Integrating structural variant calling, annotation and prioritization into whole genome analysis workflows: a practical application in the molecular diagnosis of neurodevelopmental disorders

Background: WGS is increasingly used as a first-line diagnostic test for patients with rare genetic diseases such as neurodevelopmental disorders (NDD). Clinical applications require a robust infrastructure to support processing, storage and analysis of WGS data. The identification and interpretation of SVs from WGS data also needs to be improved. Finally, there is a need for a prioritization system that enables downstream clinical analysis and facilitates data interpretation. Here, we present the results of a clinical application of WGS in a cohort of patients with NDD. Methods: We developed highly portable workflows for processing WGS data, including alignment, quality control, and variant calling of SNVs and SVs. A benchmark analysis of state-of-the-art SV detection tools was performed to select the most accurate combination for SV calling. A gene-based prioritization system was also implemented to support variant interpretation. Results: Using a benchmark analysis, we selected the most accurate combination of tools to improve SV detection from WGS data and build a dedicated pipeline. Our workflows were used to process WGS data from 77 NDD patient-parent families. The prioritization system supported downstream analysis and enabled molecular diagnosis in 32% of patients, 25% of which were SVs and suggested a potential diagnosis in 20% of patients, requiring further investigation to achieve diagnostic certainty. Conclusion: Our data suggest that the integration of SNVs and SVs is a main factor that increases diagnostic yield by WGS and show that the adoption of a dedicated pipeline improves the process of variant detection and interpretation.

[strategies For Integration Of Health Care Practices And Sanitary Surveillance In The Context Of The Implementation Of Rede Cegonha - A Brazilian Mother And Infant Health Care Network].

Mother and infant mortality has been the scope of analysis throughout the history of public health in Brazil and various strategies to tackle the issue have been proposed to date. The Ministry of Health has been working on this and the Rede Cegonha strategy is the most recent policy in this context. Given the principle of comprehensive health care and the structure of the Unified Health System in care networks, it is necessary to ensure the integration of health care practices, among which are the sanitary surveillance actions (SSA). Considering that the integration of health care practices and SSA can contribute to reduce mother and infant mortality rates, this article is a result of qualitative research that analyzed the integration of these actions in four cities in the State of São Paulo/Brazil: Campinas, Indaiatuba, Jaguariúna and Santa Bárbara D'Oeste. The research was conducted through interviews with SSA and maternal health managers, and the data were evaluated using thematic analysis. The results converge with other studies, identifying the isolation of health care practices and SSA. The insertion of SSA in collectively-managed areas appears to be a potential strategy for health planning and implementation of actions in the context under scrutiny.

Pedagogia do esporte : organização, sistematização, aplicação e avaliação de conteúdos esportivos na educação não formal = Sport pedagogy : organization, systematization and application of sports content in non-formal education

Universidade Estadual de Campinas . Faculdade de Educação Física

Analysis of Permeability and Morphology of Root Canal Dentin After Er,Cr:YSGG Laser Irradiation

Objective: The aim of this study was to evaluate the morphology and permeability of root canal walls irradiated with Er,Cr:YSGG laser after conventional endodontic treatment. Background: Laser irradiation can be used for dentinal tubule exposure, smear layer removal, and disinfection. Another potential, interesting application is as an adjunct to endodontic treatment, especially in the intracanal medication phase. Methods: Fifty-two single-rooted teeth had their crowns sectioned at the cementoenamel junction and were randomly divided into four groups (n = 13): G1: conventional preparation (CP) + irrigation with EDTA-T+rhodamine B dye solution associated with NDP (dexamethasone phosphate, paramonochlorophenol, polyethylenoglycol) (Rhod-NDP); G2: CP+EDTA-T + Er,Cr:YSGG laser irradiation 0.75W+Rhod-NDP; G3: CP + EDTA-T + Er,Cr:YSGG 1.5W+Rhod-NDP; G4: CP + EDTA-T + Er,Cr:YSGG 2.5W + Rhod-NDP. For the permeability analysis (n = 9), teeth were transversely cut and two slices of each third were selected. The images were analyzed by ImageLab software (Softium Informatica Ltda., Sao Paulo, SP, Brazil). Additional samples (n = 4) were examined by scanning electron microscopy. Results: Data were analyzed statistically using the Kruskal-Wallis and Student-Newman-Keuls tests for the following areas: apical third (H = 23.4651): G1 (14.25)(a), G2 (17.66)(ab), G3 (26.50)(b), G4 (39.58)(c); medium (H = 23.1611): G1 (14.16)(a), G2 (16.66)(ab), G3 (28.83)(b), G4 (38.33)(b); and cervical (H = 32.4810): G1 (9.66)(a), G2 (20.00)(ab), G3 (27.00)(b), G4 (41.33)(c), (p<0.01). Despite the irregular aspect of laser irradiation along the canal walls, the parameters of 1.5W and 2.5W allowed morphologic modifications that increased dentinal permeability. Conclusions: Irradiation with Er, Cr: YSGG laser could be effective in endodontic treatment for increasing dentinal permeability.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

Characterization and application of the solid waste generated in the production of calcium carbonate precipitate as a corrective for the soil acidity

The calcium carbonate industry generates solid waste products which, because of their high alkaline content (CaO, CaCO(3) and Ca (OH)(2)), have a substantial impact on the environment. The objectives of this study are to characterize and classify the solid waste products, which are generated during the hydration process of the calcium carbonate industry, according to ABNT`s NBR 10.000 series, and to determine the potential and efficiency of using these solid residues to correct soil acidity. Initially, the studied residue was submitted to gross mass, leaching, solubility, pH. X-ray Diffractometry, Inductive Coupled Plasma - Atomic Emission Spectrometry (ICP-AES), granularity and humidity analyses. The potential and efficiency of the residue for correcting soil acidity was determined by analysis of the quality attributes for soil correctives (PN, PRNT, Ca and Mg contents, granularity). Consequently, the results show that the studied residue may be used as a soil acidity corrective, considering that a typical corrective compound is recommended for each different type of soil. Additionally, the product must be further treated (dried and ground) to suit the specific requirements of the consumer market.

Enantioselective analysis of zopiclone and its metabolites in plasma by liquid chromatography/tandem mass spectrometry

A high-performance liquid chromatographic method with triple-quadrupole mass spectrometry detection (LC-MS-MS) was developed and validated for the first time for the simultaneous quantification of zopiclone and its metabolites in rat plasma samples. The analytes were isolated from rat plasma by liquid-liquid extraction and separated using a chiral stationary phase based on an amylose derivative, Chiralpak ADR-H column, and ethanol-methanol-acetonitrile (50:45:5, v/v/v) plus 0.025% diethylamine as the mobile phase, at a flow-rate of 1.0 mL min(-1). Moclobemide was used as the internal standard. The developed method was linear over the concentration range of 7.5-500 ng mL(-1). The mean absolute recoveries were 74.6 and 75.7; 61.6 and 56.9; 72.5, and 70.7 for zopiclone enantiomers, for N-desmethyl zopiclone enantiomers and for zopiclone-N-oxide enantiomers, respectively, and 75.9 for the internal standard. Precision and accuracy were within acceptable levels of confidence (<15%). The method application in a pilot study of zopiclone kinetic disposition in rats showed that the levels of (+)-(S)-zopiclone were always higher than those of (-)-R-zopiclone. Higher concentrations were also observed for (+)-(S)-N-desmethyl zopiclone and (+)-(S)-N-oxide zopiclone, confirming the stereoselective disposition of zopiclone.

A compartmental model of hepatic disposition kinetics: 1. Model development and application to linear kinetics

The conventional convection-dispersion model is widely used to interrelate hepatic availability (F) and clearance (Cl) with the morphology and physiology of the liver and to predict effects such as changes in liver blood flow on F and Cl. The extension of this model to include nonlinear kinetics and zonal heterogeneity of the liver is not straightforward and requires numerical solution of partial differential equation, which is not available in standard nonlinear regression analysis software. In this paper, we describe an alternative compartmental model representation of hepatic disposition (including elimination). The model allows the use of standard software for data analysis and accurately describes the outflow concentration-time profile for a vascular marker after bolus injection into the liver. In an evaluation of a number of different compartmental models, the most accurate model required eight vascular compartments, two of them with back mixing. In addition, the model includes two adjacent secondary vascular compartments to describe the tail section of the concentration-time profile for a reference marker. The model has the added flexibility of being easy to modify to model various enzyme distributions and nonlinear elimination. Model predictions of F, MTT, CV2, and concentration-time profile as well as parameter estimates for experimental data of an eliminated solute (palmitate) are comparable to those for the extended convection-dispersion model.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Relationships between NPM, the use of PM practices and the organizational performance: empirical evidence from government agencies

Purpose – this paper has two main purposes: (1)explore if government agencies more oriented to NPM postulates are more willing to use PM practices and to improve their performance; and (2) investigate whether the fit between the use of PM practices and the organizationa performance is dependent upon from the capacity of agencies to adapt its structures to changes introduced by NPM reforms. Design/methodology/approach - this paper is based on the survey method and provides empirical evidence from Portuguese government agencies.Findings (mandatory) - Our findings suggest that government agencies that made structural arrangements under the NPM reforms are more willing to use PM practices and will perform better than other agencies. In addition, this paper show that therelationship between the use of PM practices and the organizational performance is dependent upon from the agencies capacity to adopt new structural arrangements under the NPM reforms.Practical implications – this paper has three main contributions: (1) contribute to knowledge about the relationship between the introduction of NPM changes in the use of PM practices; (2) contribute to clarify whether agencies more oriented to NPM postulates are improving performance; and (3) help to clarify the way the organizations should adapt their structures for to be more effective in the use of PM practices. Originality/value - The quantitative empirical research, based on the unique survey applied to Portuguese government agencies on this field, allow us to add to prior research mainly based on case studies and oriented to local governments (Budding, 2004).

Analysis of mediation and reciprocal effects of changes in weight, self-esteem, and exercise in a behavioral weight loss treatment

Improving the treatment of obesity remains a critical challenge. Several health behaviour change models, often based on a social-cognitive framework, have been used to design weight management interventions (Baranowski et al., 2003). However, most interventions have only produced modest weight reductions (Wadden et al., 2002) and socialcognitive variables have shown limited power to predict weight outcomes (Palmeira et al., 2007). Other predictors, and possibl alte nati e e planatory models, are needed to better understand the mechanisms by which weight loss and other obesity treatment-outcomes are brought about (Baranowski, 2006). Self-esteem is one of these possible mechanisms, because is commonly reported to change during the treatment, although these changes are not necessarily associated with weight loss (Blaine et al., 2007; Maciejewski et al., 2005). This possibility should be more evident if the program integrates regular exercise, as it promotes improvements in subjective well-being (Biddle & Mutrie, 2001), with possible influences on long-term behavioral adherence (e.g. diet, exercise). Following the reciprocal effects model tenets (Marsh & Craven, 2006), we expect that the influences between changes in weight, selfesteem and exercise to be reciprocal and might present one of the mechanisms by which obesity treatments can be improved.

Chlormequat selective electrodes: construction, evaluation and application at FIA systems

A flow injection analysis (FIA) system having a chlormequat selective electrode is proposed. Several electrodes with poly(vinyl chloride) based membranes were constructed for this purpose. Comparative characterization suggestedthe use of membrane with chlormequat tetraphenylborate and dibutylphthalate. On a single-line FIA set-up, operating with 1x10-2 mol L-1 ionic strength and 6.3 pH, calibration curves presented slopes of 53.6±0.4mV decade-1 within 5.0x10-6 and1.0x10-3 mol L-1, andsquaredcorrelation coefficients >0.9953. The detection limit was 2.2x10-6 mol L-1 and the repeatability equal to ±0.68mV (0.7%). A dual-channel FIA manifold was therefore constructed, enabling automatic attainment of previous ionic strength andpH conditions and thus eliminating sample preparation steps. Slopes of 45.5±0.2mV decade -1 along a concentration range of 8.0x10-6 to 1.0x10-3 mol L-1 with a repeatability ±0.4mV (0.69%) were obtained. Analyses of real samples were performed, and recovery gave results ranging from 96.6 to 101.1%.

Practices and trends of telework in the Portuguese industry: the results of surveys in the textile, metal and software sectors

The aim of the TeleRisk Project on labour relations and professional risks within the context of teleworking in Portugal – supported by IDICT – Institute for Development and Inspection of Working Conditions (Ministry of Labour), is to study the practices and forms of teleworking in the manufacturing sectors in Portugal. The project chose also the software industry as a reference sector, even though it does not intend to exclude from the study any other sector of activity or the so-called “hybrid” forms of work. However, the latter must have some of the characteristics of telework. The project thus takes into account the so-called “traditional” sectors of activity, namely textile and machinery and metal engineering (machinery and equipment), not usually associated to this type of work. However, telework could include, in the so-called “traditional” sectors, other variations that are not found in technologically based sectors. One of the evaluation methods for the dynamics associated to telework consisted in carrying out surveys by means of questionnaires, aimed at employers in the sectors analysed. This paper presents some of the results of those surveys. It is important to mention that, being a preliminary analysis, it means that it does not pretend to have exhausted all the issues in the survey, but has meant that it shows the bigger tendencies, in terms of teleworking practices, of the Portuguese industry.