Evidence map›Paper›PMID 40727295›Full record

ArticleRSC advances2025

Packed-nanofiber solid phase extraction for daidzein, genistein, glycitein in human urine and their simultaneous detection.

Yuqi Dai, Lanmei Zhang, Yuemeng Wang, Anni Fu, Lanling Chu, Lei Zhao

Abstract read
In one paragraph

Article in RSC advances, 2025. 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
–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

1 citing paper in PubMed.

  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

6 authors.

Yuqi DaiNational Key Laboratory for the Development and Utilization of Forest Food Resources, Nanjing Forestry University Nanjing 210037 China chu_lanling@126.com.
Lanmei ZhangNational Key Laboratory for the Development and Utilization of Forest Food Resources, Nanjing Forestry University Nanjing 210037 China chu_lanling@126.com.
Yuemeng WangYantai Key Laboratory of Special Medical Food (Preparatory), School of Food and Biological Engineering, Yantai Institute of Technology Yantai 264005 China zhaolei@yitsd.edu.cn.
Anni FuYantai Key Laboratory of Special Medical Food (Preparatory), School of Food and Biological Engineering, Yantai Institute of Technology Yantai 264005 China zhaolei@yitsd.edu.cn.
Lanling ChuNational Key Laboratory for the Development and Utilization of Forest Food Resources, Nanjing Forestry University Nanjing 210037 China chu_lanling@126.com.ORCID https://orcid.org/0000-0001-5088-2994
Lei ZhaoYantai Key Laboratory of Special Medical Food (Preparatory), School of Food and Biological Engineering, Yantai Institute of Technology Yantai 264005 China zhaolei@yitsd.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, an integrated method based on the novel packed-fiber solid-phase extraction (PFSPE) combined with high-performance liquid chromatography-ultraviolet detector (HPLC-UV) detection system was proposed for the detection of daidzein, genistein and glycitein in human urine. To efficiently adsorb three kinds of isoflavones in biological fluid, polystyrene-based nanofibers were prepared and used as adsorbents in customized solid phase extraction devices. The composition of the nanofibers, the amount of different salt ions added, the type of eluent, and the interaction of eluent volume, the amounts of nanofibers added, and the extraction time were analyzed to find the optimal adsorption conditions, respectively. The method of optimal extraction conditions for the analysis of three soy isoflavones exhibited low limits of detection (LOD) and limits of quantitation (LOQ) of 1.68-2.74 μg L

Identifiers

PMID40727295
PMCPMC12291530

What OpenQuestion holds

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LicenceCC BY-NC
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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.