Mesenchymal stem cell (MSC) has been applied for the therapy of allergic disorders due to its beneficial immunomodulatory abilities. However, the underlying mechanisms for therapeutic efficacy are reported to be diverse according to the source of cell isolation or the route of administration. We sought to investigate the safety and the efficacy of human adipose tissue-derived MSCs (hAT-MSCs) in mouse atopic dermatitis (AD) model and to determine the distribution of cells after intravenous administration. Murine AD model was established by multiple treatment of Dermatophagoides farinae. AD mice were intravenously infused with hAT-MSCs and monitored for clinical symptoms. The administration of hAT-MSCs reduced the gross and histological signatures of AD, as well as serum IgE level. hAT-MSCs were mostly detected in lung and heart of mice within 3 days after administration and were hardly detectable at 2 weeks. All of mice administered with hAT-MSCs survived until sacrifice and did not demonstrate any adverse events. Co-culture experiments revealed that hAT-MSCs significantly inhibited the proliferation and the maturation of B lymphocytes via cyclooxygenase (COX)-2 signaling. Moreover, mast cell (MC) degranulation was suppressed by hAT-MSC. In conclusion, the intravenous infusion of hAT-MSCs can alleviate AD through the regulation of B cell function.

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Background Prognostic genes or gene signatures have been widely used to predict patient survival and aid in making decisions pertaining to therapeutic actions. Although some web-based survival analysis tools have been developed, they have several limitations. Objective Taking these limitations into account, we developed ESurv (Easy, Effective, and Excellent Survival analysis tool), a web-based tool that can perform advanced survival analyses using user-derived data or data from The Cancer Genome Atlas (TCGA). Users can conduct univariate analyses and grouped variable selections using multiomics data from TCGA. Methods We used R to code survival analyses based on multiomics data from TCGA. To perform these analyses, we excluded patients and genes that had insufficient information. Clinical variables were classified as 0 and 1 when there were two categories (for example, chemotherapy: no or yes), and dummy variables were used where features had 3 or more outcomes (for example, with respect to laterality: right, left, or bilateral). Results Through univariate analyses, ESurv can identify the prognostic significance for single genes using the survival curve (median or optimal cutoff), area under the curve (AUC) with C statistics, and receiver operating characteristics (ROC). Users can obtain prognostic variable signatures based on multiomics data from clinical variables or grouped variable selections (lasso, elastic net regularization, and network-regularized high-dimensional Cox-regression) and select the same outputs as above. In addition, users can create custom gene signatures for specific cancers using various genes of interest. One of the most important functions of ESurv is that users can perform all survival analyses using their own data. Conclusions Using advanced statistical techniques suitable for high-dimensional data, including genetic data, and integrated survival analysis, ESurv overcomes the limitations of previous web-based tools and will help biomedical researchers easily perform complex survival analyses.

BACKGROUNDOsteosarcoma is the most common primary bone malignancy. We meta-analyzed the prognostic value of altered miRNAs in patients with osteosarcoma.METHODSSources from MEDLINE (from inception to August 2016) and EMBASE (from inception to August 2016) were searched. Studies of osteosarcoma with results of miRNA and studies that reported survival data were included and two authors performed the data extraction independently. Any discrepancies were resolved by a consensus. The outcome was overall survival and event-free survival assessed using hazard ratios (HRs).RESULTSAfter reviewing the full text of 65 articles, 25 studies including 2,278 patients were eligible in this study. The pooled HR for deaths was 1.40 (95% confidence interval [CI] 1.01-1.94, p=0.04) with random-effects model (χ2=113.08, p<0.00001, I2=79%) for patients of osteosarcoma with lower expression of miRNA. However, the pooled HR for events was not significant (HR 0.97, 0.63-1.48, p=0.87, χ2=72.65, p<0.00001, I2=79%). In pathway analysis of miRNAs, miRNA449a, 199-5p, 542-5p have common target genes.CONCLUSIONSExpression level of miRNA in patients of osteosarcoma is important as a prognostic factor.

Porous hydroxyapatite (HA) artificial bone scaffolds were prepared via the freeze-gel casting process in order to improve their mechanical strengths. As a porogen, various volumes of poly (methyl methacrylate) (PMMA) powders were added to obtain high porosity, such as in cancellous bone. After fabrication, the porous and mechanical properties of the scaffolds were examined. The HA60 scaffold, with a porosity over 80%, had proper compressive strength and modulus and satisfied the range of properties of cancellous bone. Moreover, it was found that the investigated mechanical properties were affected by the scaffolds’ porosity. However, a section was found where the compressive strength was high despite the increase in the porosity. Specifically, HA30 had a porosity of 62.9% and a compressive strength of 1.73 MPa, whereas the values for HA60 were 81.9% and 3.23 MPa, respectively. The results indicate that there are factors that can preserve the mechanical properties even if the porosity of the scaffold increases. Therefore, in this study, various parameters affecting the porous and mechanical properties of the scaffolds during the manufacturing process were analyzed. It is expected that the improvement in the mechanical properties of the artificial bone scaffold having a high porosity can be applied to tissue engineering.