Molecular mechanisms of drug resistance in clinical Candida species isolated from tunisian hospitals.

Antifungal resistance of Candida species is a clinical problem in the management of diseases caused by these pathogens. In this study we identified from a collection of 423 clinical samples taken from Tunisian hospitals two clinical Candida species (Candida albicans JEY355 and Candida tropicalis JEY162) with decreased susceptibility to azoles and polyenes. For JEY355, the fluconazole (FLC) MIC was 8 μg/ml. Azole resistance in C. albicans JEY355 was mainly caused by overexpression of a multidrug efflux pump of the major facilitator superfamily, Mdr1. The regulator of Mdr1, MRR1, contained a yet-unknown gain-of-function mutation (V877F) causing MDR1 overexpression. The C. tropicalis JEY162 isolate demonstrated cross-resistance between FLC (MIC > 128 μg/ml), voriconazole (MIC > 16 μg/ml), and amphotericin B (MIC > 32 μg/ml). Sterol analysis using gas chromatography-mass spectrometry revealed that ergosterol was undetectable in JEY162 and that it accumulated 14α-methyl fecosterol, thus indicating a perturbation in the function of at least two main ergosterol biosynthesis proteins (Erg11 and Erg3). Sequence analyses of C. tropicalis ERG11 (CtERG11) and CtERG3 from JEY162 revealed a deletion of 132 nucleotides and a single amino acid substitution (S258F), respectively. These two alleles were demonstrated to be nonfunctional and thus are consistent with previous studies showing that ERG11 mutants can only survive in combination with other ERG3 mutations. CtERG3 and CtERG11 wild-type alleles were replaced by the defective genes in a wild-type C. tropicalis strain, resulting in a drug resistance phenotype identical to that of JEY162. This genetic evidence demonstrated that CtERG3 and CtERG11 mutations participated in drug resistance. During reconstitution of the drug resistance in C. tropicalis, a strain was obtained harboring only defective Cterg11 allele and containing as a major sterol the toxic metabolite 14α-methyl-ergosta-8,24(28)-dien-3α,6β-diol, suggesting that ERG3 was still functional. This strain therefore challenged the current belief that ERG11 mutations cannot be viable unless accompanied by compensatory mutations. In conclusion, this study, in addition to identifying a novel MRR1 mutation in C. albicans, constitutes the first report on a clinical C. tropicalis with defective activity of sterol 14α-demethylase and sterol Δ(5,6)-desaturase leading to azole-polyene cross-resistance.

Analysis of a finite volume element method for the Stokes problem

In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.

A Novel Pulse-Chase SILAC Strategy Measures Changes in Protein Decay and Synthesis Rates Induced by Perturbation of Proteostasis with an Hsp90 Inhibitor.

Standard proteomics methods allow the relative quantitation of levels of thousands of proteins in two or more samples. While such methods are invaluable for defining the variations in protein concentrations which follow the perturbation of a biological system, they do not offer information on the mechanisms underlying such changes. Expanding on previous work [1], we developed a pulse-chase (pc) variant of SILAC (stable isotope labeling by amino acids in cell culture). pcSILAC can quantitate in one experiment and for two conditions the relative levels of proteins newly synthesized in a given time as well as the relative levels of remaining preexisting proteins. We validated the method studying the drug-mediated inhibition of the Hsp90 molecular chaperone, which is known to lead to increased synthesis of stress response proteins as well as the increased decay of Hsp90 "clients". We showed that pcSILAC can give information on changes in global cellular proteostasis induced by treatment with the inhibitor, which are normally not captured by standard relative quantitation techniques. Furthermore, we have developed a mathematical model and computational framework that uses pcSILAC data to determine degradation constants kd and synthesis rates Vs for proteins in both control and drug-treated cells. The results show that Hsp90 inhibition induced a generalized slowdown of protein synthesis and an increase in protein decay. Treatment with the inhibitor also resulted in widespread protein-specific changes in relative synthesis rates, together with variations in protein decay rates. The latter were more restricted to individual proteins or protein families than the variations in synthesis. Our results establish pcSILAC as a viable workflow for the mechanistic dissection of changes in the proteome which follow perturbations. Data are available via ProteomeXchange with identifier PXD000538.

A Bayesian network approach to the database serch problem in criminal proceedings

Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.