Lasiodiplodan, an exocellular (1→6)-β-<scp>d</scp>-glucan from <i>Lasiodiplodia theobromae</i> MMPI: production on glucose, fermentation kinetics, rheology and anti-proliferative activity
Bibliographic record
Abstract
Lasiodiplodan, an exopolysaccharide of the (1→6)-β-D: -glucan type, is produced by Lasiodiplodia theobromae MMPI when grown under submerged culture on glucose. The objective of this study was to evaluate lasiodiplodan production by examining the effects of carbon (glucose, fructose, maltose, sucrose) and nitrogen sources (KNO(3), (NH(4))(2)SO(4), urea, yeast extract, peptone), its production in shake flasks compared to a stirred-tank bioreactor, and to study the rheology of lasiodiplodan, and lasiodiplodan's anti-proliferative effect on breast cancer MCF-7 cells. Although glucose (2.05 ± 0.05 g L(-1)), maltose (2.08 ± 0.04 g L(-1)) and yeast extract (2.46 ± 0.06 g L(-1)) produced the highest amounts of lasiodiplodan, urea as N source resulted in more lasiodiplodan per unit biomass than yeast extract (0.74 ± 0.006 vs. 0.22 ± 0.008 g g(-1)). A comparison of the fermentative parameters of L. theobromae MMPI in shake flasks and a stirred-tank bioreactor at 120 h on glucose as carbon source showed maximum lasiodiplodan production in agitated flasks (7.01 ± 0.07 g L(-1)) with a specific yield of 0.25 ± 0.57 g g(-1) and a volumetric productivity of 0.06 ± 0.001 g L(-1) h(-1). A factorial 2(2) statistical design developed to evaluate the effect of glucose concentration (20-60 g L(-1)) and impeller speed (100-200 rpm) on lasiodiplodan production in the bioreactor showed the highest production (6.32 g L(-1)) at 72 h. Lasiodiplodan presented pseudoplastic behaviour, and the apparent viscosity increased at 60°C in the presence of CaCl(2). Anti-proliferative activity of lasiodiplodan was demonstrated in MCF-7 cells, which was time- and dose-dependent with an IC(50) of 100 μg lasiodiplodan mL(-1).
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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) | 0.000 | 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".