Radical-Scavenging Activities of Cactus Cladodes (<i>O</i> <i>puntia Humifusa</i> Raf.) in a Submerged Culture
Bibliographic record
Abstract
The aim of this work was to select suitable fermentation treatments for the efficient bioconversion of cactus bioactive components with an improved radical-scavenging activity for use as a nutraceutical. To obtain microorganisms for the microbial conversion of cactus, various fungi including Monascus pilosus KCCM 60029 (ATCC 22080) were used for the fermentation of cactus. DPPH (2,2-diphenyl-2-picrylhydrazyl hydrate) and ABTS [2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt] radical-scavenging activities in M. pilosus fermentation were enhanced by 70 and 50%, respectively, compared with control. In particular, uronic acid levels showed a remarkable increase (approximately over threefold) in fermentation. The polyphenol and quercetin content of the fermented cactus showed a large increase from 180 and 2 μg/mL to 233.4 and 8.5 μg/mL, respectively, showing a maximum level at 4 days of fermentation. This result correlated with the increase of the radical-scavenging activity, meaning that polyphenol and quercetin contents are associated with radical-scavenging activity. M. pilosus is a very useful tool in the fermentation of cactus and enhancement of radical-scavenging activity. Practical Applications We adopted fungi-mediated fermentation for bioconversion of bioactive compounds with the improvement of radical-scavenging activity in Opuntia cladodes. Our study suggests that Monascus pilosus-mediated fermentation could be used for desirable modification of edible plant-derived components. This biochemical process would be applied as a way to convert compositions of various components in food substrates, including enhancement of bioactive components, in the food industry. Thus, our study would give useful information in the utility of microbial fermentation for biochemical conversion of food-derived bioactive components.
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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) | 0.001 | 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) | 0.001 | 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".