<i>Entamoeba histolytica</i> induces caspase‐4/11 activation in inflammasome signaling (152.5)
Bibliographic record
Abstract
A hallmark of amebiasis is acute intestinal inflammation dominated by secretions of pro‐inflammatory cytokines from macrophages. Entamoeba histolytica (Eh) in contact with macrophages activates caspase‐1 by the inflammasome complex resulting in the maturation of IL‐1β and ‐18. The role of inflammatory caspase‐4, ‐5, ‐12 in humans, and caspase‐11, ‐12 in mice are less understood. Caspase‐11, the murine ortholog of caspase‐4, mediates non‐canonical inflammasome activation, suggesting that caspase‐4 may have similar roles. As caspase‐4 might be an immune sensor in Eh infection the aim of this study was to identify the requirements for Eh‐induced caspase‐4/11 activation. Macrophages were treated with live Eh, soluble Eh proteins and secreted components derived from viable Eh. Only live Eh activated caspase‐1, ‐4, and ‐11 in a contact‐dependent manner. Blockade of Eh Gal‐lectin adhesin inhibited binding to macrophages and caspase‐1, ‐4 and ‐11 secretions. Interestingly, cysteine protease 5, another protein critical for Eh virulence, was required for caspase‐1 inflammasome activation but not for caspase‐4/11 activation. To summarize, caspase‐4/11 activation occurred in a contact‐dependent manner and the requirements for their activation are different from caspase‐1, arguing for distinct, non‐redundant roles. Determining how Eh activates these caspases may lead to new therapeutics to treat amebiasis. Grant Funding Source : Supported by NSERC
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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 | 0.001 |
| 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".