Understanding and meeting the needs of the older population: a global challenge.

BACKGROUND: In the past century, there has been a significant rise in life expectancy in almost all regions of the world, contributing to an increasingly older population. The aging of the population, in conjunction with urbanization and industrialization, has resulted in an important epidemiological transition marked by a widespread increase in the prevalence of chronic diseases and their sequelae. Current trends suggest that the transition will have a greater impact on developing countries compared to developed countries. An adequate response to the transition requires a strong emphasis on primary prevention and adequate resource allocation.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

The functions of DNA methylation by CcrM in Caulobacter crescentus: a global approach.

DNA methylation is involved in a diversity of processes in bacteria, including maintenance of genome integrity and regulation of gene expression. Here, using Caulobacter crescentus as a model, we exploit genome-wide experimental methods to uncover the functions of CcrM, a DNA methyltransferase conserved in most Alphaproteobacteria. Using single molecule sequencing, we provide evidence that most CcrM target motifs (GANTC) switch from a fully methylated to a hemi-methylated state when they are replicated, and back to a fully methylated state at the onset of cell division. We show that DNA methylation by CcrM is not required for the control of the initiation of chromosome replication or for DNA mismatch repair. By contrast, our transcriptome analysis shows that >10% of the genes are misexpressed in cells lacking or constitutively over-expressing CcrM. Strikingly, GANTC methylation is needed for the efficient transcription of dozens of genes that are essential for cell cycle progression, in particular for DNA metabolism and cell division. Many of them are controlled by promoters methylated by CcrM and co-regulated by other global cell cycle regulators, demonstrating an extensive cross talk between DNA methylation and the complex regulatory network that controls the cell cycle of C. crescentus and, presumably, of many other Alphaproteobacteria.

Transcatheter aortic valve replacement for degenerative bioprosthetic surgical valves: results from the global valve-in-valve registry.

BACKGROUND: Transcatheter aortic valve-in-valve implantation is an emerging therapeutic alternative for patients with a failed surgical bioprosthesis and may obviate the need for reoperation. We evaluated the clinical results of this technique using a large, worldwide registry. METHODS AND RESULTS: The Global Valve-in-Valve Registry included 202 patients with degenerated bioprosthetic valves (aged 77.7±10.4 years; 52.5% men) from 38 cardiac centers. Bioprosthesis mode of failure was stenosis (n=85; 42%), regurgitation (n=68; 34%), or combined stenosis and regurgitation (n=49; 24%). Implanted devices included CoreValve (n=124) and Edwards SAPIEN (n=78). Procedural success was achieved in 93.1% of cases. Adverse procedural outcomes included initial device malposition in 15.3% of cases and ostial coronary obstruction in 3.5%. After the procedure, valve maximum/mean gradients were 28.4±14.1/15.9±8.6 mm Hg, and 95% of patients had ≤+1 degree of aortic regurgitation. At 30-day follow-up, all-cause mortality was 8.4%, and 84.1% of patients were at New York Heart Association functional class I/II. One-year follow-up was obtained in 87 patients, with 85.8% survival of treated patients. CONCLUSIONS: The valve-in-valve procedure is clinically effective in the vast majority of patients with degenerated bioprosthetic valves. Safety and efficacy concerns include device malposition, ostial coronary obstruction, and high gradients after the procedure.

Promoter recognition and activation by the global response regulator CbrB in Pseudomonas aeruginosa.

In Pseudomonas aeruginosa, the CbrA/CbrB two-component system is instrumental in the maintenance of the carbon-nitrogen balance and for growth on carbon sources that are energetically less favorable than the preferred dicarboxylate substrates. The CbrA/CbrB system drives the expression of the small RNA CrcZ, which antagonizes the repressing effects of the catabolite repression control protein Crc, an RNA-binding protein. Dicarboxylates appear to cause carbon catabolite repression by inhibiting the activity of the CbrA/CbrB system, resulting in reduced crcZ expression. Here we have identified a conserved palindromic nucleotide sequence that is present in upstream activating sequences (UASs) of promoters under positive control by CbrB and σ(54) RNA polymerase, especially in the UAS of the crcZ promoter. Evidence for recognition of this palindromic sequence by CbrB was obtained in vivo from mutational analysis of the crcZ promoter and in vitro from electrophoretic mobility shift assays using crcZ promoter fragments and purified CbrB protein truncated at the N terminus. Integration host factor (IHF) was required for crcZ expression. CbrB also activated the lipA (lipase) promoter, albeit less effectively, apparently by interacting with a similar but less conserved palindromic sequence in the UAS of lipA. As expected, succinate caused CbrB-dependent catabolite repression of the lipA promoter. Based on these results and previously published data, a consensus CbrB recognition sequence is proposed. This sequence has similarity to the consensus NtrC recognition sequence, which is relevant for nitrogen control.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Socioeconomics status and quality of care in a population-based sample of swiss diabetic patients

Introduction: Low socioeconomic status (SES) is associated with higher prevalence of diabetes and worse outcomes; it has also been shown to be associated with worse quality of care. We aimed to explore the relationship between SES and quality of care in the Swiss context. Methods: We used data from a population-based survey including 519 adult diabetic patients living in the canton of Vaud. Self-reported data on patients' and diabetes characteristics, indicators of process and outcomes of care and quality of life were collected. Dependent variables included 6 processes of care (PoC) received during the last 12 months (HbA1C, lipid, microalbuminuria, fundoscopy, feet examination and influenza vaccination) and selected clinical outcomes (blood pressure, LDL, HbA1C, diabetes-specific (ADDQoL) and generic quality of life (SF-12)). Regression analyses were performed to assess the relationship between education and income, respectively, and quality of care as measured by PoC and clinical outcomes. Adjustment was made for age, gender and comorbidities. Results: Mean age was 64.5 years, 40% were women; 19%, 56% and 25% of the patients reported primary (I), secondary (II) and tertiary (III) education. Fundoscopy was the only PoC significantly associated with education, with III education patients more likely to get the exam than those with primary education (adjOR 1.8, 95% CI 1.0-3.3). Use of composite indicators of PoC showed that compared to patients with primary education, patients with III education were more likely to receive ≥5/6 PoC (adjOR 1.9, 95% CI 1.1-3.4), and that those with II or III education were more likely to receive 4/4 PoC (adjOR 1.9, 95% CI 1.0-3.3; adjOR 2.1, 95% CI 1.1-4.1, respectively). Quality of life was the only clinical outcome significantly associated with education, with II and III education patients reporting better quality of life compared to primary education patients, as measured by the ADDQoL (β 0.6, 95% CI 0.3-1.0, β 0.6, 95% CI 0.2-1.0, respectively) and the physical component score of the SF-12 (β 2.5, 95% CI 0.2-4.8, β 3.6, 95% CI 0.9-6.4, respectively). No associations were found between income and quality of care. Conclusion: Social inequalities have been demonstrated in Switzerland for global health indicators. Our results suggest that similar associations are found when considering quality of care measures in individuals with diabetes, but only for a few indicators.