Health Benefits, Food Applications, and Sustainability of Microalgae-Derived N-3 PUFA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Today's consumers are increasingly aware of the beneficial effects of n-3 PUFA in preventing, delaying, and intervening various diseases, such as coronary artery disease, hypertension, diabetes, inflammatory and autoimmune disorders, neurodegenerative diseases, depression, and many other ailments. The role of n-3 PUFA on aging and cognitive function is also one of the hot topics in basic research, product development, and clinical applications. For decades, n-3 PUFA, especially EPA and DHA, have been supplied by fish oil and seafood. With the continuous increase of global population, awareness about the health benefits of n-3 PUFA, and socioeconomic improvement worldwide, the supply chain is facing increasing challenges of insufficient production. In this regard, microalgae have been well considered as promising sources of n-3 PUFA oil to mitigate the supply shortages. The use of microalgae to produce n-3 PUFA-rich oils has been explored for over two decades and some species have already been used commercially to produce n-3 PUFA, in particular EPA- and/or DHA-rich oils. In addition to n-3 PUFA, microalgae biomass contains many other high value biomolecules, which can be used in food, dietary supplement, pharmaceutical ingredient, and feedstock. The present review covers the health benefits of n-3 PUFA, EPA, and DHA, with particular attention given to the various approaches attempted in the nutritional interventions using EPA and DHA alone or combined with other nutrients and bioactive compounds towards improved health conditions in people with mild cognitive impairment and Alzheimer's disease. It also covers the applications of microalgae n-3 PUFA in food and dietary supplement sectors and the economic and environmental sustainability of using microalgae as a platform for n-3 PUFA-rich oil production.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it