Azasulfurylpeptide Modulation of CD36-Mediated Inflammation Without Effect on Neovascularization
Bibliographic record
Abstract
Modulation of the cluster of differentiation-36 receptor (CD36) has proven promising for dampening pro-inflammatory macrophage signaling. For example, azapeptides (e.g., 1 and 2) bind CD36 selectively with high affinity, mitigate Toll-like receptor (TLR) agonist-induced overproduction of nitric oxide (NO), and reduce pro-inflammatory cytokine and chemokine production in macrophages. Moreover, semicarbazides 1 and 2 inhibit microvascular sprouting mediated through CD36 in the choroid explant. Seeking a selective CD36 modulator that mediated inflammation without influencing neovascularization, a set of azasulfurylpeptides (e.g., 3a–e) were synthesized in which the semicarbazide was replaced by an N-aminosulfamide residue using a novel solid-phase approach. Notably, azasulfurylpeptide 3c diminished selectively CD36-mediated TLR-2-triggered inflammatory response without affecting neovascularization. Subtle chemical modification at the peptide backbone from a carbonyl to a sulfuryl residue has had a selective effect on biological activity providing a valuable probe for studying CD36 chemical biology.
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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) | 0.001 | 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".