Evidence map›Paper›PMID 35571892›Full record

ArticleFrontiers in nutrition2022

Improvement in Mung Bean Peptide on High-Fat Diet-Induced Insulin Resistance Mice Using Untargeted Serum Metabolomics.

Lina Li, Yu Tian, Yuchao Feng, Shu Zhang, Yingjun Jiang, Yiwei Zhang, Yuanyuan Zhan, Changyuan Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.4field-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

7 citing papers in PubMed, 22 citations in OpenAlex.

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  6. Gut microbiota in insulin resistance: a bibliometric analysis.Journal of diabetes and metabolic disorders · 2024
    Review
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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

8 authors at 1 institution in 1 country.

Lina LiCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Yu TianCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Yuchao FengCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Shu ZhangCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Yingjun JiangCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Yiwei ZhangCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Yuanyuan ZhanCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Changyuan WangCollege of Food, Heilongjiang Bayi Agricultural University, Daqing, China.
Heilongjiang Bayi Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to elucidate the potential regulatory mechanism of mung bean peptides (MBPs) on glucolipid metabolism in insulin-resistant mice induced by high-fat diet (HFD) using untargeted serum metabolomics, enzyme linked immunosorbent assay (ELISA), intraperitoneal injection glucose tolerance test (IPGTT), insulin tolerance test (IPITT), and hematoxylin-eosin staining (H&E). The regulatory effect of MBPs for alleviating insulin resistance was studied by measuring body weight, fasting blood glucose (FBG) and serum insulin levels, C-Peptide levels, inflammatory and antioxidant factors, and histopathological observation of C57BL/6 mice. The experimental results showed that dietary intervention with MBPs (245 mg/kg/d) for 5 weeks significantly relieved insulin resistance in HFD mice. The body weight, insulin resistance index, and the levels of FBG, C-Peptide, IL-6, TNF-α, and MDA in the serum of HFD mice significantly decreased (

Indexed as

glucolipid metabolisminsulin-resistant (IR)mung bean peptides (MBPs)obesityuntargeted serum metabolomics

Identifiers

PMID35571892
PMCPMC9101312
OpenAlexW4225136184

What OpenQuestion holds

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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.