Evidence map›Paper›PMID 32489401›Full record

ArticleChinese medicine2020

Transcriptomics- and metabolomics-based integration analyses revealed the potential pharmacological effects and functional pattern of in vivo Radix Paeoniae Alba administration.

Sining Wang, Huihua Chen, Yufan Zheng, Zhenyu Li, Baiping Cui, Pei Zhao, Jiali Zheng, Rong Lu, Ning Sun

Open access · goldAbstract read
In one paragraph

Article in Chinese medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
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

9 authors at 3 institutions in 1 country.

Sining Wang *Department of Pathology, School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, 1200 CaiLun Ave, Pudong, 201203 Shanghai China.
Huihua Chen *Department of Pathology, School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, 1200 CaiLun Ave, Pudong, 201203 Shanghai China.
Yufan Zheng *Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, 130 DongAn Ave, Xuhui, 200032 Shanghai China.
Zhenyu LiCollege of Information and Computer Engineering, Northeast Forestry University, Harbin, China.
Baiping CuiDepartment of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, 130 DongAn Ave, Xuhui, 200032 Shanghai China.
Pei ZhaoPublic Laboratory Platform, School of Basic Medical Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Jiali ZhengDepartment of Pathology, School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, 1200 CaiLun Ave, Pudong, 201203 Shanghai China.
Rong LuDepartment of Pathology, School of Basic Medical Sciences, Shanghai University of Traditional Chinese Medicine, 1200 CaiLun Ave, Pudong, 201203 Shanghai China.
Ning SunDepartment of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, 130 DongAn Ave, Xuhui, 200032 Shanghai China.
Shanghai University of Traditional Chinese Medicine · CNFudan University · CNNortheast Forestry University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRadix Paeoniae Alba (RPA) and other natural medicines have remarkable curative effects and are widely used in traditional Chinese Medicine (TCM). However, due to their multi-component and multi-target characteristics, it is difficult to study the detailed pharmacological mechanisms for those natural medicines in vivo. Therefore, their real effects on organisms is still uncertain.

methodsRPA was selected as research object, the present study was designed to study the complex mechanisms of RPA in vivo by integrating and interpreting the transcriptomic based RNA-seq and metabolomic based NMR spectrum after RPA administration in mice. A variety of dimension-reduction algorithms and classifier models were applied to the processing of high-throughput data.

resultsAmong serum metabolites, the contents of PC and glucose were significantly increased, while the contents of various amino acids, lipids and their metabolites were significantly decreased in mice after RPA administration. Based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, differential analysis showed that the liver was the site where RPA exerted a significant effect, which confirmed the rationality of "meridian tropism" in the theory in TCM. In addition, RPA played a role in lipid metabolism by regulating genes encoding enzymes of the glycerolipid metabolism pathway, such as 1-acyl-sn-glycerol-3-phosphate acyltransferase (Agpat), phosphatidate phosphatase (Lpin), phospholipid phosphatase (Plpp) and endothelial lipase (Lipg). We also found that RPA regulates several substance addiction pathways in the brain, such as the cocaine addiction pathway, and the related targets were predicted based on the sequencing data from pathological model in the GEO database. The overall effective pattern of RPA was intuitively presented with a multidimensional radar map through a self-designed model which found that liver and brain were mainly regulated by RPA compared with the traditional meridian tropism theory.

conclusionsOverall this study expanded the potential application of RPA and provided possible targets and directions for further mechanism study, meanwhile, it also established a multi-dimensional evaluation model to represent the overall effective pattern of TCM for the first time. In the future, such study based on the high-throughput data sets can be used to interpret the theory of TCM and to provide a valuable research model and clinical medication reference for the TCM researchers and doctors.

Indexed as

BioinformaticsMetabolomicsRadix Paeoniae AlbaTraditional Chinese medicineTranscriptomics

Identifiers

PMID32489401
PMCPMC7245909
OpenAlexW3031069693

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.