ArticlePurinergic signalling2019
Integrated use of LC/MS/MS and LC/Q-TOF/MS targeted metabolomics with automated label-free microscopy for quantification of purine metabolites in cultured mammalian cells.
Article in Purinergic signalling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Metabolomics-guided machine learning reveals diagnostic and mechanistic biomarkers in CHB with MASLD.PloS one · 2026Article
- Alteration of Metabolic Profile in Patients with Narcolepsy Type 1.Metabolites · 2025Article
- Article
- Liver metabolomic characteristics in three different rat models of deficiency based on ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2023Article
- Identification of disordered metabolic networks in postpartum dairy cows with left displacement of the abomasum through integrated metabolomics and pathway analyses.The Journal of veterinary medical science · 2020Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Purine metabolites have been implicated as clinically relevant biomarkers of worsening or improving Parkinson's disease (PD) progression. However, the identification of purine molecules as biomarkers in PD has largely been determined using non-targeted metabolomics analysis. The primary goal of this study was to develop an economical targeted metabolomics approach for the routine detection of purine molecules in biological samples. Specifically, this project utilized LC/MS/MS and LC/QTOF/MS to accurately quantify levels of six purine molecules in samples from cultured N2a murine neuroblastoma cells. The targeted metabolomics workflow was integrated with automated label-free digital microscopy, which enabled normalization of purine concentration per unit cell in the absence of fluorescent dyes. The established method offered significantly enhanced selectivity compared to previously published procedures. In addition, this study demonstrates that a simple, quantitative targeted metabolomics approach can be developed to identify and quantify purine metabolites in biological samples. We envision that this method could be broadly applicable to quantification of purine metabolites from other complex biological samples, such as cerebrospinal fluid or blood.
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Registered trials
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