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Yutao Wang, China Medical University, China The tumor microenvironment (TME) has been shown to impact the prognosis of tumors in patients including cutaneous melanoma (CM); however, not all components of TME are important. Given the aforementioned situation, the functional immune cell contents correlated with CM patient prognosis are needed to optimize present predictive models and reflect the overall situation of TME. We developed a novel risk score named core tumor-infiltrating immune cell score (cTICscore), which showed certain advantages over existing biomarkers or TME-related signatures in predicting the prognosis of CM patients. Furthermore, we explored a new gene signature named cTILscore-related module gene score (cTMGs), based on four identified TME-associated genes (GCH1, GZMA, PSMB8, and PLAAT4) showing a close correlation with the cTICscore, which was generated by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis to facilitate clinical application. Patients with low cTMGs had significantly better overall survival (OS, P = 0.002,< 0.001, = 0.002, and = 0.03, respectively) in the training and validating CM datasets. In addition, the area under the curve values used to predict the immune response in four CM cohorts were 0.723, 0.723, 0.754, and 0.792, respectively, and that in one gastric cohort was 0.764. Therefore, the four-gene signature, based on cTICscore, might improve prognostic information, serving as a predictive tool for CM patients receiving immunotherapy. cutaneous melanoma, tumor microenvironment, prognosis, immunotherapy, cTICscore. [ABSTRACT FROM AUTHOR]

The Dynamical--Statistical--Analog Ensemble Forecast model for landfalling typhoon precipitation (the DSAEF_ LTP model) identifies tropical cyclones (TCs) from history data that are similar to a target TC and then assembles the precipitation amounts and distributions of those identified to obtain those of the target TC. Two original ensemble methods in the DSAEF_LTP model, namely, mean and maximum, tend to under- and over- forecast TC precipitation, respectively. In addition, these two methods are unable to forecast precipitation at stations beyond their maxima. To overcome the shortcomings and improve the forecast performance of the DSAEF_LTP model, the following five new ensemble methods are incorporated: optimal percentile, fuse, probability-matching mean, equal difference-weighted mean, and TC track Similarity Area Index-weighted mean. Then, model experiments for landfalling TCs over China in 2018 are conducted to evaluate the forecast performance of the DSAEF_LTP model with the new ensemble methods. Results show that the overall performance of the optimal percentile (the 90th percentile) ensemble method is superior, with the false alarm rate lower than that of the original ensemble methods. As compared to five operational numerical weather prediction models, the improved DSAEF_LTP model shows advantages in predicting accumulated rainfall, especially with rainfall of over 250 mm. When implementing the experiments, above results, however, it is found that the model forecast performance varies, depending on the type of TC tracks. That is, the accumulated rainfall forecast for westbound TCs is significantly better than that of northbound TCs. To address this issue, different schemes are used to forecast the accumulated rainfall of TCs with the two different track types. The precipitation forecast performance for westbound and northbound TCs, using the 90th percentile and the probability-matching ensemble mean ensemble method, respectively, is much better than that using a single ensemble method for all TCs. [ABSTRACT FROM AUTHOR]

The article discusses a study of clade 2.3.2 avian influenza virus (H5N1) isolated in the Qinghai Lake Region of China from May to June 2009 and 2010. Several migratory birds found to be having the H5N1 virus isolate are great cormorants, brown-headed gulls and great-crested grebes. It suggests the likelihood that viruses previously isolated in Mongolia and Russia, and the China isolates were transmitted between the two lake regions by bird migration. It notes that the 2009 and 2010 viruses are related to various viruses isolated from plateau pikas near Qinghai Lake. It calls for investigation of new outbreaks of H5N1 viruses along the migratory route near Qinghai Lake.