Evidence map›Paper›PMID 36685214›Full record

ReviewFrontiers in physiology2022

Single-cell transcriptomics: A new tool for studying diabetic kidney disease.

Zi-Hui Mao, Zhong-Xiuzi Gao, Yong Liu, Dong-Wei Liu, Zhang-Suo Liu, Peng Wu

Abstract readReview
In one paragraph

Review in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Observational
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

6 authors.

Zi-Hui MaoTraditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Zhong-Xiuzi GaoTraditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yong LiuTraditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Dong-Wei LiuTraditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Zhang-Suo LiuTraditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Peng WuTraditional Chinese Medicine Integrated Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The kidney is a complex organ comprising various functional partitions and special cell types that play important roles in maintaining homeostasis in the body. Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease and is an independent risk factor for cardiovascular diseases. Owing to the complexity and heterogeneity of kidney structure and function, the mechanism of DKD development has not been fully elucidated. Single-cell sequencing, including transcriptomics, epigenetics, metabolomics, and proteomics etc., is a powerful technology that enables the analysis of specific cell types and states, specifically expressed genes or pathways, cell differentiation trajectories, intercellular communication, and regulation or co-expression of genes in various diseases. Compared with other omics, RNA sequencing is a more developed technique with higher utilization of tissues or samples. This article reviewed the application of single-cell transcriptomics in the field of DKD and highlighted the key signaling pathways in specific tissues or cell types involved in the occurrence and development of DKD. The comprehensive understanding of single-cell transcriptomics through single-cell RNA-seq and single-nucleus RNA-seq will provide us new insights into the pathogenesis and treatment strategy of various diseases including DKD.

Indexed as

diabetic kidney diseasesignaling pathwaysingle-cell RNA-seqsingle-nucleus RNA-seqspatial transcriptomics

Identifiers

PMID36685214
PMCPMC9846140

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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.