Hydrogen sulfide‐releasing NSAIDs attenuate neuroinflammation induced by microglial and astrocytic activation
Bibliographic record
Abstract
Endogenously generated hydrogen sulfide (H(2)S) may have multiple functions in brain. It has been shown that H(2)S attenuates the expression of pro-inflammatory cytokines by lipopolysaccharide (LPS)-activated microglia. Here we demonstrate a neuroprotective effect of NaSH and three H(2)S-releasing compounds, ADT-OH, S-diclofenac, and S-aspirin. When activated by LPS and gamma-interferon, human microglia and THP-1 cells release materials that are toxic to human neuroblastoma SH-SY5Y cells. These phenomena also occur with gamma-interferon-stimulated human astroglia and U118 cells. When these cell types are pretreated with aspirin, diclofenac, NASH, or ADT-OH, the supernatants are significantly less toxic. When they are treated with the NSAID-H(2)S hybrid molecules S-diclofenac and S-aspirin, which are here referred to as S-NSAIDs, there is a significant enhancement of the protection. The effect is concentration and incubation time dependent. Such pretreatment also reduces the release of the proinflammatory mediators TNFalpha, IL-6, and nitric oxide. The H(2)S-releasing compounds are without effect when applied directly to SH-SY5Y cells. These data suggest that hybrid H(2)S releasing compounds have significant antiinflammatory properties and may be candidates for treating neurodegenerative disorders that have a prominent neuroinflammatory component such as Alzheimer disease and Parkinson disease.
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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".