Recognition of nonself is necessary to activate Drosophila’s immune response against an insect parasite
Bibliographic record
Abstract
BACKGROUND: Innate immune responses can be activated by pathogen-associated molecular patterns (PAMPs), danger signals released by damaged tissues, or the absence of self-molecules that inhibit immunity. As PAMPs are typically conserved across broad groups of pathogens but absent from the host, it is unclear whether they allow hosts to recognize parasites that are phylogenetically similar to themselves, such as parasitoid wasps infecting insects. RESULTS: Parasitoids must penetrate the cuticle of Drosophila larvae to inject their eggs. In line with previous results, we found that the danger signal of wounding triggers the differentiation of specialized immune cells called lamellocytes. However, using oil droplets to mimic infection by a parasitoid wasp egg, we found that this does not activate the melanization response. This aspect of the immune response also requires exposure to parasite molecules. The unidentified factor enhances the transcriptional response in hemocytes and induces a specific response in the fat body. CONCLUSIONS: We conclude that a combination of danger signals and the recognition of nonself molecules is required to activate Drosophila's immune response against parasitic insects.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".