Objective. To identify the shared genetic and epigenetic mechanisms between the osteogenic differentiation of dental pulp stem cells (DPSC) and bone marrow stem cells (BMSC). Materials and Methods. The profiling datasets of miRNA expression in the osteogenic differentiation of mesenchymal stem cells from the dental pulp (DPSC) and bone marrow (BMSC) were searched in the Gene Expression Omnibus (GEO) database. The differential expression analysis was performed to identify differentially expressed miRNAs (DEmiRNAs) dysregulated in DPSC and BMSC osteodifferentiation. The target genes of the DEmiRNAs that were dysregulated in DPSC and BMSC osteodifferentiation were identified, followed by the identification of the signaling pathways and biological processes (BPs) of these target genes. Accordingly, the DEmiRNA-transcription factor (TFs) network and the DEmiRNAs-small molecular drug network involved in the DPSC and BMSC osteodifferentiation were constructed. Results. 16 dysregulated DEmiRNAs were found to be overlapped in the DPSC and BMSC osteodifferentiation, including 8 DEmiRNAs with a common expression pattern (8 upregulated DEmiRNAs (miR-101-3p, miR-143-3p, miR-145-3p/5p, miR-19a-3p, miR-34c-5p, miR-3607-3p, miR-378e, miR-671-3p, and miR-671-5p) and 1 downregulated DEmiRNA (miR-671-3p/5p)), as well as 8 DEmiRNAs with a different expression pattern (i.e., miR-1273g-3p, miR-146a-5p, miR-146b-5p, miR-337-3p, miR-382-3p, miR-4508, miR-4516, and miR-6087). Several signaling pathways (TNF, mTOR, Hippo, neutrophin, and pathways regulating pluripotency of stem cells), transcription factors (RUNX1, FOXA1, HIF1A, and MYC), and small molecule drugs (curcumin, docosahexaenoic acid (DHA), vitamin D3, arsenic trioxide, 5-fluorouracil (5-FU), and naringin) were identified as common regulators of both the DPSC and BMSC osteodifferentiation. Conclusion. Common genetic and epigenetic mechanisms are involved in the osteodifferentiation of DPSCs and BMSCs.

Background and Objective: Concerning current clinical practice, laser-assisted lipoplasty is still secondary to other procedures. In order to evaluate effects of thermal interaction with fatty-tissue, a near infrared diode laser was examined under reproducible conditions. Methods: Based on optical spectroscopy of fatty-tissue, a high-powered diode laser (l ¼ 940 nm) was used to irradiate n ¼ 59 fat samples of fresh corpses in non-contact mode. Thermal effects were histologically evaluated by computer based metric measurements. Calculated values included ablation rate (AR) and the ratio of cavity diameter to diameter of collateral damage (CCD ratio ). Pearson's correlation and analysis of covariance (ANCOVA) were used for statistical evaluation. P values of less than 0.05 were considered to indicate statistical significance. Results: Regarding the conditions examined, irradiances from 250 to 400 W/cm 2 revealed both increased ablation capacities and decreased collateral damages. An average irradiance of 370 AE 0 W/cm 2 shows an average CCD ratio of 2:1 and an average AR of 9.98 AE 7.65 mm 3 /second. Conclusion: Near infrared high-powered diode laser energy proved to be eligible for tissue protective ablation of fat in vitro. Further studies are necessary to improve efficiency and safety of this procedure.

Hair follicle outer root sheath (ORS) is a putative source of stem cells with therapeutic capacity. ORS contains several multipotent stem cell populations, primarily in the distal compartment of the bulge region. However, the bulge is routinely obtained using invasive isolation methods, which require human scalp tissue ex vivo. Non-invasive sampling has been standardized by means of the plucking procedure, enabling to reproducibly obtain the mid-ORS part. The mid-ORS shows potential for giving rise to multiple stem cell populations in vitro. To demonstrate the phenotypic features of distal, middle, and proximal ORS parts, gene and protein expression profiles were studied in physically separated portions. The mid-part of the ORS showed a comparable or higher NGFR, nestin/NES, CD34, CD73, CD44, CD133, CK5, PAX3, MITF, and PMEL expression on both protein and gene levels, when compared to the distal ORS part. Distinct subpopulations of cells exhibiting small and round morphology were characterized with flow cytometry as simultaneously expressing CD73/CD271, CD49f/CD105, nestin, and not CK10. Potentially, these distinct subpopulations can give rise to cultured neuroectodermal and mesenchymal stem cell populations in vitro. In conclusion, the mid part of the ORS holds the potential for yielding multiple stem cells, in particular mesenchymal stem cells.

ObjectiveTo identify the genetic linkage mechanisms underlying Parkinson’s disease (PD) and periodontitis, and explore the role of immunology in the crosstalk between both these diseases.MethodsThe gene expression omnibus (GEO) datasets associated with whole blood tissue of PD patients and gingival tissue of periodontitis patients were obtained. Then, differential expression analysis was performed to identify the differentially expressed genes (DEGs) deregulated in both diseases, which were defined as crosstalk genes. Inflammatory response-related genes (IRRGs) were downloaded from the MSigDB database and used for dividing case samples of both diseases into different clusters using k-means cluster analysis. Feature selection was performed using the LASSO model. Thus, the hub crosstalk genes were identified. Next, the crosstalk IRRGs were selected and Pearson correlation coefficient analysis was applied to investigate the correlation between hub crosstalk genes and hub IRRGs. Additionally, immune infiltration analysis was performed to examine the enrichment of immune cells in both diseases. The correlation between hub crosstalk genes and highly enriched immune cells was also investigated.ResultsOverall, 37 crosstalk genes were found to be overlapping between the PD-associated DEGs and periodontitis-associated DEGs. Using clustering analysis, the most optimal clustering effects were obtained for periodontitis and PD when k = 2 and k = 3, respectively. Using the LASSO feature selection, five hub crosstalk genes, namely, FMNL1, MANSC1, PLAUR, RNASE6, and TCIRG1, were identified. In periodontitis, MANSC1 was negatively correlated and the other four hub crosstalk genes (FMNL1, PLAUR, RNASE6, and TCIRG1) were positively correlated with five hub IRRGs, namely, AQP9, C5AR1, CD14, CSF3R, and PLAUR. In PD, all five hub crosstalk genes were positively correlated with all five hub IRRGs. Additionally, RNASE6 was highly correlated with myeloid-derived suppressor cells (MDSCs) in periodontitis, and MANSC1 was highly correlated with plasmacytoid dendritic cells in PD.ConclusionFive genes (i.e., FMNL1, MANSC1, PLAUR, RNASE6, and TCIRG1) were identified as crosstalk biomarkers linking PD and periodontitis. The significant correlation between these crosstalk genes and immune cells strongly suggests the involvement of immunology in linking both diseases.

Objective. This study investigated the nature of shared transcriptomic alterations in PBMs from periodontitis and atherosclerosis to unravel molecular mechanisms underpinning their association. Methods. Gene expression data from PBMs from patients with periodontitis and those with atherosclerosis were each downloaded from the GEO database. Differentially expressed genes (DEGs) in periodontitis and atherosclerosis were identified through differential gene expression analysis. The disease-related known genes related to periodontitis and atherosclerosis each were downloaded from the DisGeNET database. A Venn diagram was constructed to identify crosstalk genes from four categories: DEGs expressed in periodontitis, periodontitis-related known genes, DEGs expressed in atherosclerosis, and atherosclerosis-related known genes. A weighted gene coexpression network analysis (WGCNA) was performed to identify significant coexpression modules, and then, coexpressed gene interaction networks belonging to each significant module were constructed to identify the core crosstalk genes. Results. Functional enrichment analysis of significant modules obtained by WGCNA analysis showed that several pathways might play the critical crosstalk role in linking both diseases, including bacterial invasion of epithelial cells, platelet activation, and Mitogen-Activated Protein Kinases (MAPK) signaling. By constructing the gene interaction network of significant modules, the core crosstalk genes in each module were identified and included: for GSE23746 dataset, RASGRP2 in the blue module and VAMP7 and SNX3 in the green module, as well as HMGB1 and SUMO1 in the turquoise module were identified; for GSE61490 dataset, SEC61G, PSMB2, SELPLG, and FIBP in the turquoise module were identified. Conclusion. Exploration of available transcriptomic datasets revealed core crosstalk genes (RASGRP2, VAMP7, SNX3, HMGB1, SUMO1, SEC61G, PSMB2, SELPLG, and FIBP) and significant pathways (bacterial invasion of epithelial cells, platelet activation, and MAPK signaling) as top candidate molecular linkage mechanisms between atherosclerosis and periodontitis.