Evidence map›Paper›PMID 36120453›Full record

ArticleFrontiers in endocrinology2022

Transcriptomic signatures responding to PKM2 activator TEPP-46 in the hyperglycemic human renal proximal epithelial tubular cells.

Zhimin Wang, Jiating Yu, Dan Hao, Xin Liu, Xiao Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Zhimin WangDivision of Endocrinology and Metabolic Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jiating YuDivision of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Dan HaoShijiazhuang Zhongnongtongchuang (ZNTC) Biotechnology Co., Ltd., Shijiazhuang, China.
Xin LiuDivision of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Xiao WangKonge Larsen ApS, Kongens Lyngby, Denmark.
First Affiliated Hospital of Zhengzhou University · CNQingdao Agricultural University · CNUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pyruvate kinase M2 (PKM2), as the terminal and last rate-limiting enzyme of the glycolytic pathway, is an ideal enzyme for regulating metabolic phenotype. PKM2 tetramer activation has shown a protective role against diabetic kidney disease (DKD). However, the molecular mechanisms involved in diabetic tubular have not been investigated so far. In this study, we performed transcriptome gene expression profiling in human renal proximal tubular epithelial cell line (HK-2 cells) treated with 25 mM high D-glucose (HG) for 7 days before the addition of 10 μM TEPP-46, an activator of PKM2 tetramerization, for a further 1 day in the presence of HG. Afterwards, we analyzed the differentially expressed (DE) genes and investigated gene relationships based on weighted gene co-expression network analysis. The results showed that 2,902 DE genes were identified (adjusted

Indexed as

Diabetic NephropathiesMicroRNAsBiomarkersErbB ReceptorsGlucoseHumansPyridazinesPyrrolesPyruvate KinasePyruvic AcidTranscriptomeTumor Suppressor Protein p53BiomarkersErbB ReceptorsGlucoseMicroRNAsML-265PyridazinesPyrrolesPyruvate KinasePyruvic AcidTumor Suppressor Protein p53diabetic kidney diseasehigh D-glucosehuman renal proximal epithelial tubular cellsTEPP-46transcriptomic analysis

Identifiers

PMID36120453
PMCPMC9471676
OpenAlexW4293767592

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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.