Harmonizing neuropsychological assessment for mild neurocognitive disorders in Europe

INTRODUCTION Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts. METHODS To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives. RESULTS With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes. DISCUSSION This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION: The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015. METHODS: We used standard searches to find publications using ADNI data. RESULTS: (1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers. DISCUSSION: Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial desig

A hierarchy of heuristic-based models of crowd dynamics

International audienceWe derive a hierarchy of kinetic and macroscopic models from a noisy variant of the heuristic behavioral Individual-Based Model of Moussaid et al, PNAS 2011, where the pedestrians are supposed to have constant speeds. This IBM supposes that the pedestrians seek the best compromise between navigation towards their target and collisions avoidance. We first propose a kinetic model for the probability distribution function of the pedestrians. Then, we derive fluid models and propose three different closure relations. The first two closures assume that the velocity distribution functions are either a Dirac delta or a von Mises-Fisher distribution respectively. The third closure results from a hydrodynamic limit associated to a Local Thermodynamical Equilibrium. We develop an analogy between this equilibrium and Nash equilibia in a game theoretic framework. In each case, we discuss the features of the models and their suitability for practical use

Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder.

Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause of neurodevelopmental disability. Whole transcriptome sequencing (RNA-Seq) offer insights into mechanisms underlying FASD, but gene-level analysis provides limited information regarding complex transcriptional processes such as alternative splicing and non-coding RNAs. Moreover, traditional analytical approaches that use multiple hypothesis testing with a false discovery rate adjustment prioritize genes based on an adjusted p-value, which is not always biologically relevant. We address these limitations with a novel approach and implemented an unsupervised machine learning model, which we applied to an exon-level analysis to reduce data complexity to the most likely functionally relevant exons, without loss of novel information. This was performed on an RNA-Seq paired-end dataset derived from alcohol-exposed neural fold-stage chick crania, wherein alcohol causes facial deficits recapitulating those of FASD. A principal component analysis along with k-means clustering was utilized to extract exons that deviated from baseline expression. This identified 6857 differentially expressed exons representing 1251 geneIDs; 391 of these genes were identified in a prior gene-level analysis of this dataset. It also identified exons encoding 23 microRNAs (miRNAs) having significantly differential expression profiles in response to alcohol. We developed an RDAVID pipeline to identify KEGG pathways represented by these exons, and separately identified predicted KEGG pathways targeted by these miRNAs. Several of these (ribosome biogenesis, oxidative phosphorylation) were identified in our prior gene-level analysis. Other pathways are crucial to facial morphogenesis and represent both novel (focal adhesion, FoxO signaling, insulin signaling) and known (Wnt signaling) alcohol targets. Importantly, there was substantial overlap between the exomes themselves and the predicted miRNA targets, suggesting these miRNAs contribute to the gene-level expression changes. Our novel application of unsupervised machine learning in conjunction with statistical analyses facilitated the discovery of signaling pathways and miRNAs that inform mechanisms underlying FASD

The matrix metalloproteinase and insulin-like growth factor system in oral cancer – a prospective clinical study

Eik Schiegnitz,1 Peer W Kämmerer,2 Holger Schön,1 Christoph Gülle,1 Manfred Berres,3,4 Keyvan Sagheb,1 Bilal Al-Nawas5 1Department of Oral and Maxillofacial Surgery, Plastic Surgery, University Medical Center, Johannes Gutenberg University of Mainz, Mainz, 2Department of Oral and Maxillofacial Surgery, Plastic Surgery, University Medical Centre Rostock, Rostock, 3Department of Mathematics and Technology, University of Applied Sciences Koblenz, Remagen, 4Institute of Medical Biometry, Epidemiology and Informatics, Johannes Gutenberg University of Mainz, Mainz, 5Department of Oral and Maxillofacial Surgery, Plastic Surgery, University Medical Centre, Martin-Luther University Halle, Halle, Germany Aim: The absence of reliable single serum biomarkers for oral premalignant lesion (OPL) and oral squamous cell carcinoma (OSCC) limits early diagnosis, monitoring of advanced disease, and prediction of prognosis. Methods: In this prospective study, serum levels of matrix metalloproteinase (MMP)-2, MMP-3, MMP-13, insulin-like growth factor (IGF)-1, and IGF-binding protein (IGFBP)-3 were measured in 81 untreated OSCC patients, 49 healthy subjects, and 75 individuals with OPLs, and correlated with clinicopathological parameters. Results: Serum levels of MMP-3 were significantly higher in OSCC patients compared to healthy subjects (p=0.004). Mean IGF-1 and IGFBP-3 levels in OSCC patients were significantly lower in healthy subjects (p=0.001 and p<0.001). OSCC patients with an IGF-1 serum value <130 ng/mL (median) showed a significantly lower survival rate compared to ≥130 ng/mL (p=0.049). Combined use of IGF-1 (<130 ng/mL) and IGFBP-3 (<3.1 µg/mL) resulted in a significantly lower 12-month cumulative survival compared to the complementary set (78.5% vs 93.8%; p=0.031). There was a significantly positive correlation between IGF-1 and IGFBP-3 serum values (rs =0.625, p<0.001). Conclusion: This study shows that IGF-1 and IGFBP-3 have a vital role in the pathogenesis of OSCC and indicates for the first time that IGF-1 and IGFBP-3 in combination may be applied as potential tools for prognosis of OSCC. Keywords: oral cancer, OSCC, oral premalignant lesion, serum biomarker, prognosis, IGF, MM

Evaluation of a summary score of cognitive performance for use in trials in perioperative and critical care.

Background/Aims: Cognitive dysfunction after medical treatment is increasingly being recognized. Studies on this topic require repeated cognitive testing within a short time. However, with repeated testing, practice effects must be expected. We quantified practice effects in a demographically corrected summary score of a neuropsychological test battery repeatedly administered to healthy elderly volunteers. Methods: The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Neuropsychological Assessment Battery (for which a demographically corrected summary score was developed), phonemic fluency tests, and trail-making tests were administered in healthy volunteers aged 65 years or older on days 0, 7, and 90. This battery allows calculation of a demographically adjusted continuous summary score. Results: Significant practice effects were observed in the CERAD total score and in the word list (learning and recall) subtest. Based on these volunteer data, we developed a threshold for diagnosis of postoperative cognitive dysfunction (POCD) with the CERAD total score. Conclusion: Practice effects with repeated administration of neuropsychological tests must be accounted for in the interpretation of such tests. Ignoring practice effects may lead to an underestimation of POCD. The usefulness of the proposed demographically adjusted continuous score for cognitive function will have to be tested prospectively in patients