CHEMICAL AND PHARMACOLOGICAL PROPERTIES OF THE GENUS COPAIFERA IN THE TREATMENT OF INJURIES/WOUNDS: INTEGRATIVE REVIEW
Bibliographic record
Abstract
Objective: To identify chemical and pharmacological properties of Copaifera in the treatment of injuries and wounds. Method: Integrative literature review conducted in the LILACS, MEDLINE, PubMed, Taylor & Francis and Scopus databases in January 2022, using the search strategy: “Chemical Properties” AND “Copaifera” AND “Wounds and Injuries” and “Pharmacology” AND “Copaifera” AND “Wounds and Injuries.” Original articles, full text, identified according to level of evidence, written in Portuguese, English or Spanish, were included. Results: In the primary search 261 articles were found. After systematized selection, 12 studies were selected for qualitative analysis. Species of the genus Copaifera have pharmacological properties favorable for wound treatment: control of inflammatory pain, reduction of inflammatory reaction, tissue reepithelialization and repair, angiogenesis, wound retraction and scar remodeling. Among the chemical properties associated with the treatment of injuries, the presence of bioactive compounds stand out: diterpenes, 3-hydroxy-copalic, sesquiterpenes, kolavic-15-methyl ester. Among the tested diterpenes, kaurenoic and copalic acids showed significant hemolytic activities. Only copalic acid and hardwickiic acid inhibited nitric oxide production in lipopolysaccharide-activated macrophages. Conclusion: Plants of the genus Copaifera have chemical and pharmacological properties favorable for the treatment of injuries and wounds.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".