Sodium thiosulfate attenuates glial-mediated neuroinflammation in degenerative neurological diseases
Bibliographic record
Abstract
BACKGROUND: Sodium thiosulfate (STS) is an industrial chemical which has also been approved for the treatment of certain rare medical conditions. These include cyanide poisoning and calciphylaxis in hemodialysis patients with end-stage kidney disease. Here, we investigated the anti-inflammatory activity of STS in our glial-mediated neuroinflammatory model. METHODS: Firstly, we measured glutathione (GSH) and hydrogen sulfide (H2S, SH(-)) levels in glial cells after treatment with sodium hydrosulfide (NaSH) or STS. We also measured released levels of tumor necrosis factor-α (TNFα) and interleukin-6 (IL-6) from them. We used two cell viability assays, MTT and lactate dehydrogenase (LDH) release assays, to investigate glial-mediated neurotoxicity and anti-inflammatory effects of NaSH or STS. We also employed Western blot to examine activation of intracellular inflammatory pathways. RESULTS: We found that STS increases H2S and GSH expression in human microglia and astrocytes. When human microglia and astrocytes are activated by lipopolysaccharide (LPS)/interferon-γ (IFNγ) or IFNγ, they release materials that are toxic to differentiated SH-SY5Y cells. When the glial cells were treated with NaSH or STS, there was a significant enhancement of neuroprotection. The effect was concentration-dependent and incubation time-dependent. Such treatment reduced the release of TNFα and IL-6 and also attenuated activation of P38 MAPK and NFκB proteins. The compounds tested were not harmful when applied directly to all the cell types. CONCLUSIONS: Although NaSH was somewhat more powerful than STS in these in vitro assays, STS has already been approved as an orally available treatment. STS may therefore be a candidate for treating neurodegenerative disorders that have a prominent neuroinflammatory component.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".