Maternal dietary deficiencies in folic acid and choline change metabolites levels in offspring after ischemic stroke
Bibliographic record
Abstract
Abstract Ischemic stroke is a debilitating disease, with nutrition being a modifiable risk factor. Changes in levels of metabolites can be used to measure the alterations in the gut, a significant marker for the etiology of diseases. This study utilized untargeted metabolomics to investigate changes in fecal samples of offspring in response to maternal dietary deficiencies and ischemic stroke. Female mice were placed on control (CD), folic acid- (FADD), or choline-deficient (ChDD) diets prior to, during pregnancy, and lactation. Offspring were weaned on to CD and at 2 months of age an ischemic stroke was induced. Fecal samples were collected prior to ischemic stroke, and at 1- and 4-weeks post-stroke for analysis. Sex and maternal dietary differences in metabolites were observed at both the 1- and 4-week post-stroke timepoints. At the 1-week post-stroke, female FADD offspring had more changes in metabolites than males. Comparatively, at the 4-week post-stroke timepoint, female offspring on either FADD or ChDD demonstrated metabolite changes. This study demonstrates a long-lasting impact of maternal dietary deficiencies on central nervous system and gut microbiome function after ischemic stroke. Summary Statement Our study investigated metabolite changes in female and male offspring fecal samples from mothers maintained on folic acid or choline deficient diet. We report that female offspring metabolite levels were impacted.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".