Fibrillization of lentil proteins is impacted by the protein extraction conditions and co-extracted phenolics
Bibliographic record
Abstract
Legume proteins can be induced to form amyloid-like fibrils upon heating at low pH, with the exact conditions greatly impacting the fibril characteristics. The protein extraction method may also impact the resulting fibrils, although this effect has not been carefully examined. Here, the fibrillization of lentil protein prepared using various extraction methods and the corresponding fibril morphology were characterized. It was found that an acidic, rather than alkaline, protein extraction method was better suited for producing homogeneous, long, and straight fibrils from lentil proteins. During alkaline extraction, co-extracted phenolic compounds bound proteins through covalent and non-covalent interactions, contributing to the formation of heterogeneous, curly, and tangled fibrils. Recombination of isolated phenolics and proteins (from acidic extracts) at alkaline pH resulted in a distinct morphology, implicating a role for polyphenol oxidase also in modifying proteins during alkaline extraction. These results help disentangle the complex factors affecting legume protein fibrillization.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".