Evidence map›Paper›PMID 33324200›Full record

ArticleFrontiers in pharmacology2020

Species Quantification in Complex Herbal Formulas-Vector Control Quantitative Analysis as a New Method.

Bo Zhao, Chao Xiong, Jingjian Li, Deng Zhang, Yancai Shi, Wei Sun, Xiaoqun Duan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 20% 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

8 citing papers in PubMed, 12 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 4 institutions in 1 country.

Bo ZhaoCollege of Pharmacy, Guilin Medical University, Guilin, China.
Chao XiongInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Jingjian LiCollege of Pharmacy, Guilin Medical University, Guilin, China.
Deng ZhangGuangxi Institute of Botany, The Chinese Academy of Sciences, Guilin, China.
Yancai ShiGuangxi Institute of Botany, The Chinese Academy of Sciences, Guilin, China.
Wei SunInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Xiaoqun DuanCollege of Pharmacy, Guilin Medical University, Guilin, China.
Guilin Medical University · CNChinese Academy of Sciences · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNWuhan Polytechnic University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Product mislabeling and/or species fraud in Traditional Chinese Medicine (TCM) not only decrease TCM quality, but also pose a potential health issue to the end user. Up to now, methods to control TCM quality have been developed to detect specific metabolites or identify the original species. However, species quantification in complex herbal formulas is rarely concerned. Here, we reported a simple Vector Control Quantitative Analysis (VCQA) method for flexible and accurate multiplex species quantification in traditional Chinese herbal formulas. We developed PCR-based strategy to quickly generate the integrated DNA fragments from multiple targeted species, which can be assembled into the quantitative vector in one round of cloning by Golden Gate ligation and Gateway recombination technique. With this method, we recruited the nuclear ribosomal DNA Internal Transcribed Spacer (ITS) region for the quantification of

Indexed as

complex herbal formulasinternal transcribed spacer regionlimit of quantificationspecies quantificationtraditional Chinese medicine quality controlvector control quantitative analysis

Identifiers

PMID33324200
PMCPMC7725679
OpenAlexW3110445906

What OpenQuestion holds

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LicenceCC BY
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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.