Mercury and selenium speciation and toxicity in common loons
Bibliographic record
Abstract
Approximately 10,000 tones of Hg are deposited annually as a result of anthropogenic activities. This increased Hg burden is known to have adverse neurological and reproductive effects on Common loons. A positive correlation between mercury (Hg) and selenium (Se) has been reported to exist in marine mammals and various species of marine and aquatic piscivorous birds. It has been hypothesized that the Hg/Se interactions may involve in the multiple mechanisms of Hg detoxification. This study focused on the suggested Hg/Se complex that forms in association with specific proteins. Specifically, this project focuses on the nature of these interactions in different tissues from wild Common loons (Gavia immer) that have been collected by the Canadian Wildlife Service. The Hg and Se concentrations in the various tissues were quantified using AAS. MALDI-TOF-MS and protein sequencing characterized the nature of the Hg/Se complex binding protein. Among the tissues, the liver had the highest concentrations of Hg and Se followed by kidney; muscle and brain. A strong association between Hg and Se was found in liver, kidney and eggs whereas there was no association in muscle and brain. In contrast brain and muscle had highest percentage of organic Hg suggesting that only inorganic Hg is associated with Se. Two Hg-Se binding protein complexes were found in liver both in the 15,200-15,300 Da range while one such complex in the same weight range was found in kidneys, when sequenced it was found that these proteins were the alpha A chain of Hemoglobin. The protein complex found in eggs was unique and although it was impossible to fully sequence it, it represents an unknown protein. The role of Se in Hg toxicity in eggs warrants further study.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".