Metabolite Composition and Bioactivity of<i>Rhizoctonia solani</i>Sclerotial Exudates
Bibliographic record
Abstract
Sclerotia are vegetative structures that play a major role in survival of fungi under adverse conditions. The sclerotia of the plant pathogen Rhizoctonia solani AG2-2 IIIB exude liquid brown droplets that were evaluated for their bioactivity and toxicity against microorganisms and plant species. Also, their metabolic composition was analyzed by integrating Fourier transform ion cyclotron resonance-mass spectrometry (FT-ICR/MS), gas chromatography-MS (GC/MS), and proton nuclear magnetic resonance ((1)H NMR) spectroscopy. The results showed that exudates are complex mixtures composed of phenolics (17.40%), carboxylic acids (12.79%), carbohydrates (6.08%), fatty acids (3.78%), and amino acids (3.47%). The presence of such metabolites contributed to their antifungal and phytotoxic activities. The biological interpretation of the results highly suggests that the exudates not only have multiple roles in fungal physiology but also are a potential bioactive source with moderate toxicity. Our findings show with certainty that the integration of different analytical platforms is a powerful approach for extracting the maximum and reliable information on the metabolic composition of complex biological samples.
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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 | 0.000 | 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 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".