Individual variation in body burden, lipid status, and reproductive investment is related to maternal transfer of a brominated diphenyl ether (BDE-99) to eggs in the zebra finch
Bibliographic record
Abstract
Avian eggs are exposed to hydrophobic contaminants through maternal transfer. How maternal transfer of contaminants within a species is influenced by individual variation in characteristics such as body burden, yolk precursor levels, or reproductive investment is not understood. The authors investigated sources of variation in the maternal transfer of 2,2',4,4',5-pentabromodiphenyl ether (BDE-99) in zebra finches (Taeniopygia guttata). The authors dosed adult female zebra finches with levels of BDE-99 relevant to exposure in wild birds (0, 33.7 or 173.8 ng/g body wt/d) for three weeks prior to pairing. Maternal BDE-99 and very-low-density lipoprotein (VLDL) in plasma were measured during egg formation and at clutch completion, and BDE-99 was measured in the corresponding egg. The lipid-normalized egg-to-maternal tissue BDE-99 relationship decreased with increasing maternal burden. Individual variation in maternal VLDL was related to BDE-99 transfer to the eggs when BDE-99 was at background levels in control birds, but not when BDE-99 was elevated in dosed birds. The decrease in maternal plasma BDE-99 over the laying period was only significant (p < 0.05) in the high-dose birds. Finally, the decrease in BDE-99 in maternal plasma during egg-laying was significantly positively correlated with clutch mass in the high-dose group. These results suggest that the relationship between maternal and egg contaminant levels can be highly variable. This has significant implications for using eggs as indicators of adult or environmental concentrations.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".