Peptide–Gold Nanoparticle Hybrids as Promising Anti‐Inflammatory Nanotherapeutics for Acute Lung Injury: In Vivo Efficacy, Biodistribution, and Clearance
Why this work is in the frame
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Bibliographic record
Abstract
Gold nanoparticles (GNPs) have shown great promises in various biomedical applications. Although GNPs exhibit excellent therapeutic efficacy in in vitro and in vivo in numerous studies, there still exists significant biosafety concerns, mainly for their nonbiodegradability and tendency to be trapped in the liver and spleen. To tackle this problem, hexapeptides are utilized to modify the GNP surface to not only impart them with potent anti-inflammatory activity, but also facilitate their rapid clearance in vivo. Previously, a unique class of peptide-GNP hybrids that potently inhibit multiple TLR signaling pathways in macrophages was identified; in this work, it is further demonstrated that these hybrids, after intratracheal instillation, are capable of effectively reducing lung inflammation and injury by decreasing neutrophil infiltration and increasing the number of regulatory T cells in the lung in a lipopolysaccharide-induced acute lung injury (ALI) mouse model. More importantly, these hybrids can be effectively excreted 26 h post-administration with only 8.49 ± 0.70% of them remaining in the body, primarily in the lung and intestine and less than 0.03% accumulated in the liver and spleen. This work provides strong evidences that properly designed peptide-GNP hybrids can serve as the next generation of effective and safe anti-inflammatory nanotherapeutics to treat ALI.
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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