Climate variations and a local PCB hotspot have altered metabolomic profiles in ringed seals
Bibliographic record
Abstract
Environmental contaminants and climate change pose ongoing threats to Arctic marine mammals, yet their combined physiological impacts remain poorly understood. Here, we analyzed 254 metabolites in liver (n = 27, from 2010-2011) and serum/plasma (n = 38, from 2009-2011) to assess the health of ringed seals exposed to a local polychlorinated biphenyl (PCB) “hotspot” as well as other co-occurring contaminants from long-range sources. Demographic analyses revealed significant age and sex differences, with adult males carrying higher ∑PCB and ∑DDT (dichloro-diphenyl-trichloroethane) concentrations than juveniles and females, reflecting bioaccumulation and maternal offload during lactation. Liver metabolite profiles showed stronger contaminant correlations than blood, indicating hepatic metabolism is more directly affected by contaminant exposure. The year 2010, marked by high sea surface temperatures and reduced ice cover, exhibited distinct serum/plasma signatures including polyunsaturated fatty acid depletion and increased saturated fatty acids, suggesting metabolic adaptation to environmental stress. Liver methionine sulfoxide levels correlated with PCBs (r s = 0.44, p = 0.02), suggesting that PCBs may be inducing oxidative stress, while chlordanes correlated with amino acids (r s = –0.49 to 0.45, p = 0.01-0.03), suggesting disrupted protein metabolism. Significant correlations between stable isotope values and contaminant-associated metabolites indicated that dietary factors may confound toxicological relationships. For example, mercury correlations with specific fatty acids paralleled δ 13 C patterns, highlighting challenges in distinguishing direct toxicological effects from shared ecological drivers. These metabolite profiles reveal how persistent contaminants and warming conditions jointly disrupt energy balance, oxidative status, and protein metabolism, demonstrating metabolomics' value for detecting sub-lethal health impacts in Arctic marine mammals. • Metabolomics revealed tissue-specific responses to contaminants in ringed seals • Low sea ice year and warming conditions altered fatty acid profiles, suggesting nutritional stress • PCB exposure correlated with oxidative stress marker methionine sulfoxide in liver • Chlordanes disrupted amino acid metabolism pathways
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".