International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Optimising Uncertainty in Physical Sample Preparation

Uncertainty associated with the result of a measurement can be dominated by the physical sample preparation stage of the measurement process. In view of this, the Optimised Uncertainty (OU) methodology has been further developed to allow the optimisation of the uncertainty from this source, in addition to that from the primary sampling and the subsequent chemical analysis. This new methodology for the optimisation of physical sample preparation uncertainty (uprep, estimated as sprep) is applied for the first time, to a case study of myclobutanil in retail strawberries. An increase in expenditure (+7865%) on the preparatory process was advised in order to reduce the sprep by the 69% recommended. This reduction is desirable given the predicted overall saving, under optimised conditions, of £33000 per batch. This new methodology has been shown to provide guidance on the appropriate distribution of resources between the three principle stages of a measurement process, including physical sample preparation

Empirical versus modelling approaches to the estimation of measurement uncertainty caused by primary sampling

Measurement uncertainty is a vital issue within analytical science. There are strong arguments that primary sampling should be considered the first and perhaps the most influential step in the measurement process. Increasingly, analytical laboratories are required to report measurement results to clients together with estimates of the uncertainty. Furthermore, these estimates can be used when pursuing regulation enforcement to decide whether a measured analyte concentration is above a threshold value. With its recognised importance in analytical measurement, the question arises of `what is the most appropriate method to estimate the measurement uncertainty?¿. Two broad methods for uncertainty estimation are identified, the modelling method and the empirical method. In modelling, the estimation of uncertainty involves the identification, quantification and summation (as variances) of each potential source of uncertainty. This approach has been applied to purely analytical systems, but becomes increasingly problematic in identifying all of such sources when it is applied to primary sampling. Applications of this methodology to sampling often utilise long-established theoretical models of sampling and adopt the assumption that a `correct¿ sampling protocol will ensure a representative sample. The empirical approach to uncertainty estimation involves replicated measurements from either inter-organisational trials and/or internal method validation and quality control. A more simple method involves duplicating sampling and analysis, by one organisation, for a small proportion of the total number of samples. This has proven to be a suitable alternative to these often expensive and time-consuming trials, in routine surveillance and one-off surveys, especially where heterogeneity is the main source of uncertainty. A case study of aflatoxins in pistachio nuts is used to broadly demonstrate the strengths and weakness of the two methods of uncertainty estimation. The estimate of sampling uncertainty made using the modelling approach (136%, at 68% confidence) is six times larger than that found using the empirical approach (22.5%). The difficulty in establishing reliable estimates for the input variable for the modelling approach is thought to be the main cause of the discrepancy. The empirical approach to uncertainty estimation, with the automatic inclusion of sampling within the uncertainty statement, is recognised as generally the most practical procedure, providing the more reliable estimates. The modelling approach is also shown to have a useful role, especially in choosing strategies to change the sampling uncertainty, when required

Single-laboratory validation of a GC/MS method for the determination of 27 polycyclic aromatic hydrocarbons (PAHs) in oils and fats

International audienceA protocol for the measurement of 27 polycyclic aromatic hydrocarbons in vegetable oils by gas chromatography – mass spectrometry has undergone single-laboratory validation. Analytes were measured in three oils (olive pomace oil, sunflower oil and coconut oil). Five samples of each oil (one unfortified, and four fortified at concentrations between 2 mg/kg and 50 mg/kg) were analysed in replicate (four times in separate runs). Two samples (one unfortified and one fortified at 2 mg/kg) of five oils (virgin olive oil, grapeseed oil, toasted sesame oil, olive margarine and palm oil) were also analysed. The validation included an assessment of measurement bias from the results of 120 measurements of a certified reference material (coconut oil BCR CRM458 certified for 6 PAHs). The protocol is capable of reliably detecting 26 out of 27 PAHs, at concentrations less than 2 mg/kg which is the EU maximum limit for benzo[a]pyrene, in vegetable oils, olive pomace oil, sunflower oil and coconut oil. The protocol produces quantitative results that are fit for purpose for concentrations from below 2 mg/kg to 50 mg/kg for 24 out of 27 PAHs in olive pomace oil, sunflower oil and coconut oil. The reliable detection of 2 mg/kg of PAHs in five additional oils (virgin olive oil, grapeseed oil, toasted sesame oil, olive margarine and palm oil) has been demonstrated. The protocol failed to produce fit for purpose results for the measurement of dibenzo[a,h]pyrene, anthanthrene and cyclopenta[c,d]pyrene. The reason for the failure was the large variation in results. The likely cause of this was the lack of availability of 13C isotope internal standards for these analytes at the time of the study. The protocol has been shown to be fit for purpose and is suitable for formal validation by collaborative trial

A Comparison of the Extraction Methods used in the UK Nitrate Residues Monitoring Program

Summar

Modifying uncertainty from sampling to achieve fitness for purpose: a case study on nitrate in lettuce

Existing methods have been applied to estimate the uncertainty of measurement, caused by both sampling and analysis, and fitness-for-purpose of these measurements. A new approach has been taken to modify the measurement uncertainty by changing the contribution made by the sampling process. A case study on nitrate in lettuce has been used to demonstrate the applicability of this new generic approach. The sampling theory of Gy was used to predict the alterations in the sampling protocol required to achieve the necessary change in sampling uncertainty. An experimental application of this altered sampling protocol demonstrated that the predicted change in sampling uncertainty was achieved in practice. For the lettuce case study, this approach showed that composite samples containing 40 heads, rather than the usual ten heads, produced measurements of nitrate that where more fit-for-purpose

Study of functional barrier properties of multilayer recycled poly(ethylene terephthalate) bottles for soft drinks

Poly(ethylene terephthalate) (PET) flakes were ground, contaminated, washed, manufactured into multilayer preforms and bottles, and then tested for migration. The model contaminants were toluene, trichloroethane, chlorobenzene, phenyldecane, benzophenone, phenylcyclohexane, and copper(II) acetylacetonate. No migration was detected through a barrier of virgin PET (186 ± 39 μm) into 3% acetic acid food simulant using general methods of testing with a detection limit of 1 μg kg-1. Migration was <1 μg kg-1 even for 6-month-old bottles placed in contact with the simulant for a further 6 months; that is, a test period considerably in excess of the shelf life of soft drinks. Neither was migration detectable in the more severe simulating solvents (e.g., 50% aqueous ethanol and 100% ethanol). Targeted analysis by gas chromatography-mass spectroscopy was then used to achieve a sub microgram per kilogram limit of detection and establish the performance of the barrier. Three-layer bottles with the contaminated PET buried were compared with 1-layer bottles in which contaminated PET contacted the food simulant directly. Migration into 3% acetic acid from 1-layer bottles was from <0.2 to 57 μg kg-1, and the worst-case substance was chlorobenzene. Migration from 3-layer bottles was from <0.2 up to 0.4 μg kg-1, and the worst-case substance was toluene. Therefore, the virgin PET layer reduced migration from an already low level, by more than 2 orders of magnitude