Effects Of Dextromethorphan Mediated Bitter Taste Receptor Activation In Pulmonary Artery Smooth Muscle Cells
Bibliographic record
Abstract
Activation of bitter taste receptors (T2Rs) in human airway smooth muscle cells lead to muscle relaxation and bronchodilation. However, the presence of T2Rs in human pulmonary artery smooth muscle cells (hPASMCs) has not been established. The previous finding in airway smooth muscle led to our hypothesis that T2Rs, if present in hPASMCs, might be involved in regulating the vascular tone. RT‐PCR analysis revealed the expression of multiple T2R transcripts in hPASMCs. Functional analysis showed that these cells responded to many bitter‐tasting compounds, by increasing intracellular calcium concentration, indicating that T2Rs in hPASMCs are functional. Since the response of T2R1 to dextromethorphan (DXM) has been characterized in our previous studies, T2R1 was selected for further analysis in this study. Knockdown with T2R1‐specific shRNA decreased mRNA levels and DXM‐induced calcium responses by up to 40%. ELISA data obtained from in vitro studies using hPASMC showed that DXM‐treatment led to increased levels of endothelin‐1, biomarker of systemic hypertension. To analyze if T2R1 is involved in regulating the pulmonary vascular tone, ex vivo studies using pulmonary arterial rings are being pursued. Furthermore, it remains to be analyzed if this effect of DXM in hPASMCs is T2R1 specific or due to the blockade of NMDA receptors. Supported by MHRC, NSERC and a New Investigator Award from HSFC.
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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) | 0.002 | 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".