Evaluation of algorithms used to order markers on genetic maps

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

Classification of individuals with dyslipidaemia controlled by statins according to plasma biomarkers of oxidative stress using cluster analysis

Oxidative stress is a physiological condition that is associated with atherosclerosis. and it can be influenced by diet. Our objective was to group fifty-seven individuals with dyslipidaemia controlled by statins according to four oxidative biomarkers, and to evaluate the diet pattern and blood biochemistry differences between these groups. Blood samples were collected and the following parameters were evaluated: diet intake; plasma fatty acids; lipoprotein concentration; glucose; oxidised LDL (oxLDL); malondialdehyde (MDA): total antioxidant activity by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing ability power assays. Individuals were separated into five groups by cluster analysis. All groups showed a difference with respect to at least one of the four oxidative stress biomarkers. The separation of individuals in the first axis was based upon their total antioxidant activity. Clusters located on the right side showed higher total antioxidant activity, higher myristic fatty acid and lower arachidonic fatty acid proportions than clusters located on the left side. A negative correlation was observed between DPPH and the peroxidability index. The second axis showed differences in oxidation status as measured by MDA and oxLDL concentrations. Clusters located on the Upper side showed higher oxidative status and lower HDL cholesterol concentration than clusters located on the lower side. There were no differences in diet among the five clusters. Therefore, fatty acid synthesis and HDL cholesterol concentration seem to exert a more significant effect on the oxidative conditions of the individuals with dyslipidaemia controlled by statins than does their food intake.

Probing the electronic delocalization in a cyclic pyrazine ruthenium cluster hexamer

[Ru(3)O(CH(3)COO)(6)(pz)(CO)](6) is a cyclic hexamer species encompassing six triangular ruthenium cluster centers bridged by pyrazine ligands. The electronic communication among the cluster units strongly depends on their oxidation states, and has been successfully probed by means of cyclic voltammetry and UV-vis spectroelectrochemistry. (C) 2010 Elsevier B.V. All rights reserved.

Sequence analysis, chromosomal distribution and long-range organization show that rapid turnover of new and old pBuM satellite DNA repeats leads to different patterns of variation in seven species of the Drosophila buzzatii cluster

We aimed to study patterns of variation and factors influencing the evolutionary dynamics of a satellite DNA, pBuM, in all seven Drosophila species from the buzzatii cluster (repleta group). We analyzed 117 alpha pBuM-1 (monomer length 190 bp) and 119 composite alpha/beta (370 bp) pBuM-2 repeats and determined the chromosome location and long-range organization on DNA fibers of major sequence variants. Such combined methodologies in the study of satDNAs have been used in very few organisms. In most species, concerted evolution is linked to high copy number of pBuM repeats. Species presenting low-abundance and scattered distributed pBuM repeats did not undergo concerted evolution and maintained part of the ancestral inter-repeat variability. The alpha and alpha/beta repeats colocalized in heterochromatic regions and were distributed on multiple chromosomes, with notable differences between species. High-resolution FISH revealed array sizes of a few kilobases to over 0.7 Mb and mutual arrangements of alpha and alpha/beta repeats along the same DNA fibers, but with considerable changes in the amount of each variant across species. From sequence, chromosomal and phylogenetic data, we could infer that homogenization and amplification events involved both new and ancestral pBuM variants. Altogether, the data on the structure and organization of the pBuM satDNA give insights into genome evolution including mechanisms that contribute to concerted evolution and diversification.

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.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

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.

Most of the patients presenting myocardial infarction would not be eligible for intensive lipid-lowering based on clinical algorithms or plasma C-reactive protein

Objective: The study we assessed how often patients who are manifesting a myocardial infarction (MI) would not be considered candidates for intensive lipid-lowering therapy based on the current guidelines. Methods: In 355 consecutive patients manifesting ST elevation MI (STEMI), admission plasma C-reactive protein (CRP) was measured and Framingham risk score (FRS), PROCAM risk score, Reynolds risk score, ASSIGN risk score, QRISK, and SCORE algorithms were applied. Cardiac computed tomography and carotid ultrasound were performed to assess the coronary artery calcium score (CAC), carotid intima-media thickness (cIMT) and the presence of carotid plaques. Results: Less than 50% of STEMI patients would be identified as having high risk before the event by any of these algorithms. With the exception of FRS (9%), all other algorithms would assign low risk to about half of the enrolled patients. Plasma CRP was <1.0 mg/L in 70% and >2 mg/L in 14% of the patients. The average cIMT was 0.8 +/- 0.2 mm and only in 24% of patients was >= 1.0 mm. Carotid plaques were found in 74% of patients. CAC > 100 was found in 66% of patients. Adding CAC >100 plus the presence of carotid plaque, a high-risk condition would be identified in 100% of the patients using any of the above mentioned algorithms. Conclusion: More than half of patients manifesting STEMI would not be considered as candidates for intensive preventive therapy by the current clinical algorithms. The addition of anatomical parameters such as CAC and the presence of carotid plaques can substantially reduce the CVD risk underestimation. (C) 2010 Elsevier Ireland Ltd. 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.

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.

Shared and Unique Gene Expression in Systemic Lupus Erythematosus Depending on Disease Activity

Patients presenting with active Systemic lupus erythematosus (SLE) manifestations may exhibit distinct pathogenetic features in relation to inactive SLE. Also, cDNA microarrays may potentially discriminate the gene expression profile of a disease or disease variant. Therefore, we evaluated the expression profile of 4500 genes in peripheral blood lymphocytes (PBL) of SLE patients. We studied 11 patients with SLE (seven with active SLE and four with inactive SLE) and eight healthy controls. Total RNA was isolated from PBL, reverse transcribed into cDNA, and postlabeled with Cy3 fluorochrome. These probes were then hybridized to a glass slide cDNA microarray containing 4500 human IMAGE cDNA target sequences. An equimolar amount of total RNA from human cell lines served as reference. The microarray images were quantified, normalized, and analyzed using the R environment (ANOVA, significant analysis of microarrays, and cluster-tree view algorithms). Disease activity was assessed by the SLE disease activity index. Compared to the healthy controls, 104 genes in active SLE patients (80 repressed and 24 induced) and 52 genes in nonactive SLE patients (31 induced and 21 repressed) were differentially expressed. The modulation of 12 genes, either induced or repressed, was found in both disease variants; however, each disease variant had differential expression of different genes. Taken together, these results indicate that the two lupus variants studied have common and unique differentially expressed genes. Although the biological significance of the differentially expressed genes discussed above has not been completely understood, they may serve as a platform to further explore the molecular basis of immune deregulation in SLE.

Under-reporting of energy intake is more prevalent in a healthy dietary pattern cluster

The aim of the present study was to determine whether under-reporting rates vary between dietary pattern Clusters. Subjects were sixty-five Brazilian women. During 3 weeks, anthropometric data were collected. total energy expenditure (TEE) was determined by the doubly labelled water method and diet Was Measured. Energy intake (El) and the daily frequency of consumption per 1000 kJ of twenty-two food groups were obtained from a FFQ. These frequencies were entered into a Cluster analysis procedure in order to obtain dietary patterns. Under-reporters were defined Lis those who did not lose more than 1 kg of body weight during the study and presented EI:TEE less than 0.82. Three dietary pattern clusters were identified and named according to their most recurrent food groups: sweet foods (SW). starchy foods (ST) and health), (H). Subjects from the healthy cluster had the lowest mean EI:TEE (SW = 0.86, ST = 0.71 and H = 0.58: P = 0.003) and EI - TEE (SW = -0.49 MJ, ST = - 3.20 MJ and H = -5.09 MJ; P = 0.008). The proportion of Under-reporters was 45.2 (95 % CI 35.5, 55.0) % in the SW Cluster: 58.3 (95 % CI 48.6, 68.0) % in the ST Cluster and 70.0 (95 % CI 61.0, 79) % in the H cluster (P=0.34). Thus, in Brazilian women, Under-reporting of El is not uniformly distributed among, dietary pattern clusters and tends to be more severe among subjects from the healthy cluster. This cluster is more consistent with both dietary guidelines and with what lay individuals usually consider `healthy eating`.

The embedded cluster DBSB 48 in the nebula Hoffleit 18: Comparison with Trumpler 14

We derive fundamental parameters of the embedded cluster DBSB 48 in the southern nebula Hoffleit 18 and the very young open cluster Trumpler 14, by means of deep JHK(s) infrared photometry. We build colour-magnitude and colour-colour diagrams to derive reddening and age, based on main sequence and pre-main sequence distributions. Radial stellar density profiles are used to study cluster structure and guide photometric diagram extractions. Field-star decontamination is applied to uncover the intrinsic cluster sequences in the diagrams. Ages are inferred from K-excess fractions. A prominent pre-main sequence population is present in DBSB 48, and the K-excess fraction f(K) = 55 +/- 6% gives an age of 1.1 +/- 0.5 Myr. A mean reddening of A(Ks) = 0.9 +/- 0.03 was found, corresponding to A(v) = 8.2 +/- 0.3. The cluster CMD is consistent with the far kinematic distance of 5 kpc for Hoffleit 18. For Trumpler 14 we derived similar parameters as in previous studies in the optical, in particular an age of 1.7 +/- 0.7 Myr. The fraction of stars with infrared excess in Trumpler 14 is f(K) = 28 +/- 4%. Despite the young ages, both clusters are described by a King profile with core radii R-core = 0.46 +/- 0.05 pc and R-core = 0.35 +/- 0.04 pc, respectively, for DBSB 48 and Trumpler 14. Such cores are smaller than those of typical open clusters. Small cores are probably related to the cluster formation and/or parent molecular cloud fragmentation. In DBSB 48, the magnitude extent of the upper main sequence is Delta K-s approximate to 2 mag, while in Trumpler 14 it is Delta K-s approximate to 5 mag, consistent with the estimated ages. (c) 2008 Elsevier B.V. All rights reserved.

The old metal-poor open cluster ESO 92-SC05: accreted from a dwarf galaxy ?

The study of old open clusters outside the solar circle can bring constraints on formation scenarios of the outer disc. In particular, accretion of dwarf galaxies has been proposed as a likely mechanism in the area. We use BVI photometry for determining fundamental parameters of the faint open cluster ESO 92-SC05. Colour-magnitude diagrams are compared with Padova isochrones, in order to derive age, reddening and distance. We derive a reddening E(B - V) = 0.17, and an old age of similar to 6.0 Gyr. It is one of the rare open clusters known to be older than 5 Gyr. A metallicity of Z similar to 0.004 or [M/H] similar to -0.7 is found. The rather low metallicity suggests that this cluster might be the result of an accretion episode of a dwarf galaxy.