Enhancing peptide and PMO delivery to mouse airway epithelia by chemical conjugation with the amphiphilic peptide S10
Bibliographic record
Abstract
Delivery of antisense oligonucleotides (ASOs) to airway epithelial cells is arduous due to the physiological barriers that protect the lungs and the endosomal entrapment phenomenon, which prevents ASOs from reaching their intracellular targets. Various delivery strategies involving peptide-, lipid-, and polymer-based carriers are being investigated, yet the challenge remains. S10 is a peptide-based delivery agent that enables the intracellular delivery of biomolecules such as GFP, CRISPR-associated nuclease ribonucleoprotein (RNP), base editor RNP, and a fluorescent peptide into lung cells after intranasal or intratracheal administrations to mice, ferrets, and rhesus monkeys. Herein, we demonstrate that covalently attaching S10 to a fluorescently labeled peptide or a functional splice-switching phosphorodiamidate morpholino oligomer improves their intracellular delivery to airway epithelia in mice after a single intranasal instillation. Data reveal a homogeneous delivery from the trachea to the distal region of the lungs, specifically into the cells lining the airway. Quantitative measurements further highlight that conjugation via a disulfide bond through a pegylated (PEG) linker was the most beneficial strategy compared with direct conjugation (without the PEG linker) or conjugation via a permanent thiol-maleimide bond. We believe that S10-based conjugation provides a great strategy to achieve intracellular delivery of peptides and ASOs with therapeutic properties in lungs.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".