Nanogel encapsulation improves pharmacokinetics and biodistribution of antimicrobial peptide LL37 upon lung deposition: In vivo evaluation by SPECT/CT
Bibliographic record
Abstract
Antimicrobial peptides (AMPs) constitute the first line of defense in the human body and exogenous application of AMPs is a desirable therapeutic strategy to combat bacterial infections. However, the antibacterial properties of AMPs are often time limited due to fast degradation by host and bacterial proteases, and administration of the needed high doses may result in local inflammation, as well as nephro- and hepatotoxicity. In this study, we assessed the possibility of using nanogels composed of hyaluronic acid modified with octenyl succinic anhydride (HA-OSA) as a drug delivery system to improve the pharmacokinetics and safety profile of LL37, a naturally occurring AMP, when administered to the mucosal surface of the lungs. The peptide LL37 and the polymer HA-OSA were radiolabeled with 67 gallium and 111 indium, respectively, allowing for non-invasive tracking over time in mice following intratracheal administration. When non-formulated LL37 was administered, approximately 85 % of the peptide dose was cleared from the lungs over 48 h, whereas encapsulation of LL37 in HA-OSA nanogels increased peptide retention in the lungs by 36 %. Additionally, the amount of peptide in excretory organs was reduced, decreasing potential liver and kidney toxicity known to be associated with AMP-based therapies. The findings in this study indicate that encapsulation of LL37 in nanogels provides beneficial pharmacokinetic effects.
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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 | 0.001 | 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 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".