Immunosuppression in the northern leopard frog (<i>Rana pipiens</i>) induced by pesticide exposure
Bibliographic record
Abstract
An injection study and a field study were used to investigate the hypothesis that environmental xenobiotics have the potential to alter the immune function of northern leopard frogs (Rana pipiens). Three assays, IgM-specific antibody response to keyhole limpet hemocyanin linked to dinitrophenyl (KLH-DNP), zymozan induced chemiluminescence (CL) of whole blood and the delayed-type hypersensitivity (DTH), were used to assay humoral, innate and cell-mediated immune endpoints. Sublethal doses of DDT (923 ng/g wet wt), malathion (990 ng/g wet wt), and dieldrin (50 ng/g wet wt) were used in the injection study. In all pesticide-injected groups, antibody response was dramatically suppressed, DTH reactions were enhanced, and respiratory burst was lower. When the order of administration of pesticides and antigens was reversed, no differences in immune function between the control and dosed groups were apparent, indicating that frogs exposed to pathogens prior to pesticide exposure can still respond. A field study found significant differences in immune function between frog populations in pesticide-exposed and pesticide-free locations. The antibody response and CL were suppressed and the DTH enhanced in frogs from Essex County (ON, Canada). Overall, the results suggest that exposure to these pesticides can cause both stimulatory and suppressive immune changes in adult frogs and is doing so in wild populations.
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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".