Maternal dietary deficiencies in folic acid or choline reduce primary neuron viability after exposure to hypoxia through increased levels of apoptosis
Bibliographic record
Abstract
Abstract Stoke is the leading cause of death and disability globally. By addressing modifiable risk factors, particularly nutrition, the prevalence of stroke and its dire consequences can be mitigated. One-carbon (1C) metabolism is a critical biosynthetic process that is involved in neural tube closure, neuronal plasticity, and cellular proliferation in the developing embryo. Folic acid and choline are two active components of 1C metabolism, we have previously demonstrated that maternal dietary deficiencies in folic acid or choline worsen stroke outcomes in offspring. However, there is insufficient data to understand the neuronal mechanisms involved. We exposed embryonic neurons of offspring, whom mothers were on folic acid or choline deficient diets, to hypoxia conditions for 6 hours and return to normoxic conditions for 24 hours to model an ischemic stroke and reperfusion injury. To determine whether increased levels of either folic acid or choline can rescue reduced neuronal viability, we supplemented cell media with folic acid and choline prior to and after exposure to hypoxia. Our results suggest that maternal dietary deficiencies in either folic acid or choline during pregnancy negatively impacts offspring neuronal viability after hypoxia. Furthermore, increasing levels of folic acid or choline prior to and after hypoxia have a beneficial impact on neuronal viability. The findings contribute to our understanding of the intricate interplay between maternal dietary factors, 1C metabolism, and the outcome of offspring to hypoxic events, emphasizing the potential for nutritional interventions in mitigating adverse outcomes.
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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".