Laser Ablation ICP-MS Co-Localization of Mercury and Immune Response in Fish
Bibliographic record
Abstract
Mercury (Hg) contamination is a global issue with implications for both ecosystem and human health. In this study, we use a new approach to link Hg exposure to health effects in spotted gar (Lepisosteus oculatus) from Caddo Lake (TX/LA). Previous field studies have reported elevated incidences of macrophage centers in liver, kidney, and spleen of fish with high concentrations of Hg. Macrophage centers are aggregates of specialized white blood cells that form as an immune response to tissue damage, and are considered a general biomarker of contaminant toxicity. We found elevated incidences of macrophage centers in liver of spotted gar and used a new technology for ecotoxicology studies, laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), to colocalize aggregates and Hg deposits within the tissue architecture. We conclude that Hg compromises the health of spotted gar in our study and, perhaps, other fish exposed to elevated concentrations of Hg.
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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 | 0.000 |
| 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".