Brief communication: Prenatal and early postnatal stress exposure influences long bone length in adult rat offspring
Bibliographic record
Abstract
Stress during the prenatal and early postnatal periods (perinatal stress, PS) is known to impact offspring cognitive, behavioral, and physical development, but effects on skeletal growth are not clear. Our objective was to analyze effects of variable, mild, daily PS exposure on adult offspring long bone length. Twelve pregnant rat dams were randomly assigned to receive variable stress from gestational days 14-21 (Prenatal group), postpartum days 2-9 (Postnatal), both periods (Pre-Post), or no stress (Control). Differences in adult offspring tibia and femur length were analyzed among treatment groups. Mean tibia length differed among groups for males (P = 0.016) and females (P = 0.009), and differences for femur length approached significance for males (P = 0.051). Long bone length was shorter among PS-exposed offspring, especially those exposed to postnatal stress (Postnatal and Pre-Post groups). Results persisted when controlling for nose-tail length. These differences might reflect early stunting that is maintained in adulthood, or delayed growth among PS-exposed offspring. This study suggests that PS results in shorter long bones in adulthood, independently of effects on overall body size. Stunting and growth retardation are major global health burdens. Our study adds to a growing body of evidence suggesting that PS is a risk factor for poor linear growth.
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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) | 0.003 | 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".