Gene transcription and antioxidants production in <i>Arthrospira (Spirulina) platensis</i> grown under temperature variation
Bibliographic record
Abstract
AIM: To investigate the transcription of selected antioxidants and relevant genes under varying temperature conditions, and to identify the optimum temperature for antioxidants production by Arthrospira platensis. METHODS AND RESULTS: The dry weight (DW), pigment production, antioxidants production and gene transcription were examined in A. platensis growing under three temperatures of 23, 30 and 37°C. The cyanobacterial DW was highest in the high temperatures (30 and 37°C), while the pigments, such as Chl a, carotenoids, C-phycocyanin and total phycobiliprotein contents, showed their maximum value at 30°C. The total soluble protein and carbohydrate contents were highest at 30°C. Lipid peroxidation, as a marker for thermal stress, was high at 23°C, while higher temperatures remarkably reduced lipid peroxidation levels. Antioxidants activity was increased by 1·5-fold at 30°C and temperature fluctuations induced the antioxidant enzyme activities. The transcriptional abundance of heat shock protein (HSP90), glutamate synthase (GOGAT), delta-9 desaturase (desC), iron-superoxide dismutase (FeSOD) and the large subunit of Rubisco (rbcL) genes was measured under the same temperatures. CONCLUSION: The optimal temperature for growth, biochemical constituents and antioxidants of A. platensis is 30°C while some antioxidant enzyme activity increased at lower and higher temperatures. SIGNIFICANCE AND IMPACT OF THE STUDY: The study showed the significance of temperature for growth, enzymatic and non-enzymatic antioxidants and gene expression in A. platensis. This contributes to the knowledge of culturing A. platensis to harvest specific antioxidants or as an antioxidant-rich food source.
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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".