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  • 1
    ISSN: 1612-1112
    Keywords: Column liquid chromatography ; DAD and MS detection ; Liquid-solid extraction ; Catechin derivatives ; Myricetin derivatives
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Summary A liquid-solid extraction and purification procedure (LSE) was developed to identify and quantify polyphenols in the leaf tissue ofMyrtus communis L. Identification and quantitation of individual compounds was performed using HPTLC, HPLC-DAD and HPLC-MS analysis. Leaves ofMyrtus communis L. contain small amounts of phenolic acids (caffeic, ellagic and gallic acids) and quercetin derivatives (quercetin 3-O-galactoside and quercetin 3-O-rhamnoside), whereas catechin derivatives (epigallocatechin, epigallocatechin 3-O-gallate, epicatechin 3-O-gallate) and myricetin derivatives (myricetin 3-O-galactoside, myricetin 3-O-rhamnoside) are present in large amounts. This is the first report on the occurrence of galloyl-derivatives of catechin and gallo-catechin inMyrtus communis L. leaves.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1590-3478
    Keywords: Key words Multiple sclerosis ; Secondary progressive course ; Prognostic factors ; Bayesian approach ; Markov chain Monte Carlo method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Notes: Abstract Previous studies of possible prognostic indicators for multiple sclerosis have been based on “classic” Cox's proportional hazards regression model, as well as on equivalent or simpler approaches, restricting their attention to variables measured either at disease onset or at a few points during follow-up. The aim of our study was to analyse the risk of reaching secondary progression in MS patients with a relapsing remitting intial course, using two different statistical approaches: a Cox's proportional-hazards model and a Bayesian latent-variable model with Markov chain Monte Carlo methods of computation. In comparison with a standard statistical approach, our model is advantageous because, exploiting all the information gleaned from the patient as it is gradually made available, it is capable to detect even small prognostic effects.
    Type of Medium: Electronic Resource
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