A Rapid and Sensitive HPLC Method for Quantitation of Paclitaxel in Biological Samples using Liquid-Liquid Extraction and UV Detection: Application to Pharmacokinetics and Tissues Distribution Study of Paclitaxel Loaded Targeted Polymeric Micelles in.....
Bibliographic record
Abstract
A simple, rapid, and sensitive reversed-phase HPLC method was developed and validated for determination of paclitaxel (PTX) in plasma, various organs and tumor tissues of tumor-bearing mice. Tissue specimens of liver, kidneys, spleen, lungs, heart and tumor were separately homogenized in normal saline. Plasma or tissue homogenate (250 µl) containing PTX and internal standard (diazepam) were extracted by diethyl ether (6 ml). The separation was achieved on a µ-Bondapak C18 HPLC column using sodium acetate buffer solution (0.01 M)/acetonitrile (58/42 v/v) at pH 5 ± 0.1 and flow rate of 1.9 mL/min. The effluent was monitored at 227 nm and column temperature was adjusted at 58ºC. The internal standard and PTX were eluted at 4.2 and 5.2 min, respectively and no interfering peaks were observed. Calibration curves were linear over the concentration range of 0.25-10 µg/ml of PTX in plasma and 0.3-20 µg/ml PTX in tissue homogenates with acceptable precision and accuracy (<15%). The mean recoveries of the drug after plasma extraction was 87.4% ± 3.6 while those of tissue homogenates ranged from 62.1± 4.5 to 75.5± 3.2 depending on the type of tissues studied. PTX was stable in samples with no evidence of degradation during 3 freeze-thaw cycles and 3 months storage at -70 °C. The developed HPLC method was applied to quantify PTX in the mouse plasma and tissues after intravenous administration of 10 mg equivalent PTX/Kg dose of PTX-loaded tocopherol succinate-chitosan-polyethylene glycol-folate (TS-CS-PEG-FA) micelles formulation or Anzatax® (Cremophor® EL- based formulation of PTX) to female Balb/c 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".