Expression of kinin B<sub>1</sub>receptor in fresh or cultured rabbit aortic smooth muscle: role of NF-κB
Bibliographic record
Abstract
Kinin B(1) receptor (B(1)R) expression and the importance of the transcription factor nuclear factor (NF)-kappa B in this process were evaluated in models based on the rabbit aorta: freshly isolated tissue (postisolation induction) and cultured smooth muscle cells (SMCs). A 3-h incubation of freshly isolated tissues determined a sharp B(1)R mRNA increase (RT-PCR). Coincubation of tissues with a stimulus (interleukin-1 beta, fetal bovine serum, epidermal growth factor, or cycloheximide) further increased mRNA levels. Cultured SMCs possessed a basal population of surface B(1)Rs ([(3)H]Lys-des-Arg(9)-bradykinin binding) that was upregulated by treatments with the same set of stimuli (binding, mRNA, nuclear runon). Pharmacological inhibitors of NF-kappa B (MG-132, BAY 11-7082, dexamethasone) or actinomycin D reduced the postisolation induction of B(1)Rs in fresh aortic tissue (contractility or mRNA) and the cytokine effect on cells (mRNA, binding). NF-kappa B may be a common mediator of various stimuli that increase B(1)R gene transcription in the rabbit aorta, including tissue isolation, but cycloheximide also stabilizes B(1)R mRNA. The SMC models faithfully mimic the in vivo situation with regard to B(1)R regulation.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".