Analysis of tramadol and its metabolites in rat skeletal tissues following acute and repeated dose patterns using high performance liquid chromatography tandem mass spectrometry
Bibliographic record
Abstract
The use of skeletal elements for the viable analysis of drugs of abuse has seen increased prevalence in the past 10 years. Advancements in the analytical methods used, including solid phase extraction and mass spectrometry, have allowed for increased sensitivity and selectivity. Previous studies have focused on the influence of dose-death interval, microclimate, differential patterns of exposure, and the influence of body position. In this work, the opioid analgesic tramadol was investigated for its pharmacological behaviour when administered as part of three dosage patterns to male Sprague Dawley rats. The three exposure patterns consisted of an acute low (n = 4, 1 doses, 30 mg/kg) group, a repeated high survived group (n = 5, 3 doses, 30 mg/kg) and a repeated high overdosed group (n = 11, 3 doses, 30 mg/kg). Drug free rats (n = 4) served as negative controls. Following euthanasia by CO2 asphyxiation, animals were decomposed to skeleton outdoors over the summer of 2019 in Sudbury, Ontario. Bones were sorted by animal and skeletal element (skull, vertebrae, ribs, pelvis, femur, tibia/fibula), then washed and ground to powder before undergoing dynamic methanolic extraction. Semi-quantitative analysis of tramadol and four of its metabolites – O-desmethyltramadol, N-desmethyltramadol, N,Odidesmethyltramadol and tramadol N-oxide – was conducted using high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) in positive ion mode. Analyte levels were expressed as a mass-normalized response ratio (RR/m) in order to account for the exact mass of bone used. Method validation for the analysis of tramadol and its metabolites was investigated in accordance with the Scientific Working Group of Toxicologists (SWGTOX) standards of practice, with all criteria except for dilution integrity successfully met at a limit of detection and limit of quantitation of 1 ng/mL. The effect of exposure pattern on analyte level and analyte level ratio was assessed using the Kruskal-Wallis test for significant differences (P < 0.05). A total of 315 pairwise comparisons were performed to assess significant differences, with the ratio of tramadol to N-desmethyltramadol determined to be the metric most commonly able to identify these differences in 91% of tests. Additionally, the effect of skeletal element on analyte level and analyte level ratio was also assessed, with a total of 675 pairwise comparisons. Skeletal element was determined to be a significant factor in all cases. This data suggests that both skeletal element and dose pattern are important measures to evaluate with respect to the analysis of drugs of abuse in bone tissues. Furthermore, different metrics, including analyte level and analyte level ratios, may be useful for discriminating between these different dosing patterns.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
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".