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The concepts of resilience and sustainability are becoming popular in disaster planning and management. However, there is an absence of mutual considerations of the two concepts from an integrated perspective to promote post-disaster livelihood, particularly in the relocated rural communities. To fill the research gap, this paper explores the factors and relationships of resilient rural livelihoods (RRL) and sustainable rural livelihoods (SRL) in resettlement communities after a major disaster. Specifically, we construct a theoretical model that integrates resources, strategies, and outcomes of RRL and SRL in the recovery phase. We use a dataset for household-level recovery after the Jiangsu Tornado (2016) in China to validate the theoretical model with a structural equation modeling (SEM) approach. Results show that government-driven, recovery-concentrated policies of "resilience" may not promote the long-term sustainability of rural household livelihoods because financial capital and institutional participation are negatively associated with the community's self-reliance for future disaster recovery. The tangible assets are likely to make people more confident in disaster preparedness, while the intangible assets lack such an impact and even make the relocated households concerned about future disasters. For RRL outcomes, financial capital and socio-political capital can enhance the recovery, while human capital and livelihood strategies have negative effects. In addition, natural capital and financial capital positively affect household recovery, but the human capital remains a negative contributor. These findings clearly reveal the general patterns of rural livelihoods in relocated communities after a disaster and provide insights into potential measures to promote sustainable and resilient rural livelihoods. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the efficiency of the powdered formulation with the nematophagous fungi Duddingtonia flagrans against gastrointestinal nematodes of sheep under three feeding systems in Northern China. Each animal in the treatment group received approximately 5×105 spores/kg live weight at twice a week for 6 months. The control group received an equal amount of feeds without fungus. In the grazing system, two herds were selected in the Tongyu County in Northeast China. Among them, 70 sheep as the treatment group and 100 sheep as the control group. These results revealed that fungal group showed a greater reduction in eggs per gram of feces (EPG), infective larvae (L3) per kilogram in pasture and larvae per gram of feces (LPG) after administration and lower parasitic load burden in the tracer lambs compared with the control group (p<0.05). In the semi-confinement system, 20, 15, and 15 sheep from three individual farmers were selected from Zhangye City of Northwestern China; 20 sheep as the control group and the remaining sheep as the treatment group. The fungal group showed a greater reduction in EPG after 150 and 180 days and LGP from 60~180 days after administration (p<0.05). In the confinement feeding system, 40 lambs were randomly divided into the treatment and control groups. The results showed that no differences in EPG and LGP were observed in the two groups (p>0.05). In conclusion, the powder was efficient in controlling sheep gastrointestinal helminths under three feeding systems in Northern China. [ABSTRACT FROM AUTHOR]

Abstract Previous studies on air pollution exposure have mostly focused on the urban, regional, national and global scales, but the outcomes cannot well support risk assessments in urban communities. To determine how the urban form and meteorology influence the air pollution distribution at a neighborhood scale (2 km*2 km), we performed a fine-scale investigation of a typical air pollutant (i.e., PM 2.5) by mobile measurements in two communities in the inner and outer cities of Shanghai, China. The PM 2.5 mass concentrations and potential impacting factors, such as PM 2.5 background levels, road networks, traffic volumes, meteorological parameters, building heights and land use types, were collected at a 10 m spatial resolution, and their relationships were analyzed using both a generalized additive model (GAM) and land use regression (LUR). The modeling results showed that the GAM outperformed LUR in both study areas, with a higher adjusted R2 and a lower RMSE. The PM 2.5 was found to have drastic variations at the neighborhood scale, which was primarily driven by spatial patterns of the PM 2.5 background levels and traffic volumes. The GAM-based PM 2.5 concentration surface clearly disclosed the heterogeneous variation of the PM 2.5 mass concentrations in each community, and demonstrated the prominent influence from the nearby highway, especially in the central urban area. This study provides the first empirical evidence of the exposure heterogeneity of the air pollution on a neighborhood scale, which can assist planners and policymakers in evaluating planning strategies with a full consideration of reducing local air pollution. Highlights • Mobile measurements of PM 2.5 concentrations are performed in two neighborhoods of Shanghai. • Generalized additive models outperform land use regressions for assessing PM 2.5 variations. • PM 2.5 of high values are mainly distributed alongside highways up to 100–300 m. • Building height with wind speed primarily determines PM 2.5 variations in the central urban area. • PM 2.5 variations in the suburban area are mainly impacted by regional emission sources. [ABSTRACT FROM AUTHOR]

Background: According to the Japanese Esophageal Society (JES) guidelines, early esophageal squamous cell carcinoma (SCC) involving the muscularis mucosae (M3) or upper submucosal (SM1) layers are relative indications for endoscopic submucosal dissection (ESD). Additional esophagectomy or chemoradiotherapy is recommended for patients with relative indications after evaluation. However, elderly patients (≥ 60 years) with relative indications in China often refuse additional treatment because of the debilitating side effects. The aim of this study was to evaluate the long-term outcomes of elderly patients with relative indications who did not undergo additional treatment after ESD.Methods: Data from elderly patients with relative indications who underwent ESD for early esophageal SCC between January 2008 and December 2013 were reviewed retrospectively. Stricture and recurrence, and 5-year progression-free survival (PFS) and overall survival rates were compared with patients with absolute indications for ESD.Results: 158 elderly patients were included and analyzed (89 in the absolute indications group and 69 in the relative indications group). The baseline characteristics were balanced between the two groups. During 56 months (range 1 - 108) of follow-up, the postoperative stricture rates were similar in the absolute and relative indications groups (21.3 % vs. 31.9 %; P  = 0.13). The hazard ratio (HR) for PFS in the absolute vs. the relative indications groups was 1.025 (95 % confidence interval [CI] 0.36 - 2.95; P = 0.96). The 5-year PFS rates were 90.5 % (95 %CI 83.44 - 97.56) and 90.8 % (95 %CI 83.74 - 97.86) for the absolute and relative indications groups, respectively. The HR for overall survival in the absolute vs. the relative indications groups was 0.564 (95 %CI 0.13 - 2.52; P = 0.45). The 5-year overall survival rates were 96.6 % (95 %CI 92.88 - 100) and 95.6 % (95 %CI 90.70 - 100) for the absolute and relative indications groups, respectively.Conclusions: Based on this study, regular follow-up without additional treatment may be considered as another choice for elderly patients with early esophageal SCC and relative indications after ESD. [ABSTRACT FROM AUTHOR]

This paper reports the impacts of economic analysis results on sea-level rise adaptation decision making with different economic analysis methods. The methodology was applied to Hillsborough County, Florida. A general conclusion is that partial shoreline protection should be implemented to reduce the potential impacts of sea-level rise on important land use, then transportation infrastructure is preferred to be protected or accommodated, and finally managed relocation should be adopted. More specifically, the results show that the best adaptation strategy is shoreline protection plus transportation infrastructure accommodation; the length of shoreline protection plays an important role in the economic analysis results, and shoreline protection and accommodation adaptation strategies for all areas are not recommended because of either high costs or low benefits; the value of travel time saving and spatial autocorrelation play important roles in the economic analysis results of accommodation strategy, which highlights the importance of including indirect economic factors and spatial autocorrelation impacts when making sea-level rise adaptation decisions. [ABSTRACT FROM AUTHOR]

Objectives. Elevated expression of Siglec-1 on circulating monocytes has been reported in some inflammatory and autoimmune diseases, but its expression and role in RA has not been elucidated. The aims of this study were to determine the expression of Siglec-1 in peripheral blood and to explore its role in mononuclear cell reactivity to autoantigen in RA.Methods. Siglec-1 protein and mRNA levels in 42 RA patients, 39 OA patients, 28 SLE patients and 42 normal controls were determined by flow cytometry and quantitative RT-PCR, respectively. In addition, 10 patients with active RA received DMARDs for 12 weeks and the frequencies of Siglec-1-positive cells and the 28-joint DAS (DAS28) were assessed before and after therapy. Furthermore, TNF-α, IFN-γ and type II collagen were used to up-regulate Siglec-1. Peripheral blood mononuclear cells (PBMCs) from different groups were stimulated with mitogens or antigens and cell proliferation and cytokine production were determined.Results. The protein and mRNA levels of Siglec-1 on PBMCs and monocytes in RA patients were significantly higher than those in OA patients and healthy controls. Moreover, the expression of Siglec-1 protein on PBMCs was positively correlated with DAS28, ESR, high-sensitivity CRP and IgM-RF, but not with anti-CCP antibody. Interestingly, Siglec-1 expression was decreased in parallel with the decrease in the DAS28 after 12 weeks of anti-rheumatic treatment. Furthermore, TNF-α, IFN-γ and type II collagen can up-regulate Siglec-1 in PBMCs. Elevated PBMC proliferation and proinflammatory cytokine production to collagen stimulation in RA patients decreased when Siglec-1 was inhibited by anti-Siglec-1 antibodies.Conclusion. Elevated Siglec-1 expression in PBMCs and monocytes can potentially serve as a biomarker for monitoring disease activity in RA. Siglec-1 may also play a proinflammatory role in stimulating lymphocyte proliferation and activation in RA. [ABSTRACT FROM PUBLISHER]

Carya hunanensis W. C. Cheng & R. H. Chang is a tree of great economic importance in China. In this study, the complete chloroplast genome of C. hunanensis was determined and analyzed phylogenetically. The whole genome was determined to be 159,892 bp in length, presenting a typical quadripartite structure with a large single copy (LSC) region (89,466 bp), a small single copy (SSC) region (18,714 bp), and a pair of inverted repeat (IR) regions (25,856 bp each). There were 132 genes annotated in the genome, including 84 protein-coding genes, 40 tRNA genes, and eight rRNA genes. The overall GC content of C. hunanensis chloroplast genome was 36.24%. Phylogenetic analysis indicated that C. hunanensis was closely related to C. kweichowensis and Annamocarya sinensis. [ABSTRACT FROM AUTHOR]

The article looks at the developments in the public transportation infrastructure in China and its role in enabling sustainability. The Chinese government has invested on various public transportation policies and projects including high-speed railway, urban metro rail system, and bus rapid transit lines. Local authorities in China are recommended to implement rules that restrict car usage and apply advanced transit solutions to enhance bus services to enable sustainability in transportation.

Pecan is an important horticultural nut crop originally from North America and now widely cultivated in China for its high ecological, ornamental and economic value. Currently, there are over one hundred cultivars grown in China, including introduced American cultivars and Chinese seedling breeding cultivars. Molecular markers were used to assess the genetic diversity of these cultivars and to identify the pedigrees of fine pecan plants with good characteristics and no cultivar-related data. A total of 77 samples grown in China were studied, including 14 introduced cultivars, 12 domestic seedling breeding cultivars, and 49 fine pecan plants with no cultivar data, together with Carya cathayensis and Juglans nigra. A total of 77 ISSR and 19 SSR primers were prescreened; 10 ISSR and eight SSR primers were selected, yielding a total of 94 amplified bands (100% polymorphic) in the range of 140-1,950 bp for the ISSR and 70 amplified bands (100% polymorphic) in the range of 50-350 bp for SSR markers. Genetic diversity analyses indicated Chinese-grown pecan cultivars and fine plants had significant diversity at the DNA level. The dengrograms constructed with ISSR, SSR or combined data were very similar, but showed very weak grouping association with morphological characters. However, the progeny were always grouped with the parents. The great diversity found among the Chinese cultivars and the interesting germplasm of the fine pecan plants analyzed in this study are very useful for increasing the diversity of the pecan gene pool. All 77 accessions in this study could be separated based on the ISSR and SSR fingerprints produced by one or more primers. The results of our study also showed that ISSR and SSR techniques were both suitable for genetic diversity analyses and the identification of pecan resources. [ABSTRACT FROM AUTHOR]

In an environment of rapid economic development with rising incomes, escalating motorization, and growing urbanization, it is natural that government policies focus on solving congestion-related problems caused by increased car ownership and usage. The mobility needs of the urban poor have traditionally been neglected in policy and in practice, particularly in developing countries. This article addresses the mobility challenges facing the urban poor and is based on a household travel survey in the city of Hefei in China. First we present the travel behaviors, transportation costs, and commuting problems of the urban poor. Then we discuss urban transportation-policy implications and examine the prevailing trends of urban transportation policies and plans in Chinese cities. Policy recommendations are suggested to improve the mobility needs of the urban poor. [ABSTRACT FROM AUTHOR]

This paper provides a comparative overview of urban transport in the world's two most populous countries: China and India. Cities in both countries are suffering from severe and worsening transport problems: air pollution, noise, traffic injuries and fatalities, congestion, parking shortages, energy use, and a lack of mobility for the poor. The urban transport crisis in China and India results from continuing population growth, urbanization, suburban sprawl, rising incomes, and skyrocketing motor vehicle ownership and use. This paper critically assesses government policies in each country and suggests a range of specific improvements. It advocates a slowdown in the massive roadway investment in recent years and a shift in emphasis to expanding and improving public transport, cycling, and walking facilities. While continued growth in motor vehicle use is inevitable, China and India should restrict motor vehicle use in congested city centres and increase taxes, fees, and charges to reflect the enormous social and environmental costs of motor vehicle use. At the same time, much stricter regulations should be imposed on manufacturers to produce cleaner, more energy-efficient, quieter, and safer cars, motorcycles, buses, and trucks. Mitigating the many social and environmental impacts of rising motorization is obviously important for the future well-being of Chinese and Indian cities. It is also crucial for the future of the rest of the world. Unless the problems of motorization in China and India can be effectively dealt with, the world faces sharp increases in greenhouse gases, accelerating climate change, and rapid depletion of a range of non-renewable resources. [ABSTRACT FROM AUTHOR]

Objective: To assess the characteristics and factors affecting course of schizophrenia in a Chinese rural area. Method: An epidemiological investigation was conducted to identify all the patients with schizophrenia among 149 231 people in Xinjin County, Chengdu. Results: The total prevalence of schizophrenia was 4.13 per 1000 population. Males had an earlier mean age of onset (29.6 years) than females (32.3 years). Duration of illness before treatment and the total duration of illness were found to be significantly associated with level of remission. The status of treatment, family economy, housing, and families’ care of patients had a significant effect on the clinical course of the illness. Conclusions: Duration of illness before treatment may be an important predictor of course in schizophrenia. Early treatment for the patients may produce higher level of improvement in prognosis. Education intervention and community-based service are urgent priorities for these patients. [ABSTRACT FROM AUTHOR]

Typical air pollution events involving ozone (O 3) and PM 2.5 occurred frequently in China, while the fine-scale pollution variation, especially at a neighborhood level (2 km*2 km), is complex and still not clear. To assess how urban form and meteorology influence neighborhood air pollution distribution, this study took the Minhang district in Shanghai, as experimental cases, and performed a neighborhood-scale investigation on O 3 and PM 2.5 by using mobile measurements. Both land-use regression model and decision tree model were used to examine the relationship between air pollutant concentration and influenced variables. As the decision tree model captured the linear and non-linear relationship between variables, it was demonstrated that explained more variations of O 3 and PM 2.5 concentrations than the LUR model. The results also showed that O 3 concentrations were mainly affected by meteorological factors while PM 2.5 concentrations were more heavily determined by background level and residential area. Both O 3 and PM 2.5 showed a significant correlation with air temperature, traffic volume, building height, and green space. Interestingly, green spaces were negatively correlated with the PM 2.5 variations, which was almost the opposite to that of O 3. With the superiority to the discrete observation, the decision tree model based concentration surfaces clearly revealed the heterogeneity of O 3 and PM 2.5 distributions. This study not only preliminarily identifies the impacts of land-use type and meteorological factors on the spatial patterns of O 3 and PM 2.5 , but also provides a possible alternative method for assessing the neighborhood air pollution in the future. • Mobile measurements are performed on PM 2.5 /O 3 variations in two neighborhoods in Shanghai. • Decision tree models performed well in assessing both pollutant (PM 2.5 /O 3) variations. • The concentrations of O 3 were mainly affected by the meteorological factors. • The concentrations of PM 2.5 was more heavily impacted by background concentration and residential area. • Green space area was negatively correlated with the PM 2.5 variations, which was almost opposite compared with that of O 3. [ABSTRACT FROM AUTHOR]

Spatiotemporal variations in PM 2.5 are a key factor affecting personal pollution exposure levels in urban areas. However, fixed-site monitoring stations are so sparsely distributed that they hardly capture the dynamic and fine-scale variations in PM 2.5 in urban areas with complex geographical features and urban forms. Recently, a distributed air sensor network (DASN) was deployed in Dezhou city, China, to monitor fine-scale air pollution information and obtain deep insight into variations in PM 2.5. Based on the data collected by the DASN, this paper investigated the spatiotemporal patterns of PM 2.5 using the time-series clustering method. The results demonstrated that there were four stages of PM 2.5 daily variations, i.e., accumulation, continuous pollution, dispersion, and cleaning. Generally, the stage of dispersion occurred more rapidly than the stage of accumulation, and PM 2.5 accumulated easily in warm and humid weather with low wind speeds. However, the stage of dispersion was affected mainly by high wind speeds and precipitation. Additionally, the results suggested that four variation stages did not strictly correspond to seasonal divisions. The spatial distributions of PM 2.5 revealed that the main pollution source was located in a southeastern industrial park, which exhibited a significant impact throughout the four stages. Considering both the temporal and spatial characteristics of PM 2.5 , this study successfully identified pollution hotspots and confirmed the effect of industrial parks. The study demonstrates that the DASN has high prospective applicability for assessing the fine-scale spatial distribution of PM 2.5 , and the time-series clustering method can also assist environmental researchers in further exploring the spatiotemporal characteristics of urban air pollution. Image 1 • Air sensor network is arranged for environment monitoring of urban areas. • Monitoring network shows four variation patterns of the daily PM 2.5 concentration. • Spatial map reveals the pollution sources of the PM 2.5 in each variation pattern. • The entropy weight method can identify the PM 2.5 hotspots in the city. [ABSTRACT FROM AUTHOR]

Natural disasters, intentional attacks, and operational incidents are posing increasing threats on rail transit network. The vulnerability of rail transit network becomes an important concern of researchers and rail managers. This paper proposes a station-based accessibility approach addressing passenger flow and land use characteristics in rail transit network vulnerability analysis. Land use variables are measured as the independency degree on rail transit. The reduction ratio of network accessibility before and after incidents is calculated to measure the potential consequences. Based on results of comparisons with existing methods with the help of an example problem, the proposed accessibility measure demonstrates better and more reasonable results as not only the rail network and passenger flow but also the land use and travel alternative variables interacting with rail transit are accounted. The proposed method is then applied to Shanghai metro network. The data for analysis include rail transit network data, passenger flow data, and land use data around stations. Results indicate that the vulnerability of rail transit network is jointly affected by its network topology, passenger flow, and land use variables. Unbalanced land use, high plot ratio, and the less travel alternatives will increase the dependency of land on rail transit travel, leading to high network vulnerability once disrupted. Results of this work will inform rail transit managers of the degree of network vulnerability and critical stations and links as well as the land use dependency on vulnerability. Findings of this study may have implications not only for the planning of other transit modes to enhance the resilience of public transit network in vulnerable areas but also for the land use development around rail stations. [ABSTRACT FROM AUTHOR]

Transportation-related risk factors are a major source of morbidity and mortality in China, where the expansion of road networks and surges in personal vehicle ownership are having profound effects on public health. Road traffic injuries and fatalities have increased alongside increased use of motorised transport in China, and accident injury risk is aggravated by inadequate emergency response systems and trauma care. National air quality standards and emission control technologies are having a positive effect on air quality, but persistent air pollution is increasingly attributable to a growing and outdated vehicle fleet and to famously congested roads. Urban design favours motorised transport, and physical activity and its associated health benefits are hindered by poor urban infrastructure. Transport emissions of greenhouse gases contribute substantially to regional and global climate change, which compound public health risks from multiple factors. Despite these complex challenges, technological advances and innovations in planning and policy stand to make China a leader in sustainable, healthy transportation. [ABSTRACT FROM AUTHOR]

Daytime atmospheric pollution has received wide attention, while the vertical structures of atmospheric pollutants at night play a crucial role in the photochemical process on the following day, which is still less reported. Focusing on Guangzhou, a megacity of South China, we established an unmanned aerial vehicle (UAV) equipped with micro detectors to collect consecutive high-resolution samples of fine particle (PM 2.5), submicron particle (PM 1.0), black carbon (BC) and ozone (O 3) concentrations in the atmosphere, as well as the air temperature (AT) and relative humidity (RH) within a 500 m altitude during nighttime from Oct. 24th to Nov. 6th, 2018. The measurements showed that PM 2.5 , PM 1.0 , and BC decreased with altitude and were influenced by the nighttime shallow planetary boundary layer (PBL) where BC was more accumulated and fluctuated. In contrast, O 3 was positively correlated with altitude. Backward trajectory clustering and Pasquill stability classification showed that advection and convection significantly influenced the vertical distribution of all pollutants, particularly particulate matter. External air masses carrying high concentrations of pollutants increased PM 1.0 and PM 2.5 levels by 145% and 455%, respectively, compared to unaffected periods. The ratio of BC to PM 2.5 indicated that local emissions had a minor role in nighttime particulate matter. Vertical transport caused by atmospheric instability reduced the differences in pollutant concentrations at various heights. Geodetector and generalized additive model showed that RH and BC accumulation in the PBL were significant factors influencing vertical changes of the secondary aerosol intensity as indicated by the ratio of PM 1.0 to PM 2.5. The joint explanation of RH and atmospheric stability with other variables such as BC is essential to understand the generation of secondary aerosols. These findings provide insights into regional and local measures to prevent and control night-time particulate matter pollution. [Display omitted] • PM 2.5 , PM 1.0 , BC, and O 3 are detected vertically at nighttime in Guangzhou. • The vertical decline is smooth for PM 2.5 and PM 1.0 but fluctuating for BC. • Compared to PM 2.5 and PM 1.0 , BC is more sensitive to PBL. • Higher BC and humidity near the PBL reduce the secondary aerosol intensity. [ABSTRACT FROM AUTHOR]

With rapid urbanization and industrialization, the number of light-duty gasoline vehicles (LDGVs) in China has continued to grow rapidly, leading to a significant increase in traffic pollution. Therefore, it is essential to accurately calculate the emission of LDGVs for air quality monitoring and management. Fortunately, Motor Vehicle Emission Simulator (MOVES) is a sophisticated model for estimating mobile source emissions with good prediction accuracy. However, the parameters of MOVES are based on the field tests in the US, which is worth exploring whether MOVES can be applied to other countries. Hence, in this paper, we used the portable emission measurement system (PEMS) to conduct real driving emission (RDE) tests of LDGVs, aiming to explore the possibility of the MOVES application in China. Based on the field tests, we modified basic parameters in the MOVES model, but unsatisfactory prediction performance was obtained. Existing research on improving MOVES performance mainly involved new binning of operating modes, but these methods had limited improvements. Though studies have also used machine learning methods for predicting LDGV emissions, they lacked comparison and integration with the MOVES model. To further improve the prediction accuracy, we proposed a novel road vehicle emission model that integrated the machine learning method and the MOVES to predict the road-level emission rates of NO and CO 2 emissions of LDGVs. In addition, we employed the Boruta algorithm to capture the key influencing factors and promote prediction performance. The enhanced model outperformed MOVES and achieved higher R2 values. On average, the improvement for CO 2 was 0.132, and for NO, it was 0.261. This work will provide references for MOVES improvements in practical scenarios and better predict pollutant emissions for LDGVs using limited resources of field tests in cities outside the US. • Integrating engine characteristics with the MOVES model can improve model performance. • Integrating machine learning with MOVES performs well in prediction of vehicle CO 2 and NO emission. • The proposed emission model provides a possibility for calculation rather than costly an experiment in countries outside the USA. [ABSTRACT FROM AUTHOR]

On-road vehicle has been a prominent emission source, hence a key target of control for environment, health, and climate concerns. While considerable efforts have been made to investigate criteria pollutants such as adverse gaseous and particulate emissions across the world, there is limited systematic research to characterize on-road carbon emissions, especially as countries strive to set and achieve various climate goals (i.e., carbon neutrality, carbon peaking by a certain year, etc.) through cleaner vehicle technologies such as the latest vehicle emission standard, China VI (2020). This study used the portable emission measurement system (PEMS) to reveal the real-world emissions from two light-duty gasoline vehicles, one meeting the China V standard and the other China VI. The PEMS measurements were performed secondly in urban and suburban areas respectively, and finally yielded 10 h of rich and finely resolved emissions data. In addition of single-factor analysis, this study employed two machine learning models, stepwise regression and light gradient boosting machine (LightGBM), to investigate the coupling effects among vehicle/traffic parameters and identify driving behavior, engine condition, and external environment as key determining factors that affect vehicular carbon emissions. In particular, engine load percent and engine speed were confirmed to be the most dominant factors affecting vehicular carbon emissions under both China V and China VI standards, explaining ∼60% of variability in carbon emissions. As a result, vehicle specific power (VSP) is derived from vehicle travel parameters and used as a surrogate for carbon emission estimation. The external facility and environmental factors turned out significant as well in affecting vehicle carbon emissions: carbon emissions from the same vehicle were significantly higher in an urban setting then in suburban areas, mostly due to the more aggressive driving patterns in congested urban traffic. Travelling under relatively better traffic conditions on expressways gave the lowest per-distance emission factors of CO 2 , CO, and NOx. Comparing between the China V and VI vehicle, our PEMS data show significant carbon emission reduction benefits (15.9% in CO 2 , 28.8% in CO) as we move to the new China VI standard, although such benefit was not observed in NOx emissions. • CO 2 emission rate illustrated a higher relevance to engine characteristics, followed by driving characteristics. • China VI policy for light-duty gasoline vehicles show lower carbon emission rates than China V policy. • Aggressive driving behaviors results in higher CO 2 emission rates. [ABSTRACT FROM AUTHOR]

Intra-urban assessment of air pollution exposure has become a priority study while international attention was attracted to PM 2.5 pollution in China in recent years. Land Use Regression (LUR), which has previously been proved to be a feasible way to describe the relationship between land use and air pollution level in European and American cities, was employed in this paper to explain the correlations and spatial variations in Shanghai, China. PM 2.5 and NO 2 concentrations at 35–45 monitoring locations were selected as dependent variables, and a total of 44 built environmental factors were extracted as independent variables. Only five factors showed significant explanatory value for both PM 2.5 and NO 2 models: longitude, distance from monitors to the ocean, highway intensity, waterbody area, and industrial land area for PM 2.5 model; residential area, distance to the coast, industrial area, urban district, and highway intensity for NO 2 model. Respectively, both PM 2.5 and NO 2 showed anti-correlation with coastal proximity (an indicator of clean air dilution) and correlation with highway and industrial intensity (source indicators). NO 2 also showed significant correlation with local indicators of population density (residential intensity and urban classification), while PM 2.5 showed significant correlation with regional dilution (longitude as a indicator of distance from polluted neighbors and local water features). Both adjusted R squared values were strong with PM 2.5 (0.88) being higher than NO 2 (0.62). The LUR was then used to produce continuous concentration fields for NO 2 and PM 2.5 to illustrate the features and, potentially, for use by future studies. Comparison to PM 2.5 studies in New York and Beijing show that Shanghai PM 2.5 pollutant distribution was more sensitive to geographic location and proximity to neighboring regions. [ABSTRACT FROM AUTHOR]

The vertical distribution patterns of PM 2.5 (particulate matters with diameters ≤2.5 μm) are crucial for understanding the aggregation, dispersion, and regional transport of PM 2.5. However, due to the measurement limitation, the vertical observational data o is difficult to be obtained and is relatively insufficient at present stage. With this consideration, two electric-fueled rotary-wing unmanned aerial vehicles (UAVs) are used in this study to reveal the vertical distribution of PM 2.5 in Shanghai of China. Totally 53 vertical profiles of PM 2.5 concentration and meteorological factors are collected to reveal the vertical distribution pattern of PM 2.5. The results indicate that PM 2.5 vertical concentration, especially the maximum of the PM 2.5 vertical concentration, shows a good correlation with surface PM 2.5 concentration, which means it is possible to use surface PM 2.5 concentration to extrapolate PM 2.5 vertical concentration. In terms of meteorological factors, low wind speed and northerly (or northwesterly) wind direction significantly contribute to the accumulation of high concentration PM 2.5 in Shanghai during the winter. Furthermore, the low height of the planetary boundary layer (PBL) facilitates the accumulation of pollutants near the ground, but it is not imperative for the vertically high concentration of PM 2.5 , since vertically high PM 2.5 concentration exists within high PBL as well. It has been concluded that low PBL height is not mandatory for well vertical mixing within it, for the vertically even distribution of PM 2.5 occurred under both low and high PBL. In terms of the effect the temperature, although temperature makes a significant contribution to the inverse distribution of PM 2.5 , no significant linear correlation was found between temperature and PM 2.5 vertical distribution. The findings in this study could help to understand the vertical distribution patterns of PM 2.5 during the winter, and provide more evidence of how other factors impact these patterns. [Display omitted] • The accuracy in measuring PM 2.5 by the UAV platform was evaluated. • Week northerly wind are desideratum for high PM 2.5 concentration. • Low PBL accounts for high surface PM 2.5 concentration in low altitude. • Vertically, there is no significant linear correlation between temperature and PM 2.5. [ABSTRACT FROM AUTHOR]

In near-road neighborhoods, residents are more frequently exposed to traffic-related air pollution (TRAP), and they are increasingly aware of pollution levels. Given this consideration, this study adopted portable air pollutant sensors to conduct a mobile monitoring campaign in two near-road neighborhoods, one in an urban area and one in a suburban area of Shanghai, China. The campaign characterized spatiotemporal distributions of fine particulate matter (PM 2.5 ) and black carbon (BC) to help identify appropriate mitigation measures in these near-road micro-environments. The study identified higher mean TRAP concentrations (up to 4.7-fold and 1.7-fold higher for PM 2.5 and BC, respectively), lower spatial variability, and a stronger inter-pollutant correlation in winter compared to summer. The temporal variations of TRAP between peak hour and off-peak hour were also investigated. It was identified that district-level PM 2.5 increments occurred from off-peak to peak hours, with BC concentrations attributed more to traffic emissions. In addition, the spatiotemporal distribution of TRAP inside neighborhoods revealed that PM 2.5 concentrations presented great temporal variability but almost remained invariant in space, while the BC concentrations showed notable spatiotemporal variability. These findings provide valuable insights into the unique spatiotemporal distributions of TRAP in different near-road neighborhoods, highlighting the important role of hyperlocal monitoring in urban micro-environments to support tailored designing and implementing appropriate mitigation measures., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Below the boundary layer, the air pollutants have been confirmed to present the decreasing trend with the height in most situaitons. However, the disperiosn rate of air pollutants in the vertical profile is rarely investigated in detail, especially through in-situ measurement. With this consideration, we employed an unmanned aerial vehicle equipped with portable monitoring equipments to scrutinize the vertical distribution of PM 2.5 . Based on the original data, we found that PM 2.5 concentration decreases gradually with altitude below the boundary layer and demonstrated an obvious linear correlation. Therefore, the vertical distribution of PM 2.5 was quantified by representing the distribution of PM 2.5 with the slope of PM 2.5 vertical distribution. We used backward trajectories to reveal the causes of outliers (PM 2.5 increasing with altitude), and found that PM 2.5 in the high altitude came from the southwest. Besides, the relationship between the vertical distribution of PM 2.5 and various meteorological factors was investigated using stepwise regression analysis. The results show that the four meteorological factors most strongly correlated with the slope values are: (a) the difference in relative humidity between the ground and the air; (b) the difference in temperature between the ground and the air; (c) the height of the boundary layer; and (d) the wind speed. The slope values increase with increasing the difference in relative humidity between ground and air and the difference in temperature between the ground and the air, and decrease with increasing boundary layer height and wind speed. According to the Random Forest calculations, the ground-to-air relative humidity difference is the most important at 0.718; the wind speed is the least important at 0.053; and the ground-to-air temperature difference and boundary layer height are 0.140 and 0.088, respectively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Short-term prediction of urban air quality is critical to pollution management and public health. However, existing studies have failed to make full use of the spatiotemporal correlations or topological relationships among air quality monitoring networks (AQMN), and hence exhibit low precision in regional prediction tasks. With this consideration, we proposed a novel deep learning-based hybrid model of Res-GCN-BiLSTM combining the residual neural network (ResNet), graph convolutional network (GCN), and bidirectional long short-term memory (BiLSTM), for predicting short-term regional NO 2 and O 3 concentrations. Auto-correlation analysis and cluster analysis were first utilized to reveal the inherent temporal and spatial properties respectively. They demonstrated that there existed temporal daily periodicity and spatial similarity in AQMN. Then the identified spatiotemporal properties were sufficiently leveraged, and monitoring network topological information, as well as auxiliary pollutants and meteorology were also adaptively integrated into the model. The hourly observed data from 51 air quality monitoring stations and meteorological data in Shanghai were employed to evaluate it. Results show that the Res-GCN-BiLSTM model was better adapted to the pollutant characteristics and improved the prediction accuracy, with nearly 11% and 17% improvements in mean absolute error for NO 2 and O 3 , respectively compared to the best performing baseline model. Among the three types of monitoring stations, traffic monitoring stations performed the best for O 3 , but the worst for NO 2 , mainly due to the impacts of intensive traffic emissions and the titration reaction. These findings illustrate that the hybrid architecture is more suitable for regional pollutant concentration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The establishment of an effective roadside air quality forecasting model provides important information for proper traffic management to mitigate severe pollution, and for alerting resident's outdoor plans to minimize exposure. Current deterministic models rely on numerical simulation and the tuning of parameters, and empirical models present powerful learning ability but have not fully considered the temporal periodicity of air pollutants. In order to take the periodicity of pollutants into empirical air quality forecasting models, this study evaluates the temporal variations of air pollutants and develops a novel sequence to sequence model with weekly periodicity to forecast air quality. Two-year observation data from Shanghai roadside air quality monitoring stations are employed to support analyzing and modeling. The results conclude that the fine particulate matter (PM 2.5 ) and carbon monoxide (CO) concentrations show obvious daily and weekly variations, and the temporal patterns are nearly consistent with the periodicity of traffic flow in Shanghai. Compared with PM 2.5 , the CO concentrations are more affected by traffic variation. The proposed model outperforms the baseline model in terms of accuracy, and presents a higher linear consistency in PM 2.5 prediction and lower errors in CO prediction. This study could assist environmental researchers to further improve the technologies for urban air quality forecasting, and serve as tools for supporting policymakers to implement related traffic management and emission control policies.

Spatiotemporal variations in PM 2.5 are a key factor affecting personal pollution exposure levels in urban areas. However, fixed-site monitoring stations are so sparsely distributed that they hardly capture the dynamic and fine-scale variations in PM 2.5 in urban areas with complex geographical features and urban forms. Recently, a distributed air sensor network (DASN) was deployed in Dezhou city, China, to monitor fine-scale air pollution information and obtain deep insight into variations in PM 2.5 . Based on the data collected by the DASN, this paper investigated the spatiotemporal patterns of PM 2.5 using the time-series clustering method. The results demonstrated that there were four stages of PM 2.5 daily variations, i.e., accumulation, continuous pollution, dispersion, and cleaning. Generally, the stage of dispersion occurred more rapidly than the stage of accumulation, and PM 2.5 accumulated easily in warm and humid weather with low wind speeds. However, the stage of dispersion was affected mainly by high wind speeds and precipitation. Additionally, the results suggested that four variation stages did not strictly correspond to seasonal divisions. The spatial distributions of PM 2.5 revealed that the main pollution source was located in a southeastern industrial park, which exhibited a significant impact throughout the four stages. Considering both the temporal and spatial characteristics of PM 2.5 , this study successfully identified pollution hotspots and confirmed the effect of industrial parks. The study demonstrates that the DASN has high prospective applicability for assessing the fine-scale spatial distribution of PM 2.5 , and the time-series clustering method can also assist environmental researchers in further exploring the spatiotemporal characteristics of urban air pollution., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The unfavorable locations of underground infrastructures and poor ventilation facilities can result in the deterioration of enclosed air quality. Some researchers have studied air quality and ventilation measures in different types of underground buildings. However, few studies have investigated the pollution in pedestrian passageways connecting underground structures. Hence, in this paper, we attempted to investigate the spatial distribution of fine particulate matter (PM 2.5 ) in underground passageways. First, measurements were designed and conducted in a pedestrian passageway beneath the Shanghai South Railway Station, Shanghai, China. Second, numerical simulations were performed based on computational fluid dynamic (CFD) technology. Finally, the numerical simulations were extended to examine impacts of the ventilation measures on PM 2.5 concentration with different inlet positions and air velocity in underground passageways. The simulation results showed good agreement with the experimental data, and the numerical model was validated to be an effective method to investigate the spatial distribution of PM 2.5 in underground passageways. Results suggest that building additional entrances is an advisable method for improving air quality in the underground passageways of the Shanghai South Railway Station, while jet fans are not recommended. Findings of this study offer suggestions for mitigating PM 2.5 pollution in underground passageways.

Purpose: Cefathiamidine, a first-generation cephalosporin, has approval from the China Food and Drug Administration for the treatment of infections caused by susceptible bacteria in both adults and children. As pharmacokinetic data are limited in the pediatric population, we aimed to evaluate the population pharmacokinetics of cefathiamidine in children and to define the appropriate dose in order to optimize cefathiamidine treatment., Methods: Blood samples were collected from children treated with cefathiamidine, and concentrations were quantified by high-performance liquid chromatography and tandem mass spectrometry. Population pharmacokinetic analysis was conducted using NONMEM software., Results: Fifty-four children (age range: 2.0-11.8 years) were included. Sparse pharmacokinetic samples (n=120) were available for analysis. A two-compartment model with first-order elimination showed the best fit with the data. A covariate analysis identified that bodyweight had a significant impact on cefathiamidine pharmacokinetics. Monte Carlo simulation demonstrated that the currently used dosing regimen of 100 mg/kg/day q12h was associated with a high risk of underdosing in pediatric patients. To reach the target 70% fT>MIC, a dose of 100 mg/kg/day cefathiamidine q6h is required for effective treatment against Haemophilus influenzae ., Conclusion: A population pharmacokinetics model of cefathiamidine in children with hematologic disease was established. A dosing regimen of 100 mg/kg/day cefathiamidine q6h should be used in clinical practice against H. influenza infections.

Hand, foot, and mouth disease (HFMD) is caused by a group of enteroviruses. It infects millions of children in the Southeast Asian area. An accurate forecasting of outbreaks of HFMD could facilitate public health officials to suggest public health actions earlier. Many researchers tried to develop an early warning system for HFMD to lower the damage caused by a HFMD outbreak. The research data based on daily level could help figure out the relationship between HFMD and environmental factors, but nevertheless is difficult to collect. In this study, we collected the daily clinical data from the Shenzhen Health Information Center and multiple environmental factors to analyze the outbreaks of HFMD. Considering the incubation period of HFMD, we fed the previous 60 days' HFMD rates, 7 days' temperature factors and 7 days' air-quality factors into the tree model, XGBoost. The following conclusions were drawn in this study: i) Compared with the model only using the previous HFMD rate and temperature factors, the addition of the air-quality factors could make the model better, improving MAE nearly 16.7%. ii) By analyzing the Pearson correlation, we found that the temperature showed a positive correlation and the air quality showed a negative correlation for the HFMD outbreaks. Improving the air quality, especially decreasing PM2.5 and PM10 could decrease the risk of HFMD outbreaks.

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Introduction: The use of acupuncture has been suggested for the treatment of acute neck pain caused by stiff neck in China. However, current evidence is insufficient to draw any conclusions about its efficacy. Therefore this pilot study was designed to evaluate the feasibility and efficacy of acupuncture at the Houxi (SI3) acupoint for treatment of acute neck pain., Methods/analysis: This pilot study will be a two-parallel-group, assessor-blinded, randomised controlled trial. Thirty-six stiff neck participants with acute neck pain will be recruited and randomly divided into two groups in a 1:1 ratio. Participants in the control group will receive massage on the local neck region (5 min each session, three times a day for 3 days). In addition to massage, patients in the treatment group will receive acupuncture (one session a day for 3 days). Measures will be taken at 0, 3 and 15 days. The primary outcome is the Northwick Park Neck Pain Questionnaire (NPQ). The secondary outcome is the Short Form of the McGill Pain Questionnaire (SF-MPQ)., Ethics/dissemination: The protocol for this pilot randomised clinical trial has undergone ethics scrutiny and been approved by the ethics review boards of the First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine (Permission number: HZYLL201303502). The findings of this study will provide important clinical evidence on the feasibility and efficacy of acupuncture treatment for stiff neck patients with acute neck pain. In addition, it will explore the feasibility of further acupuncture research., Trial Registration Number: ChiCTR-TRC-13003911., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Background: Pressure ulcers are one of the most common health complaints, which often take months or years to heal, and affect patients' morbidity and quality of life. Medical options for pressure ulcers are limited. Electroacupuncture (EA) has been employed to relieve the symptoms for patients with pressure ulcers, but there is limited clinical evidence for its effectiveness., Methods/design: This study consists of a randomized controlled trial (RCT) with two parallel arms: a control group and an EA group. Both groups will receive standard wound care (including changing position, using mattresses and cushions, and a good diet) of five sessions per week for a total of 40 sessions during the 8-week treatment period. In addition, the EA group will receive the EA intervention. The following outcome measurements will be used in examination of participants: wound surface area (WSA), visual analogue scale (VAS), and the proportion of ulcers healed within trial period (PUHTP). All the outcomes will be evaluated at the start of the study, at the end of the fourth week, at 8 weeks after randomization, and 1 month after treatment cessation., Discussion: The aim of this study is to evaluate the effectiveness of EA for the treatment of patients with pressure ulcers., Trial Registration: Chinese Clinical Trial Register: ChiCTR-TRC-11001693.

Background: Neck pain caused by cervical spondylosis (CS) has become one of the most common health problems around the world. Electroacupuncture (EA) has been employed to relieve CS neck pain, but there is limited clinical evidence for its effectiveness., Methods/design: This study consists of a randomized controlled trial (RCT) with two parallel arms: an acupuncture group and an EA group. Both groups will receive acupuncture at Jing-jiaji points for 30 minutes each time, for five sessions per week for a total of 20 sessions during this four-week period. In addition, the EA group will be connected with EA apparatus. The following outcome measurements will be used in examination of subjects: the Northwick Park Neck Pain Questionnaire (NPQ), McGill Pain Questionnaire (MPQ), and Short-Form 36 (SF-36) scale. All these outcomes will be examined at the start of the study, at the end of the second week, at four weeks after randomization, and one and three months after treatment cessation respectively., Discussion: This study aims to assess the efficacy of EA, compared with acupuncture intervention at Jing-jiaji points for the CS neck pain., Trial Registration: Chinese Clinical Trials Register: ChiCTR-TRC-13003422.

Aim: To investigate the clinical advantages of the stent-laparoscopy approach to treat colorectal cancer (CRC) patients with acute colorectal obstruction (ACO)., Methods: From April 2008 to April 2012, surgery-related parameters, complications, overall survival (OS), and disease-free survival (DFS) of 74 consecutive patients with left-sided CRC presented with ACO who underwent self-expandable metallic stent (SEMS) placement followed by one-stage open (n = 58) or laparoscopic resection (n = 16) were evaluated retrospectively. The stent-laparoscopy group was also compared with a control group of 96 CRC patients who underwent regular laparoscopy without ACO between January 2010 and December 2011 to explore whether SEMS placement influenced the laparoscopic procedure or reduced long-term survival by influencing CRC oncological characteristics., Results: The characteristics of patients among these groups were comparable. The rate of conversion to open surgery was 12.5% in the stent-laparoscopy group. Bowel function recovery and postoperative hospital stay were significantly shorter (3.3 ± 0.9 d vs 4.2 ± 1.5 d and 6.7 ± 1.1 d vs 9.5 ± 6.7 d, P = 0.016 and P = 0.005), and surgical time was significantly longer (152.1 ± 44.4 min vs 127.4 ± 38.4 min, P = 0.045) in the stent-laparoscopy group than in the stent-open group. Surgery-related complications and the rate of admission to the intensive care unit were lower in the stent-laparoscopy group. There were no significant differences in the interval between stenting and surgery, intraoperative blood loss, OS, and DFS between the two stent groups. Compared with those in the stent-laparoscopy group, all surgery-related parameters, complications, OS, and DFS in the control group were comparable., Conclusion: The stent-laparoscopy approach is a feasible, rapid, and minimally invasive option for patients with ACO caused by left-sided CRC and can achieve a favorable long-term prognosis.

Pecan is an important horticultural nut crop originally from North America and now widely cultivated in China for its high ecological, ornamental and economic value. Currently, there are over one hundred cultivars grown in China, including introduced American cultivars and Chinese seedling breeding cultivars. Molecular markers were used to assess the genetic diversity of these cultivars and to identify the pedigrees of fine pecan plants with good characteristics and no cultivar-related data. A total of 77 samples grown in China were studied, including 14 introduced cultivars, 12 domestic seedling breeding cultivars, and 49 fine pecan plants with no cultivar data, together with Carya cathayensis and Juglans nigra. A total of 77 ISSR and 19 SSR primers were prescreened; 10 ISSR and eight SSR primers were selected, yielding a total of 94 amplified bands (100% polymorphic) in the range of 140-1,950 bp for the ISSR and 70 amplified bands (100% polymorphic) in the range of 50-350 bp for SSR markers. Genetic diversity analyses indicated Chinese-grown pecan cultivars and fine plants had significant diversity at the DNA level. The dengrograms constructed with ISSR, SSR or combined data were very similar, but showed very weak grouping association with morphological characters. However, the progeny were always grouped with the parents. The great diversity found among the Chinese cultivars and the interesting germplasm of the fine pecan plants analyzed in this study are very useful for increasing the diversity of the pecan gene pool. All 77 accessions in this study could be separated based on the ISSR and SSR fingerprints produced by one or more primers. The results of our study also showed that ISSR and SSR techniques were both suitable for genetic diversity analyses and the identification of pecan resources.

Background: A familial clustering of patients with primary biliary cirrhosis (PBC) and the presence of immunological abnormalities in family members suggest a genetic component involved in the pathogenesis of PBC. The aims of this study are to investigate the frequencies of human leukocyte antigen HLA-A, -B, and -DRB1 alleles in Chinese patients with PBC by polymerase chain reaction (PCR)-based techniques, and to assess the correlation of the above-mentioned HLA with some clinical and laboratory features., Methods: Genotyping of HLA alleles were performed in 65 well-characterized PBC patients and 431 healthy controls with sequence-specific primers PCR amplification., Results: HLA-DRB1*07 allele detected in 19 of the 65 (29.2%) PBC patients was subtyped as DRB1*0701, as well as in 13.9% of controls (PC<0.05, OR=2.55, 95%CI: 1.4-4.6). An increased frequency of DRB1*03 (18.4% vs. 7.2% in healthy controls) and a decreased frequency of DRB1*12 (16.9% vs. 28.8%) in PBC patients were statistically significant. There was no association with HLA-DRB1*08 reported. The frequencies for HLA-A, B and the other DRB1 alleles were similar between patients and healthy controls., Conclusions: The susceptibility to PBC in Chinese individuals is associated with DRB1*0701 allele. This association differs from that in North Americans, South Americans, North Europeans and even Japanese, but it is not restricted to any particular subgroup of patients.

Aim: To investigate the association between Chinese patients with autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and the polymorphisms of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) gene promoter (-318) and exon 1 (+49)., Methods: CTLA-4 promoter (-318 T/C) and exon1 (+49A/G) polymorphisms were genotyped via restriction fragment length polymorphism methods in 62 Chinese AIH patients, 77 Chinese PBC patients and 160 healthy controls., Results: We found a significant association in CTLA-4 gene exon1 49 A/G polymorphism between PBC patients and controls (P = 0.006) and the frequency of G alleles was significantly increased in comparison with controls (P = 0.0046, OR = 1.8). We also found the frequency of C alleles in promoter -318 was significantly increased in AIH patients compared with controls (P = 0.02, OR = 0.41). Although the genotype distribution of the CTLA-4 exon 1-promoter gene was not significantly different between AIH and PBC patients and controls, the occurrence of GG-CC was increased in two groups of patients (AIH: 32.3%, PBC: 37.7%, control: 22.5%)., Conclusion: Polymorphisms of CTLA-4 gene probably confer susceptibility to AIH and PBC in Chinese population.

Objective: To investigate the association between Chinese patients with autoimmune hepatitis (AIH), primary biliary cirrhosis (PBC) and the polymorphisms of cytotoxic T lymphocyte -associated antigen-4 (CTLA-4) gene promoter (-318) and exon 1 (+49)., Methods: The CTLA-4 promoter (-318 T/C) and exon 1 (+49A/G) polymorphisms were genotyped via restriction fragment length polymorphism methods in 62 Chinese AIH patients, 77 Chinese PBC patients and 160 healthy controls., Results: There was no difference in the distribution of CTLA-4 promoter -318 T/C polymorphisms between AIH patients and controls, but the C allele frequency was significantly increased in patients with AIH, compared to controls (P=0.02, OR=2.43). The distribution of CTLA-4 gene exon 1 49 A/G genotypes exhibited significant difference between PBC patients and controls (P=0.006), and the frequency of G allele showed a significant increase in PBC group as compared with controls (P=0.0046, OR=1.8). Although the genotype distribution of the CTLA-4 exon 1-promoter gene displayed no significant difference between AIH and PBC patients and controls, the occurrence of GG-CC was increased in the patients of the two groups (AIH: 32.3%, PBC: 37.7%; control: 22.5%)., Conclusion: The above findings suggest that the polymorphisms of CTLA-4 gene probably confer susceptibility to AIH and PBC in the Chinese population.

Genetic diversity and differentiation among 50 populations of total 8 species and 1 variety of Fagopyrum tataricum and its related species from 27 counties of Sichuan and Yunnan provinces, Southwest China were investigated using allozyme electrophoresis. Seven enzymesat 12 loci were assessed. The result shows that among 8 species and 1 variety, inbreeding coefficient is -0.54(-)-0.80, which means hterozogote excess. Higher genetic diversity was found in the wild related species of F. tataricum than in F. tataricum. F. dibotrys has the highest Fst value, which means that more genetic variations exist among its populations. The lowest Fst value shows that less genetic variations exist among population of F. gracilipes whic is close to panmictic There is almost no genetic differentiation between populations of F. statice. Genetic similarity is 55.3%-65.2% between species of F. tataricum and its related species, which is close to the average level among species in seed plants. According to the cluster analysis of genetic similarity, F. gracillipes is most close to F. tataricum and F. esculentum. Jinsha River region is the distributional and original center of F. tataricum and its related species.