O-GlcNAcylation levels remain stable regardless of the anaesthesia in healthy rats
Bibliographic record
Abstract
Anaesthetics are used daily in human and veterinary medicine as well as in scientific research. Anaesthetics have an impact on cell homeostasis especially through modulation of protein post-translational modifications. O-GlcNAcylation, a ubiquitous post-translational modification, plays a role in many biological processes. The aims of this study were to evaluate whether (1) anaesthesia influences O-GlcNAcylation and (2) its stimulation affects physiological parameters. Male Wistar rats (n = 38) were anaesthetized with ketamine-xylazine or isoflurane. They randomly received either an intravenous injection of Ringer's lactate or NButGT (10mg/kg) in order to increase O-GlcNAcylation levels. One hour after induction of anaesthesia, haemodynamic parameters and plasmatic markers were evaluated. Heart, brain and lungs were harvested and O-GlcNAcylation levels and O-GlcNAc-related enzymes were evaluated by western blot. Cardiac and pulmonary O-GlcNAcylation levels and cardiac, cerebral and pulmonary O-GlcNAc associated enzyme expression were not impacted with anaesthesia. Compared with ketamine-xylazine, isoflurane had a lower impact on blood pressure, heart rate and glycaemia. Pharmacological stimulation of O-GlcNAcylation by NButGT did not affect the physiological parameters. This study offers unprecedented insights into the regulation of O-GlcNAcylation and O-GlcNAc related enzymes during anaesthesia. Pharmacological stimulation of O-GlcNAcylation over a 1-h period did not disrupt the physiological balance in healthy anaesthetized rats.
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) | 0.001 | 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 | 0.001 |
| 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".