Overcoming the Mucosal Barrier: Tetraether Lipid‐Stabilized Liposomal Nanocarriers Decorated with Cell‐Penetrating Peptides Enable Oral Delivery of Vancomycin
Bibliographic record
Abstract
Abstract Despite the high medical need for oral peptide delivery, instability in the gastrointestinal tract and low mucosal permeation still impede this preferred route of administration. Herein, a liposomal nanocarrier combining two self‐reliant strategies to overcome these delivery barriers is reported. This approach enables the design of a nanocarrier system with synergistic properties: tetraether lipids derived from archaea are incorporated into liposomes to provide the particles with the stability required to traverse the stomach. When the surface of the resulting inert particles is modified with cell‐penetrating peptides, mucosal permeation can be achieved. The designed nanocarrier is proven effective by the high mucosal uptake of the glycopeptide antibiotic vancomycin in Ussing chamber studies. Efficacy in vivo is demonstrated in naïve rats, where a highly increased oral bioavailability is obtained for vancomycin, a drug known to be minimally absorbed. In contrast, administration of liposomes with single modification (tetraether lipids) leads to a substantially lower bioavailability. Therapeutic efficacy is proven by the antimicrobial activity of vancomycin in a Galleria mellonella and a systemic infection mouse model. The high oral bioavailability in absence of cytotoxic effects demonstrates that this nanocarrier delivery strategy might boost the oral application of macromolecular drugs in general.
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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".