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1.
Chin Med J (Engl) ; 131(17): 2089-2096, 2018 Sep 05.
Article in English | MEDLINE | ID: mdl-30127219

ABSTRACT

BACKGROUND: Fibroblasts were the main seed cells in the studies of tissue engineering of the pelvic floor ligament. Basic fibroblast growth factor (bFGF) and epidermal growth factor (EGF) were widely studied but at various concentrations. This study aimed to optimize the concentrations of combined bFGF and EGF by evaluating their effects on proliferation and collagen secretion of fibroblasts. METHODS: Fibroblasts were differentiated from rat adipose mesenchymal stem cells (ADSCs). Flow cytometry and immunohistochemistry were used for cell identification. The growth factors were applied at concentrations of 0, 1, 10, and 100 ng/ml as three groups: (1) bFGF alone, (2) EGF alone, and (3) bFGF mixed with EGF. Cell proliferation was evaluated by Cell Counting Kit-8 assays. Expression of Type I and III collagen (Col-I and Col-III) mRNAs was evaluated by real-time quantitative reverse transcription-polymerase chain reaction. Statistical analysis was performed with SPSS software and GraphPad Prism using one-way analysis of variance and multiple t-test. RESULTS: ADSCs were successfully isolated from rat adipose tissue as identified by expression of typical surface markers CD29, CD44, CD90, and CD45 in flow cytometry. Fibroblasts induced from ADSC, compared with ADSCs, were with higher mRNA expression levels of Col I and Col III (F = 1.29, P = 0.0390). bFGF, EGF, and the mixture of bFGF with EGF can enhanced fibroblasts proliferation, and the concentration of 10 ng/ml of the mixture of bFGF with EGF displayed most effectively (all P < 0.05). The expression levels of Col-I and Col-III mRNAs in fibroblasts displayed significant increases in the 10 ng/ml bFGF combined with EGF group (all P < 0.05). CONCLUSIONS: The optimal concentration of both bFGF and EGF to promote cell proliferation and collagen expression in fibroblasts was 10 ng/ml at which fibroblasts grew faster and secreted more Type I and III collagens into the extracellular matrix, which might contribute to the stability of the pelvic floor microenvironment.


Subject(s)
Cell Proliferation , Collagen/metabolism , Epidermal Growth Factor/physiology , Fibroblast Growth Factor 2/physiology , Fibroblasts/physiology , Animals , Cells, Cultured , Pelvic Floor , Rats , Regeneration
2.
Chin J Dent Res ; 21(2): 101-111, 2018.
Article in English | MEDLINE | ID: mdl-29808173

ABSTRACT

OBJECTIVE: To explore graphene's effects on the gene expression profile of mesenchymal stem cells, and to reveal the mechanisms of graphene-guided osteogenic differentiation. METHODS: Human adipose-derived mesenchymal stem cells (hASCs) were cultured on single-layer graphene-coated titanium disks or titanium disks in proliferation medium (control) or osteoinduction medium for 7 days before RNA extraction. After library construction and RNA sequencing, identification of differentially expressed genes was performed through Limma package of R platform, with a cut-off value of log fold change (logFC) > = |1|. Pathway and Gene ontology (GO) analyses were conducted on DAVID Bioinformatics Resources 6.8 (NIAID/NIH). Network analyses were performed by the Ingenuity Pathways Analysis (IPA). RESULTS: Signalling pathway analysis revealed the top five pathways - cytokine-cytokine receptor interaction, neuroactive-ligand receptor interaction, calcium signalling pathway, PI3K-Akt signalling pathway and cell adhesion molecules. GO analyses demonstrated significant changes on cell adhesion, calcium signalling, and epigenetic regulation. IPA network analyses demonstrated that inflammation-related pathways were influenced by graphene, while the downstream factors of histone H3 and H4 were also altered especially under the existence of osteoinduction medium. CONCLUSION: Graphene promotes osteogenic differentiation of hASCs mainly by influencing cell adhesion, cytokine-cytokine receptor interactions, inflammatory responses, and potentially influences histone H3 and H4 through epigenetic regulation.


Subject(s)
Cell Differentiation/genetics , Mesenchymal Stem Cells/cytology , Mesenchymal Stem Cells/physiology , Osteogenesis/genetics , Transcriptome , Cell Differentiation/drug effects , Cells, Cultured , Gene Expression Regulation , Graphite/pharmacology , Humans , Mesenchymal Stem Cells/drug effects
3.
Dis Colon Rectum ; 49(10): 1517-26, 2006 Oct.
Article in English | MEDLINE | ID: mdl-17001440

ABSTRACT

PURPOSE: Surgeons often can contribute failure of sphincter-preserving procedure to a limitation of pelvis anatomy; however, they cannot determine definitely which anatomic diameter or spatial factor actually affected the success of the procedure. METHODS: Colorectal surgeons, radiologists, and research fellows collaborated closely to establish a three-dimensional digital model of the pelvis with spiral computerized tomography scanning data of patients with rectal cancer. Retrospective analysis on data of 97 patients with low rectal cancer was performed with this model to identify geometric factors that might affect a successful sphincter preservation procedure for low rectal cancer. RESULTS: A digital pelvic model was established. Multivariate analysis demonstrated that distance from the anal verge, body mass index, and pelvic factors affected the success of sphincter preservation. Sphincter preservation was more likely to succeed when the distance from anal verge was > or =5 cm and body mass index was <25 kg/m(2). Shorter diameter from the upper pubis to the sacrococcyx, distance of sacrococcyx, and excessive curvature of the sacrum predicted failure of sphincter preservation in certain cases. CONCLUSIONS: Pelvic diameters could affect the success of sphincter preservation for low rectal cancer patients besides the distance from anal verge and body mass index.


Subject(s)
Anal Canal/surgery , Digestive System Surgical Procedures/methods , Imaging, Three-Dimensional , Models, Anatomic , Pelvis/anatomy & histology , Rectal Neoplasms/surgery , Body Mass Index , Humans , Image Processing, Computer-Assisted , Logistic Models , Multivariate Analysis , Neoplasm Staging , Tomography, Spiral Computed , Treatment Failure
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