Synthesis and Biological Evaluation of Biotinyl Hydrazone Derivatives of Muramyl Peptides
Bibliographic record
Abstract
Muramyl peptides derived from bacterial peptidoglycan have long been known for their ability to trigger host innate immune responses, including inflammation and antimicrobial defense. Muramyl peptides have also been widely studied for their role as immune adjuvants. In mammals, the nucleotide-binding oligomerization domain (Nod) proteins Nod1 and Nod2 detect distinct muramyl peptide structures and mediate their biological activity. Because of the poor immunogenicity of these small peptidoglycan derivatives, research in this field is currently limited by the lack of reagents to track or immobilize specific muramyl peptides. We present here the generation and initial biological characterization of synthetic muramyl peptides covalently coupled to dansyl or biotinyl derivatives and demonstrate that biotinyl coupling on the muramyl moiety results in derivatives that can be tracked by immunofluorescence and maintain full biological activity, as observed by their capacity to trigger Nod signaling. Moreover, using digitonin-mediated permeabilization techniques on live cells, we also demonstrate that biotinylated muramyl peptides efficiently reach the host cytosol, where they activate Nod signaling. Therefore, these derivatives represent useful probes to study the cell biology and the biochemistry of host responses to muramyl peptides.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".