Designing Amyloid-Like Protein Aggregates from Microalgal Biomass
Bibliographic record
Abstract
Our societal dependence on petrochemical-derived plastics has significant environmental ramifications, with about 80% of such plastics ending up as persistent waste. To this end, we investigate the extraction and purification of proteins from microalgae, specifically spirulina and chlorella, and their self-assembly into amyloid-like aggregates as building blocks toward the development of sustainable bioplastic materials. After self-assembly, spirulina proteins formed beta-sheet-rich structures with a typical (albeit short and worm-like) fibrillar morphology, while chlorella proteins predominantly aggregated into nonfibrillar, spherical/annular structures. Despite their morphological differences, both microalgal protein aggregates exhibited impressive stability across a wide pH range, persisting up to pH 11 before disaggregating at pH 12. In short, this work highlights the importance of biomass source, protein purity, and composition on the aggregation process of differing proteins. Given the high protein content and expanding industrial production of microalgae, spirulina and chlorella present an untapped resource for the development of sustainable bioplastics.
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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".