C-176 reduces inflammation-induced pain by blocking the cGAS-STING pathway in microglia
Bibliographic record
Abstract
OBJECTIVE: Inflammatory pain, is caused by lesions or diseases of the somatosensory tissue, is a prevalent chronic condition that profoundly impacts the quality of life. However, clinical treatment for this type of pain remains limited. Traditionally, the stimulation of microglia and subsequent inflammatory reactions are considered crucial elements to promote the worsening of inflammatory pain. Recent research has shown the crucial importance of the cGAS-STING pathway in promoting inflammation. It is still uncertain if the cGAS-STING pathway plays the role in the fundamental cause of inflammatory pain. We aim to explore the treatment of inflammatory pain by interfering with cGAS-STING signaling pathway. METHODS: In this study, we established an inflammatory pain model by CFA into the plantar of mice. Activation of microglia, various inflammatory factors and cGAS-STING protein in the spinal dorsal horn were evaluated. Immunofluorescence staining was used to observe the cellular localization of cGAS and STING. The cGAS-STING pathway proteins expression and mRNA expression of indicated microglial M1/M2 phenotypic markers in the BV2 microglia were detected. STING inhibitor C-176 was intrathecal injected into mice with inflammatory pain, and the pain behavior and microglia were observed. RESULTS: This research showed that injecting CFA into the left hind paw of mice caused mechanical allodynia and increased inflammation in the spine. Our research results suggested that the cGAS-STING pathway had a function in the inflammation mediated by microglia in the spinal cord dorsal horn. Blocking the cGAS-STING pathway using STING antagonists (C-176) led to reduced release of inflammatory factors and prevented M1 polarization of BV2 microglia in a laboratory setting. Additionally, intrathecal administration of C-176 reduced the allodynia in CFA treated mice. CONCLUSION: Our results suggest that inhibiting microglial polarization through the cGAS-STING pathway represents a potential novel therapeutic strategy for inflammatory pain.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".