ABSTRACT
Metagenomic next generation sequencing (mNGS) is a non-targeted and broad-spectrum pathogen screening technology. In recent years, more and more studies have shown that mNGS pathogen detection plays a key role in the field of clinical severe infection, especially when the severe infection was caused by rare pathogens. However, due to its high cost and high requirements of experimental conditions, it has not been included as a routine clinical test yet. Nevertheless, it can be predicted that with the decrease of sequencing cost and the continuous improvement of medical level in China, the conditions for large-scale clinical application of pathogenic diagnosis based on mNGS have gradually matured. This consensus described the expert consensus of etiology diagnosis based on mNGS in the scope of detection, rules and applications in clinical moderate and severe infections, and also looked forward to the improvement of its clinical application in the future.
ABSTRACT
BACKGROUND AND OBJECTIVES: The International Society for Cellular Therapy (ISCT) proposed a set of minimal markers for identifying human mesenchymal stromal cells (hMSCs) in 2007. Since then, with the growing interest of better characterising hMSCs, various additional surface markers have been proposed. However, the impact of how culture conditions, in particular, the culture surface, vary the expression of hMSC markers was overlooked. METHODS AND RESULTS: In this study, we utilized the RNA sequencing data on hMSCs cultured on different surfaces to investigate the variation of the proposed hMSC biomarkers. One of the three ISCT proposed positive biomarker, CD90 was found to be significantly down regulated on hMSCs culture on fibrous surfaces when compared to flat surfaces. The detected gene expression values for 177 hMSCs biomarkers compiled from the literature are reported here. Correlation and cluster analysis revealed the existence of different biomarker communities that displayed a similar expression profile. We found a list of hMSCs biomarkers which are the least sensitive to a change in surface properties and another list of biomarkers which are found to have high sensitivity to a change in surface properties. CONCLUSIONS: This study demonstrated that substrate properties have paramount effect on altering the expressions of hMSCs biomarkers and the proposed list of substrate-stable and substrate-sensitive biomarkers would better assist in the population characterisation. However, proteomic level analysis would be essential to confirm the observations noted.