Dabrafenib, an inhibitor of RIP3 kinase-dependent necroptosis, reduces ischemic brain injury
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
Ischemic brain injury triggers neuronal cell death by apoptosis via caspase activation and by necroptosis through activation of the receptor-interacting protein kinases (RIPK) associated with the tumor necrosis factor-alpha (TNF-α)/death receptor. Recent evidence shows RIPK inhibitors are neuroprotective and alleviate ischemic brain injury in a number of animal models, however, most have not yet undergone clinical trials and safety in humans remains in question. Dabrafenib, originally identified as a B-raf inhibitor that is currently used to treat melanoma, was later revealed to be a potent RIPK3 inhibitor at micromolar concentrations. Here, we investigated whether Dabrafenib would show a similar neuroprotective effect in mice subjected to ischemic brain injury by photothrombosis. Dabrafenib administered intraperitoneally at 10 mg/kg one hour after photothrombosis-induced focal ischemic injury significantly reduced infarct lesion size in C57BL6 mice the following day, accompanied by a markedly attenuated upregulation of TNF-α. However, subsequent lower doses (5 mg/kg/day) failed to sustain this neuroprotective effect after 4 days. Dabrafenib blocked lipopolysaccharides-induced activation of TNF-α in bone marrow-derived macrophages, suggesting that Dabrafenib may attenuate TNF-α-induced necroptotic pathway after ischemic brain injury. Since Dabrafenib is already in clinical use for the treatment of melanoma, it might be repurposed for stroke therapy.
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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 | 0.001 | 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