Xenohormone transactivities are inversely associated to serum POPs in Inuit
Bibliographic record
Abstract
BACKGROUND: The persistent organic pollutants (POPs) are highly lipophilic and resistant to biodegradation and found in e.g. seafood and marine mammals. Greenlandic Inuit have high intake of marine food and thus high POP burden that varies according to local conditions and dietary preference. We do for the very first time report the serum POP related non-steroidal xenohormone activity of Inuit across Greenland. The aims were 1) to determine the integrated xenohormone bioactivities as an exposure biomarker of the actual lipophilic serum POP mixture measuring the effect on estrogen (ER) and androgen receptor (AR) transactivity in citizens from different Greenlandic districts and 2) to evaluate associations to serum POP markers (14 PCBs and 10 pesticides) and lifestyle characteristics. METHODS: Serum samples from 121 men and 119 women from Nuuk, Sisimiut and Qaanaaq were extracted using SPE-HPLC fractionation to obtain the serum POP fraction free of endogenous hormones. The serum POP fraction was used for determination of xenohormone transactivity using ER and AR reporter gene assays. RESULTS: In overall, the xenohormone transactivities differed between districts as well as between the genders. Associations between the transactivities and age, n-3/n-6 and smoker years were observed. The xenoestrogenic and xenoandrogenic transactivities correlated negatively to the POPs for the combined female and male data, respectively. CONCLUSION: The non-steroidal xenohormone transactivities can be used as an integrated biomarker of POP exposure and lifestyle characteristics. The actual serum POP mixtures antagonized the age adjusted sex hormone receptor functions. Comparison of different study populations requires in addition to age inclusion of diet and lifestyle factors.
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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 | 0.001 |
| 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".