The celecoxib derivatives AR-12 and AR-14 induce autophagy and clear prion-infected cells from prions
Bibliographic record
Abstract
Abstract Prion diseases are fatal infectious neurodegenerative disorders that affect both humans and animals. The autocatalytic conversion of the cellular prion protein (PrPC) into the pathologic isoform PrPSc is a key feature in prion pathogenesis. AR-12 is an IND-approved derivative of celecoxib that demonstrated preclinical activity against several microbial diseases. Recently, AR-12 has been shown to facilitate clearance of misfolded proteins. The latter proposes AR-12 to be a potential therapeutic agent for neurodegenerative disorders. In this study, we investigated the role of AR-12 and its derivatives in controlling prion infection. We tested AR-12 in prion infected neuronal and non-neuronal cell lines. Immunoblotting and confocal microscopy results showed that AR-12 and its analogue AR-14 reduced PrPSc levels after only 72 hours of treatment. Furthermore, infected cells were cured of PrPSc after exposure of AR-12 or AR-14 for only two weeks. We partially attribute the influence of the AR compounds on prion propagation to autophagy stimulation, in line with our previous findings that drug-induced stimulation of autophagy has anti-prion effects in vitro and in vivo. Taken together, this study demonstrates that AR-12 and the AR-14 analogue are potential new therapeutic agents for prion diseases and possibly protein misfolding disorders involving prion-like mechanisms.
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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".