Evidence map›Paper›PMID 38893474›Full record

ArticleMolecules (Basel, Switzerland)2024

Development of a Non-Target Screening and Quantitative Analysis Strategy Based on UPLC-Q-TOF/MS and UPLC-QQQ/MS to Improve the Quality Control of Wuling Capsule.

Xiao-Feng Huang, Ying Xue, Jian Liang, Li Yong

Abstract read
In one paragraph

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

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0cells of the map it votes in
0citing papers in PubMed
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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

4 authors.

Xiao-Feng HuangChengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China.
Ying XueSichuan Center for Disease Control and Prevention, Chengdu 610041, China.
Jian LiangChengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China.
Li YongSichuan Center for Disease Control and Prevention, Chengdu 610041, China.

Funding

Sichuan Science and Technology Program 2022YFS0011
6 · The paper itself

Abstract

Herbal medicine has been widely valued because of its remarkable efficacy and minimal side effects. The quantitative analysis of herbal medicines is essential to ensure their safety and efficacy. The simultaneous detection of multiple quality markers (Q-markers) has emerged as an important approach and trend in herbal medicine quality control. In recent years, non-targeted screening has become an effective strategy for the discovery and identification of unknown compounds. This study developed a non-targeted screening and quantitative analysis strategy to discover, identify and quantify the multiple components that truly represent the efficacy of Wuling capsule. Within this strategy, 18 types of flavonoids were tentatively discovered and identified from Wuling capsule by analyzing mass cleavage pathways, the precise molecular weights of compounds, and comparing the data with a database. Ten types of flavonoids were determined after the comparison of the standards. Additionally, following the evaluation of the regression equation, linear range, limit of detection (LOD), limit of quantitation (LOQ), precision, repeatability, and recovery of the proposed quantitative method, six flavonoids were quantified. This method successfully screened, identified, and quantified the potential active components in Wuling capsule, providing insights for improving the quality control standards in other herbal medicines.

Indexed as

Drugs, Chinese HerbalFlavonoidsQuality ControlCapsulesChromatography, High Pressure LiquidLimit of DetectionReproducibility of ResultsTandem Mass SpectrometryCapsulesDrugs, Chinese HerbalFlavonoidsflavonoidsnon-target screeningquality controlquantitative analysisUPLC-QQQ/MSUPLC-Q-TOF/MS

Identifiers

PMID38893474
PMCPMC11173814

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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.