Exploring the Interplay between Carotenoids, Lipid Oxidation, and Cognitive Impairment in Aging
Bibliographic record
Abstract
Abstract Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterised by cognitive decline, memory loss, and impaired daily functioning. As the global population ages, the prevalence of AD continues to rise, emphasising the urgent need for effective preventive and therapeutic strategies. Carotenoids, a group of naturally occurring pigments with antioxidant properties, have gained attention for their potential neuroprotective effects. Carotenoids interrupt the oxidative process by scavenging free radicals and quenching singlet oxygen, ultimately reducing lipid oxidation and preserving the integrity of lipids in biological systems. This project investigated the relationship between blood carotenoid levels, lipid oxidation and their impact on cognitive impairment. Method Serum samples were collected from 49 healthy individuals (17 male, 32 female) who are 65 years or older. Serum carotenoids (Retinol, Lutein, Zeaxanthin, Lycopene, Alpha‐Tocopherol, β‐Carotene) were analysed by reversed phase HPLC method using methanol/acetonitrile/water gradient. Method validation was performed to establish linearity, sensitivity, recovery, and accuracy. Lipid oxidation products (oxysterols and oxidised phospholipids) were analysed using targeted mass spectrometry methods developed in our laboratory. Cognitive functions were measured using Montreal Cognitive Assessment, Trail Making Tests, letter fluency, category fluency and CogState. Result HPLC assay for carotenoids assay showed a linear dynamic range (R2 > 0.94) of 0.01 µM‐20 µM for the six carotenoids that were tested. High intra‐ and inter‐day precision (CV < 9%) and high concentration accuracy (< 15% absolute error) were observed for the QC plasma samples. Correlation analyses did not show any relationship between cognitive status with serum carotenoids or oxysterols; 7‐ketocholesterol, 7β hydroxycholesterol and 25‐hydroxycholesterol and 27‐hydroxycholesterol). 27‐hydroxycholesterol was increased in individuals >80 years old. Conclusion Our data suggests some lipid oxidation products such as 27‐ hydroxycholesterol may increase with age. However, further analysis is needed to conclude how lipophilic carotenoids may associate with lipid oxidation and cognitive impairment.
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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 | 0.001 |
| 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 | 0.001 | 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".