Input of Cd from agriculture phosphate fertilizer application in China during 2006-2016.

Phosphate fertilizer applications are an important source of soil Cd in China. However, the input of Cd from phosphate fertilizer has always been neglected in China because of its low content. In this paper, we calculated the Cd input from phosphate fertilizer in China during 2006-2016.

LEP: A Statistical Method Integrating Individual-Level and Summary-Level Data of the Same Trait From Different Populations.

Statistical approaches for integrating multiple data sets in genome-wide association studies (GWASs) are increasingly important. Proper utilization of more relevant information is expected to improve statistical efficiency in the analysis. Among these approaches, LEP was proposed for joint analysis of individual-level data and summary-level data in the same population by leveraging pleiotropy.

Assessing heavy metal pollution in paddy soil from coal mining area, Anhui, China.

Heavy metal pollution in agricultural soil has negative impact on crop quality and eventually on human health. A total of 24 top soil samples were collected from paddy field near the Zhangji Coal Mine in Huainan City, Anhui Province. Seven heavy metals (Cu, Zn, As, Cr, Cd, Pb, and Ni) were selected to evaluate the pollution status through total content and chemical speciation, geo-accumulation index (I), and risk assessment code (RAC) and investigate leaching behavior of heavy metals under simulated rainfall.

Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy.

Motivation: A large number of recent genome-wide association studies (GWASs) for complex phenotypes confirm the early conjecture for polygenicity, suggesting the presence of large number of variants with only tiny or moderate effects. However, due to the limited sample size of a single GWAS, many associated genetic variants are too weak to achieve the genome-wide significance. These undiscovered variants further limit the prediction capability of GWAS.

LPG: A four-group probabilistic approach to leveraging pleiotropy in genome-wide association studies.

Background: To date, genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants among a variety of traits/diseases, shedding light on the genetic architecture of complex disease. The polygenicity of complex diseases is a widely accepted phenomenon through which a vast number of risk variants, each with a modest individual effect, collectively contribute to the heritability of complex diseases. This imposes a major challenge on fully characterizing the genetic bases of complex diseases.

Current status and environment impact of direct straw return in China's cropland - A review.

With the development of grain production technologies and improvement of rural living standard, the production and utilization of straw have significantly been changed in China. More than 1 billion tones of straw are produced per year, and vast amount of them are discarded without effective utilization, leading various environmental and social impacts. Straw return is an effective approach of the straw utilization that has been greatly recommended by government and scientists in China.

LSMM: a statistical approach to integrating functional annotations with genome-wide association studies.

Motivation: Thousands of risk variants underlying complex phenotypes (quantitative traits and diseases) have been identified in genome-wide association studies (GWAS). However, there are still two major challenges towards deepening our understanding of the genetic architectures of complex phenotypes. First, the majority of GWAS hits are in non-coding region and their biological interpretation is still unclear.

IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies.

Motivation: Results from genome-wide association studies (GWAS) suggest that a complex phenotype is often affected by many variants with small effects, known as 'polygenicity'. Tens of thousands of samples are often required to ensure statistical power of identifying these variants with small effects. However, it is often the case that a research group can only get approval for the access to individual-level genotype data with a limited sample size (e.

[Establishment of a genetic transformation system for Penicillium brevicompactum to produce mycophenolic acid].

Objective: We established a genetic transformation system for Penicillium brevicompactum to produce mycophenolic acid.

Methods: We developed protoplast transformation methods mediated by Polyethylene glycol, using phleomycin resistance gene (Sh ble) as a dominant selection marker.

Result: The frequency of transformation was up to 2 - 3 transformants per microg DNA; analysis of the transformants by PCR showed that the foreign DNA had been integrated into the host genome.

Fast and efficient strategies for model selection of Gaussian support vector machine.

Two strategies for selecting the kernel parameter (sigma) and the penalty coefficient (C) of Gaussian support vector machines (SVMs) are suggested in this paper. Based on viewing the model parameter selection problem as a recognition problem in visual systems, a direct parameter setting formula for the kernel parameter is derived through finding a visual scale at which the global and local structures of the given data set can be preserved in the feature space, and the difference between the two structures can be maximized. In addition, we propose a heuristic algorithm for the selection of the penalty coefficient through identifying the classification extent of a training datum in the implementation process of the sequential minimal optimization (SMO) procedure, which is a well-developed and commonly used algorithm in SVM training.