Risk Factors for tuberculosis among human immunodeficiency virus-infected persons. A case-control study in Belo Horizonte, Minas Gerais, Brazil (1985-1996)

The objective of this study was to identify tuberculosis risk factors and possible surrogate markers among human immunodeficiency virus (HIV)-infected persons. A retrospective case-control study was carried out at the HIV outpatient clinic of the Universidade Federal de Minas Gerais in Belo Horizonte. We reviewed the demographic, social-economical and medical data of 477 HIV-infected individuals evaluated from 1985 to 1996. The variables were submitted to an univariate and stratified analysis. Aids related complex (ARC), past history of pneumonia, past history of hospitalization, CD4 count and no antiretroviral use were identified as possible effect modifiers and confounding variables, and were submitted to logistic regression analysis by the stepwise method. ARC had an odds ratio (OR) of 3.5 (CI 95% - 1.2-10.8) for tuberculosis development. Past history of pneumonia (OR 1.7 - CI 95% 0.6-5.2) and the CD4 count (OR 0.4 - CI 0.2-1.2) had no statistical significance. These results show that ARC is an important clinical surrogate for tuberculosis in HIV-infected patients. Despite the need of confirmation in future studies, these results suggest that the ideal moment for tuberculosis chemoprophylaxis could be previous to the introduction of antiretroviral treatment or even just after the diagnosis of HIV infection.

Capillaria spp. eggs in Patagonian archaeological sites: statistical analysis of morphometric data

Discriminant analysis was used to identify eggs of Capillaria spp. at specific level found in organic remains from an archaeological site in Patagonia, Argentina, dated of 6,540 ± 110 years before present. In order to distinguish eggshell morphology 149 eggs were measured and grouped into four arbitrary subsets. The analysis used on egg width and length discriminated them into different morphotypes (Wilks' lambda = 0.381, p < 0.05). The correlation analysis suggests that width was the most important variable to discriminate among the Capillaria spp. egg morphotypes (Pearson coefficient = 0.950, p < 0.05). The study of eggshell patterns, the relative frequency in the sample, and the morphometric data allowed us to correlate the four morphotypes with Capillaria species.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Critical values of nitrogen indices in tomato plants grown in soil and nutrient solution determined by different statistical procedures

The objective of this study was to establish critical values of the N indices, namely soil-plant analysis development (SPAD), petiole sap N-NO3 and organic N in the tomato leaf adjacent to the first cluster (LAC), under soil and nutrient solution conditions, determined by different statistical approaches. Two experiments were conducted in randomized complete block design with four repli-cations. Tomato plants were grown in soil, in 3 L pot, with five N rates (0, 100, 200, 400 and 800 mg kg-1) and in solution at N rates of 0, 4, 8, 12 and 16 mmol L-1. Experiments in nutrient solution and soil were finished at thirty seven and forty two days after transplanting, respectively. At those times, SPAD index and petiole sap N-NO3 were evaluated in the LAC. Then, plants were harvested, separated in leaves and stem, dried at 70ºC, ground and weighted. The organic N was determined in LAC dry matter. Three statistical procedures were used to calculate critical N values. There were accentuated discrepancies for critical values of N indices obtained with plants grown in soil and nutrient solution as well as for different statistical procedures. Critical values of nitrogen indices at all situations are presented.

Spatial statistical analysis and selection of genotypes in plant breeding

The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

Validation and statistical analysis of two high performance liquid chromatography methods for the determination of indinavir sulfate raw material and capsules

Two high performance liquid chromatography (HPLC) methods for the quantitative determination of indinavir sulfate were tested, validated and statistically compared. Assays were carried out using as mobile phases mixtures of dibutylammonium phosphate buffer pH 6.5 and acetonitrile (55:45) at 1 mL/min or citrate buffer pH 5 and acetonitrile (60:40) at 1 mL/min, an octylsilane column (RP-8) and a UV spectrophotometric detector at 260 nm. Both methods showed good sensitivity, linearity, precision and accuracy. The statistical analysis using the t-student test for the determination of indinavir sulfate raw material and capsules indicated no statistically significant difference between the two methods.

Optimization of solvent mixtures for extraction from bark of Schinus terebinthifolius by a statistical mixture-design technique and development of a UV-Vis spectrophotometric method for analysis of total polyphenols in the extract

A statistical mixture-design technique was used to study the effects of different solvents and their mixtures on the yield, total polyphenol content, and antioxidant capacity of the crude extracts from the bark of Schinus terebinthifolius Raddi (Anacardiaceae). The experimental results and their response-surface models showed that ternary mixtures with equal portions of all the three solvents (water, ethanol and acetone) were better than the binary mixtures in generating crude extracts with the highest yield (22.04 ± 0.48%), total polyphenol content (29.39 ± 0.39%), and antioxidant capacity (6.38 ± 0.21). An analytical method was developed and validated for the determination of total polyphenols in the extracts. Optimal conditions for the various parameters in this analytical method, namely, the time for the chromophoric reaction to stabilize, wavelength of the absorption maxima to be monitored, the reference standard and the concentration of sodium carbonate were determined to be 5 min, 780 nm, pyrogallol, and 14.06% w v-1, respectively. UV-Vis spectrophotometric monitoring of the reaction under these conditions proved the method to be linear, specific, precise, accurate, reproducible, robust, and easy to perform.

Statistical Model to DNA Melting

We explore a DNA statistical model to obtain information about the behavior of the thermodynamics quantities. Special attention is given to the thermal denaturation of this macromolecule.

Multivariate statistical analysis to support the minimum streamflow regionalization

ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.

Impact of ivermectin-resistant gastrointestinal nematodes in feedlot cattle in Argentina

The aim was to evaluate for 75 days the impact on production of the remaining burden of ivermectin (IVM)-resistant parasites in naturally infected feedlot calves. The herds came from tick-infested areas of cattle breeding where the systematic use of IVM to control tick increases the gastrointestinal parasites resistant to this drug. This investigation was carried out in two commercial feedlots in Buenos Aires province. In feedlot A, two groups of 35 animal each received IVM 1% and the other received ricobendazole (RBZ) 10% respectively. The same was done in feedlot B. On day 0, two groups of 35 animals were made in feedlots A and B. Fecal samples were taken on days 0, 22, 54 and 75 pos-treatment (PT), and body weight was registered, from each animal. Fecal samples were processed for individual count of eggs per gram (EPG) and pooled fecal culture was carried out for identification of the parasite genus in each sampling. Fecal egg count reduction test (FECR) was calculated on day 22 PT. The study design used was a totally randomized block, with commercial feedlot and sex as block variables. For data analysis, a mixed model of the SAS statistical program was used. The FECR average on day 22 was 28.4% in the IVM group, and 94,2 % in the RBZ group . From this date on, significant differences in EPG were kept until day 54. EPG counts were only equal near the end of the trial, on day 75 (p=0.16). In both commercial feedlots, especially in the IVM group, Cooperia spp. was the most prevalent parasite in the fecal cultures. Significant differences in weight (P<0.01) on post-treatment day 75 was found between the average weight in the RBZ and the IVM group (246 vs. 238 kg respectively), what means a difference of 8.3% in gains. The importance for production in the antiparasite failure treatment in commercial feedlots was demonstrated, and the need of pos-treatment controls to evaluate the efficacy of the antiparasitic administered is emphasized.

Variability in the fecal egg count and the parasitic burden of hair sheep after grazing in nematode infected paddocks

This study aimed to evaluate the variability in the fecal egg count (FEC) and the parasitic burden of naive hair sheep after grazing in nematode infected paddocks. The research was carried out in Tabasco, Mexico, during two periods (August and December). In each period 32 lambs were grazed for one month on African star grass (Cynodon plectostachyus) contaminated with gastrointestinal parasitic nematodes. FEC, packed cell volume (PCV) and body weight (BW) were recorded. Gastrointestinal worms were recovered at necropsy. Data were analyzed with the MIXED procedure of SAS using a model of repeated measurements over time. A higher number of Haemonchus contortus worms was found in December (2814±838) than in August (1166±305). The opposite occurred with Cooperia curticei (2167±393 and 3638±441, respectively). The FEC and correlation coefficient in respect to the worm burden were higher in December (6516 ± 1599, r=0.83, respectively) than in August (4364±771, r=0.44, respectively). A high variability in resistance-susceptibility to gastrointestinal nematodes (GIN) occurred in Katahdin × Pelibuey lambs after grazing.

Statistical analysis of event-related potential elicited by verb-complement merge in Brazilian Portuguese

An interesting fact about language cognition is that stimulation involving incongruence in the merge operation between verb and complement has often been related to a negative event-related potential (ERP) of augmented amplitude and latency of ca. 400 ms - the N400. Using an automatic ERP latency and amplitude estimator to facilitate the recognition of waves with a low signal-to-noise ratio, the objective of the present study was to study the N400 statistically in 24 volunteers. Stimulation consisted of 80 experimental sentences (40 congruous and 40 incongruous), generated in Brazilian Portuguese, involving two distinct local verb-argument combinations (nominal object and pronominal object series). For each volunteer, the EEG was simultaneously acquired at 20 derivations, topographically localized according to the 10-20 International System. A computerized routine for automatic N400-peak marking (based on the ascendant zero-cross of the first waveform derivative) was applied to the estimated individual ERP waveform for congruous and incongruous sentences in both series for all ERP topographic derivations. Peak-to-peak N400 amplitude was significantly augmented (P < 0.05; one-sided Wilcoxon signed-rank test) due to incongruence in derivations F3, T3, C3, Cz, T5, P3, Pz, and P4 for nominal object series and in P3, Pz and P4 for pronominal object series. The results also indicated high inter-individual variability in ERP waveforms, suggesting that the usual procedure of grand averaging might not be considered a generally adequate approach. Hence, signal processing statistical techniques should be applied in neurolinguistic ERP studies allowing waveform analysis with low signal-to-noise ratio.

Sleep deprivation reduces the lymphocyte count in a non-obese mouse model of type 1 diabetes mellitus

The objective of the present study was to determine whether sleep deprivation (SD) would promote changes in lymphocyte numbers in a type 1 diabetes model (non-obese diabetic, NOD, mouse strain) and to determine whether SD would affect female and male NOD compared to Swiss mice. The number of lymphocytes in peripheral blood after 24 and 96 h of SD (by multiple platform method) or equivalent period of time in home-cage controls was examined prior to the onset of diabetes. SD for 96 h significantly reduced lymphocytes in male Swiss mice compared to control (8.6 ± 2.1 vs 4.1 ± 0.7 10³/µL; P < 0.02). In male NOD animals, 24- and 96-h SD caused a significant decrease of lymphocytes compared to control (4.4 ± 0.3 vs 1.6 ± 0.5; P < 0.001 and 4.4 ± 0.3 vs 0.9 ± 0.1 10³/µL; P < 0.00001, respectively). Both 24- and 96-h SD induced a reduction in the number of lymphocytes in female Swiss (7.5 ± 0.5 vs 4.5 ± 0.5, 4.4 ± 0.6 10³/µL; P < 0.001, respectively) and NOD mice (4 ± 0.6 vs 1.8 ± 0.2, 1.2 ± 0.4 10³/µL; P < 0.01, respectively) compared to the respective controls. Loss of sleep induced lymphopenia in peripheral blood in both genders and strains used. Since many cases of autoimmunity present reduced numbers of lymphocytes and, in this study, it was more evident in the NOD strain, our results suggest that SD should be considered a risk factor in the onset of autoimmune disorders.