Thermoregulatory strategy may shape immune investment in<i>Drosophila melanogaster</i>
Bibliographic record
Abstract
As temperatures change, insects alter the amount of melanin in their cuticle to improve thermoregulation. However, melanin is also central to insect immunity, suggesting that thermoregulatory strategy may indirectly impact immune defense by altering the abundance of melanin pathway components (a hypothesis we refer to as thermoregulatory-dependent immune investment). This may be the case in the cricket Allonemobius socius, where warm environments (both seasonal and geographical) produced crickets with lighter cuticles and increased pathogen susceptibility. Unfortunately, the potential for thermoregulatory strategy to influence insect immunity has not been widely explored. Here we address the relationships between temperature, thermoregulatory strategy and immunity in the fruit fly Drosophila melanogaster. To this end, flies from two separate Canadian populations were reared in either a summer- or autumn-like environment. Shortly after adult eclosion, flies were moved to a common environment where their cuticle color and susceptibility to a bacterial pathogen (Pseudomonas aeruginosa) were measured. As with A. socius, individuals from summer-like environments exhibited lighter cuticles and increased pathogen susceptibility, suggesting that the thermoregulatory-immunity relationship is evolutionarily conserved across the hemimetabolous and holometabolous clades. If global temperatures continue to rise as expected, then thermoregulation might play an important role in host infection and mortality rates in systems that provide critical ecosystem services (e.g. pollination), or influence the prevalence of insect-vectored disease (e.g. malaria).
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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".