<i>Drosophila</i> hemocytes recognize lymph gland tumors of <i>mxc</i> mutants and activate the Toll pathway in reactive oxygen species-dependent manner
Bibliographic record
Abstract
ABSTRACT Mechanisms of cancer cell recognition and elimination by the innate immune system remains unclear. Circulating hemocytes are associated with the hematopoietic tumors in Drosophila mxc mbn1 mutant larvae. The innate immune signalling pathways are activated in the fat body to suppress the tumor growth by inducing antimicrobial peptides (AMP). Here, we investigated the regulatory mechanism underlying the activation in the mutant. Reactive oxygen species accumulated in the hemocytes due to induction of dual oxidase and its activator. The hemocytes were also localized on the fat body. These were essential for transmitting the information on tumors toward the fat body to induce AMP expression. Regarding to the tumor recognition, we found that matrix metalloproteinase 1 (MMP1) and MMP2 were highly expressed in the tumors. Ectopic expression of MMP2 was associated with AMP induction in the mutants. Furthermore, the basement membrane components in the tumors were reduced and ultimately lost. The hemocytes may recognize the disassembly in the tumors. Our findings highlight the underlying mechanism via which macrophage-like hemocytes recognize tumor cells and relay the information toward the fat body to induce AMPs. and contribute to uncover the immune system’s roles against cancer. SUMMARY STATEMENT Drosophila blood cells transmit information regarding the existence of tumor cells to the fat body and induce the production of anti-tumor peptides via the generation of reactive oxygen species.
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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) | 0.003 | 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".