Li Shao

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Mesenchymal stem cells (MSCs), the major stem cells for cell therapy, have been used in the clinic for approximately 10 years. From animal models to clinical trials, MSCs have afforded promise in the treatment of numerous diseases, mainly tissue injury and immune disorders. In this review, we summarize the recent opinions on methods, timing and cell sources(More)
Liver cirrhosis occurs as a consequence of many chronic liver diseases that are prevalent worldwide. Here we characterize the gut microbiome in liver cirrhosis by comparing 98 patients and 83 healthy control individuals. We build a reference gene set for the cohort containing 2.69 million genes, 36.1% of which are novel. Quantitative metagenomics reveals(More)
The novel avian origin influenza A (H7N9) virus has caused severe diseases in humans in eastern China since the spring of 2013. Fatal outcomes of H7N9 infections are often attributed to the severe pneumonia and acute respiratory distress syndrome (ARDS). There is urgent need to discover biomarkers predicting the progression of disease and fatal outcome of(More)
Conflicting evidence exists with regard to the relationship between maternal infection during pregnancy and the risk of autism spectrum disorder (ASD) in offspring. The aim of this meta-analysis was to systematically assess this relationship. To identify relevant studies, we conducted systematic searches in PubMed and Embase of scientific articles published(More)
The role of LeuRS, an aminoacyl-tRNA synthetase, as an intracellular l-leucine sensor for the mTORC1 pathway has been the subject of much research recently. Despite this, the association between LeuRS and lactation in dairy cow mammary epithelial cells (DCMECs) remains unknown. In this study, we found that LeuRS expression in mammary gland tissue was(More)
Constructing a highly predictive model and exploiting the underlying mechanism associated with a specific property of chemicals are the two main goals of quantitative structure-activity relationship analysis (QSAR). However, the latter has long been carried out as a byproduct of model construction. Here we confirmed for the first time in this study that(More)
High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets(More)
Constructing an accurate predictive model for clinical decision-making on the basis of a relatively small number of tumor samples with high-dimensional microarray data remains a very challenging problem. The validity of such models has been seriously questioned due to their failure in clinical validation using independent samples. Besides the statistical(More)
The era of personalized medicine for cancer therapeutics has taken an important step forward in making accurate prognoses for individual patients with the adoption of high-throughput microarray technology. However, microarray technology in cancer diagnosis or prognosis has been primarily used for the statistical evaluation of patient populations, and thus(More)