Cost of Illness and Contingent Valuation : Controlling for the Motivations of Expressed Preferences in an Attempt to Avoid Double-Counting

This paper addresses the issue of double counting of health impacts in the context of cost of illness valuation. Double counting occurs when estimates are jointly used, which rely on valuation techniques that overlap. As a solution, we propose to limit the scope of each of the valuation method to a specific range of impacts. In order to limit the contingentvaluation method to the exclusive valuation of intangible costs, we propose a three steps approach : (1) leave the respondents free to valuate the consequences which matter to them, (2) elicit respondent's motivations, (3) control for the influence motivations have on elicited values. This procedure was applied in a Swiss contingent-valuation. An econometric treatment was applied in order to limit the scope of the estimates of the contingent valuation method to intangibles,therefore the possibility to a combination of methods with the risk of double-counting and underestimating costs being kept to a minimum.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Characterization of the Aspergillus nidulans biotin biosynthetic gene cluster and use of the bioDA gene as a new transformation marker.

The genes involved in the biosynthesis of biotin were identified in the hyphal fungus Aspergillus nidulans through homology searches and complementation of Escherichia coli biotin-auxotrophic mutants. Whereas the 7,8-diaminopelargonic acid synthase and dethiobiotin synthetase are encoded by distinct genes in bacteria and the yeast Saccharomyces cerevisiae, both activities are performed in A. nidulans by a single enzyme, encoded by the bifunctional gene bioDA. Such a bifunctional bioDA gene is a genetic feature common to numerous members of the ascomycete filamentous fungi and basidiomycetes, as well as in plants and oömycota. However, unlike in other eukaryota, the three bio genes contributing to the four enzymatic steps from pimeloyl-CoA to biotin are organized in a gene cluster in pezizomycotina. The A. nidulans auxotrophic mutants biA1, biA2 and biA3 were all found to have mutations in the 7,8-diaminopelargonic acid synthase domain of the bioDA gene. Although biotin auxotrophy is an inconvenient marker in classical genetic manipulations due to cross-feeding of biotin, transformation of the biA1 mutant with the bioDA gene from either A. nidulans or Aspergillus fumigatus led to the recovery of well-defined biotin-prototrophic colonies. The usefulness of bioDA gene as a novel and robust transformation marker was demonstrated in co-transformation experiments with a green fluorescent protein reporter, and in the efficient deletion of the laccase (yA) gene via homologous recombination in a mutant lacking non-homologous end-joining activity.

Leukemic cluster growth in culture is an independent risk factor for acute myeloid leukemia and short survival in patients with myelodysplastic syndrome

In patients with myelodysplastic syndrome (MDS) precursor cell cultures (colony-forming unit cells, CFU-C) can provide an insight into the growth potential of malignant myeloid cells. In a retrospective single-center study of 73 untreated MDS patients we assessed whether CFU-C growth patterns were of prognostic value in addition to established criteria. Abnormalities were classified as qualitative (i.e. leukemic cluster growth) or quantitative (i.e. strongly reduced/absent growth). Thirty-nine patients (53%) showed leukemic growth, 26 patients (36%) had strongly reduced/absent colony growth, and 12 patients showed both. In a univariate analysis the presence of leukemic growth was associated with strongly reduced survival (at 10 years 4 vs. 34%, p = 0.004), and a high incidence of transformation to AML (76 vs. 32%, p = 0.01). Multivariate analysis identified leukemic growth as a strong and independent predictor of early death (relative risk 2.12, p = 0.03) and transformation to AML (relative risk 2.63, p = 0.04). Quantitative abnormalities had no significant impact on the disease course. CFU- C assays have significant predictive value in addition to established prognostic factors in MDS. Leukemic growth identifies a subpopulation of MDS patients with poor prognosis.

Universal screening and decolonization for control of MRSA in nursing homes : a cluster randomized controlled study

OBJECTIVE The risk of carrying methicillin-resistant Staphylococcus aureus (MRSA) is higher among nursing home (NH) residents than in the general population. However, control strategies are not clearly defined in this setting. In this study, we compared the impact of standard precautions either alone (control) or combined with screening of residents and decolonization of carriers (intervention) to control MRSA in NHs. DESIGN Cluster randomized controlled trial SETTING NHs of the state of Vaud, Switzerland PARTICIPANTS Of 157 total NHs in Vaud, 104 (67%) participated in the study. INTERVENTION Standard precautions were enforced in all participating NHs, and residents underwent MRSA screening at baseline and 12 months thereafter. All carriers identified in intervention NHs, either at study entry or among newly admitted residents, underwent topical decolonization combined with environmental disinfection, except in cases of MRSA infection, MRSA bacteriuria, or deep skin ulcers. RESULTS NHs were randomly allocated to a control group (51 NHs, 2,412 residents) or an intervention group (53 NHs, 2,338 residents). Characteristics of NHs and residents were similar in both groups. The mean screening rates were 86% (range, 27%-100%) in control NHs and 87% (20%-100%) in intervention NHs. Prevalence of MRSA carriage averaged 8.9% in both control NHs (range, 0%-43%) and intervention NHs (range, 0%-38%) at baseline, and this rate significantly declined to 6.6% in control NHs and to 5.8% in intervention NHs after 12 months. However, the decline did not differ between groups (P=.66). CONCLUSION Universal screening followed by decolonization of carriers did not significantly reduce the prevalence of the MRSA carriage rate at 1 year compared with standard precautions

Characterization of the hcnABC gene cluster encoding hydrogen cyanide synthase and anaerobic regulation by ANR in the strictly aerobic biocontrol agent Pseudomonas fluorescens CHA0.

The secondary metabolite hydrogen cyanide (HCN) is produced by Pseudomonas fluorescens from glycine, essentially under microaerophilic conditions. The genetic basis of HCN synthesis in P. fluorescens CHA0 was investigated. The contiguous structural genes hcnABC encoding HCN synthase were expressed from the T7 promoter in Escherichia coli, resulting in HCN production in this bacterium. Analysis of the nucleotide sequence of the hcnABC genes showed that each HCN synthase subunit was similar to known enzymes involved in hydrogen transfer, i.e., to formate dehydrogenase (for HcnA) or amino acid oxidases (for HcnB and HcnC). These similarities and the presence of flavin adenine dinucleotide- or NAD(P)-binding motifs in HcnB and HcnC suggest that HCN synthase may act as a dehydrogenase in the reaction leading from glycine to HCN and CO2. The hcnA promoter was mapped by primer extension; the -40 sequence (TTGGC ... ATCAA) resembled the consensus FNR (fumarate and nitrate reductase regulator) binding sequence (TTGAT ... ATCAA). The gene encoding the FNR-like protein ANR (anaerobic regulator) was cloned from P. fluorescens CHA0 and sequenced. ANR of strain CHA0 was most similar to ANR of P. aeruginosa and CydR of Azotobacter vinelandii. An anr mutant of P. fluorescens (CHA21) produced little HCN and was unable to express an hcnA-lacZ translational fusion, whereas in wild-type strain CHA0, microaerophilic conditions strongly favored the expression of the hcnA-lacZ fusion. Mutant CHA21 as well as an hcn deletion mutant were impaired in their capacity to suppress black root rot of tobacco, a disease caused by Thielaviopsis basicola, under gnotobiotic conditions. This effect was most pronounced in water-saturated artificial soil, where the anr mutant had lost about 30% of disease suppression ability, compared with wild-type strain CHA0. These results show that the anaerobic regulator ANR is required for cyanide synthesis in the strictly aerobic strain CHA0 and suggest that ANR-mediated cyanogenesis contributes to the suppression of black root rot.

Leukemic cluster growth in culture is an independent risk factor for acute myeloid leukemia and short survival in patients with myelodysplastic syndrome.

In patients with myelodysplastic syndrome (MDS) precursor cell cultures (colony-forming unit cells, CFU-C) can provide an insight into the growth potential of malignant myeloid cells. In a retrospective single-center study of 73 untreated MDS patients we assessed whether CFU-C growth patterns were of prognostic value in addition to established criteria. Abnormalities were classified as qualitative (i.e. leukemic cluster growth) or quantitative (i.e. strongly reduced/absent growth). Thirty-nine patients (53%) showed leukemic growth, 26 patients (36%) had strongly reduced/absent colony growth, and 12 patients showed both. In a univariate analysis the presence of leukemic growth was associated with strongly reduced survival (at 10 years 4 vs. 34%, p = 0.004), and a high incidence of transformation to AML (76 vs. 32%, p = 0.01). Multivariate analysis identified leukemic growth as a strong and independent predictor of early death (relative risk 2.12, p = 0.03) and transformation to AML (relative risk 2.63, p = 0.04). Quantitative abnormalities had no significant impact on the disease course. CFU-C assays have a significant predictive value in addition to established prognostic factors in MDS. Leukemic growth identifies a subpopulation of MDS patients with poor prognosis.

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

Improvement of antibiotic prescription in outpatient care: a cluster-randomized intervention study using a sentinel surveillance network of physicians.

OBJECTIVES: To assess the effectiveness of implementing guidelines, coupled with individual feedback, on antibiotic prescribing behaviour of primary care physicians in Switzerland. METHODS: One hundred and forty general practices from a representative Swiss sentinel network of primary care physicians participated in this cluster-randomized prospective intervention study. The intervention consisted of providing guidelines on treatment of respiratory tract infections (RTIs) and uncomplicated lower urinary tract infections (UTIs), coupled with sustained, regular feedback on individual antibiotic prescription behaviour during 2 years. The main aims were: (i) to increase the percentage of prescriptions of penicillins for all RTIs treated with antibiotics; (ii) to increase the percentage of trimethoprim/sulfamethoxazole prescriptions for all uncomplicated lower UTIs treated with antibiotics; (iii) to decrease the percentage of quinolone prescriptions for all cases of exacerbated COPD (eCOPD) treated with antibiotics; and (iv) to decrease the proportion of sinusitis and other upper RTIs treated with antibiotics. The study was registered at ClinicalTrials.gov (NCT01358916). RESULTS: While the percentage of antibiotics prescribed for sinusitis or other upper RTIs and the percentage of quinolones prescribed for eCOPD did not differ between the intervention group and the control group, there was a significant increase in the percentage of prescriptions of penicillins for all RTIs treated with antibiotics [57% versus 49%, OR=1.42 (95% CI 1.08-1.89), P=0.01] and in the percentage of trimethoprim/sulfamethoxazole prescriptions for all uncomplicated lower UTIs treated with antibiotics [35% versus 19%, OR=2.16 (95% CI 1.19-3.91), P=0.01] in the intervention group. CONCLUSIONS: In our setting, implementing guidelines, coupled with sustained individual feedback, was not able to reduce the proportion of sinusitis and other upper RTIs treated with antibiotics, but increased the use of recommended antibiotics for RTIs and UTIs, as defined by the guidelines.