Proton pump inhibitors reduce interferon‐γ‐induced neurotoxicity and STAT3 phosphorylation of human astrocytes
Bibliographic record
Abstract
Proton pump inhibitors (PPIs) are known to possess anti-inflammatory properties. Inflammatory processes, including astrocytic activation, are implicated in the pathogenesis of different neurodegenerative diseases. Our recent study has indicated that interferon (IFN)-γ-induced astrocytic neurotoxicity is mediated, at least in part, by phosphorylation of signal transducer and activator of transcription (STAT) 3. We therefore studied the effects of PPIs on IFN-γ-induced neurotoxicity and STAT3 activation of human astrocytes. Both lansoprazole (LPZ) and omeprazole (OPZ) significantly attenuated IFN-γ-induced neurotoxicity of human astrocytes and astrocytoma cells. These drugs inhibited IFN-γ-induced phosphorylation of STAT 3, but not STAT1. We found that LPZ significantly reduced secretion of IFN-γ-inducible T cell α chemoattractant from IFN-γ-activated astrocytes. Neither LPZ nor OPZ suppressed expression of intercellular adhesion molecule-1 by IFN-γ-activated astrocytes. These results suggest that PPIs attenuate IFN-γ-induced neurotoxicity of human astrocytes through inhibition of the STAT3 signaling pathway. PPIs that possess antineurotoxic properties may be a useful treatment option for Alzheimer's disease and other neuroinflammatory disorders associated with activated astrocytes.
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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".