Psilocybin alleviates high-glucose and high-lipid-induced skin aging in BJ5Ta fibroblasts
Bibliographic record
Abstract
Cellular aging, driven by oxidative stress, mitochondrial dysfunction, and inflammation, is exacerbated by a high-glucose and high-lipid (HGHL) diet, leading to collagen degradation and skin aging. Psilocybin, a naturally occurring compound, has shown potential in reducing symptoms of aging. This study explores the protective effects of psilocybin on BJ-5ta fibroblasts exposed to HGHL, focusing on cellular viability, apoptosis, senescence, the inflammatory responses, and wound healing. First, fibroblasts were exposed to 25 mmol/L glucose and 400 µmol/L palmitic acid to establish cell aging. Then, psilocybin effects were tested in co- and post-treatment with HGHL. Post-treatment with psilocybin at 15 µmol/L (P15) and co-treatment with psilocybin at 10 µmol/L (P10) preserved cellular viability and decreased beta-galactosidase activity. P10 was most effective in reducing apoptosis and alleviating HGHL-induced S phase arrest. P15 also reduced senescence markers and decreased the expression of inflammatory cytokines IL-1β, IL-6, and COX-2. Additionally, psilocybin promoted nonsignificant fibroblast migration, and P10 co-treated with HGHL significantly upregulated elastin gene expression. These findings suggest that psilocybin’s antioxidative, anti-inflammatory, and regenerative properties make it a promising natural compound for reducing skin aging, particularly under oxidative stress conditions. Further research is needed to explore its long-term effects, optimal dosages, and clinical applications.
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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 | 0.000 | 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) | 0.000 | 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".