Accurate detection of GATA1 mutation is highly significant in patients with acute myeloid leukemia (AML) and trisomy 21 as it allows optimization of clinical protocol. This study was aimed at (a) enhanced search for GATA1 mutations; and (b) characterization of molecular landscapes for such conditions. The DNA samples from 44 patients with newly diagnosed de novo AML with trisomy 21 were examined by fragment analysis and Sanger sequencing of the GATA1 exon 2, complemented by targeted high-throughput sequencing (HTS). Acquired GATA1 mutations were identified in 43 cases (98%). Additional mutations in the genes of JAK/STAT signaling, cohesin complex, and RAS pathway activation were revealed by HTS in 48%, 36%, and 16% of the cases, respectively. The GATA1 mutations were reliably determined by fragment analysis and/or Sanger sequencing in a single PCR amplicon manner. For patients with extremely low blast counts and/or rare variants, the rapid screening with simple molecular approaches must be complemented with HTS. The JAK/STAT and RAS pathway-activating mutations may represent an extra option of targeted therapy with kinase inhibitors. The GATA1 mutations were reliably determined by fragment analysis and/or Sanger sequencing in a single PCR amplicon manner. For patients with extremely low blast counts and/or rare variants, the rapid screening with simple molecular approaches must be complemented with HTS. The JAK/STAT and RAS pathway-activating mutations may represent an extra option of targeted therapy with kinase inhibitors. Thymic epithelial tumors constitute a morphologically and clinically diverse group of rare neoplasm of the anterior mediastinum. Here, we present an analysis of 188 patients diagnosed with primary thymic tumors between 1995 and 2015. The prognostic value of selected clinical and morphological factors was assessed in relation to overall survival and recurrence-free survival. The risk of recurrence increased significantly in thymic carcinoma diagnosis (P = 0.0036), co-occurrence of other diseases, and weight loss (P = 0.0012 and 0.0348, respectively). Multivariate analysis showed that the most important independent risk factor for disease recurrence was clinical stage IV (P = 0.0036). A total of 63 patients (33.5%) died. In the univariate analysis, the following factors were considered as independent prognostic factors for overall survival clinical stage (P < 0.0001), histological type (P < 0.0001), lymph node involvement (P < 0.001), WHO performance status 2 (P < 0.0001), anemia (Hb <9.5 g/dL; P = 0.0002), leucocytosis (>12.5 G/L; P = 0.0011), LDH level (>185 U/L; P < 0.0001), concomitant diseases (P = 0.0012) and weight loss (P < 0.0001).The strongest independent risk factor for death was stage IV disease (P < 0.001). The results confirmed a fairly good prognosis for patients with thymic epithelial tumors. Clinical stage was the most important prognostic factor, but, some additional clinical factors may also have prognostic value. The results confirmed a fairly good prognosis for patients with thymic epithelial tumors. Clinical stage was the most important prognostic factor, but, some additional clinical factors may also have prognostic value.Despite community health centers (CHCs) having many potential benefits, their utilisation rate is still low in urban China. Using the health belief model, the study conducted cross-sectional survey to examine factors that affected individuals' intentions to use primary care services in China. This study on 942 participants from Shanghai revealed that low cost had insignificant effect on the choice of CHCs once other key factors were accounted for. Older age, greater perceived susceptibility to contracting common diseases and more benefits of individualised care greatly increased the likelihood of using primary care services. Perceived low competencies of medical personnel along with outdated medical facilities had significant negative relationships with the intention of choosing CHCs. Based on these findings, some policy recommendations are proposed such as promoting education on prevalence of common diseases, recruiting qualified medical personnel, increasing professional training and cooperation, updating medical facilities, and offering high-quality individualised care in order to improve efficiency of primary care utilisation.Retrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective method that can reduce a large number of the initially predicted enzymatic reactions has been needed. Here, we present Deep learning-based Reaction Feasibility Checker (DeepRFC) to classify the feasibility of a given enzymatic reaction with high performance and speed. DeepRFC is designed to receive Simplified Molecular-Input Line-Entry System (SMILES) strings of a reactant pair, which is defined as a substrate and a product of a reaction, as an input, and evaluates whether the input reaction is feasible. A deep neural network is selected for DeepRFC as it leads to better classification performance than five other representative machine learning methods examined. For validation, the performance of DeepRFC is compared with another in-house reaction feasibility checker that uses the concept of reaction similarity. Finally, the use of DeepRFC is demonstrated for the retrobiosynthesis-based design of novel one-carbon assimilation pathways. DeepRFC will allow retrobiosynthesis to be more practical for metabolic engineering applications by efficiently screening a large number of retrobiosynthesis-derived enzymatic reactions. DeepRFC is freely available at https//bitbucket.org/kaistsystemsbiology/deeprfc.Developing methods for the systematic and rapid identification of the chemical compositions of fresh plant tissues has long attracted the attention of phytochemists and pharmacologists. In the present study, based on highly efficient sample pretreatment and high-throughput analysis of high-performance liquid chromatography coupled with quadrupole time of flight tandem mass spectrometry data using molecular networks, a method was developed for systematically analyzing the chemical constituents of the fresh flowers of Robinia hispida L. and Robina pseudoacacia L., two congeneric ornamental species that lack prior consideration. A total of 44 glycosylated structures were characterized. https://www.selleckchem.com/products/m4205-idrx-42.html And on the basis of establishing of the fragmentation pathways of 11 known flavonoid glycosides, together with the molecular networking analysis, 18 other ions of flavonoid glycosides in five classes were clustered. Moreover, 15 soyasaponins/triterpenoid glycosides were tentatively identified by comparison of their tandem mass spectrometry characteristic ions with those reported in the literature or the online Global Natural Product Social Molecular Networking database.