Exploiting the potential of Cyanidiales as a valuable resource for biotechnological applications
Bibliographic record
Abstract
The biotechnological uses of algae and cyanobacteria have been widely discussed in the context of climate change and consequent efforts to circularize economies, minimize carbon release and reuse waste streams. Their great potential in bioproduction and bioremediation has barely been exploited, particularly for the well-characterized red algae Galdieria sulphuraria and Cyanidioschyzon merolae. These and other Cyanidiales are excellent candidates for biotechnological enhancement and metabolic engineering for a broad spectrum of applications including the production of biofuels and thermostable colourants. In particular, extremophily, such as growth at thermophilic temperatures – up to 60°C – and at low pH and high salinity, make these algae unusually resistant to contamination and pathogens, and therefore potentially more commercially viable. We review existing applications of the Cyanidiales, as well as their available molecular tools. Their varied nutritional demands, from the broad heterotrophy of G. sulphuraria to strongly autotrophic C. merolae, along with their ability to grow to high densities, confer great potential as expression hosts. We also discuss the deficiencies that must be overcome to unlock further applications and ultimately to embed thermophilic red algae into a framework of circular and sustainable economic activity relying on bio-based sources.
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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".