BackgroundInflammation and nutrition are two main causes contributing to progression of gastric cancer (GC), and inflammatory biomarker may be presented as its valuable prognostic factor. Thus, this study was carried out to investigate the prognostic significance of preoperative circulating albumin/fibrinogen ratio (AFR), fibrinogen/pre-Albumin ratio (FPR), fibrinogen (Fib), albumin (Alb) and pre-Albumin (pAlb) in surgical GC.Materials and MethodsThree hundred and sixty surgical stage II and III GC patients from June 2011 to December 2013 were enrolled in this retrospective study. X-tile software, Kaplan–Meier curve and Cox regression model were used to evaluate the prognostic role of them. A predictive nomogram was established to predict prognosis of overall survival (OS), and its accuracy was assessed by concordance index (c-index).ResultsDecreased Alb, pAlb, AFR and elevated FPR were significantly associated with shorter OS. FPR was identified as the most effective prognostic factor to predict 3-year’s OS by time-dependent ROC analysis. A long survival was observed in patients with low level of FPR and the prognosis of stage III FPR-low GC patients undergoing chemotherapy was significantly superior to the patients without the treatment (P=0.002). However, no difference of survival was examined in stage II subgroups stratified by FPR and high FRP of stage III patients with or not the treatment of chemotherapy. C-index of nomogram containing FPR (c-index=0.756) was high in comparison with the nomogram without FPR (c-index =0.748).ConclusionPreoperative FPR might be a feasible prognostic biomarker in surgical stage II and III GC and it could precisely distinguish stage III patients who appeared to obviously benefit from adjuvant chemotherapy. Meanwhile established nomogram based on clinical parameters and FPR could improve its predictive efficacy.

Biomedical named entity recognition (BioNER) is one subtask of named entity recognition (NER) research. Although there are a number of named entity recognition systems, they can not obtain good performances extended to biomedical subfield. BioNER becomes a challenging work. We employ a skip-chain conditional random fields (CRFs) model for BioNER. This model completely considers to the long-range dependencies about biomedical information. These distant dependencies are powerful to identify some frequent appearing named entities and to classify them, especially for both classes protein and cell type. When we test the GENIA corpus, our approach obtains significant improvement over other methods, which achieves precision, recall and F-score of 72.8%, 73.6% and 73.2%, respectively.

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Summary Imatinib mesylate (IM) resistance has become a major clinical problem for chronic myeloid leukaemia (CML). It is known that Bcl‐x splicing is deregulated and is involved in multiple malignant cancer initiation and chemotherapy resistance, including CML. The aim of the present study was to correct the abnormal splicing of Bcl‐x in CML and investigate the subsequent malignant phenotype changes, especially response to IM. The aberrant Bcl‐x splicing in CML cells was effectively restored using vivo‐Morpholino Antisense Oligomer (vMO). CCK‐8 cell viability assay and flow cytometry showed that restoring of Bcl‐x splicing increases IM‐induced growth inhibition and apoptosis of K562 cells. Moreover, a more significant similar phenomenon was observed in imatinib‐resistant CML cell lines K562/G01. Finally, establishment of CML xenograft model had also proved that correcting Bcl‐x splicing in vivo can also enhance the anti‐tumor effect of IM. Our findings suggest that vMO co‐operating with IM can effectively increase the sensitivity of CML cells to IM both in vitro and in vivo, and Bcl‐x splicing could become good candidates for chemotherapy‐sensitized target in IM‐resistant CML.