Distinct cathepsins control necrotic cell death mediated by pyroptosis inducers and lysosome-destabilizing agents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Necrotic cell death triggers a range of biological responses including a strong adaptive immune response, yet we know little about the cellular pathways that control necrotic cell death. Inhibitor studies suggest that proteases, and in particular cathepsins, drive necrotic cell death. The cathepsin B-selective inhibitor CA-074-Me blocks all forms of programmed necrosis by an unknown mechanism. We found that cathepsin B deficiency does not prevent induction of pyroptosis and lysosome-mediated necrosis suggesting that CA-074-Me blocks necrotic cell death by targeting cathepsins other than cathepsin B. A single cathepsin, cathepsin C, drives necrotic cell death mediated by the lysosome-destabilizing agent Leu-Leu-OMe (LLOMe). Here we present evidence that cathepsin C-deficiency and CA-074-Me block LLOMe killing in a distinct and cell type-specific fashion. Cathepsin C-deficiency and CA-074-Me block LLOMe killing of all myeloid cells, except for neutrophils. Cathepsin C-deficiency, but not CA-074-Me, blocks LLOMe killing of neutrophils suggesting that CA-074-Me does not target cathepsin C directly, consistent with inhibitor studies using recombinant cathepsin C. Unlike other cathepsins, cathepsin C lacks endoproteolytic activity, and requires activation by other lysosomal proteases, such as cathepsin D. Consistent with this theory, we found that lysosomotropic agents and cathepsin D downregulation by siRNA block LLOMe-mediated necrosis. Our findings indicate that a proteolytic cascade, involving cathepsins C and D, controls LLOMe-mediated necrosis. In contrast, cathepsins C and D were not required for pyroptotic cell death suggesting that distinct cathepsins control pyroptosis and lysosome-mediated necrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it