Evidence map›Paper›PMID 36950525›Full record

ArticleFrontiers in molecular biosciences2023

Development of the thin film solid phase microextraction (TF-SPME) method for metabolomics profiling of steroidal hormones from urine samples using LC-QTOF/MS.

Wiktoria Struck-Lewicka, Beata Karpińska, Wojciech Rodzaj, Antoni Nasal, Bartosz Wielgomas, Michał Jan Markuszewski, Danuta Siluk

Open access · goldFull text read
In one paragraph

Article in Frontiers in molecular biosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

4 citing papers in PubMed, 18 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Wiktoria Struck-LewickaDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Gdańsk, Poland.
Beata KarpińskaDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Gdańsk, Poland.
Wojciech RodzajDepartment of Toxicology, Medical University of Gdańsk, Gdańsk, Poland.
Antoni NasalDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Gdańsk, Poland.
Bartosz WielgomasDepartment of Toxicology, Medical University of Gdańsk, Gdańsk, Poland.
Michał Jan MarkuszewskiDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Gdańsk, Poland.
Danuta SilukDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Gdańsk, Poland.
Gdańsk Medical University · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the present study, the development and optimization of a thin film solid phase microextraction method (TF-SPME) was conducted for metabolomics profiling of eight steroid compounds (androsterone, dihydrotestosterone, dihydroepiandrosterone, estradiol, hydroxyprogesterone, pregnenolone, progesterone and testosterone) from urine samples. For optimization of extraction method, two extraction sorbents (PAN-C18 and PS-DVB) were used as they are known to be effective for isolation of low-polarity analytes. The stages of sample extraction and analyte desorption were considered as the most crucial steps in the process. Regarding the selection of the most suitable desorption solution, six different mixtures were analyzed. As a result, the mixture of ACN: MeOH (1:1,

Indexed as

endogenous steroid hormonesLC-QTOF/MSthin-film solid phase microextraction TF-SPMEuntargeted metabolomics profilingurine

Identifiers

PMID36950525
PMCPMC10025495
OpenAlexW4323316474

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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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.