典型矿冶区周边土壤微生物功能特征及影响因素

土壤微生物对重金属污染胁迫敏感,但在实际野外环境中,土壤微生物群落生态效应通常是污染胁迫和环境因素综合作用的结果。为探究重金属污染土壤中微生物群落生态效应发生变化的主控因素,本研究以湖南省某典型矿冶区周边不同土地利用类型土壤为研究对象,以土壤碳氮循环过程主要的微生物功能指标土壤微生物生物量碳(MBC)、基础呼吸(BR)、诱导呼吸(SIR)和硝化潜势(PNR)为生态效应终点,进行采样调查分析。结果表明: 土地利用类型对MBC、BR和SIR影响均不显著;研究区土壤微生物功能的主要影响因子包括CaCl₂提取态Pb(CaCl₂-Pb)含量与土壤有机质(SOM)含量。多元回归分析结果表明,在CaCl₂-Pb含量为0.004～13.14 mg·kg^-1及SOM含量为0.24%～4.34%的条件下,土壤CaCl₂-Pb和SOM含量可以共同解释土壤中BR、SIR和PNR总变异的39.8%～58.3%;中等含量下(SOM在1.70%～2.36%,CaCl₂-Pb在0.004～12.98 mg·kg^-1),土壤CaCl₂-Pb和SOM含量与BR、SIR和PNR的变化能够建立显著的暴露-效应关系,可以作为测定终点定量评价重金属污染对微生物群落功能的生态效应。     

4D reconstruction of murine developmental trajectories using spherical harmonics

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Panel semiparametric quantile regression neural network for electricity consumption forecasting

Addressing the forecasting issues is one of the core objectives of developing and restructuring of electric power industry in China. However, there are not enough efforts that have been made to develop an accurate electricity consumption forecasting procedure. In this paper, a panel semiparametric quantile regression neural network (PSQRNN) is developed by combining an artificial neural network and semiparametric quantile regression for panel data. By embedding penalized quantile regression with least absolute shrinkage and selection operator (LASSO), ridge regression and backpropagation, PSQRNN keeps the flexibility of nonparametric models and the interpretability of parametric models simultaneously. The prediction accuracy is evaluated based on China's electricity consumption data set, and the results indicate that PSQRNN performs better compared with three benchmark methods including BP neural network (BP), Support Vector Machine (SVM) and Quantile Regression Neural Network (QRNN).     

Immune Signature Against Plasmodium falciparum Antigens Predicts Clinical Immunity in Distinct Malaria Endemic Communities

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Highlights

• •A predictive modelling framework has been established to analyze IgG antibody responses against a large panel of P. falciparum-specific antigens to identify a specific antigen signature of NAI.
• •An individual's immune status can be accurately predicted by measuring IgG responses against a small set of 15 defined parasite antigens.
• •Proteins identified in the 15-antigen signature represent potential candidates for next-generation malaria vaccines or biomarkers for monitoring the impact of malaria interventions.
• •The developed predictive framework can be adapted for developing novel surveillance and intervention tools for other infectious diseases.

     

Comparison of a culture‐based and a PCR‐based methods for estimating bacterial abundance on eggshells,with comments on statistical analyses

Field ornithologists have used traditional culture‐based techniques to determine the presence and abundance of microbes on surfaces such as eggshells, but culture‐independent PCR‐based methods have recently been introduced. We compared the traditional culture‐based and the real‐time PCR‐based methods for detecting and quantifying Escherichia coli on the eggshells of Eurasian Magpies (Pica pica). PCR estimates of bacterial abundance were ～10 times higher than culture‐based estimates, and the culture‐based technique failed to detect bacteria at lower densities. When both methods detected bacteria, bacterial densities determined by the two methods were positively correlated, indicating that both methods can be used to study factors affecting bacterial densities. The difference between the two methods is consistent with generally acknowledged higher sensitivity of the PCR method, but the extent of the difference in our study (10×) may have been influenced by both a PCR‐based overestimation and culture‐based underestimation of bacterial densities. Our results also illustrate that bacterial counts may sometimes produce left‐censored data (i.e., we did not detect E. coli in 62% of our samples using the culture‐based method). Specific statistical methods have been developed for analyzed left‐censored data, but, to our knowledge, have not been used by ornithologists. In future studies, investigators studying bacterial loads should provide information about the possible degree of left censoring and should justify their choice of statistical methods from the broad set of available methods, including those explicitly designed for censored data.     

Imputation of missing prostate cancer stage in English cancer registry data based on clinical assumptions

BackgroundCancer stage can be missing in national cancer registry records. We explored whether missing prostate cancer stage can be imputed using specific clinical assumptions.MethodsProstate cancer patients diagnosed between 2010 and 2013 were identified in English cancer registry data and linked to administrative hospital and mortality data (n = 139,807). Missing staging items were imputed based on specific assumptions: men with recorded N-stage but missing M-stage have no distant metastases (M0); low/intermediate-risk men with missing N- and/or M-stage have no nodal disease (N0) or metastases; and high-risk men with missing M-stage have no metastases. We tested these clinical assumptions by comparing 4-year survival in men with the same recorded and imputed cancer stage. Multi-variable Cox regression was used to test the validity of the clinical assumptions and multiple imputation.ResultsSurvival was similar for men with recorded N-stage but missing M-stage and corresponding men with M0 (89.5% vs 89.6%); for low/intermediate-risk men with missing M-stage and corresponding men with M0 (92.0% vs 93.1%); and for low/intermediate-risk men with missing N-stage and corresponding men with N0 (90.9% vs 93.7%). However, survival was different for high-risk men with missing M-stage and corresponding men with M0. Imputation based on clinical imputation performs as well as statistical multiple imputation.ConclusionSpecific clinical assumptions can be used to impute missing information on nodal involvement and distant metastases in some patients with prostate cancer.     

Heavier halides of transition metals by halide exchange

Examples are reported of heavier (bromides or iodides) metal halides of the d or f transition series being prepared through the halide exchange reaction from the lighter congeners (fluorides or chlorides, easily prepared by direct combination from the elements), by using gaseous hydrogen halides HX or alkyl halides RX in an anhydrous organic solvent at room temperature or even below. This represents a considerable improvement with respect to the traditional high-temperature experimental procedures from the elements. Thermodynamic data show that this synthetic route is of quite general validity.     

Integrating vegetation field surveys with remotely sensed data

Summary   This paper explores data compatibility issues arising from the assessment of remnant native vegetation condition using satellite remote sensing and field-based data. Space-borne passive remote sensing is increasingly used as a way of providing a total sample and synoptic overview of the spectral and spatial characteristics of native vegetation canopies at a regional scale. However, integrating field-collected data often not designed for integration with remotely sensed data can lead to data compatibility issues. Subsequent problems associated with the integration of unsuited datasets can contribute to data uncertainty and result in inconclusive findings. It is these types of problems (and potential solutions) that form the basis of this paper. In other words, how can field surveys be designed to support and improve compatibility with remotely sensed total surveys? Key criteria were identified for consideration when designing field-based surveys of native vegetation condition (and other similar applications) with the intent to incorporate remotely sensed data. The criteria include recommendations for the siting of plots, the need for reference location plots, the number of sample sites and plot size and distribution, within a study area. The difficulties associated with successfully integrating these data are illustrated using real examples taken from a study of the vegetation in the Little River Catchment, New South Wales, Australia.