Transfer and uptake of polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs) and polychlorinated biphenyls (PCBs) into meat and organs of indoor and outdoor reared pigs
Bibliographic record
Abstract
This study was designed to investigate how and to what extent PCDD/Fs and PCBs are transmitted from exposure sources to porcine muscle and other tissues derived from pigs. The experimental approach involved two longitudinal studies in which indoor and outdoor pigs were reared to market readiness using typical animal husbandry practices; closely matched samples of soil, feed, bedding, meat, etc. were collected and analysed for PCDD/Fs and PCBs. The total PCDD/F + PCB WHO-TEQs in pig liver were much higher than in meat and kidney samples from the same animals and exceeded the current relevant European Union maximum limits (6 ng PCDD/F-TEQ kg−1 fat). Liver samples were also characterised by much lower PCB contributions to the total TEQ than for the corresponding meat and kidney samples, and by a predominance of many of the hepta- and octa-substituted PCDD/Fs. At ages approaching market readiness, TEQ values in meat samples from outdoor pigs tended to be slightly higher than those from comparable ages in the indoor programme, possibly due to additional intake from soil. Biotransfer factors (BTFs) were derived for each of the 39 PCDD/F and PCB congeners measured. Interpretation of the findings focused particularly on trends in four selected congeners, namely: 2,3,7,8-TCDD, 2,3,4,7,8-PeCDF, PCB 153 and PCB 169. Increases in the BTF for PCB 169 in the pig-rearing programmes were noticed when the diet changed from being dominated by sow's milk to feed. Much higher transfer factors for many of the more heavily chlorinated PCDD/Fs (e.g. 2,3,4,7,8-PeCDF) were found in liver compared with meat or kidney samples from the same animals. Soil consistently accounted for at least 30% of input for many hexa- or higher chlorinated PCDD/Fs, while it rarely representing more than 10% of the total intake.
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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".