Selective killing of human M1 macrophages by Smac mimetics alone and M2 macrophages by Smac mimetics and caspase inhibition
Bibliographic record
Abstract
The inflammatory and anti-inflammatory Mϕs have been implicated in many diseases including rheumatoid arthritis, multiple sclerosis, and leprosy. Recent studies suggest targeting Mϕ function and activation may represent a potential target to treat these diseases. Herein, we investigated the effect of second mitochondria-derived activator of caspases (SMAC) mimetics (SMs), the inhibitors of apoptosis (IAPs) proteins, on the killing of human pro- and anti-inflammatory Mϕ subsets. We have shown previously that human monocytes are highly susceptible whereas differentiated Mϕs (M0) are highly resistant to the cytocidal abilities of SMs. To determine whether human Mϕ subsets are resistant to the cytotoxic effects of SMs, we show that M1 Mϕs are highly susceptible to SM-induced cell death whereas M2a, M2b, and M2c differentiated subsets are resistant, with M2c being the most resistant. SM-induced cell death in M1 Mϕs was mediated by apoptosis as well as necroptosis, activated both extrinsic and intrinsic pathways of apoptosis, and was attributed to the IFN-γ-mediated differentiation. In contrast, M2c and M0 Mϕs experienced cell death through necroptosis following simultaneous blockage of the IAPs and the caspase pathways. Overall, the results suggest that survival of human Mϕs is critically linked to the activation of the IAPs pathways. Moreover, agents blocking the cellular IAP1/2 and/or caspases can be exploited therapeutically to address inflammation-related diseases.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".