Provitamin A carotenoids are independently associated with matrix metalloproteinase-9 in plasma samples from a general population
Bibliographic record
Abstract
BACKGROUND AND AIM: Carotenoids in plasma are inversely associated with cardiovascular risk. Low levels can be explained by low dietary intake but also by a number of other factors including inflammatory activity. Given that matrix metalloproteinase (MMP)-9 has an important role in inflammation and cardiovascular disease, we hypothesized that circulating MMP-9 levels would be inversely related to total or single carotenoids in a general population cohort. METHODS: A well-characterized population-based cohort of 285 Swedish men and women (45-69 years) was used for the present study. The intake of carotenoid-rich fruits and vegetables was estimated from a food frequency questionnaire. Levels of MMP-9, C-reactive protein (CRP), interleukin (IL)-6 and six major carotenoids [β-cryptoxanthine, α-carotene, β-carotene, lutein (+zeaxanthin) and lycopene] were determined in plasma. RESULTS: Lower plasma levels of total and single carotenoids were associated with lower dietary intake of carotenoids, older age, male sex, lower physical activity, higher alcohol consumption, higher body mass index (BMI), higher systolic and diastolic blood pressures, lower levels of total cholesterol and HDL cholesterol and higher levels of CRP, IL-6 and MMP-9. After multivariate adjustments, plasma levels of total carotenoids and provitamin A carotenoids (β-cryptoxanthine, α-carotene and β-carotene) remained independently associated with sex, dietary intake of carotenoids, BMI, HDL cholesterol and MMP-9, whilst associations with CRP and IL-6 were not maintained. Neither dietary intake of carotenoid-rich fruits and vegetables, nor vitamin supplement use was associated with MMP-9, CRP or IL-6 levels. CONCLUSION: Plasma carotenoids were associated with a variety of factors including age, sex, dietary intake and metabolic variables. A new finding was the independent relationship in plasma between low provitamin A carotenoids and high MMP-9, suggesting a link between these carotenoids, matrix turnover and arterial remodelling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".