Validation of a gas chromatographic method to quantify sesquiterpenes in copaiba oils

Copaifera species (Leguminoseae) are popularly known as ""copaiba"" or ""copaiva"". The oleoresins obtained from the trunk of these species have been extensively used in folk medicine and are commercialized in Brazil as crude oil and in several pharmaceutical and cosmetic products. This work reports a complete validated method for the quantification of beta-caryophyllene, alpha-copaene, and alpha-humulene in distinct copaiba oleoresins available commercially. Thus, essential oil samples (100 mu L) were dissolved in 20 mL of hexanes containing internal standard (1,2,4,5-tetramethylbenzene, 3.0 mM) in a 25 mL glass flask. A 1 mu L aliquot was injected into the GC-FID system. A fused-silica capillary column HP-5, coated with 5% phenylmethylsiloxane was used for this study. The developed method gave a good detection response with linearity in the range of 0.10-18.74 mM. Limits of detection and quantitation variety ranged between 0.003 and 0.091 mM. beta-Caryophyllene, alpha-copaene, and alpha-humulene were recovered in a range from 74.71% to 88.31%, displaying RSD lower than 10% and relative errors between -11.69% and -25.30%. Therefore, this method could be considered as an analytical tool for the quality control of different Copaifera oil samples and its products in both cosmetic and pharmaceutical companies. (C) 2010 Elsevier B.V. All rights reserved.

Penetration of Quantum Dot Particles Through Human Skin

The skin is a large and accessible area of the body, offering the possibility to be used as an alternative route for drug delivery. In the last few years strong progress has been made on the developing of nanoparticulate systems for specific applications. The interaction of such small particles with human skin and their possible penetration attracted some interest from toxicological as well as from drug delivery perspectives. As size is assumed to play a key role, the aim of the present work was to investigate the penetration profile of very small model particles (similar to 4 nm) into excised human skin under conditions chosen to mimic the in vivo situation. Possible application procedures such as massaging the formulation (5 to 10 minutes) were analyzed by non-invasive multiphoton- and confocal laser scanning microscopy (MPM, CLSM). Furthermore, the application on damaged skin was taken into account by deliberately removing parts of the stratum corneum. Although it was clearly observed that the mechanical actions affected the distribution pattern of the QDs on the skin surface, there was no evidence of penetration into the skin in all cases tested. QDs could be found in deeper layers only after massaging of damaged skin for 10 min. Taking these data into account, obtained on the gold standard human skin, the potential applications of nanoparticulate systems to act as carrier delivering drugs into intact skin might be limited and are only of interest for partly damaged skin.

The 2008 update of the Aspergillus nidulans genome annotation: A community effort

The identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology. (C) 2009 Elsevier Inc. All rights reserved.

Crotalus durissus collilineatus venom gland transcriptome: Analysis of gene expression profile

Crotalus durissus rattlesnakes are responsible for the most lethal cases of snakebites in Brazil. Crotalus durissus collilineatus subspecies is related to a great number of accidents in Southeast and Central West regions, but few studies on its venom composition have been carried out to date. In an attempt to describe the transcriptional profile of the C. durissus collilineatus venom gland, we generated a cDNA library and the sequences obtained could be identified by similarity searches on existing databases. Out of 673 expressed sequence tags (ESTs) 489 produced readable sequences comprising 201 singletons and 47 clusters of two or more ESTs. One hundred and fifty reads (60.5%) produced significant hits to known sequences. The results showed a predominance of toxin-coding ESTs instead of transcripts coding for proteins involved in all cellular functions. The most frequent toxin was crotoxin, comprising 88% of toxin-coding sequences. Crotoxin B, a basic phospholipase A(2) (PLA(2)) subunit of crotoxin, was represented in more variable forms comparing to the non-enzymatic subunit (crotoxin A), and most sequences coding this molecule were identified as CB1 isoform from Crotalus durissus terrificus venom. Four percent of toxin-related sequences in this study were identified as growth factors, comprising five sequences for vascular endothelial growth factor (VEGF) and one for nerve growth factor (NGF) that showed 100% of identity with C. durissus terrificus NGF. We also identified two clusters for metalloprotease from PII class comprising 3% of the toxins, and two for serine proteases, including gyroxin (2.5%). The remaining 2.5% of toxin-coding ESTs represent singletons identified as homologue sequences to cardiotoxin, convulxin, angiotensin-converting enzyme inhibitor and C-type natriuretic peptide, Ohanin, crotamin and PLA(2) inhibitor. These results allowed the identification of the most common classes of toxins in C. durissus collilineatus snake venom, also showing some unknown classes for this subspecies and even for C. durissus species, such as cardiotoxins and VEGF. (C) 2009 Published by Elsevier Masson SAS.

Determination of mitragynine in rat plasma by LC-MS/MS: Application to pharmacokinetics

This study used for the first time LC-MS/MS for the analysis of mitragynine (MIT), a mu-opioid agonist with antinociceptive and antitussive properties, in rat plasma. Mitragynine and the internal standard (amitriptyline) were extracted from plasma with hexane-isoamyl alcohol and resolved on a Lichrospher (R) RP-SelectB column (9.80 and 12.90 min, respectively). The quantification limit was 0.2 ng/mL within a linear range of 0.2-1000 ng/mL The method was applied to quantify mitragynine in plasma samples of rats (n = 8 per sampling time) treated with a single oral dose of 20 mg/kg. The following pharmacokinetic parameters were obtained (mean): maximum plasma concentration: 424 ng/mL; time to reach maximum plasma concentration: 1.26 h; elimination half-life: 3.85 h, apparent total clearance: 6.35 L/h/kg, and apparent volume of distribution: 37.90 L/kg. (C) 2009 Elsevier B.V. All rights reserved.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

A matching pursuit-based signal complexity measure for the analysis of newborn EEG

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

Effect of multiple transverse modes in self-mixing sensors based on vertical-cavity surface-emitting lasers

We investigate the effect of coexisting transverse modes on the operation of self-mixing sensors based on vertical-cavity surface-emitting lasers (VCSELs). The effect of multiple transverse modes on the measurement of displacement and distance were examined by simulation and in laboratory experiment. The simulation model shows that the periodic change in the shape and magnitude of the self-mixing signal with modulation current can be properly explained by the different frequency-modulation coefficients of the respective transverse modes in VCSELs. The simulation results are in excellent agreement with measurements performed on single-mode and multimode VCSELs and on self-mixing sensors based on these VCSELs.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Chemical treatment of Escherichia coli. II. Direct extraction of recombinant protein from cytoplasmic inclusion bodies in intact cells

A method is presented for the direct extraction of the recombinant protein Long-R-3-IGF-I from inclusion bodies located in the cytoplasm of intact Escherichia coli cells. Chemical treatment with 6M urea, 3 mM EDTA, and 20 mM dithiothreitol (DTT) at pH 9.0 proved an effective combination for extracting recombinant protein from intact cells. Comparable levels of Long-R-3-IGF-I were recovered by direct extraction as achieved by in vitro dissolution following mechanical disruption. However, the purity of directly extracted recombinant protein was lower due to contamination by bacterial cell components. The kinetics of direct extraction are described using a first-order equation with the time constant of 3 min. Urea appears important for permeabilization of the cell and dissolution of the inclusion body. Conversely, EDTA is involved in permeabilization of the cell wall and DTT enhances protein release. pH proved to be important with lower levels of protein release achieved at low pH values (

Development of a dietary supplement database

Data describing the composition of dietary supplements are not readily available to the public health community. As a result, intake from dietary supplements is generally not considered in most dietary surveys and, hence, little is known about the significance of supplement intake in relation to total diet or disease risk. To enable a more comprehensive analysis of dietary data, a database of the composition of various dietary supplements has been compiled. Active ingredients of all dietary supplements sold in Australia are included in the Australian Register of Therapeutic Goods (ARTG), maintained by the Therapeutic Goods Administration. Products included in the database were restricted to those vitamin, mineral and other supplements identified in dietary data collected from studies conducted in southeast Queensland and New South Wales (850 supplements). Conversion factors from ingredients compounds to active elements were compiled from standard sources. No account has been made for bioavailability, consistent with current practice for food composition databases. The database can be queried by ARTG identification number, brand, product title, or a variety of other fields. Expected future developments include development of standard formulations for use when supplements are incompletely specified, and expansion of products included for more widespread use.

Expressed sequenced tags and new genes from the cattle tick, Boophilus microplus

We used the expressed sequenced tags (ESTs) approach to study the genome of the cattle tick Boophilus microplus. One hundred and forty-two of our 234 unique ESTs were from genes not previously identified from ticks, mites or any other arachnids. The largest class of identified ESTs (29%) was from genes involved in transcription and translation. Ninety-one ESTs (39% of all ESTs) did not match any sequences in international databases; some of these may be specific to ticks. Thirteen percent of our ESTs were from ribosomal proteins and two ESTs were for genes implicated in resistance to pesticides. (C) 1998 Chapman & Hall Ltd.

Potential errors in the application of mixture theory to multifrequency bioelectrical impedance analysis

Potential errors in the application of mixture theory to the analysis of multiple-frequency bioelectrical impedance data for the determination of body fluid volumes are assessed. Potential sources of error include: conductive length; tissue fluid resistivity; body density; weight and technical errors of measurement. Inclusion of inaccurate estimates of body density and weight introduce errors of typically < +/-3% but incorrect assumptions regarding conductive length or fluid resistivities may each incur errors of up to 20%.

Data analysis in multiple-frequency bioelectrical impedance analysis

The performance of three analytical methods for multiple-frequency bioelectrical impedance analysis (MFBIA) data was assessed. The methods were the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Method performance was assessed from the adequacy of the curve fitting techniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determining the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better for most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally within 1-2% of the theoretical values, followed by the Siconolfi procedure using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic limits of the impedance meter used. These data suggest that Cole-Cole modelling remains the preferred method for the analysis of MFBIA data.

Data partitioning for parallel spatial join processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.