Phytotherapy used in the Treatment of Oral Diseases: a Cross-Sectional Study in Indigenous Population
Bibliographic record
Abstract
Phytotherapy studies the pharmacological effects of plants with the therapeutic purpose of preventing, curing, or minimizing disease symptoms. The use of plants by indigenous people to treat health conditions has been documented since ancient times. This study aimed to report an indigenous community's herbal medicines for oral diseases. An online questionnaire was administered, in which the participant indicated the type of plant and the part used, the preparation form, the administration route, and the dental condition. Subsequently, a descriptive analysis was performed. Most study participants were women (n=72, 62.1%). Peppermint tea (21.5%) was the most used substance for mouthwash and halitosis (42.2%). The bark of Açoita (34.5%) and Aroeira (31.9%) were the most frequently used to treat dental pain. Regarding gingival diseases, most responded that they used Guamirim (64.5%). Only mallow tea was reported to treat canker sores (81%). However, for herpetic lesions, participants reported the application of clay in a wasp nest (Polistes canada), an insect present at the site (55.2%). Oral inflammation had the lowest reported use of herbal medicine, with Marcela tea being the most frequently used (10.3%). Finally, fern roots were the most frequently used for infections (32 %). In conclusion, indigenous people widely use phytotherapeutics to treat oral diseases. Learning about the use of herbal medicines in indigenous communities may increase the clinical applicability of these plants in the dental field and, in the future, serve as a basis for developing new drugs.
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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".