Exploring the Mechanism of CaoHuangGuiXiang Formula in Ameliorating Systemic Candida albicans Infection: A Study Integrating Network Pharmacology and Animal Experiments
Bibliographic record
Abstract
Purpose: CaoHuangGuiXiang (CHGX) formula is a traditional Chinese medicine (TCM) used for the treatment of Candida -related infections. In this study, we adopted a comprehensive approach integrating network pharmacology and animal validation to investigate the potential targets and underlying mechanisms of the CHGX formula against systemic candidiasis. Methods: Active ingredients and potential targets of CHGX were identified via the TCMSP, Swiss Target Prediction, and TCMID databases. Systemic Candida infection targets were retrieved from the GeneCards and OMIM databases. The protein-protein interaction (PPI) network of common targets was constructed via STRING, followed by topological analysis to identify hub nodes. Functional enrichment analyses were conducted via Metascape. Molecular docking studies were performed via AutoDock. A murine model of systemic Candida albicans infection was established to evaluate the therapeutic efficacy of CHGX formula. Results: A total of 103 active compounds and 279 potential targets of the CHGX formula were identified, yielding 53 common targets between Candida infection-related targets and drug-related targets. Topological analysis of the PPI network identified 15 core targets, 25 significantly enriched KEGG pathways, and 38 enriched GO terms. Molecular docking studies demonstrated robust binding affinity between key CHGX compounds and the identified core targets. In vivo animal experiments revealed that CHGX significantly reduced mortality, improved body weight, mitigated renal pathology, decreased the kidney index, reduced the fungal burden, and alleviated tissue damage in systemic Candida infection. Furthermore, CHGX exerts immunomodulatory and anti-inflammatory effects by modulating macrophage and Th17/Treg cell populations, as well as by regulating cytokines levels. Conclusion: This study elucidates the potential multi-pathway and multi-target mechanisms underlying the therapeutic efficacy of the CHGX formula against Candida infectious diseases, indicating its potential as a novel alternative antifungal drug and providing a scientific basis for its clinical application and further development. Keywords: CaoHuangGuiXiang formula, systemic candidiasis, network pharmacology, antifungal activity, anti-inflammatory effect
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".