Evidence map›Paper›PMID 23573250›Full record

ArticlePloS one2013

Systemic perturbations of key metabolites in diabetic rats during the evolution of diabetes studied by urine metabonomics.

Mimi Guan, Liyun Xie, Chengfeng Diao, Na Wang, Wenyi Hu, Yongquan Zheng, Litai Jin, Zhihan Yan, Hongchang Gao

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

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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

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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

31 citing papers in PubMed, 64 citations in OpenAlex.

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  13. The total flavonoids fromIranian journal of basic medical sciences · 2020
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  19. [Metabonomics studies of urine fromZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2018
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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

9 authors at 1 institution in 1 country.

Mimi GuanSchool of Pharmacy, Wenzhou Medical College, Wenzhou, China.
Liyun Xie
Chengfeng Diao
Na Wang
Wenyi Hu
Yongquan Zheng
Litai Jin
Zhihan Yan
Hongchang Gao
Wenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElucidation of metabolic profiles during diabetes progression helps understand the pathogenesis of diabetes mellitus. In this study, urine metabonomics was used to identify time-related metabolic changes that occur during the development of diabetes mellitus and characterize the biochemical process of diabetes on a systemic, metabolic level. METHODOLOGY/PRINCIPAL

findingsUrine samples were collected from diabetic rats and age-matched controls at different time points: 1, 5, 10, and 15 weeks after diabetes modeling. (1)H nuclear magnetic resonance ((1)H NMR) spectra of the urine samples were obtained and analyzed by multivariate data analysis and quantitative statistical analysis. The metabolic patterns of diabetic groups are separated from the controls at each time point, suggesting that the metabolic profiles of diabetic rats were markedly different from the controls. Moreover, the samples from the diabetic 1-wk group are closely associated, whereas those of the diabetic 15-wk group are scattered, suggesting that the presence of various of complications contributes significantly to the pathogenesis of diabetes. Quantitative analysis indicated that urinary metabolites related to energy metabolism, tricarboxylic acid (TCA) cycle, and methylamine metabolism are involved in the evolution of diabetes. CONCLUSIONS/SIGNIFICANCE: The results highlighted that the numbers of metabolic changes were related to diabetes progression, and the perturbed metabolites represent potential metabolic biomarkers and provide clues that can elucidate the mechanisms underlying the generation and development of diabetes as well as its complication.

Indexed as

MetabolomicsAnimalsBiomarkersBlood Urea NitrogenCreatinineDiabetes Mellitus, ExperimentalDiscriminant AnalysisDisease ProgressionLeast-Squares AnalysisMaleRatsRats, Sprague-DawleyUreaUric AcidBiomarkersCreatinineUreaUric Acid

Identifiers

PMID23573250
PMCPMC3616076
OpenAlexW2017189194

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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.