The Role of Diet on Cognitive Decline and Dementia
Bibliographic record
Abstract
3. Luchsinger JA, Mayeux R. Dietary factors and Alzheimer’s disease. Lancet Neurol 2004;579–87. 4. Gillette-Guyonnet S, Abellan van Kan G, Andrieu S, et al. IANA Task Force on nutrition and cognitive decline in aging. J. Nutr. Health Aging 2007;11:132–52. 5. Parrott MD, Grenwood CE. Dietary influences on cognitive function with aging. From high fat diets to healthful eating. Ann NY Acad Sci 2007;1114:389–97. 6. Heude B, Ducimetiere P, Berr C. Cognitive decline and fatty acids composition of erythrocyte membranes. The EVA study. Am J Clin Nutr 2003;77:803–8. 7. Schaefer EJ, Bongard V, Beiser A, et al. Plasma phosphatidylcholine docosahexaenoic acid content and risk of dementia and Alzheimer’s disease. The Framingham Heart Study. Arch Neurol 2006;63:1545–50. 8. Morris MC, Evans DA, Bienias JL, Tangney CC, Bennett DA, Aggarwal N, Schneider J, Wilson RS. Dietary fats and the risk of incident Alzheimer’s disease. Arch Neurol 2003;60:194–200. 9. Morris MC, Evans DA, Bienias JL, Tangney CC, Wilson RS. Dietary fat intake and 6-year cognitive change in an older biracial community population. Neurology 2004;62:1573–9. 10. Solfrizzi V, Colacicco AM, D’Introno A, Capurso C, Torres F, Rizzo C, Capurso A, Panza F. Dietary intake of unsaturated fatty acids and age-related cognitive decline: a 8.5 years follow-up of the Italian Longitudinal Study on Aging. Neurobiol Aging 2006;27:1694–704. 12. Luchsinger JA, Min-Xing T, Shea S, Mayeux R. Caloric intake and the risk of Alzheimer’disease. Arch Neurol 2002;59:1258–63. 13. Laitinen MH, Ngandu T, Rovio S, et al. Fat intake at midlife and risk of dementia and Alzheimer’s disease: a population-based study. Dementia Geriatr Cogn Dis 2006;22:99–107. 14. Freund-Levi Y, Eriksdotter-Jonhagen M, Cederholm T, et al. Omega-3 fatty acid treatment in 174 patients with mild to moderate Alzheimer disease: omega-AD: a randomized trial. Arch Neurol 2006;63:1402–8. 15. Kotani S, Sakaguchi E, Warashina S, et al. Dietary supplementation of arachidonic acid and docosahexaenoic acids improves cognitive dysfunction. Neurosci Res 2006;56:159–64. 16. Fotuhi M, Mohassel P, Yaffe K. Fish consumption, longchain omega-3 fatty acids and risk of cognitive or Alzheimer disease: a complex association. Nature Clin Practice Neurol 2009;5:140–52. 18. Morris MC, Evans DA, Biennas JL, Tangney CC, Bennett DA, Wislon RS, Aggarwal N, Schneider J. Consumption of fish and n-3 fatty acids and risk of incident Alzheimer disease. Arch Neurol 2003;940–6. 19. Kalmijn S, Launer LJ, Ott A, Witteman JC, Hofman A, Breteler MM. Dietary fat intake and the risk of incident dementia in the Rotterdam Study. Ann Neurol 1997;42:776–82. 20. Huang TL, Zandi PP, Tucker KL, Fitzpatrick AL, Kuller LH, Fried LP, Burke GL, Carlson MC. Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon 4. Neurology 2005;65:1409–14. 21. Laurin D, Verreault R, Letenneur R, Lindsay J, Dewailly E, Holub BJ. Omega-3 fatty acids and risk of cognitive impairment and dementia. J Alzheimer Dis 2003;5:315– 22. 22. Devoree EE, Grodstein F, van Rooij FJ, Hofman A, Rosner B, Stampfer MJ, Witteman JC, Breteler MM. Dietary intake of fish and omega-3 fatty acids in relation to long-term dementia risk. Am J Clin Nutr 2009;90: 170–6. 23. Kroger E, Verreault R, Carmichael PH, Lindsay J, Julien P, Dewailly E, Ayotte P, Laurin D. Omega-3 fatty acids and risk of dementia: the Canadian Study of Health and Aging. Am J Clin Nutr 2009;90:184–92.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".