LOCAL STIMULATION OF α7 CHOLINERGIC RECEPTORS INHIBITS LPS-INDUCED TNF-α RELEASE IN THE MOUSE LUNG
Bibliographic record
Abstract
The cholinergic nervous system can inhibit the release of proinflammatory cytokines such as TNF-alpha from LPS-stimulated macrophages. Acetylcholine, the principal neurotransmitter of the vagus nerve, is the key mediator of this so-called cholinergic anti-inflammatory pathway, specifically interacting with alpha7 cholinergic receptors expressed by macrophages and other cell types to inhibit TNF-alpha production. The aim of the current study was to determine the capacity of the selective alpha7 cholinergic receptor agonist 3-(2,4-dimethoxybenzylidene) anabaseine (GTS-21), administered locally into the airways, to inhibit LPS-induced inflammatory responses in the mouse lung in vivo. GTS-21 dose-dependently inhibited LPS-induced TNF-alpha release by MH-S mouse alveolar macrophages in vitro. Intranasal inoculation with GTS-21 also dose-dependently inhibited TNF-alpha release into the lung compartment after intrapulmonary delivery of LPS in mice in vivo, whereas IL-6 concentrations were not affected. However, GTS-21 did not influence the influx of neutrophils into bronchoalveolar lavage fluid elicited by LPS and increased the concentrations of the neutrophil-attracting chemokines cytokine-induced neutrophil chemoattractant and macrophage inflammatory protein 2. These data indicate that local administration of GTS-21 inhibits TNF-alpha release in the lung during LPS-induced inflammation.
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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) | 0.001 | 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) | 0.001 | 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".