A CASE STUDY OF CHINA ́S WIND POWER RESOURCES

At present, China is the largest energy producer and the second largest energy consumer in the world. With the increasing pressure to cut GHS emissions and to improve energy efficiency, China is now changing its traditional energy mix, mainly through consuming more renewable energy instead of fossil energy. This change has resulted in a policy adjustment which in turn boosts the utilization of the wind power resources. However, the development of the wind power resources in China is confronted with some significant challenges, such as greater installed electricity capacity than the electricity generation, greater electricity generation than the electricity transmission capacity and greater inland wind power generation than the offshore wind power generation. Therefore, the further development of China’s wind power electricity in the coming years depends largely on the ways these challenges will be addressed

The Systemic Evaluation and Clinical Significance of Immunological Function for Advanced Lung Cancer Patients

Background and objective The actual evaluation of immunological function is significant for studing the tumor development and devising a treatment in time. The aim of this study is to evaluate the immunological function of advanced lung cancer patients systematically, and to discuss the clinical significance. Methods The nucleated cell amounts of advanced lung cancer patients and the healthy individuals were counted. The immune cell subsets and the levels of IL-4, INF-γ, perforin and granzyme in CD8+T cells by the flow cytometry were measured. The proliferation activity and the inhibition ratio of immune cells to several tumor cell lines were evaluated by MTT assay. Results The absolute amounts and subsets of T, B, NK cells of advanced lung cancer patients were lower than the healthy individuals (P < 0.05); However, the proportion of regulatory T cells of advanced lung cancer patients (4.00±1.84)% was lower than the healthy individuals (1.27±0.78)% (P < 0.05). The positive rates of IFN-γ perforin, granzyme in CD8+T cells decreased while them in IL-4 did not in the advanced lung cancer patients compared to the healthy control group (P < 0.05). The proliferation activity of immune cells, the positive rate of PPD masculine and the inhibition ratio to tumor cells in the advanced lung cancer patients was lower than the healthy subsets obviously (P < 0.05). Conclusion There was a significant immune depression in the advanced lung cancer patients compared to the healthy individuals

Pulse Diagnosis Signals Analysis of Fatty Liver Disease and Cirrhosis Patients by Using Machine Learning

Objective. To compare the signals of pulse diagnosis of fatty liver disease (FLD) patients and cirrhosis patients. Methods. After collecting the pulse waves of patients with fatty liver disease, cirrhosis patients, and healthy volunteers, we do pretreatment and parameters extracting based on harmonic fitting, modeling, and identification by unsupervised learning Principal Component Analysis (PCA) and supervised learning Least squares Regression (LS) and Least Absolute Shrinkage and Selection Operator (LASSO) with cross-validation step by step for analysis. Results. There is significant difference between the pulse diagnosis signals of healthy volunteers and patients with FLD and cirrhosis, and the result was confirmed by 3 analysis methods. The identification accuracy of the 1st principal component is about 75% without any classification formation by PCA, and supervised learning’s accuracy (LS and LASSO) was even more than 93% when 7 parameters were used and was 84% when only 2 parameters were used. Conclusion. The method we built in this study based on the combination of unsupervised learning PCA and supervised learning LS and LASSO might offer some confidence for the realization of computer-aided diagnosis by pulse diagnosis in TCM. In addition, this study might offer some important evidence for the science of pulse diagnosis in TCM clinical diagnosis

Comparison of proteomic landscape of extracellular vesicles in pleural effusions isolated by three strategies

Extracellular vesicles (EVs) derived from pleural effusion (PE) is emerging as disease biomarkers. However, the methods for isolation of EVs from PE (pEVs) were rarely studied. In our study, three methods for isolating pEVs of lung cancer patients were compared, including ultracentrifugation (UC), a combination of UC and size exclusion chromatography (UC-SEC) and a combination of UC and density gradient ultracentrifugation (UC-DGU). The subpopulation of pEVs was identified by nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), Western blotting (WB) and nano-flow cytometry (nFCM). Additionally, the proteomic landscape of pEVs was analyzed by Label-free proteomics. The results showed that, compared with UC and UC-DGU, the UC-SEC method separated pEVs with the highest purity. In the proteomic analysis, on average, 1595 proteins were identified in the pEVs isolated by UC-SEC, much more than pEVs isolated by UC (1222) or UC-DGU (807). Furthermore, approximately 90% of identified proteins in each method were found in the EVs public database ExoCarta. Consistent with this, GO annotation indicated that the core proteins identified in each method were mainly enriched in “extracellular exosome.” Many of the top 100 proteins with high expression in each method were suggested as protein markers to validate the presence of EVs in the MISEV2018 guidelines. In addition, combined with lung tissue-specific proteins and vesicular membrane proteins, we screened out and validated several novel protein markers (CD11C, HLA DPA1 and HLA DRB1), which were enriched in pEVs rather than in plasma EVs. In conclusion, our study shows that the method of UC-SEC could significantly improve the purity of EVs and the performance of mass spectrometry-based proteomic profiling in analyzing pEVs. The exosomal proteins CD11C, HLA DPA1 and HLA DRB1 may act as potential markers of pEVs. The proteomic analysis of pEVs provides important information and new ideas for studying diseases complicated with PE

Exploring the diversity and potential functional characteristics of microbiota associated with different compartments of Schisandra chinensis

IntroductionSymbiotic microbial have a significant impact on the growth and metabolism of medicinal plants. Schisandra chinensis is a very functionally rich medicinal herb; however, its microbial composition and diversity have been poorly studied.MethodsIn the present study, the core microbiomes associated with the rhizospheric soil, roots, stems, leaves, and fruits of S. chinensis from six geographic locations were analyzed by a macro-genomics approach.ResultsAlpha and beta diversity analyses showed that the diversity of microbial composition of S. chinensis fruits did not differ significantly among the geographic locations as compared to that in different plant compartments. Principal coordinate analysis showed that the microbial communities of S. chinensis fruits from the different ecological locations were both similar and independent. In all S. chinensis samples, Proteobacteria was the most dominant bacterial phylum, and Ascomycota and Basidiomycota were the most dominant fungal phyla. Nitrospira, Bradyrhizobium, Sphingomonas, and Pseudomonas were the marker bacterial populations in rhizospheric soils, roots, stems and leaves, and fruits, respectively, and Penicillium, Golubevia, and Cladosporium were the marker fungal populations in the rhizospheric soil and roots, stems and leaves, and fruits, respectively. Functional analyses showed a high abundance of the microbiota mainly in biosynthesis.DiscussionThe present study determined the fungal structure of the symbiotic microbiome of S. chinensis, which is crucial for improving the yield and quality of S. chinensis