The diversity and antimicrobial activity of endophytic fungi associated with medicinal plant<i>Baccharis trimera</i>(<i>Asteraceae</i>) from the Brazilian savannah
Bibliographic record
Abstract
The fungal endophyte community associated with Baccharis trimera, a Brazilian medicinal plant, was characterized and screened for its ability to present antimicrobial activity. By using molecular methods, we identified and classified the endophytic fungi obtained into 25 different taxa from the phyla Ascomycota and Basidiomycota. The most abundant species were closely related to Diaporthe phaseolorum, Pestalotiopsis sp. 1, and Preussia pseudominima. The differences observed in endophytic assemblages from different B. trimera specimens might be associated with their crude extract activities. Plants that had higher α-biodiversity were also those that contributed more to the regional (γ) diversity. All fungal isolates were cultured and their crude extracts screened to examine the antimicrobial activities. Twenty-three extracts (12.8%) displayed antimicrobial activities against at least one target microorganism. Among these extracts, those obtained from Epicoccum sp., Pestalotiopsis sp. 1, Cochliobolus lunatus, and Nigrospora sp. presented the best minimum inhibitory concentration values. Our results show that the endophytic fungal community associated with the medicinal plant B. trimera included few dominant bioactive taxa, which may represent sources of compounds with antifungal activity. Additionally, the discovery of these bioactive fungi in association with B. trimera suggests that Brazilian plants used as folk medicine may shelter a rich fungal diversity as well as taxa able to produce bioactive metabolites with antimicrobial activities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".