Disequilibrium Coefficient: A Bayesian Perspective

Hardy-Weinberg Equilibrium (HWE) is an important genetic property that populations should have whenever they are not observing adverse situations as complete lack of panmixia, excess of mutations, excess of selection pressure, etc. HWE for decades has been evaluated; both frequentist and Bayesian methods are in use today. While historically the HWE formula was developed to examine the transmission of alleles in a population from one generation to the next, use of HWE concepts has expanded in human diseases studies to detect genotyping error and disease susceptibility (association); Ryckman and Williams (2008). Most analyses focus on trying to answer the question of whether a population is in HWE. They do not try to quantify how far from the equilibrium the population is. In this paper, we propose the use of a simple disequilibrium coefficient to a locus with two alleles. Based on the posterior density of this disequilibrium coefficient, we show how one can conduct a Bayesian analysis to verify how far from HWE a population is. There are other coefficients introduced in the literature and the advantage of the one introduced in this paper is the fact that, just like the standard correlation coefficients, its range is bounded and it is symmetric around zero (equilibrium) when comparing the positive and the negative values. To test the hypothesis of equilibrium, we use a simple Bayesian significance test, the Full Bayesian Significance Test (FBST); see Pereira, Stern andWechsler (2008) for a complete review. The disequilibrium coefficient proposed provides an easy and efficient way to make the analyses, especially if one uses Bayesian statistics. A routine in R programs (R Development Core Team, 2009) that implements the calculations is provided for the readers.

Orbitofrontal Cortex Volumes in Medication Naive Children with Major Depressive Disorder: A Magnetic Resonance Imaging Study

Objectives: Adults with major depressive disorder (MDD) are reported to have reduced orbitofrontal cortex (OFC) volumes, which could be related to decreased neuronal density. We conducted a study on medication naive children with MDD to determine whether abnormalities of OFC are present early in the illness course. Methods: Twenty seven medication naive pediatric Diagnostic and Statistical Manual of Mental Disorders, 4(th) edition (DSM-IV) MDD patients (mean age +/- SD = 14.4 +/- 2.2 years; 10 males) and 26 healthy controls (mean age +/- SD = 14.4 +/- 2.4 years; 12 males) underwent a 1.5T magnetic resonance imaging (MRI) with 3D spoiled gradient recalled acquisition. The OFC volumes were compared using analysis of covariance with age, gender, and total brain volume as covariates. Results: There was no significant difference in either total OFC volume or total gray matter OFC volume between MDD patients and healthy controls. Exploratory analysis revealed that patients had unexpectedly larger total right lateral (F = 4.2, df = 1, 48, p = 0.05) and right lateral gray matter (F = 4.6, df = 1, 48, p = 0.04) OFC volumes compared to healthy controls, but this finding was not significant following statistical correction for multiple comparisons. No other OFC subregions showed a significant difference. Conclusions: The lack of OFC volume abnormalities in pediatric MDD patients suggests the abnormalities previously reported for adults may develop later in life as a result of neural cell loss.

Determination of Threshold Dose of Photodynamic Therapy to Measure Superficial Necrosis

Background Data: Photodynamic therapy (PDT) involves the photoinduction of cytotoxicity using a photosensitizer agent, a light source of the proper wavelength, and the presence of molecular oxygen. A model for tissue response to PDT based on the photodynamic threshold dose (Dth) has been widely used. In this model cells exposed to doses below Dth survive while at doses above the Dth necrosis takes place. Objective: This study evaluated the light Dth values by using two different methods of determination. One model concerns the depth of necrosis and the other the width of superficial necrosis. Materials and Methods: Using normal rat liver we investigated the depth and width of necrosis induced by PDT when a laser with a gaussian intensity profile is used. Different light doses, photosensitizers (Photogem, Photofrin, Photosan, Foscan, Photodithazine, and Radachlorin), and concentrations were employed. Each experiment was performed on five animals and the average and standard deviations were calculated. Results: A simple depth and width of necrosis model analysis allows us to determine the threshold dose by measuring both depth and surface data. Comparison shows that both measurements provide the same value within the degree of experimental error. Conclusion: This work demonstrates that by knowing the extent of the superficial necrotic area of a target tissue irradiated by a gaussian light beam, it is possible to estimate the threshold dose. This technique may find application where the determination of Dth must be done without cutting the tissue.

Hypothalamic-pituitary axis and peripheral tissue responses to TRH stimulation and Liothyronine suppression tests in normal subjects evaluated by current methods

Objective: To reevaluate the responses of thyrotropin-releasing hormone ( TRH) stimulation test in baseline condition as well as after the administration of graded supraphysiological doses of liothyronine ( L- T-3) in normal subjects. Design: To assess various parameters related to the hypothalamic-pituitary axis and peripheral tissue responses to L- T-3 in 22 normal individuals ( median age: 30.5 years). Subjects were submitted to an intravenous TRH test at baseline condition and also to the oral administration of sequential and graded doses of L- T-3 ( 50, 100, and 200 mu g/day), each given over 3 days, at an outpatient clinic. Blood samples were obtained for thyrotropin (TSH) and prolactin (PRL) at basal and then 15, 30, and 60 minutes after the TRH injection. Effects of L- T3 administration on cholesterol, creatine kinase, retinol, ferritin, and sex hormone-binding globulin ( SHBG) were also measured at basal and after the oral administration of L- T-3. Main outcome: TRH administration resulted in an increase of 4-to 14-fold rise in serum TSH ( 8.3 +/- 2.5-fold), and in a slight rise in serum PRL concentrations ( 3.8 +/- 1.5-fold). Administration of graded doses of triiodothyronine ( T-3) resulted in a dose-dependent suppression of TSH and PRL. Basal thyroxine- binding globulin (TBG) and cholesterol levels decreased, and ferritin and SHBG increased after L- T-3 administration, while creatine kinase and retinol did not change throughout the study. There was a positive correlation between basal TSH and TSH peak response to TRH at basal condition and after each sequential L- T-3 doses. On the other hand, TSH peak response to the TRH test did not predict cholesterol, TBG, ferritin, or SHBG values. Conclusion: Using the current methods on hormone and biochemical analysis, we standardized the response of many parameters to TRH stimulation test after sequential and graded T-3 suppression test in normal subjects. Our data suggest that the evaluation of the responses of the hypothalamus-pituitary axis to TRH test as well as the impact of L- T-3 on peripheral tissues were not modified by the current methods.

Reciprocal Modulation of Cognitive and Emotional Aspects in Pianistic Performances

Background: High level piano performance requires complex integration of perceptual, motor, cognitive and emotive skills. Observations in psychology and neuroscience studies have suggested reciprocal inhibitory modulation of the cognition by emotion and emotion by cognition. However, it is still unclear how cognitive states may influence the pianistic performance. The aim of the present study is to verify the influence of cognitive and affective attention in the piano performances. Methods and Findings: Nine pianists were instructed to play the same piece of music, firstly focusing only on cognitive aspects of musical structure (cognitive performances), and secondly, paying attention solely on affective aspects (affective performances). Audio files from pianistic performances were examined using a computational model that retrieves nine specific musical features (descriptors) - loudness, articulation, brightness, harmonic complexity, event detection, key clarity, mode detection, pulse clarity and repetition. In addition, the number of volunteers' errors in the recording sessions was counted. Comments from pianists about their thoughts during performances were also evaluated. The analyses of audio files throughout musical descriptors indicated that the affective performances have more: agogics, legatos, pianos phrasing, and less perception of event density when compared to the cognitive ones. Error analysis demonstrated that volunteers misplayed more left hand notes in the cognitive performances than in the affective ones. Volunteers also played more wrong notes in affective than in cognitive performances. These results correspond to the volunteers' comments that in the affective performances, the cognitive aspects of piano execution are inhibited, whereas in the cognitive performances, the expressiveness is inhibited. Conclusions: Therefore, the present results indicate that attention to the emotional aspects of performance enhances expressiveness, but constrains cognitive and motor skills in the piano execution. In contrast, attention to the cognitive aspects may constrain the expressivity and automatism of piano performances.

Esophageal Ulcer in Brazilian Patients with HIV: Prevalence and Comparative Analysis Among Diagnostic Methods

Esophageal ulcer (EU) represents an important comorbidity in AIDS. We evaluated the prevalence of EU, the accuracy of the endoscopic and histologic methods used to investigate viral EU in HIV-positive Brazilian patients and the numerical relevance of tissue sampling. A total of 399 HIV-positive patients underwent upper gastrointestinal (UGI) endoscopy. HIV-positive patients with EU determined by UGI endoscopy followed by biopsies were analyzed by the hematoxylin-eosin (HE) and immunohistochemical (IH) methods. EU was detected in 41 patients (mean age, 39.2 years; 23 males), with a prevalence of 10.27%. The median CD4 count was 49 cells/mm(3) (range, 1-361 cells/mm(3)) and the viral load was 58,869 copies per milliliter (range, 50-77,3290 copies per milliliter). UGI endoscopy detected 29 of 41 EU suggestive of cytomegalovirus (CMV) infection and 7 of 41 indicating herpes simplex virus (HSV) infection. HE histology confirmed 4 of 29 ulcers induced by CMV, 2 of 7 induced by HSV, and 1 of 7 induced by HSV plus CMV. IH for CMV and HSV confirmed the HE findings and detected one additional CMV-induced case. UGI endoscopy showed 100% sensitivity and 15% specificity for the diagnosis of EU due to CMV or HSV compared to HE and IH. HE proved to be an adequate method for etiologic evaluation, with 87% sensitivity and 100% specificity compared to IH. The number of samples did not influence the etiologic evaluation. The data support the importance of IH as a complementary method for HE in the diagnosis of EU of viral etiology.

PAR evaluation of treated Class I extraction patients

Objective: To evaluate treatment changes and quality of finishing occlusion in Class I patients treated with four premolar extractions. Material and Methods: Dental casts of 94 subjects (50 males and 44 females) were evaluated. Mean pretreatment age was 13.46 years, and mean treatment time was 2.09 years. The peer assessment rating (PAR) index was obtained from pretreatment and posttreatment dental casts. Results: The mean pretreatment PAR index of 29.46 was reduced to 6.32 at posttreatment stage, achieving a reduction of 78.54% with treatment. There was correlation between the initial PAR and correction during treatment, that is, the more severe the malocclusion the greater the treatment changes. Conclusion: The cases evaluated showed a high-standard orthodontic finishing.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

uvby-beta photometry of solar twins The solar colors, model atmospheres, and the T(eff) and metallicity scales

Aims. Solar colors have been determined on the uvby-beta photometric system to test absolute solar fluxes, to examine colors predicted by model atmospheres as a function of stellar parameters (T(eff), log g, [Fe/H]), and to probe zero-points of T(eff) and metallicity scales. Methods. New uvby-beta photometry is presented for 73 solar-twin candidates. Most stars of our sample have also been observed spectroscopically to obtain accurate stellar parameters. Using the stars that most closely resemble the Sun, and complementing our data with photometry available in the literature, the solar colors on the uvby-beta system have been inferred. Our solar colors are compared with synthetic solar colors computed from absolute solar spectra and from the latest Kurucz (ATLAS9) and MARCS model atmospheres. The zero-points of different T(eff) and metallicity scales are verified and corrections are proposed. Results. Our solar colors are (b - y)(circle dot) = 0.4105 +/- 0.0015, m(1,circle dot) = 0.2122 +/- 0.0018, c(1,circle dot) = 0.3319 +/- 0.0054, and beta(circle dot) = 2.5915 +/- 0.0024. The (b - y)(circle dot) and m(1,circle dot) colors obtained from absolute spectrophotometry of the Sun agree within 3-sigma with the solar colors derived here when the photometric zero-points are determined from either the STIS HST observations of Vega or an ATLAS9 Vega model, but the c(1,circle dot) and beta(circle dot) synthetic colors inferred from absolute solar spectra agree with our solar colors only when the zero-points based on the ATLAS9 model are adopted. The Kurucz solar model provides a better fit to our observations than the MARCS model. For photometric values computed from the Kurucz models, (b - y)(circle dot) and m(1,circle dot) are in excellent agreement with our solar colors independently of the adopted zero-points, but for c(1,circle dot) and beta circle dot agreement is found only when adopting the ATLAS9 zero-points. The c(1,circle dot) color computed from both the Kurucz and MARCS models is the most discrepant, probably revealing problems either with the models or observations in the u band. The T(eff) calibration of Alonso and collaborators has the poorest performance (similar to 140 K off), while the relation of Casagrande and collaborators is the most accurate (within 10 K). We confirm that the Ramirez & Melendez uvby metallicity calibration, recommended by Arnadottir and collaborators to obtain [Fe/H] in F, G, and K dwarfs, needs a small (similar to 10%) zero-point correction to place the stars and the Sun on the same metallicity scale. Finally, we confirm that the c(1) index in solar analogs has a strong metallicity sensitivity.

Espacialização da temperatura do ar anual no estado de Alagoas com diferentes modelos digitais de elevação e resoluções espaciais

The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

Comparative analysis of two sampling techniques for pollen gathered by Nannotrigona testaceicornis Lepeletier (Apidae, Meliponini)

Pollen counts from samples taken from storage pots throughout one year (from October to September) were adjusted by Tasei's volumetric correction coefficient for the determination of pollen sources exploited by two colonies of Nannotrigona testaceicornis in Sao Paulo, Brazil. The results obtained by this sampling technique for seven months (December to June) were compared with those from corbicula load samples taken within the same period. This species visited a large variety of plant species, but few of them were frequently used. As a rule, pollen sources that appeared at frequencies greater than 1% were found with both sampling methods and significant positive correlations (Spearman correlation coefficient) were found between their values. The pollen load sample data showed that N. testaceicornis gathered pollen throughout the external activity period.

Lossless filter for multiple repeats with bounded edit distance

Background: Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results: The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion: To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

LATENT RANK CHANGE DETECTION FOR ANALYSIS OF SPLICE-JUNCTION MICROARRAYS WITH NONLINEAR EFFECTS

Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over-or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.

Evaluation of grinding methods for pellets preparation aiming at the analysis of plant materials by laser induced breakdown spectrometry

It has been demonstrated that laser induced breakdown spectrometry (LIBS) can be used as an alternative method for the determination of macro (P, K. Ca, Mg) and micronutrients (B, Fe, Cu, Mn, Zn) in pellets of plant materials. However, information is required regarding the sample preparation for plant analysis by LIBS. In this work, methods involving cryogenic grinding and planetary ball milling were evaluated for leaves comminution before pellets preparation. The particle sizes were associated to chemical sample properties such as fiber and cellulose contents, as well as to pellets porosity and density. The pellets were ablated at 30 different sites by applying 25 laser pulses per site (Nd:YAG@1064 nm, 5 ns, 10 Hz, 25J cm(-2)). The plasma emission collected by lenses was directed through an optical fiber towards a high resolution echelle spectrometer equipped with an ICCD. Delay time and integration time gate were fixed at 2.0 and 4.5 mu s, respectively. Experiments carried out with pellets of sugarcane, orange tree and soy leaves showed a significant effect of the plant species for choosing the most appropriate grinding conditions. By using ball milling with agate materials, 20 min grinding for orange tree and soy, and 60 min for sugarcane leaves led to particle size distributions generally lower than 75 mu m. Cryogenic grinding yielded similar particle size distributions after 10 min for orange tree, 20 min for soy and 30 min for sugarcane leaves. There was up to 50% emission signal enhancement on LIBS measurements for most elements by improving particle size distribution and consequently the pellet porosity. (C) 2011 Elsevier B.V. All rights reserved.