Bibliographic record
Abstract
Folates are a group of enzyme co-factors responsible for carrying out cellular one-carbon metabolic reactions.This one-carbon metabolic pathway plays a critical role in the de novo production of purines, thymidylates and the precursors required for various methylation reactions.Adequate folate status is vital for growth, development, and maintenance of health in both humans and animals.However, like many essential nutrients, there are concerns over potential adverse health effects associated with both inadequate and excess folate consumption.Specifically, folic acid (FA), the synthetic form of folate used in fortified foods and supplements, has been associated with both beneficial and potentially adverse effects.Hence, characterization of safe and adequate FA intakes while avoiding the risk of an adverse health effect is important for the nutritional risk assessment of FA.Animal-derived data play an important role in the elucidation of the specific mechanisms of action linked to FA intake.However, poor reporting of study details, and the inconsistent use of diets and animal models, hinders knowledge translation from animals to humans.Here I report the outcomes of two studies.The first was a scoping review of the literature to determine the reporting quality of studies examining the effect of dietary FA interventions in mice.The findings of our scoping review showed that 14% of studies did not report ≥1 generic reporting item(s) (i.e., sex, strain and age) and 41% did not report ≥1 nutrition-specific reporting item(s) (i.e., base diet composition, intervention doses, duration, and exposure verification).This incomplete reporting of findings notably limits their generalizability, reproducibility and interpretation.The second study was designed to facilitate the knowledge translation of animalderived data to human nutrition by establishing biomarkers of folate intake, status and function in mice.This FA dose-response study allowed me to identify a biomarker of folate deficiency, namely a homocysteine concentration ≥ 3.88 umol/L as a functional marker of deficiency.I also iii propose that an unmetabolized FA concentration ≥ 7.71 nmol/L represents a marker of excess FA intake.The observations made in these two studies will inform future study designs for assessing the effects of FA on health outcomes in mouse models.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".