Evidence map›Paper›PMID 31096578›Full record

ArticleMolecules (Basel, Switzerland)2019

Dietary Supplementation of Vine Tea Ameliorates Glucose and Lipid Metabolic Disorder via Akt Signaling Pathway in Diabetic Rats.

Jiamei Xiang, Qiuyue Lv, Fan Yi, Yanjun Song, Liang Le, Baoping Jiang, Lijia Xu, Peigen Xiao

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2019. 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
3.4field-weighted citation impact, top 7% 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

11 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. China Medicinal Plants of theMolecules (Basel, Switzerland) · 2023
    Review
  7. Article
  8. Article
  9. Flavonoids in Ampelopsis grossedentata as covalent inhibitors of SARS-CoV-2 3CLInternational journal of biological macromolecules · 2021
    Article
  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

8 authors at 2 institutions in 1 country.

Jiamei XiangInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. xiangjiamei2014@163.com.
Qiuyue LvInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. lqiuyue@126.com.
Fan YiKey Laboratory of Cosmetic, China National Light Industry, Beijing Technology and Business University, Beijing 100048, China. fantasyee@btbu.edu.cn.ORCID 0000-0002-7476-616X
Yanjun SongInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. eryue1024@163.com.
Liang LeInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. llfxcy@163.com.
Baoping JiangInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. bpjiang@implad.ac.cn.ORCID 0000-0003-1035-5078
Lijia XuInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. ljxu@implad.ac.cn.
Peigen XiaoInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. xiaopg@public.bta.net.cn.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNBeijing Technology and Business University · CN

Funding

Beijing Natural Science Foundation 7182112China Postdoctoral Science Foundation 2017M611127National Natural Science Foundation of China Grant 81703223, 81573576Open Research Fund Program of Key Laboratory of Cosmetics (Beijing Technology and Business University), China National Light Industry KLC-2018-YB4
6 · The paper itself

Abstract

A traditional Chinese tea with many pharmacological effects, vine tea (VT) is considered a potential dietary supplement to improve type 2 diabetes (T2D). To investigate the effect and mechanism of VT on glucose and lipid metabolic disorders in T2D rats, Wistar rats fed a normal diet served as the normal control, while rats fed a high-fat diet combined with low-dose streptozotocin (STZ)-induced T2D were divided into three groups: The model group (MOD); the positive control group (MET, metformin at 200 mg/kg/d); and the VT-treated group (VT500, allowed to freely drink 500 mg/L VT). After four weeks of intervention, biochemical metrics indicated that VT significantly ameliorated hyperglycemia, hyperlipidemia and hyperinsulinemia in T2D rats. Metabolomics research indicated that VT regulated the levels of metabolites closely related to glucose and lipid metabolism and promoted glycogen synthesis. Furthermore, VT had a significant influence on the expression of key genes involved in the Akt signaling pathway, inhibited gluconeogenesis through the Akt/Foxo1/Pck2 signaling pathway, and reduced fatty acid synthesis via the SREBP1c/Fasn signaling pathways. In conclusion, VT has great potential as a dietary supplement to ameliorate glucose and lipid metabolic disorders via the Akt signaling pathway in T2D rats.

Indexed as

Dietary SupplementsAnimalsBiomarkersCarbohydrate MetabolismDiabetes Mellitus, ExperimentalDiabetes Mellitus, Type 2Disease Models, AnimalGlucoseLipid MetabolismLiverMetabolomeMetabolomicsProto-Oncogene Proteins c-aktRatsSignal TransductionTeaBiomarkersGlucoseProto-Oncogene Proteins c-aktTeaAkt signaling pathwayglucose and lipid metabolic disordersmetabolomicstype 2 diabetesvine tea

Identifiers

PMID31096578
PMCPMC6571802
OpenAlexW2945951813

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.