Background The cerebrospinal fluid (CSF) biomarkers amyloid beta 1–42, total tau, and phosphorylated tau are used increasingly for Alzheimer’s disease (AD) research and patient management. However, there are large variations in biomarker measurements among and within laboratories. Methods Data from the first nine rounds of the Alzheimer’s Association quality control program was used to define the extent and sources of analytical variability. In each round, three CSF samples prepared at the Clinical Neurochemistry Laboratory (Mölndal, Sweden) were analyzed by single-analyte enzyme-linked immunosorbent assay (ELISA), a multiplexing xMAP assay, or an immunoassay with electrochemoluminescence detection. Results A total of 84 laboratories participated. Coefficients of variation (CVs) between laboratories were around 20% to 30%; within-run CVs, less than 5% to 10%; and longitudinal within-laboratory CVs, 5% to 19%. Interestingly, longitudinal within-laboratory CV differed between biomarkers at individual laboratories, suggesting that a component of it was assay dependent. Variability between kit lots and between laboratories both had a major influence on amyloid beta 1–42 measurements, but for total tau and phosphorylated tau, between-kit lot effects were much less than between-laboratory effects. Despite the measurement variability, the between-laboratory consistency in classification of samples (using prehoc-derived cutoffs for AD) was high (>90% in 15 of 18 samples for ELISA and in 12 of 18 samples for xMAP). Conclusions The overall variability remains too high to allow assignment of universal biomarker cutoff values for a specific intended use. Each laboratory must ensure longitudinal stability in its measurements and use internally qualified cutoff levels. Further standardization of laboratory procedures and improvement of kit performance will likely increase the usefulness of CSF AD biomarkers for researchers and clinicians.

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In a field study carried out in 2011 and 2014 adult dragonflies were identified as a rapid and easy-to-use means of assessing habitat quality and biological integrity of Mediterranean streams and rivers in the province of Barcelona (Region Catalonia, Iberian Peninsula). The study included sampling sites from five different river catchments: Besòs, Foix, Llobregat, Ter and Tordera. Multivariate statistical procedures and indicator species analysis were used to investigate the relationship between river ecological status, study sites and dragonfly species or species assemblages' occurrence. The dragonfly association identified with western Mediterranean permanent streams, i.e. Cordulegaster boltonii, Boyeria irene, Onychogomphus uncatus and Calopteryx virgo meridionalis, was found only at the sites with the highest status. All these taxa were identified as indicator species of sites with the best scores for the macroinvertebrate based IBMWP index and for the combined IASPT index, which reflects the sensitivity of the macroinvertebrate families present to environmental changes; besides, B. irene and C. virgo meridionalis also proved to be indicator species of the riparian forest quality index and C. boltonii of the more inclusive ECOSTRIMED, which assesses the overall conservation status of the riverine habitats. The information obtained on habitat preferences and indicator value showed that adults of these taxa may constitute a valuable tool for preliminary or complementary cost-effective monitoring of river status and restoration practices as part of a broader set of indices reflecting biodiversity and ecosystem integrity.

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Data-driven simulation of pedestrian dynamics is an incipient and promising approach for building reliable microscopic pedestrian models. We propose a methodology based on generalized regression neural networks, which does not have to deal with a huge number of free parameters as in the case of multilayer neural networks. Although the method is general, we focus on the one pedestrian -one obstacle problem. Experimental data were collected in a motion capture laboratory providing high-precision trajectories. The proposed model allows us to simulate the trajectory of a pedestrian avoiding an obstacle from any direction.