). Glycemia and HbA(1c) were positively correlated with the quantitative sensory testing results of pain (p < 0.05) and cold (p = 0.044) perceptions. Higher pain thresholds were correlated with higher glycemia and glycated hemoglobin (p = 0.027 and p = 0.026). Conclusions: There was a high prevalence of orofacial pain and burning mouth was the most common complaint. The association of loss of pain sensation and higher glycemia and glycated hemoglobin can be of clinical use for the follow-up of DM complications. (C) 2010 Elsevier Ltd. All rights reserved.

Three-dimensional model for multi-component reactive transport with variable density groundwater flow

PHWAT is a new model that couples a geochemical reaction model (PHREEQC-2) with a density-dependent groundwater flow and solute transport model (SEAWAT) using the split-operator approach. PHWAT was developed to simulate multi-component reactive transport in variable density groundwater flow. Fluid density in PHWAT depends not on only the concentration of a single species as in SEAWAT, but also the concentrations of other dissolved chemicals that can be subject to reactive processes. Simulation results of PHWAT and PHREEQC-2 were compared in their predictions of effluent concentration from a column experiment. Both models produced identical results, showing that PHWAT has correctly coupled the sub-packages. PHWAT was then applied to the simulation of a tank experiment in which seawater intrusion was accompanied by cation exchange. The density dependence of the intrusion and the snow-plough effect in the breakthrough curves were reflected in the model simulations, which were in good agreement with the measured breakthrough data. Comparison simulations that, in turn, excluded density effects and reactions allowed us to quantify the marked effect of ignoring these processes. Next, we explored numerical issues involved in the practical application of PHWAT using the example of a dense plume flowing into a tank containing fresh water. It was shown that PHWAT could model physically unstable flow and that numerical instabilities were suppressed. Physical instability developed in the model in accordance with the increase of the modified Rayleigh number for density-dependent flow, in agreement with previous research. (c) 2004 Elsevier Ltd. All rights reserved.

Evaluation of fly ash as a component of potting substrates

A series of laboratory and glasshouse experiments were undertaken to assess the potential for incorporation of fly ash in soilless potting substrates. The physical and chemical properties of a commercially available bark based substrate, the University of California (UC) 1:1 peat:sand mix and a range uf test substrates containing fly ash were characterised. In test mixtures, fly ash was substituted for a portion of either the peat or sand component of the UC mix, at rates of 10, 20, 30 and 50% of the mix volume, Incorporation of fly ash greatly increased the plant available water capacity (10-1500 kPa) of the substrate. However, high pH, increased substrate strength and reduced air-filled porosity were considered adverse effects, particularly at ash rates > 20%. The growth of tomato (Lycopersicon esculentum), petunia (Petunia x hybrida grandiflora) and Boston fern (Nephrolepis exaltata) in the substrates was assessed. Two watering regimes, capillary watering and irregular hosing, were used to identify effects of available water capacity on plant growth, but no effect was identified. Test mixtures containing fly ash as 20% of the substrate volume produced growth equal to that in the UC mix, with substrates containing 10% ash producing significantly greater growth of tomato and petunia. At rates of incorporation > 20% reduced plant growth was attributed to both adverse physical and chemical characteristics of the substrate. As fly ash is available at low cost and can be successfully substituted for a considerable portion of the expensive peat component, its use at low application rates in potting substrates may be desirable from an economic viewpoint.

A framework for specification-based testing

Test templates and a test template framework are introduced as useful concepts in specification-based testing. The framework can be defined using any model-based specification notation and used to derive tests from model-based specifications-in this paper, it is demonstrated using the Z notation. The framework formally defines test data sets and their relation to the operations in a specification and to other test data sets, providing structure to the testing process. Flexibility is preserved, so that many testing strategies can be used. Important application areas of the framework are discussed, including refinement of test data, regression testing, and test oracles.

Standard errors of fitted component means of normal mixtures

In this paper use consider the problem of providing standard errors of the component means in normal mixture models fitted to univariate or multivariate data by maximum likelihood via the EM algorithm. Two methods of estimation of the standard errors are considered: the standard information-based method and the computationally-intensive bootstrap method. They are compared empirically by their application to three real data sets and by a small-scale Monte Carlo experiment.

Laboratory wear testing of polyurethane elastomers

A dry sand-rubber wheel abrasion test was used to investigate the wear behaviour of polyurethanes. The dry sand-rubber wheel abrasion test (DSRW test) is an approved ASTM test designed primarily for testing metals, therefore, in this study the set of test conditions was optimized for use with polyurethane elastomers. The wear performance of polyurethanes was assessed for the range of Shore hardness 85A to 65D, and a correlation was identified between the wear rate and the sample hardness. Polyurethane elastomers can be separated into three classes according to their hardness and wear performance, and each class shows a different dependence on the specimen temperature. This work has implications for use of the DSRW test for the prediction of field performance of polyurethanes. (C) Elsevier Science S.A.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Testing market efficiency: Evidence from the NFL sports betting market

This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In-sample tests indicate that probit-based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out-of-sample testing, there is some inconsistency among the remaining out-of-sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.

Lymphocyte proliferation testing in chromium allergic contact dermatitis

Background. Lymphocyte proliferation testing (LPT) has some advantages over patch testing to diagnose allergic contact dermatitis. It is harmless, objective and can be used in clinical situations where patch testing is not recommended. Unfortunately, significant success has only been achieved with nickel. There are few studies on chromium LPT and they were performed with different methods, leading to inconsistent results. Methods. To determine the best parameters for chromium LPT, we tested 20 patients with allergic contact dermatitis to the metal and 20 controls, using various protocols. Results. The best sensitivity and specificity ratios were achieved with 6-day cultures stimulated with a range from 7.5 x 10(-4) to 5 x 10(-3) mol/L of nonfiltered chromium chloride solutions. The sensitivity, specificity and accuracy values found within this range were 65%, 95% and 80%, respectively. Conclusion. Further investigation is necessary to achieve better sensitivity values.

Acinar cell carcinoma of the pancreas: is the absence of neuroendocrine component related to a more malignant behavior?

Background/Aims: Acinar cell carcinomas are uncommon malignant tumors of the pancreas, accounting for 1-2% of all the cases of exocrine pancreatic tumor. Some authors have estimated acinar cell tumors to be as aggressive as ductal adenocarcinoma of the pancreas whereas other series showed acinar cell tumors to have a favorable clinical outcome. This discrepancy in prognosis may be related to the cellular components of the tumor. Methodology: With the aim to evaluate the possible relationship between the presence of neuroendocrine differentiation and behavior of these tumors, the authors reviewed all patients presenting acinar cell carcinoma of the pancreas in the last 5 years with emphasis in the immunohistochemical evaluation. Results: Four patients presented neuroendocrine differentiation on immunohistochemical evaluation and had a more benign outcome. Two patients without neuroendocrine component had a disseminated disease at presentation. This data suggests that this tumor is less aggressive than ductal adenocarcinoma and even with nodal involvement, long term survival after complete resection can be achieved. Conclusions: It is possible that the absence of neuroendocrine component may be related to a less favorable outcome and adjuvant therapy may be necessary. Due to the rarity of this pancreatic tumor, this relationship remains to be confirmed with a multicentric study including a larger number of patients.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Independent component analysis applied to raman spectra for classification of in vitro human coronary arteries

Optical diagnostic methods, such as near-infrared Raman spectroscopy allow quantification and evaluation of human affecting diseases, which could be useful in identifying and diagnosing atherosclerosis in coronary arteries. The goal of the present work is to apply Independent Component Analysis (ICA) for data reduction and feature extraction of Raman spectra and to perform the Mahalanobis distance for group classification according to histopathology, obtaining feasible diagnostic information to detect atheromatous plaque. An 830nm Ti:sapphire laser pumped by an argon laser provides near-infrared excitation. A spectrograph disperses light scattered from arterial tissues over a liquid-nitrogen cooled CCD to detect the Raman spectra. A total of 111 spectra from arterial fragments were utilized.

Application of Real-Time PCR Stool Assay for Helicobacter pylori Detection and Clarithromycin Susceptibility Testing in Brazilian Children

Background: Helicobacter pylori ClariRes assay is a novel commercially available real-time PCR assay allowing H. pylori detection and clarithromycin susceptibility testing in either gastric biopsy or stool specimens. Objective: The aim of this study was to validate the novel biprobe real-time assay in stool specimens from 217 dyspeptic children. Methods: DNA from gastric biopsies and stool specimens were obtained and submitted to the biprobe real time assay for H. pylori detection and clarithromycin susceptibility testing. Results: The sensitivity, specificity, and test accuracy were 69, 100 and 93.9% for the detection of H. pylori infection and 83.3, 100 and 95.6%, for detection of clarithromycin resistance. Conclusion: This assay proved to be appropriate for H. pylori clarithromycin susceptibility testing, particularly in children populations where a high prevalence of clarithromycin-resistant strains is suspected.

HER2 Testing in Breast Carcinoma Very Low Concordance Rate Between Reference and Local Laboratories in Brazil

Breast cancer accounts for approximately one quarter of all cancers in females. HER2 gene amplification or HER2 protein overexpression, detected in about 20% of breast carcinomas, predicts a more aggressive clinical course and determines eligibility for targeted therapy with trastuzumab. HER2 testing has become an essential part of the clinical evaluation of all breast carcinoma patients, and accurate HER2 results are critical in identifying patients who may be benefited from targeted therapy. This study investigated the concordance in the results of HER2 immunohistochemistry assays performed in 500 invasive breast carcinomas between a reference laboratory and 149 local laboratories from all geographic regions of Brazil. Our results showed an overall poor concordance (171 of 500 cases, 34.2%) regarding HER2 results between local and reference laboratories, which may be related to the low-volume load of HER2 assays, inexperience with HER2 scoring system, and/or technical issues related to immunohistochemistry in local laboratories. Standardization of HER2 testing with rigorous quality control measures by local laboratories is highly recommended to avoid erroneous treatment of breast cancer patients.

Integrating toxicity testing in the wastewater management of chemical storage terminals - A proposal based on a ten-year study

Wastewater control at storage terminals of liquid chemical products in bulk is very difficult because of the variety of products handled in the facilities generating effluents of variable composition. The main objective of this work was to verify if the Vibrio fischeri acute toxicity test could be routinely included in the wastewater management of those facilities along with physical and chemical analysis in order to evaluate and improve the quality of the generated effluents. The study was performed in two phases before and after the implementation of better operational practices/treatment technologies. Chemical oxygen demand (COD) and toxicity of treated effluents did not correlate showing that effluents with low COD contain toxic substances and non-biodegradable organic matter, which may be not degraded when discharged into the aquatic environment. Segregation of influents or pre-treatment based on toxicity results and biodegradability index were implemented in the facilities generating significant improvements in the quality of final effluents with reduction of Biochemical oxygen demand (BOD) and toxicity. The integration of physical and chemical analysis with the V.fischeri toxicity test turned out to be an excellent tool for wastewater management in chemical terminals allowing rapid decision making for pollution control and prevention measures. Reuse of rain water was also proposed and when implemented by the facilities resulted in economical and environmental benefits. (C) 2010 Elsevier B.V. All rights reserved.