Evidence map›Paper›PMID 32498849›Full record

ArticleTalanta2020

A microfluidic platform integrating paper adsorption-based sample clean-up and voltage-assisted liquid desorption electrospray ionization mass spectrometry for biological sample analysis.

Xiangtang Li, Xun Liao, Yi-Ming Liu

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Talanta, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Xiangtang LiDepartment of Chemistry and Biochemistry, Jackson State University, 1400 Lynch St., Jackson, MS, 39217, USA.
Xun LiaoChengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.
Yi-Ming LiuDepartment of Chemistry and Biochemistry, Jackson State University, 1400 Lynch St., Jackson, MS, 39217, USA. Electronic address: yiming.liu@jsums.edu.
Jackson State University · USChengdu Institute of Biology · CN

Funding

Microfluidic mass spectrometry based fast chemical characterization of exosomesSC1GM089557 · NIGMS · JACKSON STATE UNIVERSITY · PI LIU, YIMING · 2010 to 2018
$1.4M
NIGMS NIH HHS SC1 GM089557
6 · The paper itself

Abstract

Clinical application of direct sampling electrospray ionization mass spectrometry (ESI-MS) remains limited due to problems associated with very "dirty" sample matrices. Herein we report on a microfluidic platform that allows direct mass spectrometric analysis of serum samples of microliter sizes. The platform integrates in-line paper adsorption-based sample clean-up and voltage assisted liquid desorption ESI-MS/MS (VAL DESI-MS/MS) to detect multiple targeted compounds of clinical interest. Adenosine monophosphate (AMP), adenosine diphosphate (ADP), and adenosine triphosphate (ATP) were selected as model analytes. Simultaneous quantification of these compounds in human serum samples was demonstrated. For all the three compounds, linear calibration curves were obtained in a concentration range from 0.20 to 20.0 μmol/L with r

Indexed as

Electrochemical TechniquesLab-On-A-Chip DevicesPaperAdenosine DiphosphateAdenosine MonophosphateAdenosine TriphosphateAdsorptionHumansSpectrometry, Mass, Electrospray IonizationAdenosine DiphosphateAdenosine MonophosphateAdenosine TriphosphateDirect analysisIn-line sample clean-upLiquid desorption electrospray ionizationMass spectrometryMicrofluidic chipsSerum

Identifiers

PMID32498849
PMCPMC7275932
OpenAlexW3023069430

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.