Formation and Stability of Pea Proteins Nanoparticles Using Ethanol-Induced Desolvation
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Bibliographic record
Abstract
Protein nanoparticles have recently found a lot of interests due to their unique physicochemical properties and structure-functionality compared to the conventional proteins. The aim of this research was to synthesize pea protein nanoparticles (PPN) using ethanol-induced desolvation, to determine the changes in secondary structures and the particle stability in an aqueous dispersion. The nanoparticles were prepared by diluting 3.0 wt% pea protein solutions in 1-5 times ethanol at pH 3 and 10 at different temperatures. Higher ratios of ethanol caused greater extent of desolvation and larger sizes of PPN. After homogenization at 5000 psi for 5 min, PPN displayed uniform size distribution with a smaller size and higher zeta potential at pH 10 compared to pH 3. PPN prepared from a preliminary thermal treatment at 95 °C revealed a smaller size than those synthesized at 25 °C. Electron microscopy showed roughly spherical shape and extensively aggregated state of the nanoparticles. Addition of ethanol caused a reduction in β-sheets and an increase in α-helices and random coil structures of the proteins. When PPN were separated from ethanol and re-dispersed in deionized water (pH 7), they were stable over four weeks, although some solubilization of proteins leading to a loss in particle size was observed.
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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) | 0.000 | 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 it