Increased circulating placental growth factor during percutaneous coronary intervention is associated with applied radiocontrast agent

BACKGROUND AND AIM OF THE STUDY: Recent studies have suggested placental growth factor (PlGF) and vascular endothelial growth factor (VEGF) as promising new biomarkers for risk stratification in acute coronary syndromes (ACS). However, little is known about the influence of percutaneous coronary intervention (PCI) on circulating PlGF and VEGF levels. METHODS: Thirty-five patients with ACS, 27 patients with stable coronary artery disease (sCAD), and nine healthy controls were enrolled in the study. Although all patients with ACS and 14 patients with stable angina pectoris underwent PCI, 13 patients with coronary artery disease required no revascularization (sCAD). PlGF and VEGF plasma concentrations were measured by immunoassay during and at the end of PCI and coronary angiography. RESULTS: Plasma PlGF levels were comparable in patients with ACS and sCAD on admission. Although coronary angiography or heparin alone did not alter PlGF and VEGF levels, immediately after PCI a dramatic increase was seen in circulating PlGF and a decrease in VEGF, which was independent of the clinical presentation of the patients, heparin administration, or the angiographic procedure itself, but was associated with the extent of coronary artery disease and the amount of the injected contrast media. In-vitro experiments revealed that radiocontrast agents induced the release of PlGF from endothelial cells without altering PlGF mRNA expression. CONCLUSION: Patients undergoing PCI exhibit an increase in circulating PlGF, probably caused by posttranslational modifications of radiocontrast agents in endothelial cells. Therefore, analysis of plasma PlGF and VEGF levels may consider the timing of blood sampling with respect to PCI and contrast media exposure.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Phenotypic associations of Crohn's disease with antibodies to flagellins A4-Fla2 and Fla-X, ASCA, p-ANCA, PAB, and NOD2 mutations in a Swiss Cohort

BACKGROUND: Distinct Crohn's disease (CD) phenotypes correlate with antibody reactivity to microbial antigens. We examined the association between antibody response to 2 new flagellins called A4-Fla2 and Fla-X, anti-Saccharomyces cerevisiae antibodies (ASCA), anti-neutrophil cytoplasmic antibodies (p-ANCA), anti-pancreas antibodies (PAB), NOD2 mutations (R702W, G908R, and L1007fsinsC), and clinical CD phenotypes (according to Vienna criteria). METHODS: All the above-mentioned antibodies as well as NOD2 mutations were determined in 252 CD patients, 53 with ulcerative colitis (UC), and 43 healthy controls (HC) and correlated with clinical data. RESULTS: A seroreactivity for A4-Fla2/Fla-X/ASCA/p-ANCA/PAB (in percent) was found in 59/57/62/12/22 of CD patients, 6/6/4/51/0 of UC patients, and 0/2/5/0/0 of healthy controls. CD behavior: 37% B1, 36% B2, and 27% B3. In multivariate logistic regression, antibodies to A4-Fla2, Fla-X, and ASCA were significantly associated with stricturing phenotype (P = 0.027, P = 0.041, P < 0.001), negative associations were found with inflammatory phenotype (P = 0.001, P = 0.005, P < 0.001). Antibodies to A4-Fla2, Fla-X, ASCA, and NOD2 mutations were significantly associated with small bowel disease (P = 0.013, P = 0.01, P < 0.001, P = 0.04), whereas ASCA was correlated with fistulizing disease (P = 0.007), and small bowel surgery (P = 0.009). Multiple antibody responses against microbial antigens were associated with stricturing (P < 0.001), fistulizing disease (P = 0.002), and small bowel surgery (P = 0.002). CONCLUSIONS: Anti-flagellin antibodies and ASCA are strongly associated with complicated CD phenotypes. CD patients with serum reactivity against multiple microbes have the greatest frequency of strictures, perforations, and small bowel surgery. Further prospective longitudinal studies are needed to show that antibody-based risk stratification improves the clinical outcome of CD patients.

[Treatment of acute coronary syndromes]

This article reviews the diagnostic steps and risk stratification in acute coronary syndromes. Therapeutic measures according to risk stratification are discussed as well. The article also reviews quality assurance in Switzerland (AMIS Plus Registry). Potential future perspectives in the treatment of acute coronary syndromes are shown.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

How well do radiographic absorptiometry and quantitative ultrasound predict osteoporosis at spine or hip? A cost-effectiveness analysis

Dual energy X-ray absorptiometry (DXA) is widely accepted as the reference method for diagnosis and monitoring of osteoporosis and for assessment of fracture risk, especially at hip. However, axial-DXA is not suitable for mass screening, because it is usually confined to specialized centers. We propose a two-step diagnostic approach to postmenopausal osteoporosis: the first step, using an inexpensive, widely available screening technique, aims at risk stratification in postmenopausal women; the second step, DXA of spine and hip is applied only to potentially osteoporotic women preselected on the basis of the screening measurement. In a group of 110 healthy postmenopausal woman, the capability of various peripheral bone measurement techniques to predict osteoporosis at spine and/or hip (T-score < -2.5SD using DXA) was tested using receiver operating characteristic (ROC) curves: radiographic absorptiometry of phalanges (RA), ultrasonometry at calcaneus (QUS. CALC), tibia (SOS.TIB), and phalanges (SOS.PHAL). Thirty-three women had osteoporosis at spine and/or hip with DXA. Areas under the ROC curves were 0.84 for RA, 0.83 for QUS.CALC, 0.77 for SOS.PHAL (p < 0.04 vs RA) and 0.74 for SOS.TIB (p < 0.02 vs RA and p = 0.05 vs QUS.CALC). For levels of sensitivity of 90%, the respective specificities were 67% (RA), 64% (QUS.CALC), 48% (SOS.PHAL), and 39% (SOS.TIB). In a cost-effective two-step, the price of the first step should not exceed 54% (RA), 51% (QUS.CALC), 42% (SOS.PHAL), and 25% (SOS.TIB). In conclusion, RA, QUS.CALC, SOS.PHAL, and SOS.TIB may be useful to preselect postmenopausal women in whom axial DXA is indicated to confirm/exclude osteoporosis at spine or hip.

Prevalence study of Staphylococcus aureus in quarter milk samples of dairy cows in the Canton of Bern, Switzerland

In the present study, the prevalence of S. aureus in mammary gland quarters of dairy cows in Switzerland was estimated and a risk factor analysis was carried out. Dairy cows were selected by one-step-cluster sampling with stratification by herd size. Forty-seven of 50 randomly chosen farms participated in the study, resulting in 603 cows and 2388 quarter samples. Milk samples were collected in all herds on two occasions two weeks apart. In 6% of cows (95% CI: 2.7-9.3%) at least one milk sample was positive for S. aureus and from 2% (0.8-3.2%) of all quarters, S. aureus was cultured at least once. In four quarters a latent S. aureus infection (agent detected and somatic cell count (SCC) <100,000cell/ml) was diagnosed. Multivariable hierarchic logistical regression analysis yielded five significant risk factors for observing S. aureus in a milk sample: high SCC, a S. aureus-positive neighbouring quarter, a palpable induration in the quarter, and a wound, scar tissue or crush injury affecting the teat. The type of housing (P=0.1596) was also a factor that remained in the model. The mentioned risk factors must be considered during the evaluation of herds with S. aureus problems. The occurrence of latent S. aureus infections emphasises that not only quarters with a high SCC but all quarters of all cows must be cultured for control measures to be effective.

High life in the sky? Mortality by floor of residence in Switzerland

Living in high-rise buildings could influence the health of residents. Previous studies focused on structural features of high-rise buildings or characteristics of their neighbourhoods, ignoring differences within buildings in socio-economic position or health outcomes. We examined mortality by floor of residence in the Swiss National Cohort, a longitudinal study based on the linkage of December 2000 census with mortality and emigration records 2001-2008. Analyses were based on 1.5 million people living in buildings with four or more floors and 142,390 deaths recorded during 11.4 million person-years of follow-up. Cox models were adjusted for age, sex, civil status, nationality, language, religion, education, professional status, type of household and crowding. The rent per m² increased with higher floors and the number of persons per room decreased. Mortality rates decreased with increasing floors: hazard ratios comparing the ground floor with the eighth floor and above were 1.22 [95% confidence interval (CI) 1.15-1.28] for all causes, 1.40 (95% CI 1.11-1.77) for respiratory diseases, 1.35 (95% CI 1.22-1.49) for cardiovascular diseases and 1.22 (95% CI 0.99-1.50) for lung cancer, but 0.41 (95% CI 0.17-0.98) for suicide by jumping from a high place. There was no association with suicide by any means (hazard ratio 0.81; 95% CI 0.57-1.15). We conclude that in Switzerland all-cause and cause-specific mortality varies across floors of residence among people living in high-rise buildings. Gradients in mortality suggest that floor of residence captures residual socioeconomic stratification and is likely to be mediated by behavioural (e.g. physical activity), and environmental exposures, and access to a method of suicide.

LakeMIP Kivu: evaluating the representation of a large, deep tropical lake by a set of one-dimensional lake models

The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the model’s performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible.