Hemodynamic and behavioral differences after administration of meloxicam, buprenorphine, or tramadol as analgesics for telemeter implantation in mice.
Bibliographic record
Abstract
Cannulation of the common carotid artery for chronic, continuous radiotelemetric recording of aortic hemodynamic properties in mice is a highly invasive recovery surgery. Radiotelemetric recording, by its continuous nature, gives the most accurate measurements of hemodynamic variables in experimental animals, and is widely used in the study of cardiovascular diseases including hypertension. The American Heart Association has recommended data acquisition by radiotelemetric recording but did not provide guidelines regarding postoperative analgesic support. We assessed hemodynamic parameters, locomotor activity, food intake, and weight loss in radiotransmitter-implanted CD1 female mice receiving analgesic support during the first 48 h after surgery. The efficacy of analgesic support from the NSAID meloxicam was compared with that of the widely used opioid agonist buprenorphine and the related compound, tramadol. Meloxicam-treated mice recovered lost body weight more rapidly than did tramadol-or buprenorphine-treated mice. Furthermore, meloxicam-treated mice maintained circadian rhythm after surgery and had tighter regulation of mean arterial pressure than did tramadol- or buprenorphine-treated mice. Meloxicam was also superior with regard to food intake, locomotor activity, and limiting variance in hemodynamic parameters. This study indicates that when compared with buprenorphine and tramadol, meloxicam should be the postoperative analgesic of choice for radiotelemeter implantation in mice.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".