Mepivacaine-induced contraction involves phosphorylation of extracellular signal-regulated kinase through activation of the lipoxygenase pathway in isolated rat aortic smooth muscle
Bibliographic record
Abstract
Mepivacaine is an aminoamide local anesthetic with an intermediate duration that intrinsically produces vasoconstriction both in vivo and in vitro. This study investigated the arachidonic acid metabolic pathways involved in mepivacaine-induced contraction, and elucidated the associated cellular mechanism with a particular focus on extracellular signal-regulated kinase (ERK) in endothelium-denuded rat aorta. Isolated rat thoracic aortic rings were suspended for isometric tension recording. Cumulative mepivacaine concentration-response curves were generated in the presence or absence of the following inhibitors: quinacrine dihydrochloride, nordihydroguaiaretic acid, phenidone, AA-861, indomethacin, NS-398, SC-560, fluconazole, PD 98059, and verapamil. Mepivacaine-induced ERK phosphorylation, 5-lipoxygenase (5-LOX) expression, and cyclooxygenase (COX)-2 expression in rat aortic smooth muscle cells were detected by Western blot analysis in the presence or absence of inhibitors. Mepivacaine produced tonic contraction in isolated endothelium-denuded rat aorta. Quinacrine dihydrochloride, nordihydroguaiaretic acid, phenidone, AA-861, NS-398, PD 98059, and verapamil attenuated mepivacaine-induced contraction in a concentration-dependent manner. However, fluconazole had no effect on mepivacaine-induced contraction. PD 98059, quinacrine dihydrochloride, nordihydroguaiaretic acid, AA-861, phenidone, and indomethacin attenuated mepivacaine-induced ERK phosphorylation. Mepivacaine upregulated 5-LOX and COX-2 expression. These results suggest that mepivacaine-induced contraction involves ERK activation, which is primarily mediated by the 5-LOX pathway and in part by the COX-2 pathway.
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 | 0.001 |
| 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 | 0.000 | 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".