Camless engines require independent actuators which can provide accurate control, sufficient force, and yet only require a small percentage of engine output power. A valve actuation system that meets these requirements is designed, modeled, and simulated at engine speeds up to 6000 rpm. Based on consideration of valve actuation cycles and hydraulic power efficiency, an open-center system employing control valves in series is simulated under various operating conditions and using a range of design parameter values. The results demonstrate that the proposed system is capable of meeting the 6000 rpm engine speed requirement while using as little as 1–2% of available engine power. In addition, the system lends itself well to either open-loop or closed-loop control without requiring a separate position sensor on each engine valve [1]. This potentially reduces the cost and increases the reliability of an actuation system designed for camless engines.

Objective Due to the high awareness of coeliac disease and improvement of serological tests, the number of requested laboratory tests has increased substantially over the years. In the current study we have evaluated the requesting behaviour of distinct clinical disciplines in relation to the prevalence of positive results and in the context of existing guidelines. Methods Data were retrospectively extracted from the laboratory information system over a time-span of 5 years in a tertiary hospital and compared with the situation in a secondary hospital. Results Data reveal that for initial testing (n=18,183) the percentage positive results for IgA anti-TTG is <2%. Paediatricians have a slightly higher percentage of seropositive results (2.4–4.0%). Early confirmation (<2 months) of positive results by IgA anti-endomysium antibodies in an independent sample is only performed in a minority of paediatric patients. The majority of positive patients, however, have follow-up measurements (<14 months) in order to examine compliance to a gluten-free diet. Interestingly, initial requests for paediatric patients reveal an equal distribution between boys and girls, while in adult patients there is a two times preponderance of requests in female patients, similar to the female/male ratio in patients with positive results, being either paediatric or adult patients. Conclusion Although laboratory testing for coeliac disease may be primarily used to exclude the disease, it is evident that the percentage positive results for IgA anti-TTG is extremely low. This may indicate that the clinical manifestations that warrant testing, should be further specified in order to increase the pre-test probability. As the specific serology is important to bypass a biopsy in the diagnosis of coeliac disease according to the paediatric guideline, the confirmation in an independent sample needs to get more attention.

BackgroundPlasma biomarkers for Alzheimer’s disease (AD) have demonstrated great performance to identify AD pathology in research cohorts, and recent studies also support their potential to monitor effects of disease‐modifying treatments. To properly interpret these biomarkers in research settings and to inform power calculations of future trials using them as surrogate outcomes, information on their physiological variability over time is needed. We conducted a 10‐week biological variation (BV) study to assess the within‐individual (CVI; CV: coefficient of variation), between‐individual (CVG) and analytical variability (CVA) of blood‐based AD biomarkers. These parameters can provide the reference change value (RCV), which determines how much biomarker values must change to represent a significant abnormality‐related change, i.e. exceeding analytical and biological variation.MethodPlasma samples were collected weekly for 10 weeks from 20 healthy individuals from the European Biological Variation Study (n=20; 50% female, median age 46.4). Biomarkers for tau pathology (p‐tau181), brain amyloidosis (Aβ42, Aβ40, Aβ42/40), glial activation (GFAP) and neurodegeneration (NfL) were quantified in duplicate using the Simoa technology. The CV‐ANOVA statistical method was used to compute BV estimates. To evaluate diurnal rhythm of these biomarkers, we also conducted a study with non‐demented older adults (n=24; 58‐82yo), with hourly blood collections during 26h in strictly‐controlled environmental conditions (NCT02091427). P‐tau217 (Lily) analyses are ongoing for both studies.ResultIndividual‐level (Figure 1) and pooled biomarker levels are shown (Figure 2), as well as BV estimates (Table 1). The 10‐week within‐individual physiological variation (CVI) was lower for Aβ42/40 (4.3%), followed by Aβ42 (6.0%), Aβ40 (6.4%), NfL (7.9%), GFAP (9.3%) and p‐tau181 (15.8%). Between‐individual variation (CVG) was lower for Aβ42/40 (8.8%), followed by Aβ42 (13.3%), Aβ40 (17.0%), p‐tau181 (20.5%), NfL (23.0%) and GFAP (31.5%). Analytical variation was low for all biomarkers (CVA range: 2.5‐6.6%). The RCV was higher for p‐tau181 (45.6%), followed by GFAP (31.7%), NfL (27.6%), Aβ40 (19.0%), Aβ42 (18.8%) and Aβ42/40 (15.6%).ConclusionBlood‐based AD biomarkers demonstrate good week‐to‐week stability, but their CVG and RCV’s can be rather high, with implications both for use in clinical routine (misclassification risk) and for future trial designs (high numbers of participants needed). Results for the diurnal variation study will also be presented.

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