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Background The aim of this study was to determine the effects of myeloma cells exposed to fluid shear stress on osteocytes and osteoclasts, and clarify the potential underlying mechanisms. Material/methods A flow and a non-flow model were established using a flow fluid chamber. The myeloma cell line U266 and murine osteocytic MLO-Y4 cells were cultured in vitro . The osteocytes and osteoclasts were examined under a microscope. Osteoclasts were stained for tartrate-resistant acid phosphatase (TRAP) activity. RANKL and osteoprotegerin (OPG) gene expression were detected using reverse transcription-quantitative polymerase chain reaction. Results Compared with the controls, Y4 cells cultured with U266 culture supernatant showed altered morphology, fewer osteocytes, increased RANKL gene expression, a higher RANKL/OPG gene ratio, and a greater number of TRAP-positive osteoclasts ( P <0.05 for all). Compared to the no-flow model, the flow model showed a higher number of Y4 cells, increased OPG gene expression, decreased RANKL gene expression, a lower RANKL/OPG gene ratio, and fewer TRAP-positive osteoclasts ( P <0.05 for all). Conclusions Our study revealed that fluid shear stress ameliorated the inhibitory effects of myeloma cells on osteocyte growth and inhibited osteoclast proliferation by means of decreasing RANKL/OPG gene expression. This may have clinical implications in patients with multiple myeloma in that mechanical loading with low-intensity vibration or mild exercise may prevent the progression of myeloma bone disease.

Background Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM. Material/Methods A microarray dataset was mined, which contains the transcriptome profiles of 588 MM patients. Univariate Cox analysis was performed to analyze the relationships between genes and clinical outcome. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were determined. Protective and risky genes were uploaded to Connectivity Map (CMAP) database to identify the potentially unknown effects of existing drugs. An example was selected to be docked on the known molecules. Results A total of 1445 genes significantly correlated with the event free survival (EFS) of MM patients were identified and included 676 protective and 769 risky indicators. KEGG pathway analysis revealed that these prognosis-associated genes were enriched in the “cell cycle,” “DNA replication,” and “P53 signaling pathway”. The top t3 most significant potential molecules were vorinostat, trifluoperazine, and thioridazine. CDK1 (cyclin-dependent kinase-1) ranked as the core in the class of prognosis-related genes in MM based on protein-protein interaction (PPI) network analysis. With Sybyl-X 2.0, the majority of the top 10 molecules aforementioned displayed high binding forces with CDK1. Among these molecules, trichostatin A had the greatest ability in combining with CDK1. Conclusions Genes that mainly accumulate in the cell cycle pathway play an essential role in the prognosis of MM, and these prognosis-related genes also have great value in drug development.

BackgroundMultiple myeloma (MM) remains an incurable malignant tumor of plasma cells. Increasing evidence has reported that hypoxia and immune status contribute to the progression of MM. In this research, the prognostic value of the hypoxia–immune-related gene SLC19A1 in MM was evaluated by bioinformatics analysis.MethodRNA-sequencing (RNA-seq) data along with clinical information on MM were downloaded from the Gene Expression Omnibus (GEO) database. Consistent clustering analysis and ESTIMATE algorithms were performed to establish the MM sample subgroups related to hypoxia and immune status, respectively, based on the GSE24080 dataset. The differentially expressed analysis was performed to identify the hypoxia–immune-related genes. Subsequently, a hypoxia–immune-gene risk signature for MM patients was constructed by univariate and multivariate Cox regression analyses, which was also verified in the GSE4581 dataset. Furthermore, the mRNA expression of SLC19A1 was determined using qRT-PCR in 19 MM patients, and the correlations between the genetic expression of SLC19A1 and clinical features were further analyzed.ResultA total of 47 genes were identified as hypoxia–immune-related genes for MM. Among these genes, SLC19A1 was screened to construct a risk score model that had better predictive power for MM. The constructed prognostic signature based on SLC19A1 was verified in the GSE4581 dataset. All independent prognostic factors (age, β2-microglobulin, LDH, albumin, MRI, and gene risk score) were used to develop a nomogram that showed a better performance for predicting the survival probability of MM patients for 1–5 years. Furthermore, SLC19A1 was highly expressed in newly diagnosed and relapsed MM patients, and high expression of SLC19A1 is correlated with higher bone marrow aspiration plasma cells and β2-microglobulin levels in MM patients.ConclusionIn conclusion, our results suggest that SLC19A1 is aberrantly expressed in MM and highly expressed SLC19A1 might be a biomarker correlated with inferior prognosis. More importantly, we identified SLC19A1 as a hypoxia–immune-related gene in MM. Future functional and mechanistic studies will further clarify the roles of SLC19A1 in MM.

Cellulose nanofibrils (CNFs) have potential applications in the development of innovative materials and enhancement of conventional materials properties. This paper focused on the mixed cellulase hydrolysis with major activity of exoglucanase and endoglucanase on the cellulose length shearing. By the cooperation of two-step production route, including (1) enzymatic pretreatment using cellulase fromTrichoderma virideand (2) mechanical grinding twice, a shorter cellulose nanofiber was fabricated. The influence of enzymatic charge and hydrolysis time on cellulose fibers was analyzed by using scanning electron microscopy (SEM), Fourier Transform Infrared Spectrometer (FTIR), and X-ray diffractometer (XRD). SEM images revealed that the surface morphology change, effective diameter sharpening, and length shearing of cellulose fibers are as a result of cellulase hydrolysis. The XRD suggested that the cellulase acted on the amorphous regions more strongly than the crystalline domains during layer-by-layer hydrolysis. The enzymatic charge and hydrolysis time significantly affected the yields and hydrolysis products concentration. The enzymatic pretreatment assisted mechanical grinding could improve the uniformity of CNF and helped to obtain CNF with exact length according to the requirement for special applications.