Norepinephrine Transporter is Involved in Down-Regulation of β1-Adrenergic Receptors Caused by Adjuvant Arthritis
Bibliographic record
Abstract
PURPOSE: Inflammation in forms of rheumatoid and experimental arthritis cause not only joint pain but also excessive cardiovascular mortality. The condition also reduces response to calcium channel and beta-adrenergic (beta1-AR) antagonists. For calcium channel inhibitors, the reduced response is shown to be due to the reduced expression of target proteins. Hydroxymethylglutaryl CoA reductase inhibitors (statins) restore response to propranolol and verapamil. We tested the effect of adjuvant arthritis on the norepinephrine (NE) transporter (NET) density since altered sympathetic nervous system innervation has been observed in rheumatoid arthritis. METHODS: Male Sprague-Dawley rats were divided into the following groups: Healthy/Placebo, Healthy/Statin, Pre-AA/Placebo, and Pre-AA/Statin (n=7-8/group). On Day 0, to the Pre-AA and Healthy groups, was injected Mycobacterium butyricum or saline, respectively. On Days 4-8, Statin and Placebo groups received either pravastatin (6 mg/kg) or placebo twice daily, respectively. On day 8, heart and blood samples were collected. The density of NET and 1-AR in heart homogenate; NE in plasma and heart and inflammatory mediators (nitrite and interferon-gamma) in serum were determined. RESULTS: Inflammation was associated with a significant reduction in both beta1-AR and NET density with a positive correlation between the two proteins (r=0.978, p<0.0001). The down-regulating effect of inflammation was not reversed by pravastatin. Inflammation had no significant effect on the plasma or heart NE concentration. CONCLUSION: The close relations of NET and beta1-AR implicates altered sympathetic innervation and/or local NE handling in pharmacotherapeutic desensitization observed in arthritis.
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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) | 0.002 | 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".