A new and promising C-phycocyanin-producing cyanobacterial strain, Cyanobium sp. MMK01: practical strategy towards developing a methodology to achieve C-phycocyanin with ultra-high purity
Bibliographic record
Abstract
Selecting a suitable cyanobacterial strain and developing easy-to-afford purification processes are two crucial aspects impacting the optimal production yield and appropriate purity of C-phycocyanin (C-PC). Cyanobium sp. MMK01, a highly efficient C-PC-producing bacterium, was identified among four cyanobacterial isolates using morphological characteristics and 16S rRNA gene sequencing. The purification process of C-PC began with ammonium sulfate precipitation, leading to a purity index (PI) of 4.04. Subsequent purification through ion exchange chromatography ultimately resulted in an ultra-highly purified form of C-PC with a significant PI of 5.82. SDS-PAGE analysis of purified C-PC showed the presence of two distinct bands, α (13 kDa) and β (15 kDa). Significantly effective at scavenging free radicals, C-PC also inhibits the viability of human lung cancer cells (Calu-6). Antibacterial, anti-inflammatory, antioxidant, and cancer-preventive compounds were detected in the MMK01 cells’ methanolic extract following GC–MS analysis. The promising results indicate that Cyanobium sp. MMK01 has a great deal of potential for producing C-PC that is on par with strains found in the market, and the tried-and-true two-step purification process proved to work well to achieve an ultra-highly purified form of C-PC.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".