Evidence map›Paper›PMID 25960133›Full record

ArticleActa pharmacologica Sinica2015

Deciphering the therapeutic mechanisms of Xiao-Ke-An in treatment of type 2 diabetes in mice by a Fangjiomics approach.

Zhen-zhong Yang, Wei Liu, Feng Zhang, Zheng Li, Yi-yu Cheng

Abstract read
In one paragraph

Article in Acta pharmacologica Sinica, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Investigating chemical features ofJournal of ginseng research · 2018
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. 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

5 authors.

Zhen-zhong YangPharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Wei LiuPharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Feng ZhangPharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Zheng LiState Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China.
Yi-yu ChengPharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimXiao-Ke-An (XKA) is a traditional Chinese medicine (TCM) formula for the treatment of type 2 diabetes (T2D), and the effective ingredients and their targets as well as the mechanisms of XKA remain to be elucidated. In this study we investigated the therapeutic mechanisms of XKA in the treatment of T2D in mice using a Fangjiomics approach.

methodsKKAy mice feeding on a high-fat diet were used as models of T2D, and were orally treated with XKA (0.75 or 1.5 g · kg(-1) · d(-1)) for 32 d. Microarray mRNA expression data were obtained from the livers of the mice. Differentially expressed genes (DEGs) were identified by reverse rate analysis and ANOVA analysis. The compounds in XKA were identified by LC-MS analysis or collected from TCM databases. The relationships between the compounds and targets were established by combining the DEGs with information derived from mining literature or herb target databases. Relevant pathways were identified through a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using WebGestalt.

resultsThe compound-target-pathway network based on compounds identified by LC-MS analysis (NCA) included 20 constituent compounds, 46 targets and 36 T2D-related pathways, whereas the compound-target-pathway network based on compounds collected from databases (NCD) consisted of 40 compounds, 68 targets and 21 pathways. In the treatment of T2D, XKA might act mainly by improving carbohydrate and lipid metabolism, as well as ameliorating insulin resistance, inflammation and diabetic vascular complications.

conclusionThe network-based approach reveals complex therapeutic mechanisms of XKA in the treatment of T2D in mice that involve numerous compounds, targets, and signaling pathways.

Indexed as

Administration, OralAnimalsBlood GlucoseChromatography, LiquidCluster AnalysisDatabases, GeneticData MiningDiabetes Mellitus, Type 2Diet, High-FatDisease Models, AnimalDrugs, Chinese HerbalGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksGenomicsHypoglycemic AgentsBlood GlucoseDrugs, Chinese HerbalHypoglycemic AgentsRNA, MessengerXiao-Ke-An

Identifiers

PMID25960133
PMCPMC4594179

What OpenQuestion holds

Textmetadata
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.