Bioinspired zwitterionic polyphosphoester modified porous silicon nanoparticles for efficient oral insulin delivery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The intestinal epithelial and mucus barriers on the gastrointestinal tract limit the bioavailability of oral protein or peptide drugs. Therefore, efficient mucus permeability and cellular internalization are required properties for oral delivery systems. To overcome these two obstacles, porous silicon nanoparticles were modified with poly (pyridyl disulfide ethylene phosphate/sulfobetaine) polymers to make P(PyEP-g-SBm)n-AmPSiNPs (m = 0.1, 0.2, 0.3 and n = 10, 20, 30) nanoparticles (NPs). The insulin-loaded P(PyEP-g-SB)-AmPSiNPs showed favorable stability and good biocompatibility in vitro. The zwitterionic dodecyl sulfobetaine (SB) coated nanoparticles improved the mucus permeability. P(PyEP-g-SBm)20 with the optimal conjugated ratio (m = 0.3) of SB units was determined by evaluating the mucus diffusion rate of NPs. The cellular uptake of P(PyEP-g-SB0.3)n-AmPSiNPs (n = 10, 20, 30) was much higher than AmPSiNPs in the presence of inhibitors (N-acetylcysteine solution and sodium chlorate) (p < 0.01) due to the enhanced charge shielding effect of P(PyEP-g-SB) modification. The P(PyEP-g-SB0.3)20-AmPSiNPs showed about 1.4-1.7 fold increase in the apparent permeability of insulin across Caco-2/HT-29-MTX cell monolayers, compared to AmPSiNPs (p < 0.01). Finally, the in vivo study showed that insulin-loaded P(PyEP-g-SB0.3)20-AmPSiNPs generated 20% reduction of the blood glucose level with an 2-fold increase in oral bioavailability. These suggested that zwitterionic polyphosphoester modified porous silicon nanoparticles, which were of enhanced mucus permeability and cellular internalization, represent a promising carrier for oral delivery of peptide and protein.
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.
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 it