A Non‐targeted Metabolomic Approach to Identify Potential Plasma Lipophilic Biomarkers of Inadequate Vitamin B <sub>6</sub> Status, Induced by Low B <sub>6</sub> Intake, Exposure to the Anti‐B <sub>6</sub> Factor 1‐Amino D‐proline, or Their Interaction, in a Rat Model
Bibliographic record
Abstract
Vitamin B6 status in the body is affected by several factors including dietary supply of the antivitamin B6 factor, 1-amino D-proline (1ADP) which is present in flaxseed. Owing to the prevalence of moderate B6 deficiency in the general population, a co-insult of 1ADP exposure may lead to a further deterioration of B6 status. To this end, we applied a non-targeted metabolomics approach to identify potential plasma lipophilic biomarkers of 1ADP injury in moderately vitamin B6-deficient rats. Male weaning rats (n=6/treatment) received a semi-purified diet containing PN·HCl at either 7 (optimal B6) or 0.7mg/kg diet (moderate B6), each with 0 or 10mg/kg diet of synthetic 1ADP for 5 weeks. Plasma lipophilic metabolites were extracted in acetonitrile for analysis via LC-QTOF/MS. Ten potential lipophilic biomarkers: glycocholic acid, glycoursodeoxycholic acid, murocholic acid , N-docosahexaenoyl GABA, N-arachidonoyl GABA, lumula, nandrolone, orthothymotinic acid , cystamine, and 3-mehtyleneoxindole were identified out of >2500 detected entities. Changes in these metabolites revealed potential defects in the biosynthesis and metabolism of bile acids, N-acyl amino acids, analgenic androgens, anti-inflammatory and neuroprotective molecules. These data provide new insights into the impact of B6 inadequacy on pathways linked to vitamin B6 metabolism.Supported by the Natural Sciences and Engineering Research Council of Canada(NSERC).
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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) | 0.001 | 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".