Immunotoxic effects of environmental pollutants in marine mammals
Bibliographic record
Abstract
Due to their marine ecology and life-history, marine mammals accumulate some of the highest levels of environmental contaminants of all wildlife. Given the increasing prevalence and severity of diseases in marine wildlife, it is imperative to understand how pollutants affect the immune system and consequently disease susceptibility. Advancements and adaptations of analytical techniques have facilitated marine mammal immunotoxicology research. Field studies, captive-feeding experiments and in vitro laboratory studies with marine mammals have associated exposure to environmental pollutants, most notable polychlorinated biphenyls (PCBs), organochlorine pesticides and heavy metals, to alterations of both the innate and adaptive arms of immune systems, which include aspects of cellular and humoral immunity. For marine mammals, reported immunotoxicology endpoints fell into several major categories: immune tissue histopathology, haematology/circulating immune cell populations, functional immune assays (lymphocyte proliferation, phagocytosis, respiratory burst, and natural killer cell activity), immunoglobulin production, and cytokine gene expression. Lymphocyte proliferation is by far the most commonly used immune assay, with studies using different organic pollutants and metals predominantly reporting immunosuppressive effects despite the many differences in study design and animal life history. Using combined field and laboratory data, we determined effect threshold levels for suppression of lymphocyte proliferation to be between b0.001-10 ppm for PCBs, 0.002-1.3 ppm for Hg, 0.009-0.06 for MeHg, and 0.1-2.4 for cadmium in polar bears and several pinniped and cetacean species. Similarly, thresholds for suppression of phagocytosis were 0.6-1.4 and 0.08-1.9 ppm for PCBs and mercury, respectively. Although data are lacking for many important immune endpoints and mechanisms of specific immune alterations are not well understood, this review revealed a systemic suppression of immune function in marine mammals exposed to environmental contaminants. Exposure to immunotoxic contaminants may have significant population level consequences as a contributing factor to increasing anthropogenic stress in wildlife and infectious disease outbreaks.
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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 | 0.000 |
| 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".