Synthetic calibrators for the analysis of total metanephrines in urine: revisiting the conditions of hydrolysis.

BACKGROUND: The quantification of total (free+sulfated) metanephrines in urine is recommended to diagnose pheochromocytoma. Urinary metanephrines include metanephrine itself, normetanephrine and methoxytyramine, mainly in the form of sulfate conjugates (60-80%). Their determination requires the hydrolysis of the sulfate ester moiety to allow electrochemical oxidation of the phenolic group. Commercially available urine calibrators and controls contain essentially free, unhydrolysable metanephrines which are not representative of native urines. The lack of appropriate calibrators may lead to uncertainty regarding the completion of the hydrolysis of sulfated metanephrines, resulting in incorrect quantification. METHODS: We used chemically synthesized sulfated metanephrines to establish whether the procedure most frequently recommended for commercial kits (pH 1.0 for 30 min over a boiling water bath) ensures their complete hydrolysis. RESULTS: We found that sulfated metanephrines differ in their optimum pH to obtain complete hydrolysis. Highest yields and minimal variance were established for incubation at pH 0.7-0.9 during 20 min. CONCLUSION: Urinary pH should be carefully controlled to ensure an efficient and reproducible hydrolysis of sulfated metanephrines. Synthetic sulfated metanephrines represent the optimal material for calibrators and proficiency testing to improve inter-laboratory accuracy.

Quantitative Ultrasound of the Heel and Fracture Risk Assessment: an Updated Meta-Analysis

Objectives: Quantitative ultrasound (QUS) is an attractive method for assessing fracture risk because it is portable, inexpensive, without ionizing radiation, and available in areas of the world where DXA is not readily accessible or affordable. However, the diversity of QUS scanners and variability of fracture outcomes measured in different studies is an important obstacle to widespread utilisation of QUS for fracture risk assessment. We aimed in this review to assess the predictive power of heel QUS for fractures considering different characteristics of the association (QUS parameters and fracture outcomes measured, QUS devices, study populations, and independence from DXA-measured bone density).Materials/Methods : We conducted an inverse-variance randomeffects meta-analysis of prospective studies with heel QUS measures at baseline and fracture outcomes in their follow-up. Relative risks (RR) per standard deviation (SD) of different QUS parameters (broadband ultrasound attenuation [BUA], speed of sound &SOS;, stiffness index &SI;, and quantitative ultrasound index [QUI]) for various fracture outcomes (hip, vertebral, any clinical, any osteoporotic, and major osteoporotic fractures) were reported based on study questions.Results : 21 studies including 55,164 women and 13,742 men were included with a total follow-up of 279,124 person-years. All four QUS parameters were associated with risk of different fractures. For instance, RR of hip fracture for 1 SD decrease of BUA was 1.69 (95% CI 1.43-2.00), SOS was 1.96 (95% CI 1.64-2.34), SI was 2.26 (95%CI 1.71-2.99), and QUI was 1.99 (95% CI 1.49-2.67). Validated devices from different manufacturers predicted fracture risks with a similar performance (meta-regression p-values>0.05 for difference of devices). There was no sign of publication bias among the studies. QUS measures predicted fracture with a similar performance in men and women. Meta-analysis of studies with QUS measures adjusted for hip DXA showed a significant and independent association with fracture risk (RR/SD for BUA =1.34 [95%CI 1.22-1.49]).Conclusions : This study confirms that QUS of the heel using validated devices predicts risk of different fracture outcomes in elderly men and women. Further research and international collaborations are needed for standardisation of QUS parameters across various manufacturers and inclusion of QUS in fracture risk assessment tools. Disclosure of Interest : None declared.

Problems of allometric scaling analysis: examples from mammalian reproductive biology.

Biological scaling analyses employing the widely used bivariate allometric model are beset by at least four interacting problems: (1) choice of an appropriate best-fit line with due attention to the influence of outliers; (2) objective recognition of divergent subsets in the data (allometric grades); (3) potential restrictions on statistical independence resulting from phylogenetic inertia; and (4) the need for extreme caution in inferring causation from correlation. A new non-parametric line-fitting technique has been developed that eliminates requirements for normality of distribution, greatly reduces the influence of outliers and permits objective recognition of grade shifts in substantial datasets. This technique is applied in scaling analyses of mammalian gestation periods and of neonatal body mass in primates. These analyses feed into a re-examination, conducted with partial correlation analysis, of the maternal energy hypothesis relating to mammalian brain evolution, which suggests links between body size and brain size in neonates and adults, gestation period and basal metabolic rate. Much has been made of the potential problem of phylogenetic inertia as a confounding factor in scaling analyses. However, this problem may be less severe than suspected earlier because nested analyses of variance conducted on residual variation (rather than on raw values) reveals that there is considerable variance at low taxonomic levels. In fact, limited divergence in body size between closely related species is one of the prime examples of phylogenetic inertia. One common approach to eliminating perceived problems of phylogenetic inertia in allometric analyses has been calculation of 'independent contrast values'. It is demonstrated that the reasoning behind this approach is flawed in several ways. Calculation of contrast values for closely related species of similar body size is, in fact, highly questionable, particularly when there are major deviations from the best-fit line for the scaling relationship under scrutiny.

Principal components analysis for quality evaluation of cooled banana 'Nanicão' in different packing

This work aims determinate the evaluation of the quality of 'Nanicão' banana, submitted to two conditions of storage temperature and three different kinds of package, using the technique of the Analysis of Principal Components (ACP), as a basis for an Analysis of Variance. The fruits used were 'Nanicão' bananas, at ripening degree 3, that is, more green than yellow. The packages tested were: "Torito" wood boxes, load capacity: 18 kg; "½ box" wood boxes, load capacity: 13 kg; and cardboard boxes, load capacity: 18 kg. The temperatures assessed were: room temperature (control); and (13±1ºC), with humidity controlled to 90±2,5%. Fruits were discarded when a sensory analysis determined they had become unfit for consumption. Peel coloration, percentages of imperfection, fresh mass, total acidity, pH, total soluble solids and percentages of sucrose were assessed. A completely randomized design with a 2-factorial treatment structure (packing X temperature) was used. The obtained data were analyzed through a multivariate analysis known as Principal Components Analysis, using S-plus 4.2. The conclusion was that the best packages to preserve the fruit were the ½ box ones, which proves that it is necessary to reduce the number of fruits per package to allow better ventilation and decreases mechanical injuries and ensure quality for more time.

Bond strength tests of dental adhesive systems and their correlation with clinical results : a meta-analysis

OBJECTIVE: To evaluate the variability of bond strength test results of adhesive systems (AS) and to correlate the results with clinical parameters of clinical studies investigating cervical restorations. MATERIALS AND METHODS: Regarding the clinical studies, the internal database which had previously been used for a meta-analysis on cervical restorations was updated with clinical studies published between 2008 and 2012 by searching the PubMed and SCOPUS databases. PubMed and the International Association for Dental Research abstracts online were searched for laboratory studies on microtensile, macrotensile and macroshear bond strength tests. The inclusion criteria were (1) dentin, (2) testing of at least four adhesive systems, (3) same diameter of composite and (4) 24h of water storage prior to testing. The clinical outcome variables were retention loss, marginal discoloration, detectable margins, and a clinical index comprising the three parameters by weighing them. Linear mixed models which included a random study effect were calculated for both, the laboratory and the clinical studies. The variability was assessed by calculating a ratio of variances, dividing the variance among the estimated bonding effects obtained in the linear mixed models by the sum of all variance components estimated in these models. RESULTS: Thirty-two laboratory studies fulfilled the inclusion criteria comprising 183 experiments. Of those, 86 used the microtensile test evaluating 22 adhesive systems (AS). Twenty-seven used the macrotensile test with 17 AS, and 70 used the macroshear test with 24 AS. For 28 AS the results from clinical studies were available. Microtensile and macrotensile (Spearman rho=0.66, p=0.007) were moderately correlated and also microtensile and macroshear (Spearman rho=0.51, p=0.03) but not macroshear and macrotensile (Spearman rho=0.34, p=0.22). The effect of the adhesive system was significant for microtensile and macroshear (p<0.001) but not for macrotensile. The effect of the adhesive system could explain 36% of the variability of the microtensile test, 27% of the macrotensile and 33% of the macroshear test. For the clinical trials, about 49% of the variability of retained restorations could be explained by the adhesive system. With respect to the correlation between bond strength tests and clinical parameters, only a moderate correlation between micro- and macrotensile test results and marginal discoloration was demonstrated. However, no correlation between these tests and a retention loss or marginal integrity was shown. The correlation improved when more studies were included compared to assessing only one study. SIGNIFICANCE: The high variability of bond strength test results highlights the need to establish individual acceptance levels for a given test institute. The weak correlation of bond-strength test results with clinical parameters leads to the conclusion that one should not rely solely on bond strength tests to predict the clinical performance of an adhesive system but one should conduct other laboratory tests like tests on the marginal adaptation of fillings in extracted teeth and the retention loss of restorations in non-retentive cavities after artificial aging.

Analysis of vineyard differential management zones and relation to vine development, grape maturity and quality

The objective of research was to analyse the potential of Normalized Difference Vegetation Index (NDVI) maps from satellite images, yield maps and grapevine fertility and load variables to delineate zones with different wine grape properties for selective harvesting. Two vineyard blocks located in NE Spain (Cabernet Sauvignon and Syrah) were analysed. The NDVI was computed from a Quickbird-2 multi-spectral image at veraison (July 2005). Yield data was acquired by means of a yield monitor during September 2005. Other variables, such as the number of buds, number of shoots, number of wine grape clusters and weight of 100 berries were sampled in a 10 rows × 5 vines pattern and used as input variables, in combination with the NDVI, to define the clusters as alternative to yield maps. Two days prior to the harvesting, grape samples were taken. The analysed variables were probable alcoholic degree, pH of the juice, total acidity, total phenolics, colour, anthocyanins and tannins. The input variables, alone or in combination, were clustered (2 and 3 Clusters) by using the ISODATA algorithm, and an analysis of variance and a multiple rang test were performed. The results show that the zones derived from the NDVI maps are more effective to differentiate grape maturity and quality variables than the zones derived from the yield maps. The inclusion of other grapevine fertility and load variables did not improve the results.

Reconstruction and analysis of surface variation using photometric stereo

In many industrial applications, accurate and fast surface reconstruction is essential for quality control. Variation in surface finishing parameters, such as surface roughness, can reflect defects in a manufacturing process, non-optimal product operational efficiency, and reduced life expectancy of the product. This thesis considers reconstruction and analysis of high-frequency variation, that is roughness, on planar surfaces. Standard roughness measures in industry are calculated from surface topography. A fast and non-contact method to obtain surface topography is to apply photometric stereo in the estimation of surface gradients and to reconstruct the surface by integrating the gradient fields. Alternatively, visual methods, such as statistical measures, fractal dimension and distance transforms, can be used to characterize surface roughness directly from gray-scale images. In this thesis, the accuracy of distance transforms, statistical measures, and fractal dimension are evaluated in the estimation of surface roughness from gray-scale images and topographies. The results are contrasted to standard industry roughness measures. In distance transforms, the key idea is that distance values calculated along a highly varying surface are greater than distances calculated along a smoother surface. Statistical measures and fractal dimension are common surface roughness measures. In the experiments, skewness and variance of brightness distribution, fractal dimension, and distance transforms exhibited strong linear correlations to standard industry roughness measures. One of the key strengths of photometric stereo method is the acquisition of higher frequency variation of surfaces. In this thesis, the reconstruction of planar high-frequency varying surfaces is studied in the presence of imaging noise and blur. Two Wiener filterbased methods are proposed of which one is optimal in the sense of surface power spectral density given the spectral properties of the imaging noise and blur. Experiments show that the proposed methods preserve the inherent high-frequency variation in the reconstructed surfaces, whereas traditional reconstruction methods typically handle incorrect measurements by smoothing, which dampens the high-frequency variation.

Calculation of the variance in surveys of the economic climate

Public opinion surveys have become progressively incorporated into systems of official statistics. Surveys of the economic climate are usually qualitative because they collect opinions of businesspeople and/or experts about the long-term indicators described by a number of variables. In such cases the responses are expressed in ordinal numbers, that is, the respondents verbally report, for example, whether during a given trimester the sales or the new orders have increased, decreased or remained the same as in the previous trimester. These data allow to calculate the percent of respondents in the total population (results are extrapolated), who select every one of the three options. Data are often presented in the form of an index calculated as the difference between the percent of those who claim that a given variable has improved in value and of those who claim that it has deteriorated.

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Integrated multivariate analysis to evaluate effects of pre-slaughter handling on pork quality

The aim of this study was to investigate the effect of pre-slaughter handling on the occurrence of PSE (Pale, Soft, and Exudative) meat in swine slaughtered at a commercial slaughterhouse located in the metropolitan region of Dourados, Mato Grosso do Sul, Brazil. Based on the database (n=1,832 carcasses), it was possible to apply the integrated multivariate analysis for the purpose of identifying, among the selected variables, those of greatest relevance to this study. Results of the Principal Component Analysis showed that the first five components explained 89.28% of total variance. In the Factor Analysis, the first factor represented the thermal stress and fatiguing conditions for swine during pre-slaughter handling. In general, this study indicated the importance of the pre-slaughter handling stages, evidencing those of greatest stress and threat to animal welfare and pork quality, which are transport time, resting period, lairage time before unloading, unloading time, and ambience.

Critical analysis of autoregressive and fast Fourier transform markers of cardiovascular variability in rats and humans

The autonomic nervous system plays an important role in physiological and pathological conditions, and has been extensively evaluated by parametric and non-parametric spectral analysis. To compare the results obtained with fast Fourier transform (FFT) and the autoregressive (AR) method, we performed a comprehensive comparative study using data from humans and rats during pharmacological blockade (in rats), a postural test (in humans), and in the hypertensive state (in both humans and rats). Although postural hypotension in humans induced an increase in normalized low-frequency (LFnu) of systolic blood pressure, the increase in the ratio was detected only by AR. In rats, AR and FFT analysis did not agree for LFnu and high frequency (HFnu) under basal conditions and after vagal blockade. The increase in the LF/HF ratio of the pulse interval, induced by methylatropine, was detected only by FFT. In hypertensive patients, changes in LF and HF for systolic blood pressure were observed only by AR; FFT was able to detect the reduction in both blood pressure variance and total power. In hypertensive rats, AR presented different values of variance and total power for systolic blood pressure. Moreover, AR and FFT presented discordant results for LF, LFnu, HF, LF/HF ratio, and total power for pulse interval. We provide evidence for disagreement in 23% of the indices of blood pressure and heart rate variability in humans and 67% discordance in rats when these variables are evaluated by AR and FFT under physiological and pathological conditions. The overall disagreement between AR and FFT in this study was 43%.

Estimation procedures affect the center of pressure frequency analysis

Even though frequency analysis of body sway is widely applied in clinical studies, the lack of standardized procedures concerning power spectrum estimation may provide unreliable descriptors. Stabilometric tests were applied to 35 subjects (20-51 years, 54-95 kg, 1.6-1.9 m) and the power spectral density function was estimated for the anterior-posterior center of pressure time series. The median frequency was compared between power spectra estimated according to signal partitioning, sampling rate, test duration, and detrending methods. The median frequency reliability for different test durations was assessed using the intraclass correlation coefficient. When increasing number of segments, shortening test duration or applying linear detrending, the median frequency values increased significantly up to 137%. Even the shortest test duration provided reliable estimates as observed with the intraclass coefficient (0.74-0.89 confidence interval for a single 20-s test). Clinical assessment of balance may benefit from a standardized protocol for center of pressure spectral analysis that provides an adequate relationship between resolution and variance. An algorithm to estimate center of pressure power density spectrum is also proposed.

Analysis of Brazilian consumer preference of filled chocolate

Chocolate is the most popular product made from cocoa. It is mainly consumed with fillings, such as fondant, hydrogenated fat or fruits. This work aimed at assessing the sensory acceptability of chocolate filled with strawberry, orange or passion fruit pulps, mixed in fondant, in a hydrogenated fat base and as truffles. Ninety four consumers participated in the test using a 10 cm hedonic scale to rate the overall liking of the samples. Two-way analysis of variance and the Internal Preference Mapping technique were used to analyze the data. Results showed a good overall liking for almost all samples, especially for strawberry and passion fruit truffles, which obtained 8.4 and 8.8 global means, respectively (p < 0.05), in liking ratings, followed by the hydrogenated fat and fondant fillings. The Internal Preference Map presented two dimensions explaining 72.5% of the variation found. Regarding the flavors, strawberry - traditional in chocolate and confectionary in Brazil - and passion fruit obtained better acceptance, unlike the orange fillings, which showed significantly lower ratings (p < 0.05). The orange fondant filling obtained a global mean of 6.5.

Influence of distillation time and sample mass on sulfur dioxide analysis in passion fruit juice through Monier-Williams method

AbstractThis study aimed to evaluate the effect of the distillation time and the sample mass on the total SO2 content in integral passion fruit juice (Passiflora sp). For the SO2 analysis, a modified version of the Monier-Williams method was used. In this experiment, the distillation time and the sample mass were reduced to half of the values proposed in the original method. The analyses were performed in triplicate for each distilling time x sample mass binomial, making a total of 12 tests, which were performed on the same day. The significance of the effects of the different distillation times and sample mass were evaluated by applying one-factor analysis of variance (ANOVA). For a 95% confidence limit, it was found that the proposed amendments to the distillation time, sample mass, and the interaction between distilling time x sample mass were not significant (p > 0.05) in determining the SO2 content in passion fruit juice. In view of the results that were obtained it was concluded that for integral passion fruit juice it was possible to reduce the distillation time and the sample mass in determining the SO2 content by the Monier-Williams method without affecting the result.