Wide-ranging alterations in the brain fatty acid complement of subjects with late Alzheimer’s disease as detected by GC-MS
Bibliographic record
Abstract
Disturbed lipid metabolism is a well-established feature of human Alzheimer’s disease (AD). The present study used gas chromatography-mass spectrometry (GC-MS) analysis of fatty acid methyl esters (FAMES) to profile all detectable fatty acid (FA) species present in post-mortem neocortical tissue (Brodmann 7 region). Quantitative targeted analysis was undertaken from 29 subjects (n=15 age-matched controls; n=14 late-stage AD). GC-MS analysis of FAMES detected a total of 24 FAs and of these, 20 were fully quantifiable. The results showed significant and wide ranging elevations in AD brain FA concentrations. A total of 9 FAs were elevated in AD with cis-13,16-docosenoic acid increased most (170%; P=0.033). Intriguingly, docosahexanoic acid (DHA; C22:6) concentrations were elevated (47%; P=0.018) which conflicts with the findings of others (unaltered or decreased) in some brain regions after the onset of AD. Furthermore, our results appear to indicate that subject gender influences brain FA levels in AD subjects (but not in age-matched control subjects). Among AD subjects 7 FA species were significantly higher in males than in females. These preliminary findings pinpoint FA disturbances as potentially important in the pathology of AD. Further work is required to determine if such changes are influenced by disease severity or different types of dementia.
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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 | 0.000 |
| 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".