Immunity for nothing and the eggs for free: Apparent lack of both physiological trade-offs and terminal reproductive investment in female crickets (Gryllus texensis)
Bibliographic record
Abstract
Should females alter their reproductive strategy when attacked by pathogens? Two hypotheses provide opposite predictions. Terminal reproductive investment theory predicts that reproduction should increase when the risk of death increases. However, physiological trade-offs between reproduction and immune function might be expected to produce a decrease in reproduction during a robust immune response. There is evidence for both hypotheses. We examine whether age determines the effect of an immune challenge on reproductive strategy in long-winged females of the Texas field cricket, Gryllus texensis, when fed an ecologically valid (i.e. limited) diet. The limited diet reduced reproductive output. However, even under resource-limited conditions, immune challenge had no effect on the reproductive output of young or middle-aged females. Both reproductive output and immune function (lysozyme-like activity and phenoloxidase (PO) activity) increased with age, which is contrary to both hypotheses. We hypothesize that PO activity is pleiotropic and represents an investment in both reproduction and immune function. Three proPO genes (identified in a published RNA-seq dataset (transcriptome)) were expressed either in the fat body or the ovaries (supporting the hypothesis that PO is bifunctional). The possible bifunctionality of PO suggests that it may not be an appropriate immune measure for studies on immune/reproductive trade-offs. This study also suggests that the threshold for terminal reproductive investment may not decrease prior to senescence in some species.
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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) | 0.002 | 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".