2 research outputs found

    The ATLAS Fast Tracker Processing Units - track finding and fitting

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    The Fast Tracker is a hardware upgrade to the ATLAS trigger and data-acquisition system, with the goal of providing global track reconstruction by the start of the High Level Trigger starts. The Fast Tracker can process incoming data from the whole inner detector at full first level trigger rate, up to 100 kHz, using custom electronic boards. At the core of the system is a Processing Unit installed in a VMEbus crate, formed by two sets of boards: the Associative Memory Board and a powerful rear transition module called the Auxiliary card, while the second set is the Second Stage board. The associative memories perform the pattern matching looking for correlations within the incoming data, compatible with track candidates at coarse resolution. The pattern matching task is performed using custom application specific integrated circuits, called associative memory chips. The auxiliary card prepares the input and reject bad track candidates obtained from from the Associative Memory Board using the full precision and a linearized fit. The track candidates from the auxiliary card use only 8 of 12 silicon layers, the track segments are extended to the additional layers by the Second Stage Board. During the first half of 2016, the first Fast Tracker VMEbus Processing Units will be installed in the ATLAS cavern. This talk will summarize the experience with newer associative memory chips and the boards; monitoring/debugging tools, including input/output data rates, track finding efficiency and track fitting results. Comparisons of the different metrics with offline simulation will also be shown

    Penetrance estimation of Alzheimer disease in SORL1 loss-of-function variant carriers using a family-based strategy and stratification by APOE genotypes

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    International audienceAbstract Background Alzheimer disease (AD) is a common complex disorder with a high genetic component. Loss-of-function (LoF) SORL1 variants are one of the strongest AD genetic risk factors. Estimating their age-related penetrance is essential before putative use for genetic counseling or preventive trials. However, relative rarity and co-occurrence with the main AD risk factor, APOE -ε4, make such estimations difficult. Methods We proposed to estimate the age-related penetrance of SORL1 -LoF variants through a survival framework by estimating the conditional instantaneous risk combining (i) a baseline for non-carriers of SORL1- LoF variants, stratified by APOE-ε4 , derived from the Rotterdam study ( N = 12,255), and (ii) an age-dependent proportional hazard effect for SORL1- LoF variants estimated from 27 extended pedigrees (including 307 relatives ≥ 40 years old, 45 of them having genotyping information) recruited from the French reference center for young Alzheimer patients. We embedded this model into an expectation-maximization algorithm to accommodate for missing genotypes. To correct for ascertainment bias, proband phenotypes were omitted. Then, we assessed if our penetrance curves were concordant with age distributions of APOE -ε4-stratified SORL1- LoF variant carriers detected among sequencing data of 13,007 cases and 10,182 controls from European and American case-control study consortia. Results SORL1- LoF variants penetrance curves reached 100% (95% confidence interval [99–100%]) by age 70 among APOE -ε4ε4 carriers only, compared with 56% [40–72%] and 37% [26–51%] in ε4 heterozygous carriers and ε4 non-carriers, respectively. These estimates were fully consistent with observed age distributions of SORL1- LoF variant carriers in case-control study data. Conclusions We conclude that SORL1- LoF variants should be interpreted in light of APOE genotypes for future clinical applications
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