Brain levels of lutein (L) and zeaxanthin (Z) are related to cognitive function in centenarians
Bibliographic record
Abstract
Background Among the carotenoids, L and Z are preferentially taken up into human brain. Intervention with L improved cognition in older adults. Purpose To evaluate the relationship between cognition and L and Z levels in brain tissue of decedents >98 yrs at death. Methods Subjects (n=49) were from the Georgia Centenarian Study and agreed to brain donation after death. Brain tissues (cerebellum, frontal, occipital, temporal cortices) were analyzed with standard lipid extractions and reverse phase HPLC. Partial correlations adjusting for age, education, sex, and self-reported diabetes or hypertension were performed. Ante-mortem cognitive measures included the Mini Mental State Examination (MMSE), Fuld Object Memory Evaluation, WAIS-III Similarities, CERAD verbal fluency, naming, and constructional praxis subtests, and the Geriatric Deterioration Rating Scale (GDRS). Results Z levels in brain tissue were significantly related to ante-mortem measures of global cognitive function (MMSE, r=0.30 p<0.01), memory (FOME recall r=0.35, p<0.01; retention r=0.25, p<0.05), verbal fluency (r=0.35, p<0.01), and dementia severity (GDRS, r= −0.35, p<0.01). In univariate analyses, L was related to recall and verbal fluency, but the associations were attenuated with adjustment for covariates. Conclusions L and Z may be important in cognition in centenarians. Support:USDA#581950-7-07; DSM, NIH 1P01-AG17553 (L. Poon, PI)
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".