Cellular Immunity of Drosophila willistoni Reveals Novel Complexity in Insect Anti-Parasitoid Defense
Bibliographic record
Abstract
Coevolution of hosts and their parasites has shaped heterogeneity of effector hemocyte types, providing immune defense reactions with variable effectiveness. In this work, we characterize hemocytes of Drosophila willistoni, a species that has evolved a cellular immune system with extensive variation and a high degree of plasticity. Monoclonal antibodies were raised and used in indirect immunofluorescence experiments to characterize hemocyte subpopulations, follow their functional features and differentiation. Pagocytosis and parasitization assays were used to determine the functional characteristics of hemocyte types. Samples were visualized using confocal and epifluorescence microscopy. We identified a new multinucleated giant hemocyte (MGH) type, which differentiates in the course of the cellular immune response to parasitoids. These cells differentiate in the circulation through nuclear division and cell fusion, and can also be derived from the central hematopoietic organ, the lymph gland. They have a binary function as they take up bacteria by phagocytosis and are involved in the encapsulation and elimination of the parasitoid. Here, we show that, in response to large foreign particles, such as parasitoids, MGHs differentiate, have a binary function and contribute to a highly effective cellular immune response, similar to the foreign body giant cells of vertebrates.
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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) | 0.000 | 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".