Exposure to environmental contaminants and folic acid supplementation intergenerationally impact fetal skeleton development through the paternal lineage in a rat model
Bibliographic record
Abstract
Persistent organic pollutants (POPs) are ubiquitous in the environment, which is of concern since they are broadly toxic for wildlife and human health. It is generally accepted that maternal prenatal folic acid supplementation (FA) may beneficially impact offspring development, but it has been recently shown that the father's exposures also influence the health of his offspring. Bone is an endocrine organ essential for whole-body homeostasis and is susceptible to toxicants. Herein, we tested the hypotheses that prenatal paternal exposure to POPs induces developmental bone disorders in fetuses across multiple generations and that FA supplementation attenuates these disorders. We used a four-generation rat model, in which F0 founder females were divided into four treatment groups. F0 females were gavaged with corn oil or an environmentally-relevant POPs mixture and fed either a control diet (2 mg FA/kg), or FA supplemented diet (6 mg FA/kg) before mating and until parturition (four treatments in total). After the birth of the F1 litters, all F0 females and subsequent generations received the FA control diet. Staining with alcian blue and alizarin red S of male and female fetal skeletons was performed at Gestational Day 19.5. Paternal direct and ancestral exposure to POPs delayed bone ossification and decreased the length of long limb bones in fetuses. Maternal FA supplementation did not counteract the POPs-associated delayed fetal ossification and reduced long bone length. In conclusion, prenatal paternal POPs exposure causes developmental bone abnormalities over multiple generations, which were not corrected by maternal FA supplementation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".