Nanocochleates containing N-Octylglicoside extracted Vibrio cholerae antigens elicited high vibriocidal antibodies titers after intragastric immunization in a mice model.

Biological detergents are used in research laboratories, to extract or solubilize proteins from cell membranes. In order to evaluate the ability to extract antigens from the bacterial cell surface of the wild Vibrio cholerae strain C7258 and study their immunogenic potential by forming proteoliposomes and cochleate and preserving their immunogenicity, the non-ionic detergent, n-Octylglucoside (n-OG), and the Zwitterionic detergent (3-cholamidopropyl dimethylammonio 1-propanesulfonate; CHAPS) were tested in concentrations between 5 and 15%. The anionic detergent sodium deoxycholate (DOC) was used as a reference. Electrophoretic, immunochemical and electron microscopy techniques have characterized the extracts and their chromatographic fractions. With CHAPS and n-OG detergents in concentrations between 5 and 15%, a higher yield was obtained in the extraction of proteins and lipopolysaccharides (LPS) and other components from the bacterial surface compared to 10% DOC. When using 10% DOC, 15% CHAPS and n-OG between 5 and 15%, stable proteoliposomes were formed, of average size between 82 and 93 nm in diameter, with known proportions of proteins, LPS and other components. In some of the concentrations, liposomes were formed with almost pure proteins. Some cholera outer membrane proteins like the 17 kDa protein, which corresponds to the mannose-sensitive hemagglutinin (MSHA), which mediates the adhesion to the brush border of the small intestine and the outer membrane protein U (OMPU) were identified with monoclonal antibodies (mAbs) and purified. The fundamental components of liposomes, proteins and LPS, retained their molecular weights, when compared with known standards and by processing programs of electrophoretic profiles and their antigenicity, without alterations due to the extraction procedure, as could be verified by immune identification techniques with monoclonal antibodies in the case of LPS, significant antigens in this pathogen. The main purpose of the present work was to show that a new anticholera vaccine formulation based on cochleates, containing selected protein and LPS fraction extracted by detergents, is able to elicit protective high titers of bactericidal antibodies after intragastric immunization in the mice model. The objective was achieved.

Essential oil composition and antifungal activity of Melissa officinalis originating from north-Est Morocco, against postharvest phytopathogenic fungi in apples.

To investigate biological control methods against post-harvest phytopathogenic fungi in apples, tests on the antifungal activity of essential oil of Melissa officinalis were carried out. The essential oil, obtained by hydrodistillation, was analyzed by gas chromatography coupled with mass spectrometry (GC-MS). Analysis of the essential oil was able to detect 88.7% of the components. The main components are P-mentha-1,2,3-triol (13.1%), P-menth-3-en-8-ol (8.8%), pulegone (8.8%), piperitynone oxide (8.4%) and 2-piperitone oxide (7.3%). The determination of the antifungal activity of the essential oil of M. officinalisis carried out in vitro using the technique of poison food (PF) and the volatile activity test (VA). To carry out these two tests, three phytopathogens that cause the deterioration of apples have been selected: Botrytis cinerea, Penicillium expansum and Rhizopus stolonifer. The overall results of this study suggest that M. officinalis essential oil has potential as a bio-antifungal preservative for the control of post-harvest diseases of apple.

A comparison of colour flow imaging algorithms.

In this paper we will present and explain coherently the two main algorithms which are currently used in commercial colour flow imaging systems, namely the frequency domain based autocorrelation algorithm and the time domain based cross correlation algorithm. The autocorrelation algorithm is a robust optimum mean frequency baseband estimator, for both high and low signal to noise ratio (SNR). Its main disadvantage is its aliasing problem. However the cross correlation algorithm does not suffer from this problem, and this has been one of the main reasons for its development. The mathematics behind these two algorithms and the general data processing steps used for their implementation will be also presented. The subject of clutter removal filtering will be discussed and valuable points will be made. A practical relevant approach on how to discriminate between wanted blood flow related estimates and unwanted false estimates due to noise will be presented. On the aliasing problem of the autocorrelation algorithm, a promising solution known as spatial tracking of estimated mean frequency does exist, which will be also introduced in detail. Towards the end of this paper other algorithms, which are currently the subject of research and have potential for development, will be discussed.

Linear time series analysis of long term fetal heart rate variability patterns.

Long term fetal heart rate variability (LFHRV) is equivalent to detrended (when the time series trend removed) indirectly derived averaged fetal heart rate (FHR) time series. Up to now LFHRV is looked for visually in FHR traces, by obstetricians and midwifes for determination of fetal condition. The detrended averaged FHR data or LFHRV data is a random correlated non-stationary (in second moment) time series. In this paper we have applied linear stochastic time series analysis technique to identify a parsimonious stochastic model, for parametric numerical representation of the random cyclical patterns observed in short 2 minutes quasi-stationary contiguous blocks of LFHRV data. The parametric estimation technique used is based upon the optimum exact Maximum likelihood estimation (which uses Kalman filtering as part of its implementation). Diagnostics performed on the residuals indicated that a second order autoregressive model is a statistically adequate model in capturing variability patterns observed in 2 minute data windows of detrended average FHR. Also through further analysis of the spectral behavior of this identified model, pseudo-periodicity (or random periodicity) which for a long time was visually detected, can now be detected via this numerical procedure.