Pulmonary Inflammation Is Regulated by the Levels of the Vesicular Acetylcholine Transporter
Bibliographic record
Abstract
Acetylcholine (ACh) plays a crucial role in physiological responses of both the central and the peripheral nervous system. Moreover, ACh was described as an anti-inflammatory mediator involved in the suppression of exacerbated innate response and cytokine release in various organs. However, the specific contributions of endogenous release ACh for inflammatory responses in the lung are not well understood. To address this question we have used mice with reduced levels of the vesicular acetylcholine transporter (VAChT), a protein required for ACh storage in secretory vesicles. VAChT deficiency induced airway inflammation with enhanced TNF-α and IL-4 content, but not IL-6, IL-13 and IL-10 quantified by ELISA. Mice with decreased levels of VAChT presented increased collagen and elastic fibers deposition in airway walls which was consistent with an increase in inflammatory cells positive to MMP-9 and TIMP-1 in the lung. In vivo lung function evaluation showed airway hyperresponsiveness to methacholine in mutant mice. The expression of nuclear factor-kappa B (p65-NF-kB) in lung of VAChT-deficient mice were higher than in wild-type mice, whereas a decreased expression of janus-kinase 2 (JAK2) was observed in the lung of mutant animals. Our findings show the first evidence that cholinergic deficiency impaired lung function and produce local inflammation. Our data supports the notion that cholinergic system modulates airway inflammation by modulation of JAK2 and NF-kB pathway. We proposed that intact cholinergic pathway is necessary to maintain the lung homeostasis.
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 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) | 0.001 | 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".