Sugar intake interacts with temperature to influence reproduction and immunity in adult <i>Culex pipiens</i> mosquitoes
Bibliographic record
Abstract
Disease transmission by insect vectors will depend on integrated physiological responses to interacting environmental variables. We explored how interactions between temperature and sucrose concentration affected immunity and fecundity, two variables that contribute to vectorial capacity, in Culex pipiens Linnaeus, 1758 mosquitoes. We provided female C. pipiens with either 2% or 20% sucrose and exposed them to low (22 °C), moderate (25 °C), or high (30 °C) temperatures for 8 days. We then measured the strength of the melanization response in one subpopulation of females and the number of eggs laid as a measure of fecundity in another subpopulation. Temperature interacted with diet to weaken immunity under 2% sucrose at 22 and 25 °C. This effect disappeared at 30 °C, suggesting that high temperatures allowed mosquitoes to compensate for the effects of decreased sucrose. Conversely, increasing temperature increased egg production on a diet of 20% sucrose, but heat exposure on a diet of 2% sucrose decreased fecundity. Overall, we suggest that heat exposure requires investment in thermal protection, which may prompt reconfiguration of the immune system and (or) decreased investment in reproduction. Thus, our understanding of the effects of climate change rest on which physiological system we measure and under which combinations of stressors.
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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".