Antioxidative, anti‐inflammatory, and anticancer properties of the red biopigment extract from <i>Monascus purpureus</i> ( <scp>MTCC</scp> 369)
Bibliographic record
Abstract
In this study, the Monascus purpureus (MTCC 369) extracted biopigment produced by solid-state fermentation was evaluated for its therapeutic potential using human prostate LNCaP cells. Antioxidant efficacy of the red biopigment determined using 2,2 diphenyl-1-picrylhydrazyl, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid, and ferric reducing antioxidant power assays was found to be 53.16%, 86.27%, and 13.83%, respectively. In addition, expression studies of target gene superoxide dismutase 2 (SOD-2) showed that increasing concentrations (10-50 μg/ml) of the biopigment enhanced its expression from 0.91- to 1.905-fold. An inhibitory effect of 0.424-0.627-fold was observed in the expression of glutathione peroxidase (GPX) with a similar increase in biopigment concentration. Addition of quercetin (positive control) at 50 μg/ml led to 0.295-fold decrease in GPX expression. In contrast, the expression of SOD-2 increased by 1.026-fold in the presence of quercetin. The biopigment also showed an increased serological IL-10 expression (an anti-inflammatory agent) ranging from 1034.58 to 4657.89 pg/ml. Treatment of LNCaP cells with the red biopigment (10-100 μg/ml) resulted in significant (p < .05) reduction (upto 79.86%) in viability and 51.79%-89.86% reduction in cell metabolic activity. Fluorescent microscopy examination of red biopigment-treated cells showed significant inhibition of normal cellular morphology including condensed nuclei, membrane blebbing, and apoptotic bodies, thus confirming its cytotoxic potential. Results of this study revealed that the red biopigment has the potential to modulate the expression of antioxidative and anti-inflammatory markers in addition to being cytotoxic to the LNCaP cancer cells. PRACTICAL APPLICATIONS: These findings indicate that cell treatment with red biopigment has the potential to modulate anti-oxidative, pro-inflammatory and anti-inflammatory genes for therapeutic effects, which is further enhanced by its cytotoxic activity against cancer cells. Considering these cell-based observations, Monascus red biopigment has ample potential as a useful supplement to formulate therapeutic products that delay the development of inflammatory-related diseases and associated complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".