In vivo Anti-inflammatory Activity of Lipidated Peptidomimetics Pam-(Lys-βNspe)6-NH2 and Lau-(Lys-βNspe)6-NH2 Against PMA-Induced Acute Inflammation
Bibliographic record
Abstract
Host Defense Peptides (HDPs) are key components of innate immunity that exert antimicrobial, antibiofilm and immunomodulatory activities in all higher organisms. Synthetic peptidomimetic analogs were designed to retain the desirable pharmacological properties of HDPs while having improved stability toward enzymatic degradation, providing enhanced potential for therapeutic applications. Lipidated peptide/β-peptoid hybrids [e.g., Pam-(Lys-βNspe)6-NH2 (PM1) and Lau-(Lys-βNspe)6-NH2 (PM2)] are proteolytically stable HDP mimetics displaying anti-inflammatory activity and formyl peptide receptor 2 antagonism in human and mouse immune cells in vitro. Here PM1 and PM2 were investigated for their in vivo anti-inflammatory activity in a phorbol 12-myristate 13-acetate (PMA)-induced acute mouse ear inflammation model. Topical administration of PM1 or PM2 led to attenuated PMA-induced ear edema, reduced local production of the pro-inflammatory chemokines MCP-1 and CXCL-1 as well as the cytokine IL-6. In addition, diminished neutrophil infiltration into PMA-inflamed ear tissue and suppressed local release of reactive oxygen and nitrogen species were observed upon treatment. The obtained results show that these two peptidomimetics exhibit anti-inflammatory effects comparable to that of the non-steroidal anti-inflammatory drug indomethacin, and hence possess a potential for treatment of inflammatory skin conditions.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".