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The sympathetic nervous system regulates the release of anti-inflammatory peptides from salivary glands (93.18)

2009· article· en· W26148240 on OpenAlexaff
Katherine Morris, Chris D. St. Laurent, Ryan S Hoeve, Jim Wickware, Paul Forsythe, Ron Mathison, A. Dean Befus

Bibliographic record

VenueThe Journal of Immunology · 2009
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsSalivaSalivary glandMedicinePilocarpineInternal medicineInflammationSympathetic nervous systemEndocrinologySubmandibular glandAutonomic nervous systemSuperior cervical ganglionVasoactive intestinal peptideImmunologyNeuropeptideReceptorHeart rate

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.221
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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