Association of urinary calcium excretion with serum calcium and vitamin D levels.

BACKGROUND AND OBJECTIVES: Population-based data on urinary calcium excretion are scarce. The association of serum calcium and circulating levels of vitamin D [25(OH)D2 or D3] with urinary calcium excretion in men and women from a population-based study was explored. DESIGN, SETTINGS, PARTICIPANTS, & MEASUREMENTS: Multivariable linear regression was used to explore factors associated with square root-transformed 24-hour urinary calcium excretion (milligrams per 24 hours) taken as the dependent variable with a focus on month-specific vitamin D tertiles and serum calcium in the Swiss Survey on Salt Study. RESULTS: In total, 624 men and 669 women were studied with mean ages of 49.2 and 47.0 years, respectively (age range=15-95 years). Mean urinary calcium excretion was higher in men than in women (183.05 versus 144.60 mg/24 h; P<0.001). In adjusted models, the association (95% confidence interval) of square root urinary calcium excretion with protein-corrected serum calcium was 1.78 (95% confidence interval, 1.21 to 2.34) mg/24 h per milligram per deciliter in women and 0.59 (95% confidence interval, -0.11 to 1.29) mg/24 h per milligram per deciliter in men. Men in the third 25(OH)D3 tertile had higher square root urinary calcium excretion than men in the first tertile (0.99; 95% confidence interval, 0.36 to 1.63 mg/24 h per nanogram per milliliter), and the corresponding association was 0.32 (95% confidence interval, -0.22 to 0.85) mg/24 h per nanogram per milliliter in women. These sex differences were more marked under conditions of high urinary sodium or urea excretions. CONCLUSIONS: There was a positive association of serum calcium with urinary calcium excretion in women but not men. Vitamin 25(OH)D3 was associated with urinary calcium excretion in men but not women. These results suggest important sex differences in the hormonal and dietary control of urinary calcium excretion.

An introductory review on gravitational-deformation induced structures, fabrics and modeling

Recent studies have pointed out a similarity between tectonics and slope tectonic-induced structures. Numerous studies have demonstrated that structures and fabrics previously interpreted as of purely geodynamical origin are instead the result of large slope deformation, and this led in the past to erroneous interpretations. Nevertheless, their limit seems not clearly defined, but it is somehow transitional. Some studies point out continuity between failures developing at surface with upper crust movements. In this contribution, the main studies which examine the link between rock structures and slope movements are reviewed. The aspects regarding model and scale of observation are discussed together with the role of pre-existing weaknesses in the rock mass. As slope failures can develop through progressive failure, structures and their changes in time and space can be recognized. Furthermore, recognition of the origin of these structures can help in avoiding misinterpretations of regional geology. This also suggests the importance of integrating different slope movement classifications based on distribution and pattern of deformation and the application of structural geology techniques. A structural geology approach in the landslide community is a tool that can greatly support the hazard quantification and related risks, because most of the physical parameters, which are used for landslide modeling, are derived from geotechnical tests or the emerging geophysical approaches.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Trends in overweight and obesity levels in Geneva: time for optimism?

Background/Introduction: ln Switzerland, most trends in overweight and obesity levels have been assessed using reported data, a methodology which is prone to reporting bias. ln this study, we aimed at assessing trends in overweight and obesity levels using objectively measured data. Methods: We used independent cross-sectional data collected between 2005 and 2011 by the Bus Santé study on representative samples of the Geneva population. Trends were assessed overall and according to different characteristics of the participants. Overweight and obesity were defined as a body mass index (BMI) between 25 and 29.9 kg/m2 and >=30 kg/m2, respectively. Results: Data from 4093 participants (2012 men) was assessed. Mean BMI was 25.2 ± 4.3 kg/m2 (mean ±standard deviation) in 2005 and 25.4 ± 4.3 in 2011 (p for trend using linear regression=0.98). For men, mean BMI was 26.3 ± 3.8 kg/m2 in 2005 and 26.1 ± 3.7 in 2011 (p for trend=0.37); for women, the corresponding values were 24.3 ± 4.6 and 24.7 ± 4.7 kg/m2 (p for trend=0.42). Overall prevalence of overweight and obesity was 32.2% and 13.3%, respectively, in 2005 and 33.6% and 13.7% in 2011 (p for trend using polytomous logistic regression adjusting for gender, age and smoking=0.49 and 0.94 for overweight and obesity, respectively). For men, prevalence of overweight and obesity was 45.9% and 12.2% in 2005 and 42.1 % and 14.6% in 2011 (P for trend=0.03 for overweight and 0.81 for obesity); for women, the corresponding values were 20.4% and 14.2% in 2005 and 25.4% and 12.9% in 2011 (p for trend=0.13 for overweight and 0.99 for obesity). Conclusion: Overweight and obesity levels appear to have levelled in Geneva, with a possible decrease in overweight levels in men. These favorable findings should be replicated in other geographical locations.

Multifaceted roles of peroxisome proliferator-activated receptors (PPARs) at the cellular and whole organism levels.

Chronic disorders, such as obesity, diabetes, inflammation, non-alcoholic fatty liver disease and atherosclerosis, are related to alterations in lipid and glucose metabolism, in which peroxisome proliferator-activated receptors (PPAR)α, PPARβ/δ and PPARγ are involved. These receptors form a subgroup of ligand-activated transcription factors that belong to the nuclear hormone receptor family. This review discusses a selection of novel PPAR functions identified during the last few years. The PPARs regulate processes that are essential for the maintenance of pregnancy and embryonic development. Newly found hepatic functions of PPARα are the mediation of female-specific gene repression and the protection of the liver from oestrogen induced toxicity. PPARα also controls lipid catabolism and is the target of hypolipidaemic drugs, whereas PPARγ controls adipocyte differentiation and regulates lipid storage; it is the target for the insulin sensitising thiazolidinediones used to treat type 2 diabetes. Activation of PPARβ/δ increases lipid catabolism in skeletal muscle, the heart and adipose tissue. In addition, PPARβ/δ ligands prevent weight gain and suppress macrophage derived inflammation. In fact, therapeutic benefits of PPAR ligands have been confirmed in inflammatory and autoimmune diseases, such as encephalomyelitis and inflammatory bowel disease. Furthermore, PPARs promote skin wound repair. PPARα favours skin healing during the inflammatory phase that follows injury, whilst PPARβ/δ enhances keratinocyte survival and migration. Due to their collective functions in skin, PPARs represent a major research target for our understanding of many skin diseases. Taken altogether, these functions suggest that PPARs serve as physiological sensors in different stress situations and remain valuable targets for innovative therapies.

Elevated levels of MIC-1/GDF15 in the cerebrospinal fluid of patients are associated with glioblastoma and worse outcome.

For patients with brain tumors identification of diagnostic and prognostic markers in easy accessible biological material, such as plasma or cerebrospinal fluid (CSF), would greatly facilitate patient management. MIC-1/GDF15 (growth differentiation factor 15) is a secreted protein of the TGF-beta superfamily and emerged as a candidate marker exhibiting increasing mRNA expression during malignant progression of glioma. Determination of MIC-1/GDF15 protein levels by ELISA in the CSF of a cohort of 94 patients with intracranial tumors including gliomas, meningioma and metastasis revealed significantly increased concentrations in glioblastoma patients (median, 229 pg/ml) when compared with control cohort of patients treated for non-neoplastic diseases (median below limit of detection of 156 pg/ml, p < 0.0001, Mann-Whitney test). However, plasma MIC-1/GDF15 levels were not elevated in the matching plasma samples from these patients. Most interestingly, patients with glioblastoma and increased CSF MIC-1/GDF15 had a shorter survival (p = 0.007, log-rank test). In conclusion, MIC-1/GDF15 protein measured in the CSF may have diagnostic and prognostic value in patients with intracranial tumors.

Steady-state expression of self-regulated genes.

MOTIVATION: Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations. METHODOLOGY: In this study, we provide new exact formulas and efficient numerical algorithms for computing/modeling the steady-state of a class of self-regulated genes, and we use it to model/compute the stochastic expression of a gene of interest in an engineered network introduced in mammalian cells. The behavior of the genetic network is then analyzed experimentally in living cells. RESULTS: Stochastic models often reveal counter-intuitive experimental behaviors, and we find that this genetic architecture displays a unimodal behavior in mammalian cells, which was unexpected given its known bimodal response in unicellular organisms. We provide a molecular rationale for this behavior, and we implement it in the mathematical picture to explain the experimental results obtained from this network.

Genome size rather than content might affect call properties in toads of three ploidy levels (Anura: Bufonidae: Bufo viridis subgroup).

In vertebrates, genome size has been shown to correlate with nuclear and cell sizes, and influences phenotypic features, such as brain complexity. In three different anuran families, advertisement calls of polyploids exhibit longer notes and intervals than diploids, and difference in cellular dimensions have been hypothesized to cause these modifications. We investigated this phenomenon in green toads (Bufo viridis subgroup) of three ploidy levels, in a different call type (release calls) that may evolve independently from advertisement calls, examining 1205 calls, from ten species, subspecies, and hybrid forms. Significant differences between pulse rates of six diploid and four polyploid (3n, 4n) green toad forms across a range of temperatures from 7 to 27 °C were found. Laboratory data supported differences in pulse rates of triploids vs. tetraploids, but failed to reach significance when including field recordings. This study supports the idea that genome size, irrespective of call type, phylogenetic context, and geographical background, might affect call properties in anurans and suggests a common principle governing this relationship. The nuclear-cell size ratio, affected by genome size, seems the most plausible explanation. However, we cannot rule out hypotheses under which call-influencing genes from an unexamined diploid ancestral species might also affect call properties in the hybrid-origin polyploids.

The shared allelic architecture of adiponectin levels and coronary artery disease.

OBJECTIVE: A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. METHODS: Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium (n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium (n = 85,274). RESULTS: In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing (P < 4.4 × 10(-4)). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD (P = 5.4 × 10(-7)). CONCLUSION: These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

The cost-effectiveness and public health benefit of nalmefene added to psychosocial support for the reduction of alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels: a Markov model.

OBJECTIVES: To determine whether nalmefene combined with psychosocial support is cost-effective compared with psychosocial support alone for reducing alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels (DRLs) as defined by the WHO, and to evaluate the public health benefit of reducing harmful alcohol-attributable diseases, injuries and deaths. DESIGN: Decision modelling using Markov chains compared costs and effects over 5 years. SETTING: The analysis was from the perspective of the National Health Service (NHS) in England and Wales. PARTICIPANTS: The model considered the licensed population for nalmefene, specifically adults with both alcohol dependence and high/very high DRLs, who do not require immediate detoxification and who continue to have high/very high DRLs after initial assessment. DATA SOURCES: We modelled treatment effect using data from three clinical trials for nalmefene (ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941)). Baseline characteristics of the model population, treatment resource utilisation and utilities were from these trials. We estimated the number of alcohol-attributable events occurring at different levels of alcohol consumption based on published epidemiological risk-relation studies. Health-related costs were from UK sources. MAIN OUTCOME MEASURES: We measured incremental cost per quality-adjusted life year (QALY) gained and number of alcohol-attributable harmful events avoided. RESULTS: Nalmefene in combination with psychosocial support had an incremental cost-effectiveness ratio (ICER) of £5204 per QALY gained, and was therefore cost-effective at the £20,000 per QALY gained decision threshold. Sensitivity analyses showed that the conclusion was robust. Nalmefene plus psychosocial support led to the avoidance of 7179 alcohol-attributable diseases/injuries and 309 deaths per 100,000 patients compared to psychosocial support alone over the course of 5 years. CONCLUSIONS: Nalmefene can be seen as a cost-effective treatment for alcohol dependence, with substantial public health benefits. TRIAL REGISTRATION NUMBERS: This cost-effectiveness analysis was developed based on data from three randomised clinical trials: ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941).