Evidence map›Paper›PMID 38920575›Full record

ArticleBiosensors2024

Rapid Separation and Detection of Drugs in Complex Biological Matrix Using TD-CDI Mass Spectrometer.

Wenyan Shi, Zi Ye, Qin Yang, Jianhua Zhou, Jiasi Wang, Xinming Huo

Abstract read
In one paragraph

Article in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Wenyan ShiSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0001-6610-5751
Zi YeSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
Qin YangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Jianhua ZhouSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0001-9895-8679
Jiasi WangSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
Xinming HuoSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0002-1431-7506

Funding

China Postdoctoral Science Foundation 2023M732007National Natural Science Foundation of China 22374164National Natural Science Foundation of China 52301399the Foundation for Youth Innovative Talents in Higher Education of Guangdong 2023KQNCX154the Young Elite Scientists Sponsorship Program by CAST 2023QNRC001
6 · The paper itself

Abstract

The drug detection technology plays a pivotal role in the domains of pharmaceutical regulation and law enforcement. In this study, we introduce a method that combines thermal desorption corona discharge ionization (TD-CDI) with mass spectrometry for efficient drug detection. The TD-CDI module, characterized by its compact and simple design, enables the separation of analytes within seconds and real-time presentation of one or two analyte peaks on the mass spectrum most of the time, which reduces matrix interference and improves detection performance. Through experimental investigation, we studied the characteristics of TD-CDI for analyte separation and detection, even with the same mass number, and optimized the TD-CDI approach. TD-CDI-MS was employed for the rapid detection of drugs in various traditional medicine, food products, and human samples. Additionally, by utilizing TD-CDI for segmented hair direct analysis, it becomes possible to trace the drug usage cycle of individuals. This underscores the feasibility of the proposed analytical method within the realm of drug detection.

Indexed as

Mass SpectrometryHairHumansPharmaceutical PreparationsPharmaceutical Preparationsanalyte separationcorona discharge ionizationdrug analysismass spectrometrythermal desorption

Identifiers

PMID38920575
PMCPMC11202275

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.