Evidence map›Paper›PMID 37351171›Full record

ArticleTheranostics2023

Integration of metabolomics and peptidomics reveals distinct molecular landscape of human diabetic kidney disease.

Xinrong Jiang, Xingyue Liu, Xuetong Qu, Pingya Zhu, Fangjie Wo, Xinran Xu, Juan Jin, Qiang He, Jianmin Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Theranostics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  17. Observational
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  20. Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
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.

Xinrong JiangInstitution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
Xingyue LiuInstitution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
Xuetong QuInstitution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
Pingya ZhuWell-healthcare Technologies Co., Hangzhou, 310051, China.
Fangjie WoWell-healthcare Technologies Co., Hangzhou, 310051, China.
Xinran XuInstitution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
Juan JinDepartment of Nephrology, The First People's Hospital of Hangzhou Lin'an District, Affiliated Lin'an People's Hospital of Hangzhou Medical College, Hangzhou, 311300, China.
Qiang HeDepartment of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, 310006, China.
Jianmin WuInstitution of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is the most common microvascular complication of diabetes, and there is an urgent need to discover reliable biomarkers for early diagnosis. Here, we established an effective urine multi-omics platform and integrated metabolomics and peptidomics to investigate the biological changes during DKD pathogenesis.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesHumansMetabolomicsPeptidesSiliconSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationPeptidesSiliconDiabetic kidney diseaseLaser desorption/ionization mass spectrometryMulti-omicsNon-invasive diagnosisType 2 diabetes

Identifiers

PMID37351171
PMCPMC10283058

What OpenQuestion holds

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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.