Ginger attenuates acetylcholine-induced contraction and Ca<sup>2+</sup> signalling in murine airway smooth muscle cells
Bibliographic record
Abstract
Asthma is a chronic disease characterized by inflammation and hypersensitivity of airway smooth muscle cells (ASMCs) to different spasmogens. The past decade has seen increased use of herbal treatments for many chronic illnesses. Ginger (Zingiber officinale) is a common food plant that has been used for centuries in treating respiratory illnesses. In this study, we report the effect of its 70% aqueous methanolic crude extract (Zo.Cr) on acetylcholine (ACh)-induced airway contraction and Ca(2+) signalling in ASMCs using mouse lung slices. Airway contraction and Ca(2+) signalling, recorded via confocal microscopy, were induced with ACh, either alone or after pretreatment of slices with Zo.Cr and (or) verapamil, a standard Ca(2+) channel blocker. ACh (10 micromol/L) stimulated airway contraction, seen as decreased airway diameter, and also stimulated Ca(2+) transients (sharp rise in [Ca(2+)]i) and oscillations in ASMCs, seen as increased fluo-4-induced fluorescence intensity. When Zo.Cr (0.3-1.0 mg/mL) was given 30 min before ACh administration, the ACh-induced airway contraction and Ca(2+) signalling were significantly reduced. Similarly, verapamil (1 micromol/L) also inhibited agonist-induced airway contraction and Ca(2+) signalling, indicating a similarity in the modes of action. When Zo.Cr (0.3 mg/mL) and verapamil (1 micromol/L) were given together before ACh, the degree of inhibition was the same as that observed when each of these blockers was given alone, indicating absence of any additional inhibitory mechanism in the extract. In Ca(2+) -free solution, both Zo.Cr and verapamil, when given separately, inhibited Ca(2+) (10 mmol/L)-induced increase in fluorescence and airway contraction. This shows that ginger inhibits airway contraction and associated Ca(2+) signalling, possibly via blockade of plasma membrane Ca(2+) channels, thus reiterating the effectiveness of this age-old herb in treating respiratory illnesses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".