Inflammation in response to phytohemagglutinin injection in the Talas tuco-tuco (<i>Ctenomys</i><i>talarum</i>): implications for the estimation of immunocompetence in natural populations of wild rodents
Bibliographic record
Abstract
The immunological variation in wild populations and its relation to life-history traits has recently become a central topic in the field of evolutionary biology, considering the critical contribution of immunity to an individual’s fitness. A common technique used by ecologists to estimate immunocompetence in wild populations is the phytohemagglutinin (PHA) – skin test. In this test, the degree of local swelling triggered by PHA is usually considered an estimate of T-lymphocyte activity, although there is an ongoing debate regarding this interpretation. Here, we coupled the PHA–skin test with a histological analysis to examine the temporal development of the cell-mediated response in the subterranean rodent Talas tuco-tuco (Ctenomys talarum Thomas, 1898). The inflammation response involved lymphocytes, neutrophils, eosinophils, and macrophages at the site of injection, achieving an increase of total leukocytes from 12 to 48 h after injection. However, the abundance of any of the leukocytes observed did not correlate with the degree of swelling at any time studied, suggesting that caution should be taken when interpreting the results of the PHA-induced swelling response. Particularly, the magnitude of macroscopic swelling should not be considered a priori as indicative of T-lymphocyte activity in wild-caught rodents. Our results highlight the importance of avoiding oversimplified approaches to measuring immunocompetence.
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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 | 0.001 |
| 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".