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.

Thermostability of heterophile antibodies from human sera infected with Schistosoma mansoni and geo-helminths: an immuno-metric statistical analysis

Antibody in human sera that induces lysis of sheep erythrocytes in hemolytic assay was investigated. The present study showed that the presence in serum of the thermostable cytolytic anti-sheep red blood cells antibodies is dependent on the Schistosoma mansoni infection, and this is more frequent in adults than in children. The thermostable characteristic of hemolysins in normal sera was not dependent on the presence of Ascaris lumbricoides, Trichuris trichiura or hookworm geo-helminths. Further, thermostable complement-activating heterophile antibodies were noticed in children in association with massive number of S. mansoni eggs. The results were obtained by using the z- and the chi-square tests. The z-test allows us to formulate a one-sided alternative, i.e., a tendency of one of the attributes. On the other hand, the chi-square test analyzes the independence between attributes by using a contingency table. Besides the obtained results being interesting in the field of schistosomiasis mansoni, they can provide a new insight into the use of statistics in medical science.

A possible contribution to improving the therapeutic potentials of Babor's Typology of Alcohol Dependent Patients

ABSTRACT Objective The objective of this study was to replicate Babor's Typology and to explore clinical features related to personality traits that may underlie this classification, in order to improve its therapeutic possibilities. Methods Observational prospective study on a group of 273 male alcoholics. After a replication of Babor's variables, Cluster Analysis, Chi-Square – applied on clinical variables related to a Lappda Tipology – and Kappa tests were performed. Results The study identified two distinct clusters that held similar features to those described for the Type A/Type B classification. Besides presenting a lower socio-economic situation, Cluster 2 patients were associated with higher vulnerability and severe clinical features and also differed from Cluster 1 in their response to treatment. These replicated clusters retained connections and also differences in relation to the variables derived from the Lappda Typology. Conclusion Considering that each of the two replicated clusters seem to be associated to different personality traits – according to their correlations to the affective, cognitive and behavioral dimensions brought forward by the Lappda Typology – it is acceptable that this study may contribute to the development of more comprehensive and effective therapeutic strategies specifically tailored to target more specific personality traits of these subgroups of alcoholic patients.

Analysis of the Prevalence of Ventricular Late Potentials in the Late Phase of Myocardial Infarction Based on the Site of Infarction

OBJECTIVE: The initial site of myocardial infarction (MI) may influence the prevalence of ventricular late potentials (VLP), high-frequency signals, due to the time course of ventricular activation. The prevalence of VLP in a period of more than 2 years after acute MI was assessed focusing on the initially injured wall . METHODS: The prevalence of VLP in a late phase after MI (median of 924 days) in anterior/antero-septal and inferior/infero-dorsal wall lesion was analyzed using signal-averaged electrocardiogram in time domain. The diagnostic performance of the filters employed for analysis on was tested at high-pass cut-off frequencies of 25 Hz, 40 Hz and 80 Hz. RESULTS: The duration of the ventricular activation and its terminal portion were larger in inferior than anterior infarction, at high-pass cut-off frequencies of 40 Hz and 80 Hz. In patients with ventricular tachycardia, these differences were more remarked. The prevalence of ventricular late potentials was three times greater in inferior than anterior infarction. CONCLUSION: Late after myocardial infarction, the prevalence and the duration of ventricular late potentials are greater in lesions of inferior/infero-dorsal than anterior/antero-septal wall confirming their temporal process, reflecting their high-frequency content.

Diagnosis of Rejection by Analyzing Ventricular Late Potentials in Heart Transplant Patients

Background: Heart transplant rejection originates slow and fragmented conduction. Signal-averaged ECG (SAECG) is a stratification method in the risk of rejection. Objective: To develop a risk score for rejection, using SAECG variables. Methods: We studied 28 transplant patients. First, we divided the sample into two groups based on the occurrence of acute rejection (5 with rejection and 23 without). In a second phase, we divided the sample considering the existence or not of rejection in at least one biopsy performed on the follow-up period (rejection pm1: 18 with rejection and 10 without). Results: On conventional ECG, the presence of fibrosis was the only criterion associated with acute rejection (OR = 19; 95% CI = 1.65-218.47; p = 0.02). Considering the rejection pm1, an association was found with the SAECG variables, mainly with RMS40 (OR = 0.97; 95% CI = 0.87-0.99; p = 0.03) and LAS40 (OR = 1.06; 95% IC = 1.01-1.11; p = 0.03). We formulated a risk score including those variables, and evaluated its discriminative performance in our sample. The presence of fibrosis with increasing of LAS40 and decreasing of RMS40 showed a good ability to distinguish between patients with and without rejection (AUC = 0.82; p < 0.01), assuming a cutoff point of sensitivity = 83.3% and specificity = 60%. Conclusion: The SAECG distinguished between patients with and without rejection. The usefulness of the proposed risk score must be demonstrated in larger follow-up studies.

Biometric and statistical investigations on the cnidoma of the genus Hydra (Cnidaria, Hydrozoa)

This paper deals about the nematocysts like a source of biometric information for comparison between the species Hydra vulgaris Pallas, 1766, Hydra vulgaris pedunculata Deserti et al., 2011 and Hydra pseudoligactis (Hyman, 1931). This biometric tool lets us carry out statistical comparisons and adding these results to the identification of specimens from different classificatory groups. In this particular study, we obtained significant differences between species, individuals of each species and nematocysts type when compared the biometry of its nematocysts. Another result was the variation in of particular nematocysts, like atrichous isorhiza and holotrichous isorhiza for the species H. vulgaris in relation to the column size.

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.

Soil Water Potentials and Capsicum annuum L. under Salinity

ABSTRACT Investigations into water potentials in the soil-plant system are of great relevance in environments with abiotic stresses, such as salinity and drought. An experiment was developed using bell pepper in a Neossolo Flúvico (Fluvent) irrigated with water of six levels of electrical conductivity (0, 1, 3, 5, 7 and 9 dS m-1) by using exclusively NaCl and by simulating the actual condition (using a mixture of salts). The treatments were arranged in a randomized block design, in a 6 × 2 factorial arrangement, with four replicates. Soil matric (Ψm) and osmotic (Ψo) potentials were determined 70 days after transplanting (DAT). Soil total potential was considered as the sum of Ψm and Ψo. Leaf water (obtained with the Scholander Chamber) and osmotic potentials were determined before sunrise (predawn) and at noon at 42 and 70 DAT. There were no significant differences between the salt sources used in the irrigation water for soil and plant water potentials. The supply of salts to the soil through irrigation water was the main factor responsible for the decrease in Ψo in the soil and in bell pepper leaves. The total potential of bell pepper at predawn reached values of -1.30 and -1.33 MPa at 42 and 70 DAT, respectively, when water of 9 dS m-1 was used in the irrigation. The total potential at noon reached -2.19 MPa. The soil subjected to the most saline treatment reached a water potential of -1.20 MPa at 70 DAT. There was no predawn equilibrium between the total water potentials of the soil and the plant, indicating that soil potential cannot be considered similar to that of the plant. The determination of the osmotic potential in the soil solution should not be neglected in saline soils, since it has strong influence on the calculation of the total potential.

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.