Autonomic Regulation of Anti-Inflammatory Activities from Salivary Glands
Bibliographic record
Abstract
The cervical sympathetic nerves which innervate the medial basal hypothalamus-hypophyseal complex, primary and secondary lymph organs, and numerous glands, such as the pineal, thyroid, parathyroid and salivary glands form a relevant neuroimmunoendocrine structure that is involved in the regulation of systemic homeostasis. The superior cervical ganglia and the submandibular glands form a 'neuroendocrine axis' called the cervical sympathetic trunk submandibular gland (CST-SMG) axis. The identification of this axis usurps the traditional view of salivary glands as accessory digestive structures and reinforces the view that they are important sources of systemically active immunoregulatory and anti-inflammatory factors whose release is intimately controlled by the autonomic nervous system, and in particular the sympathetic branch. An end component of the CST-SMG axis is the synthesis, processing and release of submandibular rat-1 protein (SMR1), a prohormone, that generates several different peptides, one from near its N-terminus called sialorphin and another from its C-terminus called - submandibular gland peptide-T (SGP-T). SGP-T formed the template for tripeptide fragment (FEG) and its metabolically stable D-isomeric peptide feG, which are potent inhibitors of allergy and asthma (IgE-mediated allergic reactions) and several non-IgE-mediated inflammations. The translation from rat genetics and proteomics to humans has yielded structural and functional correlates that hopefully will lead to the development of new medications and therapeutic approaches for difficult to treat disorders. Although the CST-SMG axis has barely been explored in humans recognition of the importance of this axis could facilitate an understanding and improved management of periodontal disease, and other diseases with a more systemic and nervous system basis such as asthma, autoimmunity, graft-versus-host disease and even Parkinson's disease.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".