Cloning and characterization of a novel alternatively spliced transcript of the human CHD7 putative helicase

Abstract Background The CHD7 (Chromodomain Helicase DNA binding protein 7) gene encodes a member of the chromodomain family of ATP-dependent chromatin remodeling enzymes. Mutations in the CHD7 gene are found in individuals with CHARGE, a syndrome characterized by multiple birth malformations in several tissues. CHD7 was identified as a binding partner of PBAF complex (Polybromo and BRG Associated Factor containing complex) playing a central role in the transcriptional reprogramming process associated to the formation of multipotent migratory neural crest, a transient cell population associated with the genesis of various tissues. CHD7 is a large gene containing 38 annotated exons and spanning 200 kb of genomic sequence. Although genes containing such number of exons are expected to have several alternative transcripts, there are very few evidences of alternative transcripts associated to CHD7 to date indicating that alternative splicing associated to this gene is poorly characterized. Findings Here, we report the cloning and characterization by experimental and computational studies of a novel alternative transcript of the human CHD7 (named CHD7 CRA_e), which lacks most of its coding exons. We confirmed by overexpression of CHD7 CRA_e alternative transcript that it is translated into a protein isoform lacking most of the domains displayed by the canonical isoform. Expression of the CHD7 CRA_e transcript was detected in normal liver, in addition to the DU145 human prostate carcinoma cell line from which it was originally isolated. Conclusions Our findings indicate that the splicing event associated to the CHD7 CRA_e alternative transcript is functional. The characterization of the CHD7 CRA_e novel isoform presented here not only sets the basis for more detailed functional studies of this isoform, but, also, contributes to the alternative splicing annotation of the CHD7 gene and the design of future functional studies aimed at the elucidation of the molecular functions of its gene products.

Mixed colonies of two species of congeneric stingless bees (Hymenoptera: Apinae, Meliponini) display environmentally-acquired and endogenously-produced recognition signals

Nestmate recognition is fundamental for the maintenance of social organization in insect nests. It is becoming well recognized that cuticle hydrocarbons mediate the recognition process, although the origin of recognition cues in stingless bees remains poorly explored. The present study investigates the effects of endogenously-produced and environmentally-acquired components in cuticular hydrocarbons in stingless bees. The tests are conducted using colonies of Plebeia droryana Friese and Plebeia remota Holmberg. Recognition tests are performed with four different groups: conspecific nestmates, conspecific non-nestmates, heterospecifics and conspecific, genetically-related individuals that emerge in a heterospecific nest. This last group is produced by introducing brood cells of P. droryana into a P. remota colony, and the resulting adult bees are tested for acceptance 10 days after emergence. For all groups, 15 individuals are sampled for chemical analysis. The results show the acceptance of all conspecific nestmates, and the rejection of almost every conspecific non-nestmate and every heterospecific bee. Genetically-related individuals emerging from heterospecific nests present intermediate rejection (66.7% rejection). Chemical analysis shows that P. droryana individuals emerging in a P. remota nest have small amounts of alkene and diene isomers found in P. remota cuticle that are not found in workers from the natal nest. The data clearly show that the majority of the compounds present in P. droryana cuticle are endogenously produced, although a few unsaturated compounds are acquired from the environment, increasing the chemical differences and, consequently, the rejection percentages.

Petroleum contamination impact on macrobenthic communities under the influence of an oil refinery: Integrating chemical and biological multivariate data

Petroleum contamination impact on macrobenthic communities in the northeast portion of Todos os Santos Bay was assessed combining in multivariate analyses, chemical parameters such as aliphatic and polycyclic aromatic hydrocarbon indices and concentration ratios with benthic ecological parameters. Sediment samples were taken in August 2000 with a 0.05 m(2) van Veen grab at 28 sampling locations. The predominance of n-alkanes with more than 24 carbons, together with CPI values close to one, and the fact that most of the stations showed UCM/resolved aliphatic hydrocarbons ratios (UCM:R) higher than two, indicated a high degree of anthropogenic contribution, the presence of terrestrial plant detritus, petroleum products and evidence of chronic oil pollution. The indices used to determine the origin of PAH indicated the occurrence of a petrogenic contribution. A pyrolytic contribution constituted mainly by fossil fuel combustion derived PAH was also observed. The results of the stepwise multiple regression analysis performed with chemical data and benthic ecological descriptors demonstrated that not only total PAH concentrations but also specific concentration ratios or indices such as >= C24:< C24, An/178 and Fl/Fl + Py, are determining the structure of benthic communities within the study area. According to the BIO-ENV results petroleum related variables seemed to have a main influence on macrofauna community structure. The PCA ordination performed with the chemical data resulted in the formation of three groups of stations. The decrease in macrofauna density, number of species and diversity from groups III to I seemed to be related to the occurrence of high aliphatic hydrocarbon and PAH concentrations associated with fine sediments. Our results showed that macrobenthic communities in the northeast portion of Todos os Santos Bay are subjected to the impact of chronic oil pollution as was reflected by the reduction in the number of species and diversity. These results emphasise the importance to combine in multivariate approaches not only total hydrocarbon concentrations but also indices, isomer pair ratios and specific compound concentrations with biological data to improve the assessment of anthropogenic impact on marine ecosystems. (c) 2008 Elsevier Ltd. All rights reserved.

A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data

In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a user-defined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

The CUPID (Cultural and Psychosocial Influences on Disability) Study: Methods of Data Collection and Characteristics of Study Sample

Background: The CUPID (Cultural and Psychosocial Influences on Disability) study was established to explore the hypothesis that common musculoskeletal disorders (MSDs) and associated disability are importantly influenced by culturally determined health beliefs and expectations. This paper describes the methods of data collection and various characteristics of the study sample. Methods/Principal Findings: A standardised questionnaire covering musculoskeletal symptoms, disability and potential risk factors, was used to collect information from 47 samples of nurses, office workers, and other (mostly manual) workers in 18 countries from six continents. In addition, local investigators provided data on economic aspects of employment for each occupational group. Participation exceeded 80% in 33 of the 47 occupational groups, and after pre-specified exclusions, analysis was based on 12,426 subjects (92 to 1018 per occupational group). As expected, there was high usage of computer keyboards by office workers, while nurses had the highest prevalence of heavy manual lifting in all but one country. There was substantial heterogeneity between occupational groups in economic and psychosocial aspects of work; three-to fivefold variation in awareness of someone outside work with musculoskeletal pain; and more than ten-fold variation in the prevalence of adverse health beliefs about back and arm pain, and in awareness of terms such as "repetitive strain injury" (RSI). Conclusions/Significance: The large differences in psychosocial risk factors (including knowledge and beliefs about MSDs) between occupational groups should allow the study hypothesis to be addressed effectively.

A regional multirnodulus algorithm for blind equalization of QAM signals: Introduction and steady-state analysis

It is well known that constant-modulus-based algorithms present a large mean-square error for high-order quadrature amplitude modulation (QAM) signals, which may damage the switching to decision-directed-based algorithms. In this paper, we introduce a regional multimodulus algorithm for blind equalization of QAM signals that performs similar to the supervised normalized least-mean-squares (NLMS) algorithm, independently of the QAM order. We find a theoretical relation between the coefficient vector of the proposed algorithm and the Wiener solution and also provide theoretical models for the steady-state excess mean-square error in a nonstationary environment. The proposed algorithm in conjunction with strategies to speed up its convergence and to avoid divergence can bypass the switching mechanism between the blind mode and the decision-directed mode. (c) 2012 Elsevier B.V. All rights reserved.

Vaginal progesterone in women with an asymptomatic sonographic short cervix in the midtrimester decreases preterm delivery and neonatal morbidity: a systematic review and metaanalysis of individual patient data

OBJECTIVE: To determine whether the use of vaginal progesterone in asymptomatic women with a sonographic short cervix (<= 25 mm) in the midtrimester reduces the risk of preterm birth and improves neonatal morbidity and mortality. STUDY DESIGN: Individual patient data metaanalysis of randomized controlled trials. RESULTS: Five trials of high quality were included with a total of 775 women and 827 infants. Treatment with vaginal progesterone was associated with a significant reduction in the rate of preterm birth <33 weeks (relative risk [RR], 0.58; 95% confidence interval [CI], 0.42-0.80), <35 weeks (RR, 0.69; 95% CI, 0.55-0.88), and <28 weeks (RR, 0.50; 95% CI, 0.30-0.81); respiratory distress syndrome (RR, 0.48; 95% CI, 0.30-0.76); composite neonatal morbidity and mortality (RR, 0.57; 95% CI, 0.40-0.81); birthweight <1500 g (RR, 0.55; 95% CI, 0.38-0.80); admission to neonatal intensive care unit (RR, 0.75; 95% CI, 0.59-0.94); and requirement for mechanical ventilation (RR, 0.66; 95% CI, 0.44-0.98). There were no significant differences between the vaginal progesterone and placebo groups in the rate of adverse maternal events or congenital anomalies. CONCLUSION: Vaginal progesterone administration to asymptomatic women with a sonographic short cervix reduces the risk of preterm birth and neonatal morbidity and mortality.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Wilson’s disease in Southern Brazil: genotype-phenotype correlation and description of two novel mutations in ATP7B gene

OBJECTIVE: Wilson's disease (WD) is an inborn error of metabolism caused by abnormalities of the copper-transporting protein encoding gene ATP7B. In this study, we examined ATP7B for mutations in a group of patients living in southern Brazil. METHODS: 36 WD subjects were studied and classified according to their clinical and epidemiological data. In 23 subjects the ATP7B gene was analyzed. RESULTS: Fourteen distinct mutations were detected in at least one of the alleles. The c.3207C>A substitution at exon 14 was the most common mutation (allelic frequency=37.1%) followed by the c.3402delC at exon 15 (allelic frequency=11.4%). The mutations c.2018-2030del13 at exon 7 and c.4093InsT at exon 20 are being reported for the first time. CONCLUSION: The c.3207C>A substitution at exon 14, was the most common mutation, with an allelic frequency of 37.1%. This mutation is the most common mutation described in Europe.