Lipid production and mixotrophic growth features of cyanobacterial strains isolated from various aquatic sites
Bibliographic record
Abstract
The present study was conducted to determine the potential of five cyanobacteria strains isolated from aquatic zones to induce lipid production. The phylogenetic affiliation of the isolates was determined by 16S rRNA gene sequencing. Amongst the isolates, an efficient cyanobacterium, Synechococcus sp. HS01 showing maximal biomass and lipid productivity, was selected for further studies. In order to compare lipid productivity, the HS01 strain was grown in different media to screen potential significant culture ingredients and to evaluate mixotrophic cultivation. Mixotrophic cultivation of the strain using ostrich oil as a carbon source resulted in the best lipid productivity. GC analysis of fatty acid methyl esters of the selected cyanobacterial strain grown in media supplemented with ostrich oil showed a high content of C16 (palmitoleic acid and palmitic acid) and C18 (linoleic acid, oleic acid and linolenic acid) fatty acids of 42.7 and 42.8 %, respectively. Transmission electron micrographs showed that the HS01 cells exhibited an elongated rod-shaped appearance, either isolated, paired, linearly connected or in small clusters. According to initial experiments, ostrich oil, NaNO3 and NaCl were recognized as potential essential nutrients and selected for optimization of media with the goal of maximizing lipid productivity. A culture optimization technique using the response surface method demonstrated a maximum lipid productivity of 56.5 mg l(-1) day(-1). This value was 2.82-fold higher than that for the control, and was achieved in medium containing 1.12 g l(-1) NaNO3, 1 % (v/v) ostrich oil and 0.09 % (w/v) NaCl.
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 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".