276 research outputs found

    The Effect of Lifecourse Socioeconomic Position and Health on Trajectories of Cognitive Function in Older Adults.

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    Recent studies suggest that socioeconomic position (SEP) across the lifecourse may influence health, and more specifically cognitive health, through several pathways. However, few studies examining the effect of SEP on cognition have benefited from the use of longitudinal data and most have been confined to specific subpopulations of older adults or have been limited to restricted geographic areas. This overall goal of this dissertation research was to apply a lifecourse approach to the conceptualization and modeling of the social and economic determinants of cognitive performance, and attempt to further understand the relationship between disadvantage at different life stages and cognitive health in adulthood. This research uses data from the Health and Retirement Study (HRS), a nationally representative, prospective panel study of adults over 50 years of age, to: (1) estimate the effects of education and adulthood socioeconomic position on trajectories of cognitive change, (2) determine whether accumulation of socioeconomic disadvantage and social mobility from childhood to adulthood affects cognitive function, and (3) examine the association between body mass index and cognitive performance and decline in later life. These results support prior work documenting the lasting impact of education on cognition and suggest that measures of lifecourse SEP and adiposity may also be significant predictors of cognitive performance and change in older age.Ph.D.Epidemiological ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58434/1/jfaul_1.pd

    P2‐540: Polygenetic Risk For Alzheimer’S Disease And Dementia Status

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153242/1/alzjjalz2019062948.pd

    Role of Extracellular Ionized Calcium in the In Vitro Assessment of GPIIb/IIIa Receptor Antagonists

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    Several preclinical studies have found a poor correlation between the ex vivo platelet inhibitory potency and the in vivo antithrombotic efficacy of GPIIb/IIIa receptor antagonists. The present study was designed to examine the differential in vitro potencies of c7E3, MK-383, DMP-728, and SM-20302 in inhibiting ex vivo platelet aggregation under normocalcemic and hypocalcemic conditions. Human blood was collected in either trisodium citrate (0.37%) or PPACK (20 ”g/mL). Platelet aggregation assays were performed in platelet-rich plasma from citrate-anticoagulated blood (cPRP) and PPACK-anticoagulated blood (pPRP) using ADP (20 ”M) and TRAP (10 ”M) as agonists in the presence of c7E3, MK-383, DMP-728, or SM-20302. The concentration of ionized calcium in cPRP was 16–19 times lower than that in pPRP. The IC 50 of c7E3 for inhibiting ADP-induced platelet aggregation in cPRP (2.76 ± 0.11 ”g/mL) was 1.6 times lower than that in pPRP (4.46 ± 0.48 ”g/mL; P < 0.05). Similarly, the IC 50 for c7E3 for inhibiting TRAP-induced platelet aggregation in cPRP (4.52 ± 0.34 ”g/mL) was 1.7 times lower than that in pPRP (7.69 ± 0.43 ”g/mL; P < 0.05). MK-383, DMP-728, and SM-20302 also demonstrated 1.96-, 1.15-, and 1.43-fold lower IC 50 values, respectively, in cPRP as compared with pPRP. Chelation of ionized calcium in pPRP led to a progressive increase in platelet inhibition by all the antagonists. These results suggest that the observed in vitro inhibitory potency of a GPIIb/IIIa receptor antagonist is markedly enhanced when trisodium citrate is used as an anticoagulant to collect blood for ex vivo assay. These findings indicate that dosing regimens for GPIIb/IIIa receptor antagonists based on the platelet inhibition profile in citrate may provide misleading information with respect to their true in vivo antithrombotic efficacy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48046/1/11239_2004_Article_202949.pd

    Racial and Ethnic Differences in Knowledge About One’s Dementia Status

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156478/1/jgs16442.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156478/3/jgs16442_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156478/2/jgs16442-sup-0001-supinfo.pd

    Speed accuracy tradeoff? Not so fast: Marginal changes in speed have inconsistent relationships with accuracy in real-world settings

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    The speed-accuracy tradeoff suggests that responses generated under time constraints will be less accurate. While it has undergone extensive experimental verification, it is less clear whether it applies in settings where time pressures are not being experimentally manipulated (but where respondents still vary in their utilization of time). Using a large corpus of 29 response time datasets containing data from cognitive tasks without experimental manipulation of time pressure, we probe whether the speed-accuracy tradeoff holds across a variety of tasks using idiosyncratic within-person variation in speed. We find inconsistent relationships between marginal increases in time spent responding and accuracy; in many cases, marginal increases in time do not predict increases in accuracy. However, we do observe time pressures (in the form of time limits) to consistently reduce accuracy and for rapid responses to typically show the anticipated relationship (i.e., they are more accurate if they are slower). We also consider analysis of items and individuals. We find substantial variation in the item-level associations between speed and accuracy. On the person side, respondents who exhibit more within-person variation in response speed are typically of lower ability. Finally, we consider the predictive power of a person's response time in predicting out-of-sample responses; it is generally a weak predictor. Collectively, our findings suggest the speed-accuracy tradeoff may be limited as a conceptual model in its application in non-experimental settings and, more generally, offer empirical results and an analytic approach that will be useful as more response time data is collected
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