Cognitive stimulation in the workplace, plasma proteins, and risk of dementia : three analyses of population cohort studies

OBJECTIVES To examine the association between cognitively stimulating work and subsequent risk of dementia and to identify protein pathways for this association. DESIGN Multicohort study with three sets of analyses. SETTING United Kingdom, Europe, and the United States. PARTICIPANTS Three associations were examined: cognitive stimulation and dementia risk in 107 896 participants from seven population based prospective cohort studies from the IPD-Work consortium (individual participant data meta-analysis in working populations); cognitive stimulation and proteins in a random sample of 2261 participants from one cohort study; and proteins and dementia risk in 13 656 participants from two cohort studies. MAIN OUTCOME MEASURES Cognitive stimulation was measured at baseline using standard questionnaire instruments on active versus passive jobs and at baseline and over time using a job exposure matrix indicator. 4953 proteins in plasma samples were scanned. Follow-up of incident dementia varied between 13.7 to 30.1 years depending on the cohort. People with dementia were identified through linked electronic health records and repeated clinical examinations. RESULTS During 1.8 million person years at risk, 1143 people with dementia were recorded. The risk of dementia was found to be lower for participants with high compared with low cognitive stimulation at work (crude incidence of dementia per 10 000 person years 4.8 in the high stimulation group and 7.3 in the low stimulation group, age and sex adjusted hazard ratio 0.77, 95% confidence interval 0.65 to 0.92, heterogeneity in cohort specific estimates I2=0%, P=0.99). This association was robust to additional adjustment for education, risk factors for dementia in adulthood (smoking, heavy alcohol consumption, physical inactivity, job strain, obesity, hypertension, and prevalent diabetes at baseline), and cardiometabolic diseases (diabetes, coronary heart disease, stroke) before dementia diagnosis (fully adjusted hazard ratio 0.82, 95% confidence interval 0.68 to 0.98). The risk of dementia was also observed during the first 10 years of follow-up (hazard ratio 0.60, 95% confidence interval 0.37 to 0.95) and from year 10 onwards (0.79, 0.66 to 0.95) and replicated using a repeated job exposure matrix indicator of cognitive stimulation (hazard ratio per 1 standard deviation increase 0.77, 95% confidence interval 0.69 to 0.86). In analysis controlling for multiple testing, higher cognitive stimulation at work was associated with lower levels of proteins that inhibit central nervous system axonogenesis and synaptogenesis: slit homologue 2 (SLIT2, fully adjusted r3 -0.34, P(0.001), carbohydrate sulfotransferase 12 (CHSTC, fully adjusted r3 -0.33, P(0.001), and peptidyl-glycine alpha-amidating monooxygenase (AMD, fully adjusted r3 -0.32, P(0.001). These proteins were associated with increased dementia risk, with the fully adjusted hazard ratio per 1 SD being 1.16 (95% confidence interval 1.05 to 1.28) for SLIT2, 1.13 (1.00 to 1.27) for CHSTC, and 1.04 (0.97 to 1.13) for AMD. CONCLUSIONS The risk of dementia in old age was found to be lower in people with cognitively stimulating jobs than in those with non-stimulating jobs. The findings thatPeer reviewe

“Others-in-Law”: Legalism in the Economy of Religious Differences

Religious legalism encompasses a wide range of attitudes that assign religious meaning to legal content or to legal compliance. The phenomenology of religious legalism is assuming a significant role in various contemporary debates about legal pluralism, accommodation of religious minorities, religious freedom, and so forth. This article revises this conception and the commonplace equation of Judaism and legalism. It suggests that we ought to regard both as part of the economy of religious differences by which religious identities are expressed and defined as alternatives. The common ascription of religious legalism to Judaism (and Islam) is criticized here through a historical analysis of the law-religion-identity matrix in three cultural settings: late ancient Judeo-Hellenic, medieval Judeo–Arabic, and post-Reformation Europe

Cognitive stimulation in the workplace, plasma proteins, and risk of dementia: three analyses of population cohort studies

Objectives: To examine the association between cognitively stimulating work and subsequent risk of dementia and to identify protein pathways for this association.Design: Multicohort study with three sets of analyses.Setting: United Kingdom, Europe, and the United States.Participants: Three associations were examined: cognitive stimulation and dementia risk in 107 896 participants from seven population based prospective cohort studies from the IPD-Work consortium (individual participant data meta-analysis in working populations); cognitive stimulation and proteins in a random sample of 2261 participants from one cohort study; and proteins and dementia risk in 13 656 participants from two cohort studies.Main outcome measures: Cognitive stimulation was measured at baseline using standard questionnaire instruments on active versus passive jobs and at baseline and over time using a job exposure matrix indicator. 4953 proteins in plasma samples were scanned. Follow-up of incident dementia varied between 13.7 to 30.1 years depending on the cohort. People with dementia were identified through linked electronic health records and repeated clinical examinations.Results: During 1.8 million person years at risk, 1143 people with dementia were recorded. The risk of dementia was found to be lower for participants with high compared with low cognitive stimulation at work (crude incidence of dementia per 10 000 person years 4.8 in the high stimulation group and 7.3 in the low stimulation group, age and sex adjusted hazard ratio 0.77, 95% confidence interval 0.65 to 0.92, heterogeneity in cohort specific estimates I2=0%, P=0.99). This association was robust to additional adjustment for education, risk factors for dementia in adulthood (smoking, heavy alcohol consumption, physical inactivity, job strain, obesity, hypertension, and prevalent diabetes at baseline), and cardiometabolic diseases (diabetes, coronary heart disease, stroke) before dementia diagnosis (fully adjusted hazard ratio 0.82, 95% confidence interval 0.68 to 0.98). The risk of dementia was also observed during the first 10 years of follow-up (hazard ratio 0.60, 95% confidence interval 0.37 to 0.95) and from year 10 onwards (0.79, 0.66 to 0.95) and replicated using a repeated job exposure matrix indicator of cognitive stimulation (hazard ratio per 1 standard deviation increase 0.77, 95% confidence interval 0.69 to 0.86). In analysis controlling for multiple testing, higher cognitive stimulation at work was associated with lower levels of proteins that inhibit central nervous system axonogenesis and synaptogenesis: slit homologue 2 (SLIT2, fully adjusted β -0.34, PConclusions: The risk of dementia in old age was found to be lower in people with cognitively stimulating jobs than in those with non-stimulating jobs. The findings that cognitive stimulation is associated with lower levels of plasma proteins that potentially inhibit axonogenesis and synaptogenesis and increase the risk of dementia might provide clues to underlying biological mechanisms.</p

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Jesus and Scribal Authority

Sleman178 p.; 22c

Parallel Optimisation Strategies for Fusion Codes

We have previously documented the on-going work in the EUFORIA project to parallelise and optimise European fusion simulation codes, see. This involves working with a wide range of codes to try and address any performance and scaling issues that these codes have. However, as no two simulation codes are exactly the same, it is very hard to apply exactly the same approach to optimising a disparate range of codes. Indeed, it can be seen from that the codes investigated range in terms of performance and ability from well-optimised, highly parallelised codes, to serial or poorly performing codes. After analysing, optimising, and parallelising a range of codes it is, actually, possible to discern a number of distinct optimisation techniques or approaches/strategies that can be used to improve the performance or scaling of a parallel simulation code. This paper outlines the distinct approaches that we have identified, highlighting their benefits and drawbacks, giving an overview of the type of work that is often attempted for fusion simulation code optimisation