Dataset Information

The osteogenic response of undifferentiated human mesenchymal stem cells (hMSCs) to mechanical strain is inversely related to body mass index of the donor.

ABSTRACT:

Background

While the importance of physical factors in the maintenance and regeneration of bone tissue has been recognized for many years and the mechano-sensitivity of bone cells is well established, there is increasing evidence that body fat constitutes an independent risk factor for complications in bone fracture healing and aseptic loosening of implants. Although mechanical causes have been widely suggested, we hypothesized that the osteogenic mechano-response of human mesenchymal stem cells (hMSCs) may be altered in obese patients.

Methods

We determined the phenotypic and genotypic response of undifferentiated hMSCs of 10 donors to cyclic tensile strain (CTS) under controlled in vitro conditions and analyzed the potential relationship relevant to the donor's anthropomorphometric and biochemical parameters related to donor's fat and bone metabolism.

Results and interpretation

The osteogenic marker genes were all statistically significantly upregulated by CTS, which was accompanied by a significant increase in cell-based ALP activity. Linear correlation analysis revealed that there was a significant correlation between phenotypic CTS response and the body mass index of the donor (r = -0.91, p < 0.001) and phenotypic CTS response was also significantly related to leptin levels (r = -0.68) and estradiol levels (r = 0.67) within the bone marrow microenvironment of the donor. Such an upstream imprinting process mediated by factors tightly related to the donor's fat metabolism, which hampers the mechanosensitivity of hMSCs in obese patients, may be of pathogenetic relevance for the complications associated with obesity that are seen in orthopedic surgery.

SUBMITTER: Friedl G

PROVIDER: S-EPMC2823184 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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Publications

The osteogenic response of undifferentiated human mesenchymal stem cells (hMSCs) to mechanical strain is inversely related to body mass index of the donor.

Friedl Gerald G Windhager Reinhard R Schmidt Helena H Aigner Reingard R

Acta orthopaedica 20090801 4

<h4>Background</h4>While the importance of physical factors in the maintenance and regeneration of bone tissue has been recognized for many years and the mechano-sensitivity of bone cells is well established, there is increasing evidence that body fat constitutes an independent risk factor for complications in bone fracture healing and aseptic loosening of implants. Although mechanical causes have been widely suggested, we hypothesized that the osteogenic mechano-response of human mesenchymal st ...[more]

PMID: 19857181

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Project description:Human mesenchymal stem cells (hMSCs) are multipotent progenitor cells with the potential to differentiate into various cell types, including osteoblasts, chondrocytes, and adipocytes. These cells have been extensively employed in the field of cell-based therapies and regenerative medicine due to their inherent attributes of self-renewal and multipotency. Traditional approaches for assessing hMSCs differentiation capacity have relied heavily on labor-intensive techniques, such as RT-PCR, immunostaining, and Western blot, to identify specific biomarkers. However, these methods are not only time-consuming and economically demanding, but also require the fixation of cells, resulting in the loss of temporal data. Consequently, there is an emerging need for a more efficient and precise approach to predict hMSCs differentiation in live cells, particularly for osteogenic and adipogenic differentiation. In response to this need, we developed innovative approaches that combine live-cell imaging with cutting-edge deep learning techniques, specifically employing a convolutional neural network (CNN) to meticulously classify osteogenic and adipogenic differentiation. Specifically, four notable pre-trained CNN models, VGG 19, Inception V3, ResNet 18, and ResNet 50, were developed and tested for identifying adipogenic and osteogenic differentiated cells based on cell morphology changes. We rigorously evaluated the performance of these four models concerning binary and multi-class classification of differentiated cells at various time intervals, focusing on pivotal metrics such as accuracy, the area under the receiver operating characteristic curve (AUC), sensitivity, precision, and F1-score. Among these four different models, ResNet 50 has proven to be the most effective choice with the highest accuracy (0.9572 for binary, 0.9474 for multi-class) and AUC (0.9958 for binary, 0.9836 for multi-class) in both multi-class and binary classification tasks. Although VGG 19 matched the accuracy of ResNet 50 in both tasks, ResNet 50 consistently outperformed it in terms of AUC, underscoring its superior effectiveness in identifying differentiated cells. Overall, our study demonstrated the capability to use a CNN approach to predict stem cell fate based on morphology changes, which will potentially provide insights for the application of cell-based therapy and advance our understanding of regenerative medicine.

Project description:BackgroundThe osteogenic differentiation capacity of periodontal mesenchymal stem cells (PDLSCs) can be influenced by different levels of static mechanical strain (SMS) in an inflammatory microenvironment. Long non-coding RNAs (lncRNAs) are involved in various physiological processes. However, the mechanisms by which lncRNAs regulate the osteogenic differentiation of PDLSCs remain unclear.MethodsWe investigated the responses of PDLSCs obtained from periodontitis patients and healthy people to 8% and 12%SMS. Gene microarray and bioinformatics analyses were implemented and identified lncRNA00638 as a target gene for the osteogenesis of PDLSCs from periodontitis patients under SMS. Competing endogenous RNA (ceRNA) network analysis was applied and predicted interactions among lncRNA00638, miRNA-424-5p, and fibroblast growth factor receptor 1 (FGFR1). Gene expression levels were regulated by lentiviral vectors. Cell Counting Kit-8 assays, alkaline phosphatase assays, and Alizarin Red S staining were used to examine the osteogenic potential. RT-qPCR and Western blot were performed to detect the expression levels of related genes and proteins.ResultsWe found that 8% and 12% SMS exerted distinct effects on HPDLSCs and PPDLSCs, with 12% SMS having the most significant effect. By microarray analysis, we detected differentially expressed lncRNAs/mRNAs between 12% SMS strained and static PPDLSCs, among which lncRNA00638 was detected as a positive target gene to promote the osteogenic differentiation of PPDLSCs under SMS loading. Mechanistically, lncRNA00638 may act as a ceRNA for miR-424-5p to compete with FGFR1. In this process, lncRNA00638 and miR-424-5p suppress each other and form a network to regulate FGFR1.ConclusionsOur findings demonstrate that the lncRNA00638/miRNA-424-5p/FGFR1 regulatory network is actively involved in the regulation of PDLSC osteogenic differentiation from periodontitis patients under SMS loading, which may provide evidence for optimizing orthodontic treatments in patients with periodontitis.

Project description:Biomineralized collagen with intrafibrillar calcium phosphate mineral provides an excellent mimic of the composition and structure of the extracellular matrix of bone, from nano- to micro-scale. Scaffolds prepared from this material have the potential to become the next-generation of synthetic bone graft substitutes, as their unique properties make them closer to the native tissue than synthetic alternatives currently available to clinicians. To understand the interaction between biomineralized collagen and cells that are relevant in the context of bone regeneration, we studied the growth and osteogenic differentiation of bone marrow derived human mesenchymal stromal cells (hMSCs) cultured on biomineralized collagen membranes, and compared it to the cell behavior on collagen membranes without mineral. Cells proliferated normally on both biomimetic membranes, and were more triggered to differentiate toward the osteogenic lineage by the biomineralized collagen. This was shown by the elevated mRNA levels of RUNX2, SPP1, ENPP1, and OCN after 3 days of culture, and COL1A1 after 14 days of culture on mineralized collagen. The mRNA levels of the tested markers of osteogenesis were lower on collagen membranes without mineral, with the exception of OCN, which was more highly expressed on collagen than on biomineralized collagen membranes. Expression by hMSCs of OPG, a gene involved in inhibition of osteoclastogenesis, was higher on biomineralized collagen at day 3, while M-CSF, involved in osteoblast-osteoclast communication, was upregulated on both membranes at day 3 and 14 of culture. Alkaline phosphatase activity of hMSCs was high on both biomimetic membranes when compared with cells cultured on tissue culture plastic. Cell-induced mineralization was observed on collagen membranes, while the high mineral content of the biomineralized membranes prohibited a reliable analysis of cell-induced mineralization on these membranes. In conclusion, we have identified that both collagen and biomineralized collagen support proliferation, osteogenic differentiation and mineralization of hMSCs, with biomineralized membranes having a more pronounced positive effect. These findings support the existing evidence that biomineralized collagen is a promising material in the field of bone regeneration.

Dataset Information

The osteogenic response of undifferentiated human mesenchymal stem cells (hMSCs) to mechanical strain is inversely related to body mass index of the donor.

Background

Methods

Results and interpretation

Publications

The osteogenic response of undifferentiated human mesenchymal stem cells (hMSCs) to mechanical strain is inversely related to body mass index of the donor.

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