SMAC mimetics sensitize HIV-infected cells to oncolytic virus-mediated death
Bibliographic record
Abstract
Elimination of latently and persistently HIV-infected cells is one of the main barriers to finding a cure for HIV. We have demonstrated that cells latently/persistently infected with HIV impair interferon signaling, which makes them susceptible to selective infection and killing by the oncolytic virus (OV) MG1. Sensitizing these cells to MG1-mediated killing can be expected to make MG1 a more effective therapeutic. As small-molecule second mitochondria-derived activator of caspases (SMAC) mimetics have been shown to increase OV-mediated death in cancer models, we used the SMAC mimetics LCL-161 and birinapant alongside MG1 to enhance the killing of HIV-infected cell lines and monocyte-derived macrophages (MDMs). We show that SMAC mimetics enhance MG1-mediated death, but that this is not a result of an increase in OV infection. This cell death occurs via both caspase-dependent and caspase-independent mechanisms and is not completely dependent on tumor necrosis factor alpha (TNFα). Together, these results show that the use of SMAC mimetics alongside OVs may be a viable strategy to eradicate latently/persistently HIV-infected cells.
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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".