Different methods for administering 17β-estradiol to ovariectomized rats result in opposite effects on ischemic brain damage

Background  

Numerous stroke studies have controversially shown estrogens to be either neuroprotective or neurodamaging. The discordant results observed in rat brain ischemia models may be a consequence of discrepancies in estrogen administration modes resulting in plasma concentration profiles far from those intended. To test this hypothesis we reproduced in detail and extended an earlier study from our lab using a different mode of 17β-estradiol administration; home-made silastic capsules instead of commercial slow-release 17β-estradiol pellets. Four groups of female rats (n = 12) were ovariectomized and administered 17β-estradiol or placebo via silastic capsules. All animals underwent MCAo fourteen days after ovariectomy and were sacrificed three days later.     

Measurement uncertainty as a tool for evaluating the ‘grey zone’ to reduce the false negatives in immunochemical screening of blood donors for infectious diseases

The risk of misclassifying infected individuals as healthy constitutes a crucial challenge when screening blood donors by means of immunoassays. This risk is especially challenging when the numerical results are close to the clinical decision level, i.e. in the ‘grey zone’. The concept of using measurement uncertainty for evaluating the ‘grey zone’ has previously not been systematically applied in this context. This article explains methods, models and empirical (top-down) approaches for the calculation of measurement uncertainty using results from a blood bank according to the internationally accepted GUM principles, focusing on uncertainty sources in the analytical phase. Of the different approaches available, the intralaboratory empirical approaches are emphasised since modelling (bottom-up) approaches are impracticable due to the lack of reliable model equations for immunoassays. Different methods are applied to estimate the measurement uncertainty for the Abbott Prism^® HCV immunoassay. The expanded uncertainty obtained at the clinical decision level from the intralaboratory empirical approach was 36 %. The estimated uncertainty was used to set acceptance and rejection zones following the procedure set in the Eurachem guideline, emphasising the need to minimise the occurrence of false negatives.     

Minimizing end-effects in the coaxial cylinders viscometer: Viscoplastic flow inside the ConTec BML Viscometer 3

The ConTec BML Viscometer 3 is designed to measure the rheological properties of fresh concrete. The measuring unit of this device is composed of two parts, where the rheological properties are only registered by the part least affected by end-effects. Thus it is assumed that the measured data is not influenced by end-effects, allowing for the use of an algebraically derived equation to convert the data to fundamental physical quantities. In this work, this important assumption is supported by numerical analysis. This has been done by comparing values calculated by numerical means, where end-effects are included in the analysis, with values calculated by analytical means, where end-effects are excluded.     

Full method validation in clinical chemistry

Accreditation and Quality Assurance - Clinical chemistry is subject to the same principles and standards used in all branches of metrology in chemistry for validation of measurement methods. The...     

Non-parametric estimation of reference intervals in small non-Gaussian sample sets

This study aimed at validating common bootstrap algorithms for reference interval calculation.We simulated 1500 random sets of 50–120 results originating from eight different statistical distributions. In total, 97.5 percentile reference limits were estimated from bootstrapping 5000 replicates, with confidence limits obtained by: (a) normal, (b) from standard error, (c) bootstrap percentile (as in RefVal) (d) BCa, (e) basic, or (f) student methods. Reference interval estimates obtained with ordinary bootstrapping and confidence intervals by percentile method were accurate for distributions close to normality and devoid of outliers, but not for log-normal distributions with outliers. Outlier removal and transformation to normality improved reference interval estimation, and the basic method was superior in such cases. In conclusions, if the neighborhood of the relevant percentile contains non-normally distributed results, bootstrapping fails. The distribution of bootstrap estimates should be plotted, and a non-normal distribution should warrant transformation or outlier removal. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.