ArticleJournal of cellular and molecular medicine2022
Evaluating the effect of LPS from periodontal pathogenic bacteria on the expression of senescence-related genes in human dental pulp stem cells.
Article in Journal of cellular and molecular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Inflammation-Regeneration Axis of Dental Pulp Stem Cells: Wnt/NF-κB Crosstalk.International endodontic journal · 2026Review
- Tooth Decay Promotes Senescence in Dental Pulp Stem Cells, Modifying Their Biological and Proteomic Profiles.Journal of cellular physiology · 2026Article
- Lipopolysaccharides Modulate Cellular Responses in Dental Pulp Cells.International journal of dentistry · 2026Review
- Circular RNAs inducing the osteogenic differentiation of dental mesenchymal stem cellsWorld journal of stem cells · 2025Review
- Activating Transcription Factor 3 (ATF3) Regulates Cellular Senescence and Osteoclastogenesis via STAT3/ERK and p65/AP-1 Pathways in Human Periodontal Ligament Cells.International journal of molecular sciences · 2025Article
- The oral microbiome in aging: a window into health and longevity.Journal of oral microbiology · 2025Review
- Effect of Oral Pathogens Associated With Pulpitis and Apical Periodontitis on Odontogenic Mesenchymal Stem Cells.Stem cells international · 2025Review
- LL-37 regulates odontogenic differentiation of dental pulp stem cells in an inflammatory microenvironment.Stem cell research & therapy · 2024Article
- Nesfatin-1 attenuated lipopolysaccharide-induced inflammatory response and senescence in human dental pulp cells.Heliyon · 2024Article
- Dental Stem Cells and Lipopolysaccharides: A Concise Review.International journal of molecular sciences · 2024Review
- Evaluating the effect of LPS from periodontal pathogenic bacteria on the expression of senescence-related genes in human dental pulp stem cells.Journal of cellular and molecular medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
The human dental pulp stem cells (hDPSCs) are one of the readily available sources of multipotent mesenchymal stem cells (MSCs) and can be considered as a type of tool cells for cell-based therapies. However, the main limitation in the clinical use of these cells is DPSC senescence, which can be induced by lipopolysaccharide (LPS) of oral pathogenic bacteria. Up to now, far little attention has been paid to exploring the molecular mechanisms of senescence in DPSCs. So, the current study aimed to investigate the underlying molecular mechanism of senescence in hDPSCs stimulated with Porphyromonas gingivalis (P. gingivalis) and Escherichia coli (E. coli)-derived LPSs, by evaluating both mRNA and protein expression of four important senescence-related genes, including TP53, CDKN1A, CDKN2A and SIRT1. To this purpose, hDPSCs were stimulated with different LPSs for 6, 24 and 48 h and then the gene expression was evaluated using quantitative real-time polymerase chain reaction (qPCR) and western blotting. Following stimulation with P. gingivalis and E. coli-derived LPSs, the relative mRNA and protein expression of all genes were significantly up-regulated in a time-dependent manner, as compared with unstimulated hDPSCs. Moreover, the hDPSCs stimulated with P. gingivalis LPS for 6 and 24 h had the highest mRNA expression of CDKN1A and SIRT1, respectively (p < 0.0001), whereas the highest mRNA expression of CDKN2A and TP53 was seen in hDPSCs stimulated with E. coli LPS for 48 h (p < 0.0001). In summary, because DPSCs have been reported to have therapeutic potential for several cell-based therapies, targeting molecular mechanisms aiming at preventing DPSC senescence could be considered a valuable strategy.
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Registered trials
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.