Modulation of Gut Microbiota Mediates the Anti-Inflammatory Effect of Chi-Ju-Di-Huang-Wan against Dry Eye Disease
Bibliographic record
Abstract
Abstract Objective: Chi-Ju-Di-Huang-Wan (CJDHW) is commonly prescribed for the treatment of dry eye disease (DED) with well-documented effectiveness. However, the underlying mechanism remains unclear. Our study aimed to elucidate its potential mechanism by using in vivo and in vitro models. Methodology: Benzalkonium chloride (BAC)-induced DED rats and human corneal epithelial cells (HCEC) were employed to investigate the therapeutic actions of CJDHW. Results: In DED rats, tear production was reduced by over 50% compared to control but was gradually restored by Cyclosporine A (CsA) and CJDHW after 14 days of treatment. An additional 14-day treatment fully restored tear production to control level. Slit-lamp examination revealed severe corneal damage in DED rats, characterized by extensive fluorescein staining. CsA-treated rats showed minimal staining, while CJDHW-treated rats exhibited reduced staining, indicating corneal repair supported by promoted cell proliferation and wound healing in HCEC cells. Comparably to CsA, CJDHW notably decreased the pro-inflammatory cytokines in both tear fluid and corneal tissue of DED rats. This was supported by in vitro study that CJDHW significantly down-regulated pro-inflammatory cytokines in HCEC cells. Microbial analysis showed that CJDHW induced changes in microbial composition at Phylum level, with a significant higher community richness and diversity in CJDHW-treated DED rats. Principal Co-ordinate Analysis revealed a distinct separation in gut microbiota between DED rats and those treated with CJDHW (moderate dosage). Conclusions: CJDHW restores tear production and enhances corneal repair by suppressing inflammatory response in ocular surface via modulating gut microbiota, providing mechanistic understanding of the beneficial actions of CJDHW in DED treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".