Associations Between Performance on an Abbreviated CogState Battery, Other Measures of Cognitive Function, and Biomarkers in People at Risk for Alzheimer\u27s Disease

It is not known whether computerized cognitive assessments, like the CogState battery, are sensitive to preclinical cognitive changes or pathology in people at risk for Alzheimer\u27s disease(AD). In 469 late middle-aged participants from the Wisconsin Registry for Alzheimer\u27s Prevention(mean age 63.8±7 years at testing; 67% female; 39% APOE4+), we examined relationships between a CogState abbreviated battery(CAB) of seven tests and demographic characteristics, traditional paper-based neuropsychological tests as well as a composite cognitive impairment index, cognitive impairment status(determined by consensus review), and biomarkers for amyloid and tau(CSF phosphorylated-tau/Aβ42 and global PET-PiB burden) and neural injury(CSF neurofilament light protein). CSF and PET-PiB were collected in n = 71 and n = 91 participants, respectively, approximately four years prior to CAB testing. For comparison, we examined three traditional tests of delayed memory in parallel. Similar to studies in older samples, the CAB was less influenced by demographic factors than traditional tests. CAB tests were generally correlated with most paper-based cognitive tests examined and mapped onto the same cognitive domains. Greater composite cognitive impairment index was associated with worse performance on all CAB tests. Cognitively impaired participants performed significantly worse compared to normal controls on all but one CAB test. Poorer One Card Learning test performance was associated with higher levels of CSF phosphorylated-tau/Aβ42. These results support the use of the CogState battery as measures of early cognitive impairment in studies of people at risk for AD

Experimental and Theoretical Challenges in the Search for the Quark Gluon Plasma: The STAR Collaboration's Critical Assessment of the Evidence from RHIC Collisions

We review the most important experimental results from the first three years of nucleus-nucleus collision studies at RHIC, with emphasis on results from the STAR experiment, and we assess their interpretation and comparison to theory. The theory-experiment comparison suggests that central Au+Au collisions at RHIC produce dense, rapidly thermalizing matter characterized by: (1) initial energy densities above the critical values predicted by lattice QCD for establishment of a Quark-Gluon Plasma (QGP); (2) nearly ideal fluid flow, marked by constituent interactions of very short mean free path, established most probably at a stage preceding hadron formation; and (3) opacity to jets. Many of the observations are consistent with models incorporating QGP formation in the early collision stages, and have not found ready explanation in a hadronic framework. However, the measurements themselves do not yet establish unequivocal evidence for a transition to this new form of matter. The theoretical treatment of the collision evolution, despite impressive successes, invokes a suite of distinct models, degrees of freedom and assumptions of as yet unknown quantitative consequence. We pose a set of important open questions, and suggest additional measurements, at least some of which should be addressed in order to establish a compelling basis to conclude definitively that thermalized, deconfined quark-gluon matter has been produced at RHIC.Comment: 101 pages, 37 figures; revised version to Nucl. Phys.

State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event

The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P > 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother–child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field

Variations in Suppressor Molecule CTLA-4 Gene Are Related to Susceptibility to Multiple Myeloma in a Polish Population

Various phenotype and functional T-cell abnormalities are observed in multiple myeloma (MM) patients. The aim of this study was to investigate the association between polymorphisms in the gene encoding cytotoxic T-lymphocyte antigen-4 (CTLA-4), a negative regulator of the T-lymphocyte immune response and susceptibility to multiple myeloma in a Polish population. Two hundred MM patients and 380 healthy subjects were genotyped for the following polymorphisms: CTLA-4c.49A>G, CTLA-4g.319C>T, CTLA-4g.*642AT(8_33), CT60 (CTLA-4g.*6230G>A), Jo31 (CTLA-4g.*10223G>T). Our study is the largest and most comprehensive evaluation to date of the association between genetic polymorphisms in the CTLA-4 molecule and multiple myeloma. It was found that CTLA-4c.49A>G[G], CT60[G], and Jo31[G] alleles were more frequently observed in MM patients than in controls (0.50 vs. 0.44, p = 0.03, 0.65 vs. 0.58, p = 0.04, and 0.63 vs. 0.57, p = 0.03, respectively). Moreover, the haplotype CTLA-4c.49A>G[G], CTLA-4g.319C>T[C], CTLA-4g.*642AT(8_33) [8], CT60[G], Jo31[G] including all susceptibility alleles increases the risk of MM about fourfold (OR: 3.79, 95%CI: 2.08–6.89, p = 0.00001). These findings indicate that genetic variations in the CTLA-4 gene play role in susceptibility to multiple myeloma and warrant further investigation through replication studies

The role of impulsivity in the aetiology of drug dependence: reward sensitivity versus automaticity

Journal ArticleResearch Support, Non-U.S. Gov'tCopyright © The Author(s) 2011.RATIONALE: Impulsivity has long been known as a risk factor for drug dependence, but the mechanisms underpinning this association are unclear. Impulsivity may confer hypersensitivity to drug reinforcement which establishes higher rates of instrumental drug-seeking and drug-taking behaviour, or may confer a propensity for automatic (non-intentional) control over drug-seeking/taking and thus intransigence to clinical intervention. METHOD: The current study sought to distinguish these two accounts by measuring Barratt Impulsivity and craving to smoke in 100 smokers prior to their completion of an instrumental concurrent choice task for tobacco (to measure the rate of drug-seeking) and an ad libitum smoking test (to measure the rate of drug-taking-number of puffs consumed). RESULTS: The results showed that impulsivity was not associated with higher rates of drug-seeking/taking, but individual differences in smoking uptake and craving were. Rather, nonplanning impulsivity moderated (decreased) the relationship between craving and drug-taking, but not drug-seeking. CONCLUSIONS: These data suggest that whereas the uptake of drug use is mediated by hypervaluation of the drug as an instrumental goal, the orthogonal trait nonplanning impulsivity confers a propensity for automatic control over well-practiced drug-taking behaviour.MR

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guessing. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as patient-specific biomarker trends. The submission system remains open via the website https://tadpole.grand-challenge.org, while code for submissions is being collated by TADPOLE SHARE: https://tadpole-share.github.io/. Our work suggests that current prediction algorithms are accurate for biomarkers related to clinical diagnosis and ventricle volume, opening up the possibility of cohort refinement in clinical trials for Alzheimer's disease

Proton-lambda correlations in central Au+Au collisions at sqrt (s_NN)=200 GeV

We report on p-Lambda, p-Lambda bar, p bar-Lambda and p bar-Lambda bar correlation functions constructed in central Au-Au collisions at sqrt(s_NN)=200GeV by the STAR experiment at RHIC. The proton and lambda source size is inferred from the p-Lambda and p bar-Lambda bar correlation functions. They are found to be smaller than the pion source size also measured by the STAR detector. This could be a consequence of the collision fireball's collective expansion. The p-Lambda bar and p bar-Lambda correlations, which are measured for the first time, exhibit a large anti-correlation. Annihilation channels and/or a negative real part of the spin-averaged scattering length must be included in the final-state interactions calculation to reproduce the measured correlation function.Comment: 8 pages, 4 figure