Pittsburgh compound B imaging and cerebrospinal fluid amyloid-β in a multicentre European memory clinic study

The aim of this study was to assess the agreement between data on cerebral amyloidosis, derived using Pittsburgh compound B positron emission tomography and (i) multi-laboratory INNOTEST enzyme linked immunosorbent assay derived cerebrospinal fluid concentrations of amyloid-β 42 ; (ii) centrally measured cerebrospinal fluid amyloid-β 42 using a Meso Scale Discovery enzyme linked immunosorbent assay; and (iii) cerebrospinal fluid amyloid-β 42 centrally measured using an antibody-independent mass spectrometry-based reference method. Moreover, we examined the hypothesis that discordance between amyloid biomarker measurements may be due to interindividual differences in total amyloid-β production, by using the ratio of amyloid-β 42 to amyloid-β 40 . Our study population consisted of 243 subjects from seven centres belonging to the Biomarkers for Alzheimer’s and Parkinson’s Disease Initiative, and included subjects with normal cognition and patients with mild cognitive impairment, Alzheimer’s disease dementia, frontotemporal dementia, and vascular dementia. All had Pittsburgh compound B positron emission tomography data, cerebrospinal fluid INNOTEST amyloid-β 42 values, and cerebrospinal fluid samples available for reanalysis. Cerebrospinal fluid samples were reanalysed (amyloid-β 42 and amyloid-β 40 ) using Meso Scale Discovery electrochemiluminescence enzyme linked immunosorbent assay technology, and a novel, antibody-independent, mass spectrometry reference method. Pittsburgh compound B standardized uptake value ratio results were scaled using the Centiloid method. Concordance between Meso Scale Discovery/mass spectrometry reference measurement procedure findings and Pittsburgh compound B was high in subjects with mild cognitive impairment and Alzheimer’s disease, while more variable results were observed for cognitively normal and non-Alzheimer’s disease groups. Agreement between Pittsburgh compound B classification and Meso Scale Discovery/mass spectrometry reference measurement procedure findings was further improved when using amyloid-β 42/40 . Agreement between Pittsburgh compound B visual ratings and Centiloids was near complete. Despite improved agreement between Pittsburgh compound B and centrally analysed cerebrospinal fluid, a minority of subjects showed discordant findings. While future studies are needed, our results suggest that amyloid biomarker results may not be interchangeable in some individuals

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens

Cell walls of the dimorphic fungal pathogens Sporothrix schenckii and Sporothrix brasiliensis exhibit bilaminate structures and sloughing of extensive and intact layers

This work was supported by the Fundação Carlos Chagas de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), grants E-26/202.974/2015 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), grants 229755/2013-5, Brazil. LMLB is a senior research fellow of CNPq and Faperj. NG acknowledged support from the Wellcome Trust (Trust (097377, 101873, 200208) and MRC Centre for Medical Mycology (MR/N006364/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks

Biological plastic neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifetime learning. The interplay of these elements leads to the emergence of adaptive behavior and intelligence. Inspired by such intricate natural phenomena, Evolved Plastic Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed plastic neural networks with a large variety of dynamics, architectures, and plasticity rules: these artificial systems are composed of inputs, outputs, and plastic components that change in response to experiences in an environment. These systems may autonomously discover novel adaptive algorithms, and lead to hypotheses on the emergence of biological adaptation. EPANNs have seen considerable progress over the last two decades. Current scientific and technological advances in artificial neural networks are now setting the conditions for radically new approaches and results. In particular, the limitations of hand-designed networks could be overcome by more flexible and innovative solutions. This paper brings together a variety of inspiring ideas that define the field of EPANNs. The main methods and results are reviewed. Finally, new opportunities and developments are presented

EuropeaN Energy balance Research to prevent excessive weight Gain among Youth (ENERGY) project: Design and methodology of the ENERGY cross-sectional survey

Background: Obesity treatment is by large ineffective long term, and more emphasis on the prevention of excessive weight gain in childhood and adolescence is warranted. To inform energy balance related behaviour (EBRB) change interventions, insight in the potential personal, family and school environmental correlates of these behaviours is needed. Studies on such multilevel correlates of EBRB among schoolchildren in Europe are lacking. The ENERGY survey aims to (1) provide up-to-date prevalence rates of measured overweight, obesity, self-reported engagement in EBRBs, and objective accelerometer-based assessment of physical activity and sedentary behaviour and blood-sample biomarkers of metabolic function in countries in different regions of Europe, (2) to identify personal, family and school environmental correlates of these EBRBs. This paper describes the design, methodology and protocol of the survey. Method/Design: A school-based cross-sectional survey was carried out in 2010 in seven different European countries; Belgium, Greece, Hungary, the Netherlands, Norway, Slovenia, and Spain. The survey included measurements of anthropometrics, child, parent and school-staff questionnaires, and school observations to measure and assess outcomes (i.e. height, weight, and waist circumference), EBRBs and potential personal, family and school environmental correlates of these behaviours including the social-cultural, physical, political, and economic environmental factors. In addition, a selection of countries conducted accelerometer measurements to objectively assess physical activity and sedentary behaviour, and collected blood samples to assess several biomarkers of metabolic function. Discussion: The ENERGY survey is a comprehensive cross-sectional study measuring anthropometrics and biomarkers as well as assessing a range of EBRBs and their potential correlates at the personal, family and school level, among 10-12 year old children in seven European countries. This study will result in a unique dataset, enabling cross country comparisons in overweight, obesity, risk behaviours for these conditions as well as the correlates of engagement in these risk behaviours