Intra- and interspecific divergence in the nuclear sequences of the clock gene period in species of the Drosophila buzzatii cluster

We have measured nucleotide variation in the CLOCK/CYCLE heterodimer inhibition domain (CCID) of the clock X-linked gene period in seven species belonging to the Drosophila buzzatii cluster, namely D. buzzatii, Drosophila koepferae, Drosophila antonietae, Drosophila serido, Drosophila gouveai, Drosophila seriema and Drosophila borborema. We detected that the purifying selection is the main force driving the sequence evolution in period, in agreement with the important role of CCID in clock machinery. Our survey revealed that period provides valuable phylogenetic information that allowed to resolve phylogenetic relationships among D. gouveai, D. borborema and D. seriema, which composed a polytomic clade in preliminary studies. The analysis of patterns of intraspecific variation revealed two different lineages of period in D. koepferae, probably reflecting introgressive hybridization from D. buzzatii, in concordance with previous molecular data.

Allozymatic divergence between border populations of two cryptic species of the Drosophila buzzatii cluster species (Diptera: Drosophilidae)

Drosophila antonietae and Drosophila gouveai are allopatric, cactophilic, cryptic and endemic of South America species, which aedeagus morphology is considered the main diagnostic character. In this work, single close populations from the edge distributions of each species, located in an ""introgressive corridor"", were analyzed regarding temporal isozenzymatic genetic variability. Isocitrate dehydrogenase (Idh) appeared as a diagnostic locus between D. antonieate and D. gouveai because each population was fixed for different alleles. Moreover, several polymorphic loci showed accentuated divergence in the allele frequency, as evidenced by Nei`s l(0.3188) and D (1.1432), and also by Reynolds` genetic distance and identity (1.3207 and 0.7331, respectively). Our results showed that, in spite of the very similar external morphology, related evolutionary histories, close distributions, and events of introgression in the studied area, these cryptic species have high allozymatic differentiation, and this is discussed here. (C) 2010 Elsevier Ltd. All rights reserved.

On recent developments in the theory of abstract differential equations with fractional derivatives

This note is motivated from some recent papers treating the problem of the existence of a solution for abstract differential equations with fractional derivatives. We show that the existence results in [Agarwal et al. (2009) [1], Belmekki and Benchohra (2010) [2], Darwish et al. (2009) [3], Hu et al. (2009) [4], Mophou and N`Guerekata (2009) [6,7], Mophou (2010) [8,9], Muslim (2009) [10], Pandey et al. (2009) [11], Rashid and El-Qaderi (2009) [12] and Tai and Wang (2009) [13]] are incorrect since the considered variation of constant formulas is not appropriate. In this note, we also consider a different approach to treat a general class of abstract fractional differential equations. (C) 2010 Elsevier Ltd. All rights reserved.

Refractory cluster headache in a patient with bruxism and obstructive sleep apnea: a case report

Introduction This is a case report of a 39-year-old patient with a 14-year history of clinically refractory cluster headache (CH), also presenting obstructive sleep apnea (OSA) and complaining of tooth-grinding during sleep. Discussion Treatment of OSA with an intra-oral device allowed an immediate reduction in frequency and intensity of CH events. Furthermore, CH attacks did not occur during the 12-month follow-up period.

Pentoxifylline modifies three-dimensional collagen lattice model contraction and expression of collagen types I and III by human fibroblasts derived from post-burn hypertrophic scars and from normal skin

Fibroblasts are thought to be partially responsible for the persisting contractile forces that result in burn contractures. Using a monolayer cell culture and fibroblast populated collagen lattice (FPCL) three-dimensional model we subjected hypertrophic scar and non-cicatricial fibroblasts to the antifibrogenic agent pentoxifylline (PTF - 1 mg/mL) in order to reduce proliferation, collagen types I and III synthesis and model contraction. Fibroblasts were isolated from post-burn hypertrophic scars (HSHF) and non-scarred skin (NHF). Cells were grown in monolayers or incorporated into FPCL`s and exposed to PTF. In monolayer, cell number proliferation was reduced (46.35% in HSHF group and 37.73% in NHF group, p < 0.0001). PTF selectively inhibited collagen III synthesis in the HSHF group while inhibition was more evident to type I collagen synthesis in the NHF group. PTF also reduced contraction in both (HSHF and NHF) FPCL. (C) 2009 Elsevier Ltd and ISBI. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

ADHD in a representative sample of the Brazilian population: estimated prevalence and comparative adequacy of criteria between adolescents and adults according to the item response theory

Background: Attention deficit hyperactivity disorder (ADHD) is a clinically significant disorder in adulthood, but current diagnostic criteria and instruments do not seem to adequately capture the complexity of the disorder in this developmental phase. Accordingly, there are limited data on the proportion of adults affected by the disorder, specially in developing countries. Method: We assessed a representative household sample of the Brazilian population for ADHD with the Adult ADHD Self-report Scale (ASRS) Screener, and evaluated the instrument according to the Rasch model of item response theory. Results: The sample was comprised by 3007 individuals, and the overal prevalence of positive screeners for ADHD was 5.8% [95% confidence interval (CI), 4.8-7.0]. Rasch analyses revealed the misfitt of the overall sample to expectations of the model. The evaluation of the sample stratified by age revealed that data for adolescents showed a signficant fittnes to the model expectations, while items completed by adults were not adequated. Conclusions: The lack of fitness to the model for adult respondents challenges the possibility of a linear transformation of the ordinal data into interval measures and the utilization of parametric analyses of data. This result suggests that diagnostic criteria and instruments for adult ADHD must take into account a developmental perspective. Moreover, it calls for further evaluation of currently employed research methods in light of modern theories of psychometrics. Copyright (C) 2010 John Wiley & Sons, Ltd.

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.