Long-term endogenous acetylcholine deficiency potentiates pulmonary inflammation in a murine model of elastase-induced emphysema
Bibliographic record
Abstract
Abstract Acetylcholine (ACh), the neurotransmitter of the cholinergic system, regulates inflammation in several diseases including pulmonary diseases. ACh is also involved in a non-neuronal mechanism that modulates the innate immune response. Because inflammation and release of pro-inflammatory cytokines are involved in pulmonary emphysema, we hypothesized that vesicular acetylcholine transport protein (VAChT) deficiency, which leads to reduction in ACh release, can modulate lung inflammation in an experimental model of emphysema. Mice with genetical reduced expression of VAChT (VAChT KD HOM 70%) and wild-type mice (WT) received nasal instillation of 50 uL of porcine pancreatic elastase (PPE) or saline on day 0. Twenty-eight days after, animals were evaluated. Elastase instilled VAChT KD HOM mice presented an increase in macrophages, lymphocytes, and neutrophils in bronchoalveolar lavage fluid and MAC2-positive macrophages in lung tissue and peribronchovascular area that was comparable to that observed in WT mice. Conversely, elastase instilled VAChT KD HOM mice showed significantly larger number of NF-κB-positive cells and isoprostane staining in the peribronchovascular area when compared to elastase-instilled WT-mice. Moreover, elastase-instilled VAChT-deficient mice showed increased MCP-1 levels in the lungs. Other cytokines, extracellular matrix remodeling, alveolar enlargement, and lung function were not worse in elastase-instilled VAChT deficiency than in elastase-instilled WT-controls. These data suggest that decreased VAChT expression may contribute to the pathogenesis of emphysema, at least in part, through NF-κB activation, MCP-1, and oxidative stress pathways. This study highlights novel pathways involved in lung inflammation that may contribute to the development of chronic obstrutive lung disease (COPD) in cholinergic deficient individuals such as Alzheimer’s disease patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".