A Single Statistic for Monitoring the Covariance Matrix of Bivariate Processes

In this article, we present a new control chart for monitoring the covariance matrix in a bivariate process. In this method, n observations of the two variables were considered as if they came from a single variable (as a sample of 2n observations), and a sample variance was calculated. This statistic was used to build a new control chart specifically as a VMIX chart. The performance of the new control chart was compared with its main competitors: the generalized sampled variance chart, the likelihood ratio test, Nagao's test, probability integral transformation (v(t)), and the recently proposed VMAX chart. Among these statistics, only the VMAX chart was competitive with the VMIX chart. For shifts in both variances, the VMIX chart outperformed VMAX; however, VMAX showed better performance for large shifts (higher than 10%) in one variance.

Biomimetic in vitro oxidation of lapachol: A model to predict and analyse the in vivo phase I metabolism of bioactive compounds

The bioactive naphtoquinone lapachol was studied in vitro by a biomimetic model with Jacobsen catalyst (manganese(III) salen) and iodosylbenzene as oxidizing agent. Eleven oxidation derivatives were thus identified and two competitive oxidation pathways postulated. Similar to Mn(III) porphyrins, Jacobsen catalyst mainly induced the formation of para-naphtoquinone derivatives of lapachol, but also of two ortho-derivatives. The oxidation products were used to develop a GC MS (SIM mode) method for the identification of potential phase I metabolites in vivo. Plasma analysis of Wistar rats orally administered with lapachol revealed two metabolites, alpha-lapachone and dehydro-alpha-lapachone. Hence, the biomimetic model with a manganese salen complex has evidenced its use as a valuable tool to predict and elucidate the in vivo phase I metabolism of lapachol and possibly also of other bioactive natural compounds. (C) 2012 Elsevier Masson SAS. All rights reserved.