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Objective To analyze the factors affecting the prognosis of soft tissue sarcomas originating from the mediastinum and lung using relevant data from the SEER database. Methods The data of 376 patients were collected from the SEER database, and were randomly divided into the train set (n=263) and validation set (n=113). The relationship between each variable and patient survival and prognosis was analyzed using the Kaplan-Meier method and Cox proportional risk regression to establish a nomogram, to predict the overall survival of patients. The calibration curves, consistency index, and ROC curves were used to evaluate the performance of the nomogram. Results Histological type, surgery, chemotherapy, tumor size, and tumor stage were the factors affecting the prognosis of primary mediastinal and pulmonary soft tissue sarcomas. The established nomogram could predict the 6-month, 1-year, and 2-year overall survival of patients, and the calibration curves showed good prediction accuracy with measured values. C index of the train set and validation set were 0.754 and 0.745, respectively. The areas under the curve of ROC were 0.849 and 0.924. Conclusion The nomogram established in this study can predict 6-month, 1-year, and 2-year overall survival in patients with primary mediastinal and pulmonary soft tissue sarcoma.

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

Objective To analyze the disease spectrum and prognosis of each pathological subtype of rare lung malignancies. Methods We retrospectively analyzed the clinical data of rare primary lung malignancies diagnosed pathologically from 2004 to 2015 in the SEER database, as well as the composition and incidence trend of each subtype. Kaplan-Meier method was used to calculate the 1-, 3- and 5-year survival rates and draw the survival curves. Results We included 13428 patients totally, including large cell carcinoma, adenosquamous carcinoma, sarcomatoid carcinomas, salivary gland-type tumor, lympho-epithelial carcinoma, mesenchymal tumors and tumors of ectopic origin; and their composition ratios in all lung malignancies in the same period were 1.72%, 1.13%, 0.36%, 0.09%, 0.01%, 0.19% and 0.01%, respectively. The composition ratio of large cell carcinoma decreased year by year, while that of adenosquamous carcinoma increased slowly. The 5-year overall survival rate of all patients with rare lung malignancy was 16.86% and the median survival time was 8 months. Conclusion Adenosquamous carcinoma of the lung has become the first rare primary malignant lung tumor in the sequence of incidence. Rare primary malignant tumors in the lung have poor overall prognosis because the driving gene mutation rate is low and rare mutation type is common.