The Mitochondrial Genome of Baylisascaris procyonis

BACKGROUND: Baylisascaris procyonis (Nematoda: Ascaridida), an intestinal nematode of raccoons, is emerging as an important helminthic zoonosis due to serious or fatal larval migrans in animals and humans. Despite its significant veterinary and public health impact, the epidemiology, molecular ecology and population genetics of this parasite remain largely unexplored. Mitochondrial (mt) genomes can provide a foundation for investigations in these areas and assist in the diagnosis and control of B. procyonis. In this study, the first complete mt genome sequence of B. procyonis was determined using a polymerase chain reaction (PCR)-based primer-walking strategy. METHODOLOGY/PRINCIPAL FINDINGS: The circular mt genome (14781 bp) of B. procyonis contained 12 protein-coding, 22 transfer RNA and 2 ribosomal RNA genes congruent with other chromadorean nematodes. Interestingly, the B. procyonis mtDNA featured an extremely long AT-rich region (1375 bp) and a high number of intergenic spacers (17), making it unique compared with other secernentean nematodes characterized to date. Additionally, the entire genome displayed notable levels of AT skew and GC skew. Based on pairwise comparisons and sliding window analysis of mt genes among the available 11 Ascaridida mtDNAs, new primer pairs were designed to amplify specific short fragments of the genes cytb (548 bp fragment) and rrnL (200 bp fragment) in the B. procyonis mtDNA, and tested as possible alternatives to existing mt molecular beacons for Ascaridida. Finally, phylogenetic analysis of mtDNAs provided novel estimates of the interrelationships of Baylisasaris and Ascaridida. CONCLUSIONS/SIGNIFICANCE: The complete mt genome sequence of B. procyonis sequenced here should contribute to molecular diagnostic methods, epidemiological investigations and ecological studies of B. procyonis and other related ascaridoids. The information will be important in refining the phylogenetic relationships within the order Ascaridida and enriching the resource of markers for systematic, population genetic and evolutionary biological studies of parasitic nematodes of socio-economic importance

Illegal births and legal abortions – the case of China

BACKGROUND: China has a national policy regulating the number of children that a woman is allowed to have. The central concept at the individual level application is "illegal pregnancy". The purpose of this article is to describe and problematicize the concept of illegal pregnancy and its use in practice. METHODS: Original texts and previous published and unpublished reports and statistics were used. RESULTS: By 1979 the Chinese population policy was clearly a policy of controlling population growth. For a pregnancy to be legal, it has to be defined as such according to the family-level eligibility rules, and in some places it has to be within the local quota. Enforcement of the policy has been pursued via the State Family Planning (FP) Commission and the Communist Party (CP), both of which have a functioning vertical structure down to the lowest administrative units. There are various incentives and disincentives for families to follow the policy. An extensive system has been created to keep the contraceptive use and pregnancy status of all married women at reproductive age under constant surveillance. In the early 1990s FP and CP officials were made personally responsible for meeting population targets. Since 1979, abortion has been available on request, and the ratio of legal abortions to birth increased in the 1980s and declined in the 1990s. Similar to what happens in other Asian countries with low fertility rates and higher esteem for boys, both national- and local-level data show that an unnaturally greater number of boys than girls are registered as having been born. CONCLUSION: Defining a pregnancy as "illegal" and carrying out the surveillance of individual women are phenomena unique in China, but this does not apply to other features of the policy. The moral judgment concerning the policy depends on the basic question of whether reproduction should be considered as an individual or social decision

Distamycin A Inhibits HMGA1-Binding to the P-Selectin Promoter and Attenuates Lung and Liver Inflammation during Murine Endotoxemia

Background: The architectural transcription factor High Mobility Group-A1 (HMGA1) binds to the minor groove of AT-rich DNA and forms transcription factor complexes (“enhanceosomes”) that upregulate expression of select genes within the inflammatory cascade during critical illness syndromes such as acute lung injury (ALI). AT-rich regions of DNA surround transcription factor binding sites in genes critical for the inflammatory response. Minor groove binding drugs (MGBs), such as Distamycin A (Dist A), interfere with AT-rich region DNA binding in a sequence and conformation-specific manner, and HMGA1 is one of the few transcription factors whose binding is inhibited by MGBs. Objectives: To determine whether MGBs exert beneficial effects during endotoxemia through attenuating tissue inflammation via interfering with HMGA1-DNA binding and modulating expression of adhesion molecules. Methodology/Principal Findings: Administration of Dist A significantly decreased lung and liver inflammation during murine endotoxemia. In intravital microscopy studies, Dist A attenuated neutrophil-endothelial interactions in vivo following an inflammatory stimulus. Endotoxin induction of P-selectin expression in lung and liver tissue and promoter activity in endothelial cells was significantly reduced by Dist A, while E-selectin induction was not significantly affected. Moreover, Dist A disrupted formation of an inducible complex containing NF-κB that binds an AT-rich region of the P-selectin promoter. Transfection studies demonstrated a critical role for HMGA1 in facilitating cytokine and NF-κB induction of P-selectin promoter activity, and Dist A inhibited binding of HMGA1 to this AT-rich region of the P-selectin promoter in vivo. Conclusions/Significance: We describe a novel targeted approach in modulating lung and liver inflammation in vivo during murine endotoxemia through decreasing binding of HMGA1 to a distinct AT-rich region of the P-selectin promoter. These studies highlight the ability of MGBs to function as molecular tools for dissecting transcriptional mechanisms in vivo and suggest alternative treatment approaches for critical illness

Simulation of Regulation Policies for Fertilizer and Pesticide Reduction in Arable Land Based on Farmers’ Behavior—Using Jiangxi Province as an Example

A multi-agent model for the simulation of arable land management based on the complex adaptive system theory and a Swarm platform was constructed. An empirical application of the model was carried out to investigate the pollution of arable land in Jiangxi Province. Two sets of policies—a fertilizer tax and an ecological compensation scheme—were designed and simulated, and the analysis focused on the control of polluting inputs, mainly chemical fertilizers and pesticides. The environmental effects of each policy were evaluated by simulating farmers’ self-adaptive behaviours in response to the policy in the artificial village of the model. The results showed the following: (1) Both the fertilizer tax policy and the ecological compensation policy somewhat alleviated the negative impact of input factors, such as fertilizers and pesticides, on arable land; (2) if the fertilizer tax policy is implemented, the medium tax rate scheme should be given priority—the effect does not necessarily improve as the tax rate increases, and a high-tax policy will threaten food security in the long term; and (3) if an ecological compensation policy is implemented, high-government-compensation scenarios are better than low-government-compensation scenarios, and the differential-government-compensation scenario is better than the equal-government-compensation scenario, and the differential-government-compensation scenario can lighten the burden on the government

Analysis of Spatial Disparities and Driving Factors of Energy Consumption Change in China Based on Spatial Statistics

The changes of spatial pattern in energy consumption have an impact on global climate change. Based on the spatial autocorrelation analysis and the auto-regression model of spatial statistics, this study has explored the spatial disparities and driving forces in energy consumption changes in China. The results show that the global spatial autocorrelation of energy consumption change in China is significant during the period 1990–2010, and the trend of spatial clustering of energy consumption change is weakened. The regions with higher energy consumption change are significantly distributed in the developed coastal areas in China, while those with lower energy consumption change are significantly distributed in the less developed western regions in China. Energy consumption change in China is mainly caused by transportation industry and non-labor intensive industry. Rapid economic development and higher industrialization rate are the main causes for faster changes in energy consumption in China. The results also indicate that spatial autoregressive model can reveal more influencing factors of energy consumption changes in China, in contrast with standard linear model. At last, this study has put forward the corresponding measures or policies for dealing with the growing trend of energy consumption in China

Exploring the Mechanisms of Ecological Land Change Based on the Spatial Autoregressive Model: A Case Study of the Poyang Lake Eco-Economic Zone, China

Ecological land is one of the key resources and conditions for the survival of humans because it can provide ecosystem services and is particularly important to public health and safety. It is extremely valuable for effective ecological management to explore the evolution mechanisms of ecological land. Based on spatial statistical analyses, we explored the spatial disparities and primary potential drivers of ecological land change in the Poyang Lake Eco-economic Zone of China. The results demonstrated that the global Moran’s I value is 0.1646 during the 1990 to 2005 time period and indicated significant positive spatial correlation (p < 0.05). The results also imply that the clustering trend of ecological land changes weakened in the study area. Some potential driving forces were identified by applying the spatial autoregressive model in this study. The results demonstrated that the higher economic development level and industrialization rate were the main drivers for the faster change of ecological land in the study area. This study also tested the superiority of the spatial autoregressive model to study the mechanisms of ecological land change by comparing it with the traditional linear regressive model

Integration of ZiYuan-3 Multispectral and Stereo Data for Modeling Aboveground Biomass of Larch Plantations in North China

Data saturation in optical sensor data has long been recognized as a major factor that causes underestimation of aboveground biomass (AGB) for forest sites having high AGB, but there is a lack of suitable approaches to solve this problem. The objective of this research was to understand how incorporation of forest canopy features into high spatial resolution optical sensor data improves forest AGB estimation. Therefore, we explored the use of ZiYuan-3 (ZY-3) satellite imagery, including multispectral and stereo data, for AGB estimation of larch plantations in North China. The relative canopy height (RCH) image was calculated from the difference of digital surface model (DSM) data at leaf-on and leaf-off seasons, which were extracted from the ZY-3 stereo images. Image segmentation was conducted using eCognition on the basis of the fused ZY-3 multispectral and panchromatic data. Spectral bands, vegetation indices, textural images, and RCH-based variables based on this segment image were extracted. Linear regression was used to develop forest AGB estimation models, where the dependent variable was AGB from sample plots, and explanatory variables were from the aforementioned remote-sensing variables. The results indicated that incorporation of RCH-based variables and spectral data considerably improved AGB estimation performance when compared with the use of spectral data alone. The RCH-variable successfully reduced the data saturation problem. This research indicated that the combined use of RCH-variables and spectral data provided more accurate AGB estimation for larch plantations than the use of spectral data alone. Specifically, the root mean squared error (RMSE), relative RMSE, and mean absolute error values were 33.89 Mg/ha, 29.57%, and 30.68 Mg/ha, respectively, when using the spectral-only model, but they become 24.49 Mg/ha, 21.37%, and 20.37 Mg/ha, respectively, when using the combined model with RCH variables and spectral band. This proposed approach provides a new insight in reducing the data saturation problem

Complete mitochondrial genome of Nanorana pleskei (Amphibia: Anura: Dicroglossidae) and evolutionary characteristics of the amphibian mitochondrial genomes

The complete mitochondrial genome of Nanorana pleskei from the Qinghai-Tibet Plateau was sequenced. It includes 17,660 base pairs, containing 13 protein-coding genes, two rRNAs and 23 tRNAs. A tandem duplication of tRNAMet gene was found in this mitochondrial genome, and the similarity between the two tRNAMet genes is 85.8%, being the highest in amphibian mitochondrial genomes sequenced thus far. Based on gene organization, 24 types were found from 145 amphibian mitochondrial genomes. Type 1 was present in 108 species, type 11 in 11 species, types 5, 16, 17, and 20 each in two species, and the others each present in one species. Fifteen types were found in Anura, being the most diversity in three orders of the Lissamphibia. Our phylogenetic results using 11 protein-coding gene sequences of 145 amphibian mitochondrial genomes strongly support the monophyly of the Lissamphibia, as well as its three orders, the Gymnophiona, Caudata, and Anura, among which the relationships were ((Gymnophiona (Caudata, Anura)). Based on the phylogenetic trees, type 1 was recognized as the ancestral type for amphibians, and type 11 was the synapomorphic type for the Neobatrachia. Gene rearrangements among lineages provide meaningful phylogenetic information. The rearrangement of the LTPF tRNA gene cluster and the translocation of the ND5 gene only found in the Neobatrachia support the monophyly of this group; similarly, the tandem duplication of the tRNAMet genes only found in the Dicroglossidae support the monophyly of this family [Current Zoology 57 (6): 785–805, 2011]

Does the Expansion of Urban Construction Land Promote Regional Economic Growth in China? Evidence from 108 Cities in the Yangtze River Economic Belt

Since the reform and opening up, China’s economy has maintained rapid growth. At the same time, the process of urbanization in China has been accelerating and the scale of urban construction land has expanded accordingly. The purpose of the research is to explore whether there is an inevitable connection between the expansion of urban construction land and economic growth. This study uses 108 prefecture-level cities in the Yangtze River Economic Belt as an example. Considering panel data from 2005 to 2015, the spatial econometric model was used to explore the impact of urban construction land expansion on regional economic growth. The results are as follows: (1) The expansion of construction land in cities in the Yangtze River Economic Belt has a significant impact on economic growth but the extent of the impact is not as great as that of capital stock. (2) In the Yangtze River Economic Belt, the expansion of urban construction land in a certain area has not only a positive effect on the local economic growth but also a certain spillover effect and it can promote the economic development level of the adjacent areas in the economic belt. (3) Although the expansion of urban construction land along the Yangtze River Economic Belt promotes economic growth, there are obvious differences between regions. The expansion of urban construction land in the central region of the Yangtze River Economic Belt has a significant driving effect on economic growth. However, the expansion of urban construction land in the eastern and western regions has no significant effect on the economic growth of the respective regions. Finally, based on the above conclusions, this paper proposes corresponding policy recommendations for economic development in different regions. These research conclusions will also facilitate the follow-up of other researchers to further explore the driving factors of the economic development of many prefecture-level cities in the Yangtze River Economic Belt and the related mechanisms for the expansion of construction land to promote economic growth

Classification of Land Cover, Forest, and Tree Species Classes with ZiYuan-3 Multispectral and Stereo Data

The global availability of high spatial resolution images makes mapping tree species distribution possible for better management of forest resources. Previous research mainly focused on mapping single tree species, but information about the spatial distribution of all kinds of trees, especially plantations, is often required. This research aims to identify suitable variables and algorithms for classifying land cover, forest, and tree species. Bi-temporal ZiYuan-3 multispectral and stereo images were used. Spectral responses and textures from multispectral imagery, canopy height features from bi-temporal stereo imagery, and slope and elevation from the stereo-derived digital surface model data were examined through comparative analysis of six classification algorithms including maximum likelihood classifier (MLC), k-nearest neighbor (kNN), decision tree (DT), random forest (RF), artificial neural network (ANN), and support vector machine (SVM). The results showed that use of multiple source data—spectral bands, vegetation indices, textures, and topographic factors—considerably improved land-cover and forest classification accuracies compared to spectral bands alone, which the highest overall accuracy of 84.5% for land cover classes was from the SVM, and, of 89.2% for forest classes, was from the MLC. The combination of leaf-on and leaf-off seasonal images further improved classification accuracies by 7.8% to 15.0% for land cover classes and by 6.0% to 11.8% for forest classes compared to single season spectral image. The combination of multiple source data also improved land cover classification by 3.7% to 15.5% and forest classification by 1.0% to 12.7% compared to the spectral image alone. MLC provided better land-cover and forest classification accuracies than machine learning algorithms when spectral data alone were used. However, some machine learning approaches such as RF and SVM provided better performance than MLC when multiple data sources were used. Further addition of canopy height features into multiple source data had no or limited effects in improving land-cover or forest classification, but improved classification accuracies of some tree species such as birch and Mongolia scotch pine. Considering tree species classification, Chinese pine, Mongolia scotch pine, red pine, aspen and elm, and other broadleaf trees as having classification accuracies of over 92%, and larch and birch have relatively low accuracies of 87.3% and 84.5%. However, these high classification accuracies are from different data sources and classification algorithms, and no one classification algorithm provided the best accuracy for all tree species classes. This research implies the same data source and the classification algorithm cannot provide the best classification results for different land cover classes. It is necessary to develop a comprehensive classification procedure using an expert-based approach or hierarchical-based classification approach that can employ specific data variables and algorithm for each tree species class