Study of tanshinone IIA tissue distribution in rat by liquid chromatography‐tandem mass spectrometry method
Bibliographic record
Abstract
A liquid chromatography/tandem mass spectrometry (LC/MS/MS) method was developed and validated for determining tanshinone IIA in rat tissues. After a single step liquid-liquid extraction with diethyl ether, tanshinone IIA and loratadine (internal standard) was subjected to LC/MS/MS analysis using positive electro-spray ionization under selected reaction monitoring mode. Chromatographic separation of tanshinone IIA and loratadine was achieved on a Hypersil BDS C(18) column (i.d. 2.1 x 50 mm, 5 microm) with a mobile phase consisting of methanol-1% formic acid (90:10, v/v) at a flow rate of 300 microL/min. The intra-day and inter-day precision of the method were less than 10.2 and 12.4%, respectively. The intra-day and inter-day accuracies ranged from 99.7 to 109.7%. The lowest limit of quantification for tanshinone IIA was 1 ng/mL. The method was applied to a tanshinone IIA tissue distribution study after an oral dose of 60 mg/kg to rats. Tanshinone IIA tissue concentrations decreased in the order of stomach > small intestine > lung > liver > fat > muscle > kidneys > spleen > heart > plasma > brain > testes. Tanshinone IIA still could be detected in most of the tissues at 20 h post-dosing. These results indicate that the LC/MS/MS method was rapid and sensitive to quantify tanshinone IIA in different rat tissues.
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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) | 0.001 | 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 | 0.000 |
| 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".