Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Quantitative Chemical Profile and Multivariate Statistical Analysis of Alembic Distilled Sugarcane Spirit Fractions

Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Physiological effects of glyphosate over amino acid profile in conventional and transgenic soybean (Glycine max)

This paper compares the responses of conventional and transgenic soybean to glyphosate application in terms of the contents of 17 detectable soluble amino acids in leaves, analyzed by HPLC and fluorescence detection. Glutamate, histidine, asparagine, arginine + alanine, glycine + threonine and isoleucine increased in conventional soybean leaves when compared to transgenic soybean leaves, whereas for other amino acids, no significant differences were recorded. Univariate analysis allowed us to make an approximate differentiation between conventional and transgenic lines, observing the changes of some variables by glyphosate application. In addition, by means of the multivariate analysis, using principal components analysis (PCA), cluster analysis (CA) and linear discriminant analysis (LDA) it was possible to identify and discriminate different groups based on the soybean genetic origin. (C) 2011 Elsevier Inc. All rights reserved.

Multivariate analyses of UV-Vis absorption spectral data from cachaca wood extracts: a model to classify aged Brazilian cachacas according to the wood species used

Multivariate analyses of UV-Vis spectral data from cachaca wood extracts provide a simple and robust model to classify aged Brazilian cachacas according to the wood species used in the maturation barrels. The model is based on inspection of 93 extracts of oak and different Brazilian wood species by a non-aged cachaca used as an extraction solvent. Application of PCA (Principal Components Analysis) and HCA (Hierarchical Cluster Analysis) leads to identification of 6 clusters of cachaca wood extracts (amburana, amendoim, balsamo, castanheira, jatoba, and oak). LDA (Linear Discriminant Analysis) affords classification of 10 different wood species used in the cachaca extracts (amburana, amendoim, balsamo, cabreuva-parda, canela-sassafras, castanheira, jatoba, jequitiba-rosa, louro-canela, and oak) with an accuracy ranging from 80% (amendoim and castanheira) to 100% (balsamo and jequitiba-rosa). The methodology provides a low-cost alternative to methods based on liquid chromatography and mass spectrometry to classify cachacas aged in barrels that are composed of different wood species.

A comparative study on multiscale fractal dimension descriptors

Fractal theory presents a large number of applications to image and signal analysis. Although the fractal dimension can be used as an image object descriptor, a multiscale approach, such as multiscale fractal dimension (MFD), increases the amount of information extracted from an object. MFD provides a curve which describes object complexity along the scale. However, this curve presents much redundant information, which could be discarded without loss in performance. Thus, it is necessary the use of a descriptor technique to analyze this curve and also to reduce the dimensionality of these data by selecting its meaningful descriptors. This paper shows a comparative study among different techniques for MFD descriptors generation. It compares the use of well-known and state-of-the-art descriptors, such as Fourier, Wavelet, Polynomial Approximation (PA), Functional Data Analysis (FDA), Principal Component Analysis (PCA), Symbolic Aggregate Approximation (SAX), kernel PCA, Independent Component Analysis (ICA), geometrical and statistical features. The descriptors are evaluated in a classification experiment using Linear Discriminant Analysis over the descriptors computed from MFD curves from two data sets: generic shapes and rotated fish contours. Results indicate that PCA, FDA, PA and Wavelet Approximation provide the best MFD descriptors for recognition and classification tasks. (C) 2012 Elsevier B.V. All rights reserved.

AGE INFLUENCE ON THE HEART RATE BEHAVIOR ON THE REST-EXERCICIO TRANSITION: AN ANALYSIS BY DELTAS AND LINEAR REGRESSION

Background: Changes in heart rate during rest-exercise transition can be characterized by the application of mathematical calculations, such as deltas 0-10 and 0-30 seconds to infer on the parasympathetic nervous system and linear regression and delta applied to data range from 60 to 240 seconds to infer on the sympathetic nervous system. The objective of this study was to test the hypothesis that young and middle-aged subjects have different heart rate responses in exercise of moderate and intense intensity, with different mathematical calculations. Methods: Seven middle-aged men and ten young men apparently healthy were subject to constant load tests (intense and moderate) in cycle ergometer. The heart rate data were submitted to analysis of deltas (0-10, 0-30 and 60-240 seconds) and simple linear regression (60-240 seconds). The parameters obtained from simple linear regression analysis were: intercept and slope angle. We used the Shapiro-Wilk test to check the distribution of data and the "t" test for unpaired comparisons between groups. The level of statistical significance was 5%. Results: The value of the intercept and delta 0-10 seconds was lower in middle age in two loads tested and the inclination angle was lower in moderate exercise in middle age. Conclusion: The young subjects present greater magnitude of vagal withdrawal in the initial stage of the HR response during constant load exercise and higher speed of adjustment of sympathetic response in moderate exercise.

Common matrix metalloproteinase 2 gene haplotypes may modulate left ventricular remodelling in hypertensive patients

Matrix metalloproteinases (MMPs) are involved in cardiac remodelling. We examined whether MMP-2 genetic polymorphisms are associated with hypertension and left ventricular (LV) remodelling in hypertensive patients. We studied 160 hypertensive patients and 123 healthy controls. Echocardiography was performed in all patients and the C-1306T (rs243865) and C-735T (rs 2285053) MMP-2 polymorphisms were analysed. Haplo.stats analysis was used to evaluate whether MMP-2 haplotypes are associated with hypertension and with extremes in LV mass index (LVMI). Multiple linear regression analysis was performed to assess whether MMP-2 genotypes or haplotypes affect LVMI and other echocardiography parameters. The C-1306T 'CC' genotype was associated with reduced LVMI and LV end-diastolic diameter (EDD) (P=0.0365 and P=0.0438, respectively). The haplotype 'C, C' was associated with reduced LVMI and EDD (P=0.0278 and P=0.0322, respectively). The comparison of upper and lower extremes of the LVMI phenotype showed that the 'C, C' haplotype was more common in the lower LVMI group (P=0.0060), whereas the 'T, C' haplotype was more common in the higher quartile of LVMI (P=0.0187), and this haplotype was associated with increased risk of higher LVMI values (odds ratio=3.5121, 95% confidence interval 1.3193-9.3494). The findings suggest that MMP-2 polymorphisms affect hypertension-induced LV remodelling. Journal of Human Hypertension (2012) 26, 171-177; doi:10.1038/jhh.2011.8; published online 10 February 2011

On estimating the basic reproduction number in distinct stages of a contagious disease spreading

In epidemiology, the basic reproduction number R-0 is usually defined as the average number of new infections caused by a single infective individual introduced into a completely susceptible population. According to this definition. R-0 is related to the initial stage of the spreading of a contagious disease. However, from epidemiological models based on ordinary differential equations (ODE), R-0 is commonly derived from a linear stability analysis and interpreted as a bifurcation parameter: typically, when R-0 >1, the contagious disease tends to persist in the population because the endemic stationary solution is asymptotically stable: when R-0 <1, the corresponding pathogen tends to naturally disappear because the disease-free stationary solution is asymptotically stable. Here we intend to answer the following question: Do these two different approaches for calculating R-0 give the same numerical values? In other words, is the number of secondary infections caused by a unique sick individual equal to the threshold obtained from stability analysis of steady states of ODE? For finding the answer, we use a susceptibleinfective-recovered (SIR) model described in terms of ODE and also in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. The values of R-0 obtained from both approaches are compared, showing good agreement. (C) 2012 Elsevier B.V. All rights reserved.

Evaluation of genotoxicity and oxidative damage in painters exposed to low levels of toluene

Toluene is an organic solvent used in numerous processes and products, including industrial paints. Toluene neurotoxicity and reproductive toxicity are well recognized: however, its genotoxicity is still under discussion, and toluene is not classified as a carcinogenic solvent. Using the comet assay and the micronucleus test for detection of possible genotoxic effects of toluene, we monitored industrial painters from Rio Grande do Sul, Brazil. The putative involvement of oxidative stress in genetic damage and the influences of age, smoking, alcohol consumption, and exposure time were also assessed. Although all biomarkers of toluene exposure were below the biological exposure limits, painters presented significantly higher DNA damage (comet assay) than the control group; however, in the micronucleus assay, no significant difference was observed. Painters also showed alterations in hepatic enzymes and albumin levels, as well as oxidative damage, suggesting the involvement of oxidative stress. According to multiple linear regression analysis, blood toluene levels may account for the increased DNA damage in painters. In summary, this study showed that low levels of toluene exposure can cause genetic damage, and this is related to oxidative stress, age, and time of exposure. (C) 2012 Elsevier B.V. All rights reserved.

Population divergence of Melipona scutellaris (Hymenoptera: Meliponina) in two restricted areas in Bahia, Brazil

Melipona scutellaris Latreille has great economic and ecological importance, especially because it is a pollinator of native plant species. Despite the importance of this species, there is little information about the conservation status of their populations. The objective of this study was to assess the diversity in populations of M. scutellaris coming from a Semideciduous Forest Fragment and an Atlantic Forest Fragment in the Northeast Brazil, through geometric morphometric analysis of wings in worker bees. In each area, worker bees were collected from 10 colonies, 10 workers per colony. To assess the diversity on the right wings of worker bees, 15 landmarks were plotted and the measures were used in analysis of variance and multivariate analysis, principal component analysis, discriminant analysis and clustering analysis. There were significant differences in the shape of the wing venation patterns between colonies of two sites (Wilk's lambda = 0.000006; p < 0.000001), which is probably due to the geographical distance between places of origin which impedes the gene flow between them. It indicates that inter and intrapopulation morphometric variability exists (p < 0.000001) in M. scutellaris coming from two different biomes, revealing the existence of diversity in these populations, which is necessary for the conservation of this bee species.

The influence of anthropometric factors on postural balance: the relationship between body composition and posturographic measurements in young adults

OBJECTIVE: The aim of the present study was to evaluate the influence of anthropometric characteristics and gender on postural balance in adults. One hundred individuals were examined (50 males, 50 females; age range 20-40 years). METHODS: The following body composition measurements were collected (using bone densitometry measurements): fat percentage (% fat), tissue (g), fat (g), lean mass (g), bone mineral content (g), and bone mineral density (g/cm(2)). In addition, the following anthropometric measurements were collected: body mass (kg), height (cm), length of the trunk-cephalic region (cm), length of the lower limbs (cm) and length of the upper limbs (cm). The following indices were calculated: body mass index (kg/m(2)), waist-hip ratio and the support base (cm 2). Also, a postural balance test was performed using posturography variables with open and closed eyes. RESULTS: The analysis revealed poor correlations between postural balance and the anthropometric variables. A multiple linear regression analysis demonstrated that the whole group (female and male) height explained 12% of the medial-lateral displacement, 10% of the speed of oscillation, and 11% of the displacement area. The length of the trunk-cephalic length explained 6% of the displacement in the anteroposterior direction. With eyes closed, the support base and height explained 18% of the medial displacement, and the lateral height explained 10% of the displacement speed and 5% of the scroll area. CONCLUSION: Measured using posturography, the postural balance was only slightly influenced by the anthropometric variables, both with open and closed eyes. Height was the anthropometric variable that most influenced postural balance, both in the whole group and separately for each gender. Postural balance was more influenced by anthropometric factors in males than females.

Torque removal evaluation of prosthetic screws after tightening and loosening cycles: an in vitro study

Objectives: The aim of this study was to evaluate the variation in removal torque of implant prosthetic abutment screws after successive tightening and loosening cycles, in addition to evaluating the influence of the hexagon at the abutment base on screw removal torque. Material and methods: Twenty hexagonal abutments were tightened to 20 regular external hex implants with a titanium alloy screw, with an insertion torque of 32 N cm, measured with a digital torque gauge. The implant/abutment/screw assemblies were divided into two groups: ( 1) abutments without hexagon at the base and ( 2) abutments with a hexagon at the base. Each assembly received a provisional restoration and was submitted to mechanical loading cycles. After this, the screws were removed and the removal torque was measured. This sequence was repeated 10 times, then the screw was replaced by a new one, and another cycle was performed. Linear regression analysis was performed. Results: Removal torque values tended to decrease as the number of insertion/removal cycles increased, for both groups. Comparisons of the slopes and the intercepts between groups showed no statistical difference. There was no significant difference between the mean values of last five cycles and the 11th cycle. Within the limitations of this in vitro study, it was concluded that ( 1) repeated insertion/removal cycles promoted gradual reduction in removal torque of screws, ( 2) replacing the screw with a new one after 10 cycles did not increase resistance to loosening, and ( 3) removal of the hexagon from the abutment base had no effect on the removal torque of the screws.

Four-gene expression model predictive of lymph node metastases in oral squamous cell carcinoma

Background. Previous knowledge of cervical lymph node compromise may be crucial to choose the best treatment strategy in oral squamous cell carcinoma (OSCC). Here we propose a set four genes, whose mRNA expression in the primary tumor predicts nodal status in OSCC, excluding tongue. Material and methods. We identified differentially expressed genes in OSCC with and without compromised lymph nodes using Differential Display RT-PCR. Known genes were chosen to be validated by means of Northern blotting or real time RT-PCR (qRT-PCR). Thereafter we constructed a Nodal Index (NI) using discriminant analysis in a learning set of 35 patients, which was further validated in a second independent group of 20 patients. Results. Of the 63 differentially expressed known genes identified comparing three lymph node positive (pN+) and three negative (pN0) primary tumors, 23 were analyzed by Northern analysis or RT-PCR in 49 primary tumors. Six genes confirmed as differentially expressed were used to construct a NI, as the best set predictive of lymph nodal status, with the final result including four genes. The NI was able to correctly classify 32 of 35 patients comprising the learning group (88.6%; p = 0.009). Casein kinase 1alpha1 and scavenger receptor class B, member 2 were found to be up regulated in pN + group in contrast to small proline-rich protein 2B and Ras-GTPase activating protein SH3 domain-binding protein 2 which were upregulated in the pN0 group. We validated further our NI in an independent set of 20 primary tumors, 11 of them pN0 and nine pN+ with an accuracy of 80.0% (p = 0.012). Conclusions. The NI was an independent predictor of compromised lymph nodes, taking into the consideration tumor size and histological grade. The genes identified here that integrate our "Nodal Index" model are predictive of lymph node metastasis in OSCC.

Factors controlling water-column respiration in rivers of the central and southwestern Amazon Basin

We examined the factors controlling the variability in water-column respiration rates in Amazonian rivers. Our objectives were to determine the relationship between respiration rates and the in situ concentrations of the size classes of organic carbon (OC), and the biological source (C-3 and C-4 plants and phytoplankton) of organic matter (OM) supporting respiration. Respiration was measured along with OC size fractions and dissolved oxygen isotopes (delta O-18-O-2) in rivers of the central and southwestern Amazon Basin. Rates ranged from 0.034 mu mol O-2 L-1 h(-1) to 1.78 mu mol O-2 L-1 h(-1), and were four-fold higher in rivers with evidence of photosynthetic production (demonstrated by delta O-18-O-2<24.2 parts per thousand) as compared to rivers lacking such evidence (delta O-18-O-2>24.2 parts per thousand; 1.35 +/- 0.22 vs. 0.30 +/- 0.29 mu mol L-1 h(-1)). Rates were likely elevated in the former rivers, which were all sampled during low water, due to the stimulation of heterotrophic respiration via the supply of a labile, algal-derived substrate and/or the occurrence of autotrophic respiration. The organic composition of fine particulate OM (FPOM) of these rivers is consistent with a phytoplankton origin. Multiple linear regression analysis indicates that [FPOC], C:N-FPOC ratios, and [O-2] account for a high amount of the variability in respiration rates (r(2) = 0.80). Accordingly, FPOC derived from algal sources is associated with elevated respiration rates. The delta C-13 of respiration-derived CO2 indicates that the role of phytoplankton, C-3 plants, and C-4 grasses in supporting respiration is temporally and spatially variable. Future scaling work is needed to evaluate the significance of phytoplankton production to basin-wide carbon cycling.