Evidence map›Paper›PMID 33897448›Full record

ArticleFrontiers in physiology2021

Silencing of miR-150-5p Ameliorates Diabetic Nephropathy by Targeting SIRT1/p53/AMPK Pathway.

Wenmin Dong, Huiqian Zhang, Cheng Zhao, Yun Luo, Ying Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

27 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. Autophagy and Mitophagy in Diabetic Kidney Disease-A Literature Review.International journal of molecular sciences · 2025
    Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Mechanisms and implications of podocyte autophagy in chronic kidney disease.American journal of physiology. Renal physiology · 2024
    Review
  15. Review
  16. Review
  17. Review
  18. The sirtuin family in health and disease.Signal transduction and targeted therapy · 2022
    Review
  19. Article
  20. Long Non-Coding RNAs in the Pathogenesis of Diabetic Kidney Disease.Frontiers in cell and developmental biology · 2022
    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

5 authors at 1 institution in 1 country.

Wenmin DongShanghai TCM-Integrated Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Huiqian ZhangShanghai TCM-Integrated Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Cheng ZhaoShanghai TCM-Integrated Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yun LuoShanghai TCM-Integrated Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Ying ChenShanghai TCM-Integrated Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Shanghai University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic nephropathy (DN) is a common complication of diabetes and an important cause of end-stage renal disease. Increasing evidence suggests that microRNAs (miRNAs) regulate the development of DN. In a preliminary study, high levels of miR-150-5p were detected in the serum and urine of patients with DN. Consequently, we investigated the effect and mechanism of action of miR-150-5p in DN

Indexed as

autophagydiabetic nephropathymicroRNAsp53SIRT1

Identifiers

PMID33897448
PMCPMC8064124
OpenAlexW3152572534

What OpenQuestion holds

Textmetadata
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.