Evidence map›Paper›PMID 33536073›Full record

ArticleStem cell research & therapy2021

Dynamic proteomic profiling of human periodontal ligament stem cells during osteogenic differentiation.

Jianjia Li, Zhifa Wang, Xiangyu Huang, Zhaodan Wang, Zehao Chen, Runting Wang, Zhao Chen, Wei Liu, Buling Wu, Fuchun Fang and 1 more

Abstract read
In one paragraph

Article in Stem cell research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
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

11 authors.

Jianjia LiDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Zhifa WangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Xiangyu HuangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Zhaodan WangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Zehao ChenDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Runting WangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Zhao ChenShenzhen Stomatology Hospital (Pingshan), Southern Medical University, 143 Dongzong Road, Pingshan District, Shenzhen, 518118, China.
Wei LiuShenzhen Stomatology Hospital (Pingshan), Southern Medical University, 143 Dongzong Road, Pingshan District, Shenzhen, 518118, China.
Buling WuDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China. bulingwu@smu.edu.cn.
Fuchun FangDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China. fangfuchun520@163.com.
Wei QiuDepartment of Stomatology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China. qiuweiandmj@163.com.ORCID 0000-0002-5548-5629

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman periodontal ligament stem cells (hPDLSCs) are ideal seed cells for periodontal regeneration. A greater understanding of the dynamic protein profiles during osteogenic differentiation contributed to the improvement of periodontal regeneration tissue engineering.

methodsTandem Mass Tag quantitative proteomics was utilized to reveal the temporal protein expression pattern during osteogenic differentiation of hPDLSCs on days 0, 3, 7 and 14. Differentially expressed proteins (DEPs) were clustered and functional annotated by Gene Ontology (GO) terms. Pathway enrichment analysis was performed based on the Kyoto Encyclopedia of Genes and Genomes database, followed by the predicted activation using Ingenuity Pathway Analysis software. Interaction networks of redox-sensitive signalling pathways and oxidative phosphorylation (OXPHOS) were conducted and the hub protein SOD2 was validated with western blotting.

resultsA total of 1024 DEPs were identified and clustered in 5 distinctive clusters representing dynamic tendencies. The GO enrichment results indicated that proteins with different tendencies show different functions. Pathway enrichment analysis found that OXPHOS was significantly involved, which further predicted continuous activation. Redox-sensitive signalling pathways with dynamic activation status showed associations with OXPHOS to various degrees, especially the sirtuin signalling pathway. SOD2, an important component of the sirtuin pathway, displays a persistent increase during osteogenesis. Data are available via ProteomeXchange with identifier PXD020908.

conclusionThis is the first in-depth dynamic proteomic analysis of osteogenic differentiation of hPDLSCs. It demonstrated a dynamic regulatory mechanism of hPDLSC osteogenesis and might provide a new perspective for research on periodontal regeneration.

Indexed as

OsteogenesisPeriodontal LigamentCell DifferentiationCells, CulturedHumansProteomicsStem CellsDynamic proteomicsHuman periodontal ligament stem cellOsteogenic differentiationOxidative phosphorylationSOD2

Identifiers

PMID33536073
PMCPMC7860046

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.