1000 resultados para Plot Test


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La ictericia es causa frecuente de hospitalización en neonatos. El objetivo principal fue establecer la correlación entre bilirrubinometría transcutánea y bilirrubina sérica, y su utilidad para identificar requerimiento de fototerapia. Materiales y métodos: Es un estudio descriptivo de correlación. Incluyó neonatos con realización de bilirrubinometría transcutánea y bilirrubina sérica. Se calculan índices de correlación de Pearson para el tórax y la frente. La variabilidad de las diferencias entre niveles transcutáneos y bilirrubina séricas, se correlacionan, mediante diagrama de Bland-Altman. Se obtienen mediciones de desempeño de la prueba, con sensibilidad y especificidad. Resultados: Se incluyeron 88 Neonatos, con 112 bilirrubinometrías transcutáneas, (mediana en tórax: 6,0 mg/dl y en frente: 5,9 mg/dl). Se tomaron 95 muestras de bilirrubina sérica, (mediana: 7,2 mg/dl). Los índices de correlación de Pearson fueron 0.83 (tórax) y 0.93 (frente). Utilizando puntos de corte establecidos, para determinar la necesidad de fototerapia, se obtuvieron, sensibilidad del 93 % y especificidad del 86 % (tórax), y sensibilidad del 94% y especificidad del 83 % (frente). Utilizando percentiles 75 del gráfico de Buthani, se obtuvieron sensibilidad del 83% y Especificidad del 98% para la bilirrubinometría transcutánea. Discusión: Las mediciones transcutáneas se correlacionaron bien con las sanguíneas. Las sensibilidades obtenidas fueron satisfactorias. Conclusión: Las mediciones transcutáneas, hubieran detectado la mayoría de infantes que requirieron fototerapia, confirmando la utilidad como método no invasivo en la práctica clínica.

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The use of morphological data obtained from field (plot test) and glasshouse trials to identify and discriminate among four Iranian and two New Zealand lucerne (Medicago sativa L.) cultivars was investigated, following guidelines established by the International Union for the Protection of New Varieties of Plants (UPOV) for cultivar registration and the Organisation for Economic Co-operation and Development (OECD) for seed certification. Data were collected for terminal leaflet length, width and ratio, angle of stem growth, date of first flowering, stem height at first flowering, flower colour, cutting recovery height, and disease scores. None of these characters were sufficient to identify or discriminate among the six cultivars. The results indicate a need to find cost-effective and efficient laboratory techniques to enhance the assessment of distinctness of lucerne cultivars (UPOV) and for determining cultivar purity for lucerne seed certification (OECD).

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Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

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Questions: A multiple plot design was developed for permanent vegetation plots. How reliable are the different methods used in this design and which changes can we measure? Location: Alpine meadows (2430 m a.s.l.) in the Swiss Alps. Methods: Four inventories were obtained from 40 m(2) plots: four subplots (0.4 m(2)) with a list of species, two 10m transects with the point method (50 points on each), one subplot (4 m2) with a list of species and visual cover estimates as a percentage and the complete plot (40 m(2)) with a list of species and visual estimates in classes. This design was tested by five to seven experienced botanists in three plots. Results: Whatever the sampling size, only 45-63% of the species were seen by all the observers. However, the majority of the overlooked species had cover < 0.1%. Pairs of observers overlooked 10-20% less species than single observers. The point method was the best method for cover estimate, but it took much longer than visual cover estimates, and 100 points allowed for the monitoring of only a very limited number of species. The visual estimate as a percentage was more precise than classes. Working in pairs did not improve the estimates, but one botanist repeating the survey is more reliable than a succession of different observers. Conclusion: Lists of species are insufficient for monitoring. It is necessary to add cover estimates to allow for subsequent interpretations in spite of the overlooked species. The choice of the method depends on the available resources: the point method is time consuming but gives precise data for a limited number of species, while visual estimates are quick but allow for recording only large changes in cover. Constant pairs of observers improve the reliability of the records.

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The Hardy-Weinberg law, formulated about 100 years ago, states that under certainassumptions, the three genotypes AA, AB and BB at a bi-allelic locus are expected to occur inthe proportions p2, 2pq, and q2 respectively, where p is the allele frequency of A, and q = 1-p.There are many statistical tests being used to check whether empirical marker data obeys theHardy-Weinberg principle. Among these are the classical xi-square test (with or withoutcontinuity correction), the likelihood ratio test, Fisher's Exact test, and exact tests in combinationwith Monte Carlo and Markov Chain algorithms. Tests for Hardy-Weinberg equilibrium (HWE)are numerical in nature, requiring the computation of a test statistic and a p-value.There is however, ample space for the use of graphics in HWE tests, in particular for the ternaryplot. Nowadays, many genetical studies are using genetical markers known as SingleNucleotide Polymorphisms (SNPs). SNP data comes in the form of counts, but from the countsone typically computes genotype frequencies and allele frequencies. These frequencies satisfythe unit-sum constraint, and their analysis therefore falls within the realm of compositional dataanalysis (Aitchison, 1986). SNPs are usually bi-allelic, which implies that the genotypefrequencies can be adequately represented in a ternary plot. Compositions that are in exactHWE describe a parabola in the ternary plot. Compositions for which HWE cannot be rejected ina statistical test are typically “close" to the parabola, whereas compositions that differsignificantly from HWE are “far". By rewriting the statistics used to test for HWE in terms ofheterozygote frequencies, acceptance regions for HWE can be obtained that can be depicted inthe ternary plot. This way, compositions can be tested for HWE purely on the basis of theirposition in the ternary plot (Graffelman & Morales, 2008). This leads to nice graphicalrepresentations where large numbers of SNPs can be tested for HWE in a single graph. Severalexamples of graphical tests for HWE (implemented in R software), will be shown, using SNPdata from different human populations

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Decline in gait stability has been associated with increased fall risk in older adults. Reliable and clinically feasible methods of gait instability assessment are needed. This study evaluated the relative and absolute reliability and concurrent validity of the testing procedure of the clinical version of the Narrow Path Walking Test (NPWT) under single task (ST) and dual task (DT) conditions. Thirty independent community-dwelling older adults (65-87 years) were tested twice. Participants were instructed to walk within the 6-m narrow path without stepping out. Trial time, number of steps, trial velocity, number of step errors, and number of cognitive task errors were determined. Intraclass correlation coefficients (ICCs) were calculated as indices of agreement, and a graphic approach called "mountain plot" was applied to help interpret the direction and magnitude of disagreements between testing procedures. Smallest detectable change and smallest real difference (SRD) were computed to determine clinically relevant improvement at group and individual levels, respectively. Concurrent validity was assessed using Performance Oriented Mobility Assessment Tool (POMA) and the Short Physical Performance Battery (SPPB). Test-retest agreement (ICC1,2) varied from 0.77 to 0.92 in ST and from 0.78 to 0.92 in DT conditions, with no apparent systematic differences between testing procedures demonstrated by the mountain plot graphs. Smallest detectable change and smallest real change were small for motor task performance and larger for cognitive errors. Significant correlations were observed for trial velocity and trial time with POMA and SPPB. The present results indicate that the NPWT testing procedure is highly reliable and reproducible.

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The cropping system influences the interception of water by plants, water storage in depressions on the soil surface, water infiltration into the soil and runoff. The aim of this study was to quantify some hydrological processes under no tillage cropping systems at the edge of a slope, in 2009 and 2010, in a Humic Dystrudept soil, with the following treatments: corn, soybeans, and common beans alone; and intercropped corn and common bean. Treatments consisted of four simulated rainfall tests at different times, with a planned intensity of 64 mm h-1 and 90 min duration. The first test was applied 18 days after sowing, and the others at 39, 75 and 120 days after the first test. Different times of the simulated rainfall and stages of the crop cycle affected soil water content prior to the rain, and the time runoff began and its peak flow and, thus, the surface hydrological processes. The depth of the runoff and the depth of the water intercepted by the crop + soil infiltration + soil surface storage were affected by the crop systems and the rainfall applied at different times. The corn crop was the most effective treatment for controlling runoff, with a water loss ratio of 0.38, equivalent to 75 % of the water loss ratio exhibited by common bean (0.51), the least effective treatment in relation to the others. Total water loss by runoff decreased linearly with an increase in the time that runoff began, regardless of the treatment; however, soil water content on the gravimetric basis increased linearly from the beginning to the end of the rainfall.

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A method for the screening of tetanus and diphtheria antibodies in serum using anatoxin (inactivated toxin) instead of toxin was developed as an alternative to the in vivo toxin neutralization assay based on the toxin-binding inhibition test (TOBI test). In this study, the serum titers (values between 1.0 and 19.5 IU) measured by a modified TOBI test (Modi-TOBI test) and toxin neutralization assays were correlated (P < 0.0001). Titers of tetanus or diphtheria antibodies were evaluated in serum samples from guinea pigs immunized with tetanus toxoid, diphtheria-tetanus or triple vaccine. For the Modi-TOBI test, after blocking the microtiter plates, standard tetanus or diphtheria antitoxin and different concentrations of guinea pig sera were incubated with the respective anatoxin. Twelve hours later, these samples were transferred to a plate previously coated with tetanus or diphtheria antitoxin to bind the remaining anatoxin. The anatoxin was then detected using a peroxidase-labeled tetanus or diphtheria antitoxin. Serum titers were calculated using a linear regression plot of the results for the corresponding standard antitoxin. For the toxin neutralization assay, L+/10/50 doses of either toxin combined with different concentrations of serum samples were inoculated into mice for anti-tetanus detection, or in guinea pigs for anti-diphtheria detection. Both assays were suitable for determining wide ranges of antitoxin levels. The linear regression plots showed high correlation coefficients for tetanus (r² = 0.95, P < 0.0001) and for diphtheria (r² = 0.93, P < 0.0001) between the in vitro and the in vivo assays. The standardized method is appropriate for evaluating titers of neutralizing antibodies, thus permitting the in vitro control of serum antitoxin levels.

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The Hardy-Weinberg law, formulated about 100 years ago, states that under certain assumptions, the three genotypes AA, AB and BB at a bi-allelic locus are expected to occur in the proportions p2, 2pq, and q2 respectively, where p is the allele frequency of A, and q = 1-p. There are many statistical tests being used to check whether empirical marker data obeys the Hardy-Weinberg principle. Among these are the classical xi-square test (with or without continuity correction), the likelihood ratio test, Fisher's Exact test, and exact tests in combination with Monte Carlo and Markov Chain algorithms. Tests for Hardy-Weinberg equilibrium (HWE) are numerical in nature, requiring the computation of a test statistic and a p-value. There is however, ample space for the use of graphics in HWE tests, in particular for the ternary plot. Nowadays, many genetical studies are using genetical markers known as Single Nucleotide Polymorphisms (SNPs). SNP data comes in the form of counts, but from the counts one typically computes genotype frequencies and allele frequencies. These frequencies satisfy the unit-sum constraint, and their analysis therefore falls within the realm of compositional data analysis (Aitchison, 1986). SNPs are usually bi-allelic, which implies that the genotype frequencies can be adequately represented in a ternary plot. Compositions that are in exact HWE describe a parabola in the ternary plot. Compositions for which HWE cannot be rejected in a statistical test are typically “close" to the parabola, whereas compositions that differ significantly from HWE are “far". By rewriting the statistics used to test for HWE in terms of heterozygote frequencies, acceptance regions for HWE can be obtained that can be depicted in the ternary plot. This way, compositions can be tested for HWE purely on the basis of their position in the ternary plot (Graffelman & Morales, 2008). This leads to nice graphical representations where large numbers of SNPs can be tested for HWE in a single graph. Several examples of graphical tests for HWE (implemented in R software), will be shown, using SNP data from different human populations

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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FUNDAMENTO: O tabagismo altera a função autonômica. OBJETIVO: Investigar os efeitos agudos do tabagismo sobre a modulação autonômica e a recuperação dos índices de variabilidade de frequência cardíaca (VFC) pós-fumo, por meio do plot de Poincaré e índices lineares. MÉTODOS: Foram avaliados 25 fumantes jovens, os quais tiveram a frequência cardíaca analisada, batimento a batimento, na posição sentada, após 8 horas de abstinência, por 30 minutos em repouso, 20 minutos durante o fumo e 30 minutos pós-fumo. Análise de variância para medidas repetidas, seguido do teste de Tukey, ou teste de Friedman seguido do teste de Dunn foram aplicados dependendo da normalidade dos dados, com p < 0,05. RESULTADOS: Durante o fumo, houve redução dos índices SD1 (23,4 ± 9,2 vs 13,8 ± 4,8), razão SD1/SD2 (0,31 ± 0,08 vs 0,2 ± 0,04), RMSSD (32,7 ± 13 vs 19,1 ± 6,8), SDNN (47,6 ± 14,8 vs 35,5 ± 8,4), HFnu (32,5 ± 11,6 vs 19 ± 8,1) e do intervalo RR (816,8 ± 89 vs 696,5 ± 76,3) em relação ao repouso, enquanto que aumentos do índice LFnu (67,5 ± 11,6 vs 81 ± 8,1) e da razão LF/HF (2,6 ± 1,7 vs 5,4 ± 3,1) foram observados. A análise visual do plot mostrou menor dispersão dos intervalos RR durante o fumo. Com exceção da razão SD1/SD2, os demais índices apresentaram recuperação dos valores, 30 minutos após o tabagismo. CONCLUSÃO: O tabagismo produziu agudamente modificações no controle autonômico, caracterizadas por ativação simpática e retirada vagal, com recuperação 30 minutos após o fumo.

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The sugar cane crop is one of the main products in Brazil and according to several authors can generate, besides the industrialized stalks, an amount of crop residues from the order of 15 to 30 % in weight of the aerial part of the plants, depending on the field conditions. The sugar cane area in Brazil is around 5.5×106 hectares, with an amount of 400.106 tons of stalks, with stalks yield of 72 tons.ha-1. This study took place in a sugar cane plot (Latitude 22°46'S, Longitude 47°23'W and 600m of altitude) with 3% of slope, located in São Paulo State. The sugar cane variety was SP 80-1816, in its forth cut, 11 months old and with a planted row spacing of 1.40 m. By other side, several sugar mills are bringing the crop residue to their patio to produce energy with the bagasse. One choice is to bring the crop residue at the same moment with the stalks, avoiding the next operation of baling it. The objective of this study was to analyze some operational parameters of two different sugar cane harvesters under the same field conditions, which was divided in four treatments: T1 = CAMECO CHT2500B operating normally; T2 = CAMECO CHT2500B operating without the cleaning system; T3 = CASE 7700 operating normally; T4 = CASE 7700 operating without the cleaning system. The results obtained were: Table presented CEB = Gross effective capacity; CEL = Net effective capacity. The conclusion is that under normal operation the CASE harvester worked better then CAMECO in the parameters CEL stalks and Manipulation efficiency. And without the cleaning system operating CASE also worked better in the parameters of CEB raw material, CEB stalks, CEL raw material and CEL stalks.

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The Poincaré plot for heart rate variability analysis is a technique considered geometrical and non-linear, that can be used to assess the dynamics of heart rate variability by a representation of the values of each pair of R-R intervals into a simplified phase space that describes the system's evolution. The aim of the present study was to verify if there is some correlation between SD1, SD2 and SD1/SD2 ratio and heart rate variability nonlinear indexes either in disease or healthy conditions. 114 patients with arterial coronary disease and 65 healthy subjects underwent 30. minute heart rate registration, in supine position and the analyzed indexes were as follows: SD1, SD2, SD1/SD2, Sample Entropy, Lyapunov Exponent, Hurst Exponent, Correlation Dimension, Detrended Fluctuation Analysis, SDNN, RMSSD, LF, HF and LF/HF ratio. Correlation coefficients between SD1, SD2 and SD1/SD2 indexes and the other variables were tested by the Spearman rank correlation test and a regression analysis. We verified high correlation between SD1/SD2 index and HE and DFA (α1) in both groups, suggesting that this ratio can be used as a surrogate variable. © 2013 Elsevier B.V.