Plasma folate levels are inversely associated with natural killer cell degranulation in mice (135.1)
Bibliographic record
Abstract
High intake and plasma levels of folic acid (FA), the synthetic form of the B‐vitamin folate, were associated with reduced natural killer (NK) cell cytotoxicity in post‐menopausal women. This observation has not yet been confirmed. Thus, we examined the relationship between dietary FA intake/plasma folate levels and NK cell activity in an animal model. Post‐weaning C57BL/6 mice were randomized to receive diets containing 2 (control) or 20 mg FA/kg diet for 3 months. A flow cytometry based CD107a and IFN‐γ detection assay was used to assess splenic NK cell activity. Plasma folate levels were significantly higher ( p < 0.0001) in the high FA group. Plasma folate levels were significantly and inversely associated with the frequency of NK cell degranulation (%CD107a+ NK cells) in response to stimulation with the mouse T‐cell lymphoma YAC‐1 and cytokines ( r s = ‐0.520; p = 0.035) but not in response to mitogenic stimulation with phorbol 12‐myristate 13‐acetate (PMA) and ionomycin. Plasma folate levels were not associated with IFN‐γ production (%IFN‐γ+ NK cells) in response to either YAC‐1 and cytokine or PMA/ionomycin stimulation. Our findings corroborate an inverse association between high FA levels and NK cell cytotoxicity and suggest that reduced target cell recognition, evidenced by reduced degranulation in response to cancer cell targets but not in response to mitogenic stimulation, is a likely mechanism behind this inverse association. Our data suggest that impaired NK cell function may be a mechanism behind the purported tumor‐promoting effect associated with high FA supplementation. Grant Funding Source : Supported by CIHR MOP #14126
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".