Search

BackgroundObservational studies have shown reduced risk of Alzheimer dementia in users of nonsteroidal anti-inflammatory drugs.ObjectiveTo evaluate the effects of naproxen sodium and celecoxib on cognitive function in older adults.DesignRandomized, double-masked chemoprevention trial.SettingSix US memory clinics.ParticipantsMen and women aged 70 years and older with a family history of Alzheimer disease; 2117 of 2528 enrolled had follow-up cognitive assessment.InterventionsCelecoxib (200 mg twice daily), naproxen sodium (220 mg twice daily), or placebo, randomly allocated in a ratio of 1:1:1.5, respectively.Main outcome measuresSeven tests of cognitive function and a global summary score measured annually.ResultsLongitudinal analyses showed lower global summary scores over time for naproxen compared with placebo (- 0.05 SDs; P = .02) and lower scores on the Modified Mini-Mental State Examination over time for both treatment groups compared with placebo (- 0.33 points for celecoxib [P = .04] and - 0.36 points for naproxen [P = .02]). Restriction of analyses to measures collected from persons without dementia attenuated the treatment group differences. Analyses limited to measures obtained while participants were being issued study drugs produced results similar to the intention-to-treat analyses.ConclusionsUse of naproxen or celecoxib did not improve cognitive function. There was weak evidence for a detrimental effect of naproxen.

BackgroundObservational studies have shown reduced risk of Alzheimer dementia in users of nonsteroidal anti-inflammatory drugs.ObjectiveTo evaluate the effects of naproxen sodium and celecoxib on cognitive function in older adults.DesignRandomized, double-masked chemoprevention trial.SettingSix US memory clinics.ParticipantsMen and women aged 70 years and older with a family history of Alzheimer disease; 2117 of 2528 enrolled had follow-up cognitive assessment.InterventionsCelecoxib (200 mg twice daily), naproxen sodium (220 mg twice daily), or placebo, randomly allocated in a ratio of 1:1:1.5, respectively.Main outcome measuresSeven tests of cognitive function and a global summary score measured annually.ResultsLongitudinal analyses showed lower global summary scores over time for naproxen compared with placebo (- 0.05 SDs; P = .02) and lower scores on the Modified Mini-Mental State Examination over time for both treatment groups compared with placebo (- 0.33 points for celecoxib [P = .04] and - 0.36 points for naproxen [P = .02]). Restriction of analyses to measures collected from persons without dementia attenuated the treatment group differences. Analyses limited to measures obtained while participants were being issued study drugs produced results similar to the intention-to-treat analyses.ConclusionsUse of naproxen or celecoxib did not improve cognitive function. There was weak evidence for a detrimental effect of naproxen.

This study evaluated cognitive test performance in African-American and European-American Alzheimer's disease patients with equivalent years of education. Group differences were negligible on a variety of memory, language, and attentional measures, including several widely used neuropsychological tests. Differences between racial groups observed in earlier studies may have stemmed, in part, from differences in education, which may itself serve as a proxy for other potentially important sociologic and health variables.

Recent attempts to identify predictors of rate of decline in Alzheimer's disease (AD) have been extremely variable in choice of outcome variables, predictor variables tested, timing of assessments, and statistical approaches. In this study, a random effects regression model was applied to seek predictors of decline on the Mini-Mental State Exam in 132 patients with probable AD reassessed every 6 months for up to 7.5 years. Potential predictor variables at baseline were of three types: patients characteristics, clinical variables, and cognitive performances. The final multivariate analysis indicated that the following characteristics predicted more rapid cognitive decline: more education, history of dementia in a first degree relative, non-right handedness, better performances of Boston Naming Test, Gollin Incomplete Figures Test, and Benton Visual Retention Test-Delay, and worse performances on Responsive Naming Test, WAIS-R Block Design, and Benton Visual Retention Test-Copy.

Prior research has demonstrated the importance of a healthy lifestyle to protect brain health and diminish dementia risk in later life. While a multidomain lifestyle provides an ecological perspective to voluntary engagement, its association with brain health is still under-investigated. Therefore, understanding the neural mechanisms underlying multidomain lifestyle engagement, particularly in older adults at risk for Alzheimer's disease (AD), gives valuable insights into providing lifestyle advice and intervention for those in need. The current study included 139 healthy older adults with familial risk for AD from the Prevent-AD longitudinal aging cohort. Self-reported exercise engagement, cognitive activity engagement, healthy diet adherence, and social activity engagement were included to examine potential phenotypes of an individual's lifestyle adherence. Two adherence profiles were discovered using data-driven clustering methodology [i.e., Adherence to healthy lifestyle (AL) group and Non-adherence to healthy lifestyle group]. Resting-state functional connectivity matrices and grey matter brain features obtained from magnetic resonance imaging were used to classify the two groups using a support vector machine (SVM). The SVM classifier was 75% accurate in separating groups. The features that show consistently high importance to the classification model were functional connectivity mainly between nodes located in different prior-defined functional networks. Most nodes were located in the default mode network, dorsal attention network, and visual network. Our results provide preliminary evidence of neurobiological characteristics underlying multidomain healthy lifestyle choices. [ABSTRACT FROM AUTHOR]

Author(s): Maurice A. Smith (corresponding author) [1]; Jason Brandt [2]; Reza Shadmehr [1] A steady progression of motor dysfunction takes place in Huntington's disease [1] (HD). The origin of this [...]

Psychogenic nonepileptic seizures (PNES) are episodes of altered movement, sensation, or reported experience that mimic epileptic seizures (ES) but are not the result of abnormal electrical discharges from the brain. [...]

Abstract Background Although significant amounts of carbon may be stored in harvested wood products, the extraction of that carbon from the forest generally entails combustion of fossil fuels. The transport of timber from the forest to primary milling facilities may in particular create emissions that reduce the net sequestration value of product carbon storage. However, attempts to quantify the effects of transport on the net effects of forest management typically use relatively sparse survey data to determine transportation emission factors. We developed an approach for systematically determining transport emissions using: 1) -remotely sensed maps to estimate the spatial distribution of harvests, and 2) - industry data to determine landscape-level harvest volumes as well as the location and processing totals of individual mills. These data support spatial network analysis that can produce estimates of fossil carbon released in timber transport. Results Transport-related emissions, evaluated as a fraction of transported wood carbon at 4 points in time on a landscape in western Montana (USA), rose from 0.5% in 1988 to 1.7% in 2004 as local mills closed and spatial patterns of harvest shifted due to decreased logging on federal lands. Conclusion The apparent sensitivity of transport emissions to harvest and infrastructure patterns suggests that timber haul is a dynamic component of forest carbon management that bears further study both across regions and over time. The monitoring approach used here, which draws only from widely available monitoring data, could readily be adapted to provide current and historical estimates of transport emissions in a consistent way across large areas.