Synthesis Of Lactam Modulators Of The Interleukin-1 Receptor For Delaying Labor And Improving Neonatal Outcomes
Bibliographic record
Abstract
Interleukin-1β (IL-1β) is a central pro-inflammatory cytokine. On binding to its receptor (IL-1R), IL-1β plays roles in labor, inflammation and immune response against invading pathogens. Premature birth occurs in about 10% of all births worldwide and may lead to morbidity and long-term health problems. The inflammatory component of premature birth may be harmful to the newborn. Although current therapeutic interventions may delay birth, they have no effect on inflammation. Our presentation will focus on the IL-1R modulating peptide 101.10 (H-D-Arg-D-Tyr-D-Thr-D-Val-D-Glu-D-Leu-D-Ala-NH2), which delays labor and curbs inflammation without effect on immune vigilance. Employing lactams analogues of 101.10, information has been obtained regarding the active conformation. Moreover, lead lactam analogs offer promise for delaying labor and improving neonatal outcomes [1-2]. References 1. Geranurimi, A.; Cheng, C. W.; Quiniou, C.; Zhu, T.; Hou, X.; Rivera, J. C.; St-Cyr, D. J.; Beauregard, K.; Bernard-Gauthier, V.; Chemtob, S. Probing Anti-inflammatory Properties Independent of NF-κB Through Conformational Constraint of Peptide-bases Interleukin-1β Receptor Biased Ligand. Front. Chem. 2019, 7, 23. 2. Geranurimi, A.; Cheng, C. W. H.; Quiniou, C.; Cote, F.; Hou, X.; Lahaie, I.; Boudreault, A.; Chemtob, S.; Lubell, W. D. Interleukin-1 Receptor Modulation Using β-Substituted α-Amino-γ-Lactam Peptides From Solid-Phase Synthesis and Diversification. Front. Chem. 2020, 8 (1182).
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".