Endogenous growth factor stimulation of hemocyte proliferation induces resistance to <i>Schistosoma mansoni</i> challenge in the snail host
Bibliographic record
Abstract
Digenean trematodes are a large, complex group of parasitic flatworms that infect an incredible diversity of organisms, including humans. Larval development of most digeneans takes place within a snail (Gastropoda). Compatibility between snails and digeneans is often very specific, such that suitable snail hosts define the geographical ranges of diseases caused by these worms. The immune cells (hemocytes) of a snail are sentinels that act as a crucial barrier to infection by larval digeneans. Hemocytes coordinate a robust and specific immunological response, participating directly in parasite killing by encapsulating and clearing the infection. Hemocyte proliferation and differentiation are influenced by unknown digenean-specific exogenous factors. However, we know nothing about the endogenous control of hemocyte development in any gastropod model. Here, we identify and functionally characterize a progranulin [Biomphalaria glabrata granulin (BgGRN)] from the snail B. glabrata, a natural host for the human blood fluke Schistosoma mansoni Granulins are growth factors that drive proliferation of immune cells in organisms, spanning the animal kingdom. We demonstrate that BgGRN induces proliferation of B. glabrata hemocytes, and specifically drives the production of an adherent hemocyte subset that participates centrally in the anti-digenean defense response. Additionally, we demonstrate that susceptible B. glabrata snails can be made resistant to infection with S. mansoni by first inducing hemocyte proliferation with BgGRN. This marks the functional characterization of an endogenous growth factor of a gastropod mollusc, and provides direct evidence of gain of resistance in a snail-digenean infection model using a defined factor to induce snail resistance to infection.
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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".