ArticleThe Analyst2008
Highly selective and sensitive assay for paclitaxel accumulation by tumor cells based on selective solid phase extraction and micro-flow liquid chromatography coupled to mass spectrometry.
Article in The Analyst, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- Paclitaxel-Loaded Silk Fibroin Nanoparticles: Method Validation by UHPLC-MS/MS to Assess an Exogenous Approach to Load Cytotoxic Drugs.Pharmaceutics · 2019Article
- Extraction and RP-HPLC determination of taxol in rat plasma, cell culture and quality control samples.Journal of biomedical research · 2013Article
- A rapid, reproducible, on-the-fly orthogonal array optimization method for targeted protein quantification by LC/MS and its application for accurate and sensitive quantification of carbonyl reductases in human liver.Analytical chemistry · 2010Article
- Ultra-sensitive quantification of paclitaxel using selective solid-phase extraction in conjunction with reversed-phase capillary liquid chromatography/tandem mass spectrometry.Journal of chromatography. A · 2008Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The taxanes are among the most important cancer chemotherapy drugs approved for clinical use in the last two decades. Paclitaxel is used as first-line therapy for a variety of cancers, and numerous drug delivery approaches are under investigation to enhance its selectivity and effectiveness against tumors. One strategy is to produce sustained, low drug levels within the tumor to enhance apoptosis and inhibit angiogenesis. The interest in altering drug concentration/time exposure profiles to improve therapeutic outcomes creates the necessity to quantify low concentrations of paclitaxel in cells or tissues. Here, a selective solid phase extraction (SPE) method, coupled with a capillary liquid chromatography-tandem mass spectrometry (microLC-MS/MS) method, was developed to quantify low, therapeutically relevant concentrations of paclitaxel that could not be analyzed using conventional LC-MS/MS. Under optimized SPE wash and elution conditions, paclitaxel was selectively extracted from biological samples, and most matrix components were removed. A 150 x 0.5 mm ID ODS capillary column was used for microLC separation and the flow rate was 12 microL min(-1). Sample extracts were focused at the front of the microLC column and then eluted with a gradient. The lower limits of detection and quantification were 5 and 20 pg mL(-1), respectively, permitting quantification of paclitaxel in small tissue samples or in cultured cells exposed to low drug concentrations. The quantitative linear range was 20-20 000 pg mL(-1). The ability to quantify these low concentrations of paclitaxel provides an important tool to study the concentration-dependent pharmacological effects of this important drug.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.