Evidence map›Paper›PMID 37529260›Full record

ArticleNutrition research and practice2023

Ning Wang, Linman Li, Puyu Zhang, Muhammad Aamer Mehmood, Chaohua Lan, Tian Gan, Zaixin Li, Zhi Zhang, Kewei Xu, Shan Mo and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nutrition research and practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Ning WangCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-2236-6391
Linman LiCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-5002-1331
Puyu ZhangCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-6515-4575
Muhammad Aamer MehmoodCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0001-9250-7260
Chaohua LanCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0001-6989-7715
Tian GanYa'an Youyi Tea Co., Ltd, Ya'an 625000, China.ORCID https://orcid.org/0000-0002-5366-6717
Zaixin LiCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-8391-622X
Zhi ZhangCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-6548-6465
Kewei XuCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0003-4121-2379
Shan MoCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-7189-0923
Gang XiaComprehensive Agricultural Service Center of Dachuan, Lushan, Ya'an 625000, China.ORCID https://orcid.org/0000-0001-5438-9179
Tao WuSchool of Food and Biological Engineering, Xihua University, Chengdu 610039, China.ORCID https://orcid.org/0000-0003-0018-5490
Hui ZhuCollege of Bioengineering, Sichuan University of Science and Engineering, Zigong 643000, China.ORCID https://orcid.org/0000-0002-8967-3177

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesTibetan tea is a kind of dark tea, due to the inherent complexity of natural products, the chemical composition and beneficial effects of Tibetan tea are not fully understood. The objective of this study was to unravel the composition of Tibetan tea using knowledge-guided multilayer network (KGMN) techniques and explore its potential antioxidant and hypolipidemic mechanisms in mice. MATERIALS/

methodsThe C57BL/6J mice were continuously gavaged with Tibetan tea extract (T group), green tea extract (G group) and ddH

resultsThe results showed that a total of 42 flavonoids are provisionally annotated in Tibetan tea using KGMN strategies. Tibetan tea significantly reduced body weight gain and increased T-AOC and SOD activities in mice compared with the H group. Based on the results of transcriptome and qPCR, it was confirmed that Tibetan tea could play a key role in antioxidant and lipid lowering by regulating oxidative stress and lipid metabolism related pathways such as insulin resistance, P53 signaling pathway, insulin signaling pathway, fatty acid elongation and fatty acid metabolism.

conclusionsThis study was the first to use computational tools to deeply explore the composition of Tibetan tea and revealed its potential antioxidant and hypolipidemic mechanisms, and it provides new insights into the composition and bioactivity of Tibetan tea.

Indexed as

antioxidantlipid metabolismTeatranscriptome

Identifiers

PMID37529260
PMCPMC10375330

What OpenQuestion holds

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Registered trials

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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.