Lignin-Based Nanoparticles Stabilized Pickering Emulsion for Stability Improvement and Thermal-Controlled Release of <i>trans</i>-Resveratrol
Why this work is in the frame
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Bibliographic record
Abstract
In this work, we designed a novel multifunctional Pickering emulsion stabilized by lignin-based nanoparticles. We utilized the industrial waste lignin to prepare thermoresponsive lignin copolymer by grafting poly(N-isopropylacrylamide) (PNIPAM) onto lignin via atom transfer radical polymerization (ATRP) and then formed self-assembled nanoparticles (AL-g-PNIPAM NPs). AL-g-PNIPAM NPs well stabilized trans-resveratrol (trans-RSV)-containing palm oil emulsion droplets in water. Thanks to the abundant UV chromophoric groups of lignin, the light stability of trans-RSV was significantly improved by the protecting of the AL-g-PNIPAM NPs layer. Moreover, the emulsion properties and release behavior strongly depend on the temperature and nanoparticles size: decreasing temperature induced deformation of AL-g-PNIPAM NPs at the interface, an increase in droplet size, and the accelerated release of trans-RSV. These results showed the great potential of this approach of a green functional lignin-based nanoparticles stabilized Pickering emulsion for storage and thermal-controlled release of light-unstable and poorly water-soluble drugs.
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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 | 0.000 | 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