The impact of maternal dietary folic acid or choline deficiencies on cerebral blood flow, cardiac, aortic, and coronary function in young and middle-aged female mouse offspring following ischemic stroke
Bibliographic record
Abstract
Abstract Background and Purpose Adequate maternal dietary levels of one-carbon (1C) metabolites, such as folic acid and choline, play an important role in the closure of the neural tube in utero ; however, the impact of deficiencies in 1C on offspring neurological function after birth remain undefined. Stroke is one of the leading causes of death and disability globally. The aim of our study was to determine the impact of maternal 1C nutritional deficiencies on cerebral and peripheral blood flow after ischemic stroke in adult female offspring. Method In this study, female mice were placed on either control (CD), folic acid (FADD), or choline (ChDD) deficient diets prior to pregnancy. Female offspring were weaned onto a CD for the duration of the study. Ischemic stroke was induced in offspring and after six weeks cerebral and peripheral blood flow velocity was measured using ultrasound imaging. Results Our data showed that 11.5-month-old female offspring from ChDD mothers had reduced blood flow in the posterior cerebral artery compared to controls. In peripheral blood flow velocity measurements, we report an aging effect. Conclusions These results emphasize the importance of maternal 1C diet in early life neuro-programming on long-term vasculature health.
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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 | 0.001 | 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 | 0.001 |
| 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".