Mercury speciation and subcellular distribution in experimentally dosed and wild birds
Bibliographic record
Abstract
Many bird species are exposed to methylmercury (MeHg) at levels shown to cause sublethal effects. Although MeHg sensitivity and assimilation can vary among species and developmental stages, the underlying reasons (such as MeHg toxicokinetics) are poorly understood. We investigated Hg distribution at the tissue and cellular levels in birds by examining Hg speciation in blood, brain, and liver and Hg subcellular distribution in liver. We used MeHg egg injection of white leghorn chicken (Gallus gallus domesticus), sampled at 3 early developmental stages, and embryonic ring-billed gulls (Larus delawarensis) exposed to maternally deposited MeHg. The percentage of MeHg (relative to total Hg [THg]) in blood, brain, and liver ranged from 94 to 121%, indicating little MeHg demethylation. A liver subcellular partitioning procedure was used to determine how THg was distributed between potentially sensitive and detoxified compartments. The distributions of THg among subcellular fractions were similar among chicken time points, and between embryonic chicken and ring-billed gulls. A greater proportion of THg was associated with metal-sensitive fractions than detoxified fractions. Within the sensitive compartment, THg was found predominately in heat-denatured proteins (∼42-46%), followed by mitochondria (∼15-18%). A low rate of MeHg demethylation and high proportion of THg in metal-sensitive subcellular fractions further indicates that embryonic and hatchling time points are Hg-sensitive developmental stages, although further work is needed across a range of additional species and life stages. Environ Toxicol Chem 2017;36:3289-3298. © 2017 SETAC.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".