Temporal Variation and Identification of Factors Associated with Endogenous Retinoic Acid Isomers in Serum from Brazilian Women
Bibliographic record
Abstract
OBJECTIVE: Retinoids (natural and synthetic derivatives of vitamin A) have cancer chemotherapeutic and chemopreventive activities. Retinoic acid (RA) treatment has been associated with significant regression of preneoplastic lesions. However, serious toxicity associated with some therapies has made long-term chemoprevention in healthy populations unfeasible. Recently, serum RA has been shown to increase in response to oral retinol (vitamin A) supplementation. Here, we assess the variability of circulating RA levels and the lifestyle, demographic, and nutritional factors that explain such variability. METHOD: Total RA concentration and the concentrations of RA isomers (all-trans-RA, 13-cis-RA, and 9-cis-RA) were measured by high-pressure liquid chromatography in serum samples obtained 4 months apart from 502 women participating in the Ludwig-McGill Cohort (Sao Paulo, Brazil). RESULTS: The relative abundance of the three RA isomers was similar for each visit (baseline and month 4), with 13-cis-RA having the highest concentrations followed by 9-cis-RA and all-trans-RA. The within-person variability of total RA and individual isomers was low. Using multivariate logistic regression models (upper tertile versus low/middle tertile of serum RA), we found that age, race, oral contraceptive use, total number of pregnancies, and season of initial blood draw were significantly associated with at least one endogenous RA isomer level. All endogenous RA isomers were positively associated with serum retinol, beta-carotene, and beta-cryptoxanthin levels. CONCLUSION: These results have implications for the design of future epidemiologic studies focused on assessing RA-disease association and intervention studies aimed at modulating RA levels.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".