Tibouchina granulosa Leaves Present Anti-Inflammatory Effect
Bibliographic record
Abstract
The ethanol extract (EE) prepared from the leaves of Tibouchina granulosa, and its fraction in ethyl acetate (fEA) were evaluated concerning their capacity to reduce inflammation in different experimental models. fEA was also studied concerning its chemical constituents. EE and fEA were assayed for their anti-inflammatory potential, using formalin-induced licking behavior and carrageenan-induced inflammation into the subcutaneous air pouch (SAP) models. Reduction in polymorphonuclear cells (PMN) activation was performed in freshly isolated PMN. Chromatographic analysis of fEA was performed by HPLC-DAD. Hispiduloside was isolated as the main constituent in fEA, and its quantity was estimated to be 39.3% in fEA. EE (30 mg/kg) significantly reduced the second phase of formalin-induced licking. fEA demonstrated a reduction in leukocyte migration into the SAP. EE and fEA drastically reduced cytokines (TNF-α, IL-1β, and IFN-γ), nitric oxide (NO) production, in vitro PMN migration induced by C5a and IL-8, and TNF-α and IL-1β gene expression. Taken together, our data indicate that either ethanol extract or its fEA fraction from leaves of T. granulosa present an anti-inflammatory effect, contributing to the pharmacological and chemical knowledge of this species and confirming the rationale behind its traditional use.
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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 | 0.000 |
| 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".