<i>Cryptoporus volvatus</i>polysaccharides attenuate LPS-induced expression of pro-inflammatory factors via the TLR2 signaling pathway in human alveolar epithelial cells
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Bibliographic record
Abstract
CONTEXT: Cryptoporus volvatus (Peck) Hubb grows wild in China, and its fruiting bodies have been used traditionally to treat asthma and bronchitis. OBJECTIVES: This study evaluates the anti-inflammatory effect of Cryptoporus polysaccharides (CP) extracted from fruiting bodies of C. volvatus on lipopolysaccharide (LPS)-induced pro-inflammatory factors and the signaling pathways involved in human alveolar epithelial cells. MATERIALS AND METHODS: To evaluate the effects of CP on LPS-induced pro-inflammatory factors, A549 cells were pre-incubated with CP 1, 10, and 100 μg/ml for 1 h and then stimulated with LPS 10 μg/ml for 24 h. The expression of pro-inflammatory factors monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), Toll-like receptor 2 (TLR2), and phosphorylation of ERK1/2, p38, and NF-κB p65 were measured by q-PCR, ELISA, and western blotting. RESULTS: CP decreased LPS-induced mRNA expression of MCP-1, TNF-α, and IL-1β (IC50 = 83.3, 85.2, and 91.6 μg/ml, respectively) and their correspondent protein expression (IC50 = 88.6, 76.4, and 81.6 μg/ml, respectively). Investigation of potential mechanisms indicated that CP 100 μg/ml reduced LPS-induced expression of TLR2 mRNA (66.9%, p < 0.01) and protein (63.2%, p < 0.01) that was a result of the decreased pro-inflammatory factors. LPS induction increased the expression of TLR2 and the phosphorylation of p38 and ERK1/2, NF-kB p65 concomitantly. CP 100 μg/ml inhibited the LPS-induced phosphorylation of the signaling proteins (p < 0.05). CONCLUSIONS: This suggests that CP pretreatment down-regulates LPS-mediated inflammation in lung epithelial cells. This study further confirmed that CP is a potential anti-inflammatory drug for the treatment of airway inflammatory diseases.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it