Canalization and developmental instability of the fetal skull in a mouse model of maternal nutritional stress
Bibliographic record
Abstract
Nutritional imbalance is one of the main sources of stress in both extant and extinct human populations. Restricted availability of nutrients is thought to disrupt the buffering mechanisms that contribute to developmental stability and canalization, resulting in increased levels of fluctuating asymmetry (FA) and phenotypic variance among individuals. However, the literature is contradictory in this regard. This study assesses the effect of prenatal nutritional stress on FA and among-individual variance in cranial shape and size using a mouse model of maternal protein restriction. Two sets of landmark coordinates were digitized in three dimensions from skulls of control and protein restricted specimens at E17.5 and E18.5. We found that, by the end of gestation, maternal protein restriction resulted in a significant reduction of skull size. Fluctuating asymmetry in size and shape exceeded the amount of measurement error in all groups, but no significant differences in the magnitude of FA were found between treatments. Conversely, the pattern of shape asymmetry was affected by the environmental perturbation since the angles between the first eigenvectors extracted from the covariance matrix of shape asymmetric component of protein restricted and control groups were not significantly different from the expected for random vectors. In addition, among-individual variance in cranial shape was significantly higher in the protein restricted than the control group at E18.5. Overall, the results obtained from a controlled experiment do not support the view of fluctuating asymmetry of cranial structures as a reliable index for inferring nutritional stress in human populations.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".