The sympathetic nervous system regulates the release of anti-inflammatory peptides from salivary glands (93.18)
Bibliographic record
Abstract
Abstract Chronic and acute stress have profound effects on inflammation. In rats, allergic inflammation is regulated by the sympathetic nervous system acting on salivary glands. Human asthma is frequently accompanied by salivary gland inflammation. Salivary gland dysfunction in stressed individuals could enhance asthma severity. Salivary gland prohormone SMR1 (submandibular rat-1) is cleaved into two peptides that are anti-inflammatory in rats, mice, dogs, sheep, cats, and human cells in pulmonary inflammation, food allergy, septic shock, pancreatitis, and spinal cord injury. We hypothesized that modulation of the autonomic nervous system would change the expression, processing, and secretion of SMR1 and its peptides. Rats were injected with saline, isoproterenol, or pilocarpine, or the superior cervical ganglion was excised. Saliva, blood, and tissues were collected and analyzed for SMR1. Adrenergic stimulation caused the majority of SMR1 into be secreted into saliva in 60 min. Removal of the superior cervical ganglion that innervates the salivary glands changed SMR1 protein levels in the salivary glands. SMR1 secretion into saliva in response to acute stress may provide a large pool of SMR1-derived peptide products that mediate anti-inflammatory responses locally and systemically. This research is funded by AllerGen NCE.
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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) | 0.004 | 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".