Integrating biosynthesis insights with biotechnological potential of bioactive carotenoids in food systems
Bibliographic record
Abstract
: Background Carotenoids, a class of natural compounds in the terpenoid family, are known for their bioactivity and ability to improve human health, and are thus extensively linked to food applications. While current sourcing of carotenoids is principally synthetic, consumers show a strong preference for natural carotenoids, which has driven the growth of carotenoid production via microbial fermentation using algae, bacteria or yeast platforms. Scope and approach By bridging advanced biosynthetic machinery with formulation science, this review critically examines the translational potential of microbial carotenoids as multifunctional ingredients in future food products. Key findings and conclusions : Recent advances in metabolic engineering and synthetic biology have enabled efficient production of commonly utilized carotenoids, such as astaxanthin and β-carotene, and demonstrated proof-of-concept for engineering rare or new-to-nature carotenoids with potential biological activities in microbial hosts. Current developments include strategies for targeted engineering of biosynthetic pathways and precursor supply, and encapsulation technologies for enhancing the bioavailability and stability of carotenoids in functional foods. Nevertheless, biotechnological production of carotenoids and associated downstream processing approaches face both challenges and prospects in scaling up to industrial production.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".