Evidence map›Paper›PMID 35681388›Full record

ArticleFoods (Basel, Switzerland)2022

Large Yellow Tea Extract Ameliorates Metabolic Syndrome by Suppressing Lipogenesis through SIRT6/SREBP1 Pathway and Modulating Microbiota in Leptin Receptor Knockout Rats.

Guohuo Wu, Xiaoyun Sun, Huijun Cheng, Shan Xu, Daxiang Li, Zhongwen Xie

Open access · goldAbstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
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  10. Frontiers in microbiology · 2022
    Article
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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

6 authors at 1 institution in 1 country.

Guohuo WuState Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Sciences and Technology, Anhui Agricultural University, Hefei 230036, China.ORCID 0000-0001-8619-7657
Xiaoyun SunState Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Sciences and Technology, Anhui Agricultural University, Hefei 230036, China.
Huijun ChengCollege of Life Sciences, Anhui Agricultural University, Hefei 230036, China.
Shan XuState Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Sciences and Technology, Anhui Agricultural University, Hefei 230036, China.
Daxiang LiState Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Sciences and Technology, Anhui Agricultural University, Hefei 230036, China.
Zhongwen XieState Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food Sciences and Technology, Anhui Agricultural University, Hefei 230036, China.ORCID 0000-0002-3080-4881
Anhui Agricultural University · CN

Funding

China Agriculture Research System of MOF and MARA CARS-19National Natural Science Foundation of China U19A2034University Synergy Innovation Program of Anhui Province GXXT-2019-49
6 · The paper itself

Abstract

Metabolic syndrome is a chronic metabolic disorder that has turned into a severe health problem worldwide. A previous study reported that large yellow tea exhibited better anti-diabetic and lipid-lowering effects than green tea. Nevertheless, the potential mechanisms are not yet understood. In this study, we examined the prevention effects and mechanisms of large yellow tea water extract (LWE) on metabolic syndrome using leptin receptor knockout (

Indexed as

gut microbiotahyperlipidemialarge yellow teaLepr−/− ratsSIRT6/SREBP1 pathway

Identifiers

PMID35681388
PMCPMC9180543
OpenAlexW4282032625

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.