Antifungal Activity and Mechanistic Insights of 1-<i>O</i>-Alkylglycerols against <i>Monilinia fructigena</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Peach brown rot, caused by Monilinia fructigena ( M. fructigena ), is a destructive disease that affects peaches during pre- and postharvest stages. In this study, two 1- O -alkylglycerols (AKGs), namely, AKG-2 (1- O -dodecylglycerol) and AKG-4 (3-(2-ethylhexyloxy)propane-1,2-diol), demonstrated significant in vitro antifungal activity against M. fructigena, with EC 50 values of 102 and 103 μg/mL, respectively. At a concentration of 200 μg/mL, both compounds effectively suppressed brown rot symptoms in inoculated peaches, achieving a protective efficacy of 93.2%. Mechanistic investigations revealed that AKG-2 and AKG-4 disrupted the surface morphology and internal ultrastructure of fungal hyphae, compromised the integrity of the cell membrane and nucleus, and reduced mitochondrial membrane potential. Moreover, treatment with these compounds induced the accumulation of reactive oxygen species, leading to elevated malondialdehyde levels and decreased activities of key antioxidant enzymes including superoxide dismutase and catalase. These results suggest that AKG-2 and AKG-4 exhibit antifungal effects through multiple synergistic mechanisms including membrane and nuclear damage, mitochondrial dysfunction, and oxidative stress induction. This study, for the first time, provides valuable mechanistic insights into the antifungal effects of AKGs and supports their potential as naturally derived fungicidal agents for the protection of peach fruits.
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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 it