Production, isolation and bioactive estimation of extracellular polysaccharides of green microalga Neochloris oleoabundans
Bibliographic record
Abstract
Previous research revealed that green microalga Neochloris oleoabundans was able to excrete extracellular polysaccharides (EPS) in the media containing certain sugar, but detail researches on the production conditions and chemical and bioactive properties of the EPS are still limited. In this research, cultivation conditions, including 5 sugars (glucose, galactose , maltose , lactose and sucrose), 10–80 g/L of sugar concentrations, 9–36 mM of NaNO 3 and the salinity of 0.5–1.0 g/L NaCl, were investigated their effects on the production of N. oleoabundans EPS. In order to develop a fast and convenient method for assessment of EPS concentration in algal cultivation media, an indirect quantitative technique was proposed based on the consistency coefficient of the media. An EPS (EPS1) was isolated and purified, and its immune activities were investigated in vivo and in vitro . The results showed that glucose, galactose and maltose allowed N. oleoabundans to produce substantial EPS, and glucose was the best sugar for EPS production. The results also showed that 20 g/L glucose and 12 mM NaNO 3 were favorable to EPS production, whereas addition of 0.5–1.0 g/L NaCl to the medium repressed EPS production. Chemical analysis showed that the isolated EPS1 contained 0.59% (w/w) peptides and had a monosaccharide composition of glucose, mannose , galactose, xylose , ribose , arabinose and rhamnose with the molar ratio of 40.7:19.0:18.95:8.7:6.86:4.57:1.2. The bioactive tests demonstrated that EPS1 had immunomodulatory activity in vitro and in vivo .
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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".