Fabrication and characterization of lignin–xylan hybrid nanospheres as pesticide carriers with enzyme-mediated release property
Bibliographic record
Abstract
Lignin nanospheres (LNPs) are an emerging high-value material platform to realize lignin valorization. The modification or introduction of new functions to LNPs is of great significance to expand its downstream applications. This work evaluated the technical feasibility of preparing lignin-xylan hybrid nanospheres (LXNPs) through a simple solution-based self-assembly process, with the goal of achieving the application as pesticide carriers for enzyme-mediated controlled release. Hybrid LXNPs with various weigh ratios (lignin to xylan, 3 : 1, 1 : 1, 1 : 3) were obtained using deep eutectic solvent-extracted condensed lignin and water-insoluble xylan fragments, which exhibited a nanosphere size of about 166-210 nm with considerable stability in the pH range of 4-10. LXNPs with lignin to xylan ratios of 3 : 1 and 1 : 1 showed well-defined core-shell structures with enriched hydroxyl groups on the surface. It was proposed that lignin could anchor xylan fragments through van der Waals force and hydrophobic interactions between lignin phenylpropanes and xylan molecular backbones, thus facilitating the self-assembly process for the formation of this specific spherical structure. The resulting hydrophobic LXNPs core enabled the facile encapsulation of the biological pesticide avermectin (AVM) with 57.9-67.0% efficiency using one-pot synthesis. When these AVM-encapsulated LXNPs were subjected to enzymatic hydrolysis using xylanase, considerable AVM release of 44.8-55.1% was achieved after 16 h, in comparison to the 4.1% release only for those without xylanase. This work showed the high promise of fabricating hybrid LXNPs through the self-assembly process and also provided a universal nanosphere carrier for drug encapsulation and subsequent enzyme-mediated controlled release.
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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 | 0.000 | 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 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".