Maternal Dietary Deficiency in Choline Reduced Levels of MMP-2 Levels in Blood and Brain Tissue of Male Offspring Mice
Bibliographic record
Abstract
Ischemic stroke is one of the leading causes of disability and death globally, with a rising incidence in younger age groups. It is well known that maternal diet during pregnancy and lactation is vital for the early neurodevelopment of offspring. One-carbon (1C) metabolism, including folic acid and choline, plays a vital role in closure of the neural tube in utero. However, the impact of maternal dietary deficiencies in 1C on offspring neurological function following ischemic stroke later in life remains undefined. The aim of this study was to investigate inflammation in the blood and brain tissue of offspring from mothers deficient in dietary folic acid or choline. Female mice were maintained on either a control or deficient diet prior to and during pregnancy and lactation. When offspring were 3 months of age, ischemic stroke was induced. One and a half months later, blood and brain tissue were collected. We measured levels of matrix metalloproteases (MMP)-2 and 9 in both plasma and brain tissue, and reported reduced levels of MMP-2 in ChDD male offspring in both tissue types. No changes were observed in MMP-9. This observation supports our working hypothesis that maternal dietary deficiencies in folic acid or choline during early neurodevelopment impact the levels of inflammation in offspring after ischemic stroke.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".