Frontline: Inhibition of allergen‐induced pulmonary inflammation by the tripeptide feG: a mimetic of a neuro‐endocrine pathway
Bibliographic record
Abstract
Interactions between the neuro-endocrine system and immune system help maintain health. One interaction involves the superior cervical ganglia (SCG), which regulate the prohormone submandibular rat 1 (SMR1) produced by the submandibular gland (SMG). A peptide derived from SMR1, feG, has anti-inflammatory activity, and modification to D-isomer feG enhances bioactivity. We tested feG as a therapeutic agent for airways inflammation, using rats sensitized by OVA or Nippostrongylus brasiliensis (Nb). Treatment with feG but not fdG down-regulated OVA-challenge-induced increases in bronchoalveolar lavage (BAL)-derived macrophages, eosinophils and PMN (neutrophils) by 44%, 69% and 67%, respectively, at 24 h. We found that feG also reduced ICAM-1 on BAL-derived macrophages and eosinophils by 27% and 65%, and L-selectin on PMN by 55% following OVA challenge. Furthermore, feG but not fdG reduced the OVA-induced TNF increase in BAL fluid. We showed that feG also down-regulated both hyper-responsiveness to methacholine (by 27%) and microgranulomata formation in the lung parenchyma. In Nb-challenged rats, feG treatment inhibited ex vivo allergen-induced contraction of tracheal smooth muscle by up to 73%. In conclusion, feG, which is a mimetic of a peptide derived from a rat salivary gland prohormone, has anti-inflammatory properties in allergic airways inflammation in Brown-Norway rats. The role of the SCG-SMG neuro-endocrine pathway in allergic asthma and other inflammatory diseases requires additional study.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".