COMPARISON OF RNA EXTRACTION METHODS FOR Passiflora edulis SIMS LEAVES

ABSTRACT Functional genomic analyses require intact RNA; however, Passiflora edulis leaves are rich in secondary metabolites that interfere with RNA extraction primarily by promoting oxidative processes and by precipitating with nucleic acids. This study aimed to analyse three RNA extraction methods, Concert™ Plant RNA Reagent (Invitrogen, Carlsbad, CA, USA), TRIzol® Reagent (Invitrogen) and TRIzol® Reagent (Invitrogen)/ice -commercial products specifically designed to extract RNA, and to determine which method is the most effective for extracting RNA from the leaves of passion fruit plants. In contrast to the RNA extracted using the other 2 methods, the RNA extracted using TRIzol® Reagent (Invitrogen) did not have acceptable A260/A280 and A260/A230 ratios and did not have ideal concentrations. Agarose gel electrophoresis showed a strong DNA band for all of the Concert™ method extractions but not for the TRIzol® and TRIzol®/ice methods. The TRIzol® method resulted in smears during electrophoresis. Due to its low levels of DNA contamination, ideal A260/A280 and A260/A230 ratios and superior sample integrity, RNA from the TRIzol®/ice method was used for reverse transcription-polymerase chain reaction (RT-PCR), and the resulting amplicons were highly similar. We conclude that TRIzol®/ice is the preferred method for RNA extraction for P. edulis leaves.

On Option Price Information Content and Extraction of Implied Probability Distributions

In this study we used market settlement prices of European call options on stock index futures to extract implied probability distribution function (PDF). The method used produces a PDF of returns of an underlying asset at expiration date from implied volatility smile. With this method, the assumption of lognormal distribution (Black-Scholes model) is tested. The market view of the asset price dynamics can then be used for various purposes (hedging, speculation). We used the so called smoothing approach for implied PDF extraction presented by Shimko (1993). In our analysis we obtained implied volatility smiles from index futures markets (S&P 500 and DAX indices) and standardized them. The method introduced by Breeden and Litzenberger (1978) was then used on PDF extraction. The results show significant deviations from the assumption of lognormal returns for S&P500 options while DAX options mostly fit the lognormal distribution. A deviant subjective view of PDF can be used to form a strategy as discussed in the last section.

International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes.

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.

Temporal Patterns of Alcohol Consumption and Alcohol-Related Road Accidents in Young Swiss Men: Seasonal, Weekday and Public Holiday Effects.

AIMS: To assess seasonal, weekday, and public holiday effects on alcohol-related road accidents and drinking diaries among young Swiss men. METHODS: Federal road accident data (35,485 accidents) from Switzerland and drinking diary data from a large cohort of young Swiss men (11,930 subjects) were analysed for temporal effects by calendar week, weekday and public holiday (Christmas, New Years, National Day). Alcohol-related accidents were analysed using rate ratios for observed versus expected numbers of accidents and proportions of alcohol-related accidents relative to the total number. Drinking diaries were analysed for the proportion of drinkers, median number of drinks consumed, and the 90th percentile's number of drinks consumed. RESULTS: Several parallel peaks were identified in alcohol-related accidents and drinking diaries. These included increases on Fridays and Saturdays, with Saturday drinking extending until early Sunday morning, an increase during the summer on workdays but not weekends, an increase at the end of the year, and increases on public holidays and the evening before. CONCLUSIONS: Our results suggest specific time-windows that are associated with increases in drinking and alcohol-related harm. Established prevention measures should be enforced during these time-windows to reduce associated peaks.

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

Are Public Private Partnerships that Rigid ? And Why ? : Evidence from Toll Road Concession Contracts

Transport concession contracts are commonly said to be standardized and too rigid. They would not allow public authorities to adapt them to evolving context and circumstances. This paper aims at challenging this view and, more particularly, the view that contractual rigidity for transport concessions is exogenous. Using a transaction cost framework, we disentangle between three main determinants of contractual rigidity: traffic uncertainty; connivance between contracting parties; quality of the institutional environment. Using an original database of toll road concession contracts, we observe a great variety of provisions for toll adjustment. We find that these exogenous determinants significantly influence contractual choices.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

Aplicação de SPME (Solid Phase Micro-Extraction) na análise de águas potáveis de três localidades do estado de São Paulo

The technique of solid phase microextraction (SPME) was used for the extraction of halogenated contaminants of water samples from three cities of the State of São Paulo and the extracts were submitted to gas chromatographic analysis with electron capture detection (GC-ECD). In the samples of water collected at the city of São Paulo the detected level of trihalomethanes (THM) expressed as the sum of chloroform, dibromochloromethane and dichlorobromomethane, were higher than the permissible limit established by the Brazilian regulation. In the samples collected at the two other cities the level of any of the three THM remained below the sensitivity of the ECD.

Features extraction based on the Discrete Hartley Transform for closed contour

In this paper the authors propose a new closed contour descriptor that could be seen as a Feature Extractor of closed contours based on the Discrete Hartley Transform (DHT), its main characteristic is that uses only half of the coefficients required by Elliptical Fourier Descriptors (EFD) to obtain a contour approximation with similar error measure. The proposed closed contour descriptor provides an excellent capability of information compression useful for a great number of AI applications. Moreover it can provide scale, position and rotation invariance, and last but not least it has the advantage that both the parameterization and the reconstructed shape from the compressed set can be computed very efficiently by the fast Discrete Hartley Transform (DHT) algorithm. This Feature Extractor could be useful when the application claims for reversible features and when the user needs and easy measure of the quality for a given level of compression, scalable from low to very high quality.