Occurrence, distribution and ecological risk assessment of herbicide residues in cropland soils from the Mollisols region of Northeast China.

The first systematic and comprehensive investigation of herbicide residues was conducted by identifying their spatial distribution, influencing factors and ecological risk in cropland soils from the Mollisols region covering 109 million hm2 in Northeast China. Fifty-six herbicides were detected with total herbicide concentrations ranging from 1.01 to 1558.13 µg/kg (mean: 227.45). Atrazine, its degradates deethyl atrazine (DEA) and deisopropyl atrazine (DIA), trifluralin and butachlor were the most frequently detected herbicides, while DEA, clomazone, nicosulfuron, fomesafen, and mefenacet exhibited the highest concentrations. Despite being less frequently reported in Chinese soils, fomesafen, nicosulfuron, clomazone, and mefenacet were found widely present. Although most of the compounds posed a minimal or low ecological risk, atrazine, nicosulfuron and DEA exhibited medium to high potential risks. The key factors identified to regulate the fate of herbicides were soil chemical properties, amount of herbicides application, and the crop type. The soybean soils showed highest herbicide residues, while the soil mineral contents likely adsorbed more herbicides. This study provides a valuable large-scale dataset of herbicide residues across the entire Mollisols region of China along with fine-scale characterization of the ecological risks. Mitigation and management measures are needed to reduce the herbicide inputs and residues in the region.

[Research Progress and Prospect of Herbicide Residue Characteristics in Black Soil Region of China].

Food security is the top priority of a country. As an important granary in China, the northeast black land is a "ballast" to ensure national food security. However, the long-term and high-intensity application of herbicides in black land farmland has led to the accumulation and migration of herbicides in the soil, which affects soil quality, crop yield, and quality and hinders sustainable agricultural development in the black soil. To solve the problem of herbicide residues in black land farmland, it is necessary to control the application of herbicides from the source, as well as to elucidate the current situation, spatial and temporal evolution, and driving factors of herbicide residues, in order to achieve scientific prevention and control and precise policy implementation. The main contents of this study were as follows:1systematically summarize the application status and problems of herbicides in the farmland of black soil in China, suggesting that there are currently problems such as irregular application and insufficient product innovation of herbicides in the farmland of black soil; 2 comprehensively analyze the current status of herbicide residues, identify the deficiencies in recent studies on herbicide residue characteristics, spatial distribution, and pollution diagnosis in the farmland of black soil, and clarify the gaps in the research on the residue characteristics of herbicides in the farmland of black soil; and 3 propose the research prospect and key orientation for the herbicide residue diagnosis and risk management in the farmland of the black soil region of China. The results of this study can provide science and technology support for guaranteeing soil health, food security, and ecosystem security of black land farmland in China.

Coordinative Management of Soil Resources and Agricultural Farmland Environment for Food Security and Sustainable Development in China.

Major problems in China's pursuit of sustainable agricultural development include inadequate, low-quality soil and water resources, imbalanced regional allocation and unreasonable utilization of resources. In some regions, overexploitation of soil resources and excessive use of chemicals triggered a web of unforeseen consequences, including insufficient use of agricultural resources, agricultural non-point source pollution and land degradation. In the past decade, China has changed its path of agricultural development from an output-oriented one to a modern, sustainable one with agricultural ecological civilization as its goal. First, the government has formulated and improved its laws and regulations on soil resources and the environment. Second, the government has conducted serious actions to ensure food safety and coordinated management of agricultural resources. Third, the government has planned to establish national agricultural high-tech industry demonstration zones based on regional features to strengthen the connection among the government, agri-businesses, scientific community and the farming community. As the next step, the government should improve the system for ecological and environmental regulation and set up a feasible eco-incentive mechanism. At the same time, the scientific community should strengthen the innovation of bottleneck technologies and the development of whole solutions for sustainable management in ecologically fragile regions. This will enhance the alignment between policy mechanisms and technology modes and effectively promote the sustainable development of agriculture in China.

Impacts of land use/land cover and soil property changes on soil erosion in the black soil region, China.

Soil erosion (SE) is seriously threatening grain production and the ecological environment in the black soil region. Understanding the impact of changes in land use/land cover (LULC) and soil properties on SE is critical for agricultural sustainability and soil management. However, the contribution of soil property changes to SE is often ignored in existing studies. This study analyzed changes in LULC and soil properties from 1980 to 2020 in the black soil region, China. Then, the revised universal soil loss equation was used to explore the spatiotemporal changes of SE from 1980 to 2020. Finally, the contribution of LULC change and soil property change to SE was separated by scenario comparison. The results showed that cropland increased (by 24,157 km2) at the expense of grassland and forest from 1980 to 2020. Sand in cropland decreased by 21.95%, while the silt, clay, and SOC increased by 21.37%, 1.43%, and 15.38%, respectively. Soil erodibility in cropland increased greatly (+9.85%), while in forest and grassland decreased (-6.05% and -4.72%). LULC change and soil properties change together aggravated SE in the black soil region. LULC change and soil property change resulted in a 22% increase in SE, of which LULC change resulted in a 14% increase, and soil property change resulted in an 8% increase. Agricultural development policy was the main reason driving LULC change. The combination of LULC change, climatic factors, and long-term tillage resulted in changes in soil properties. Ecosystem management and policy can reduce SE through vegetation restoration and soil improvement. This study can provide important references for soil conservation and agricultural development in the black soil region.

Mapping high resolution National Soil Information Grids of China.

Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires higher quality, more consistent and detailed soil information. Accurate prediction of soil variation over large and complex areas with limited samples remains a challenge, which is especially significant for China due to its vast land area which contains the most diverse soil landscapes in the world. Here, we integrated predictive soil mapping paradigm with adaptive depth function fitting, state-of-the-art ensemble machine learning and high-resolution soil-forming environment characterization in a high-performance parallel computing environment to generate 90-m resolution national gridded maps of nine soil properties (pH, organic carbon, nitrogen, phosphorus, potassium, cation exchange capacity, bulk density, coarse fragments, and thickness) at multiple depths across China. This was based on approximately 5000 representative soil profiles collected in a recent national soil survey and a suite of detailed covariates to characterize soil-forming environments. The predictive accuracy ranged from very good to moderate (Model Efficiency Coefficients from 0.71 to 0.36) at 0-5 cm. The predictive accuracy for most soil properties declined with depth. Compared with previous soil maps, we achieved significantly more detailed and accurate predictions which could well represent soil variations across the territory and are a significant contribution to the GlobalSoilMap.net project. The relative importance of soil-forming factors in the predictions varied by specific soil property and depth, suggesting the complexity and non-stationarity of comprehensive multi-factor interactions in the process of soil development.

Plasma-Assisted Fabrication of Molecularly Imprinted NiAl-LDH Layer on Ni Nanorod Arrays for Glyphosate Detection.

An inorganic-framework molecularly imprinted NiAl layered double hydroxide (MI-NiAl-LDH) with specific template molecule (glyphosate pesticide, Glyp) recognition ability was prepared on Ni nanorod arrays (Ni NRAs) through electrodeposition followed by a low-temperature O2 plasma treatment. The freestanding Ni/MI-NiAl-LDH NRA electrode had highly enhanced sensitivity and selectivity. The electrocatalytic oxidation of Glyp was proposed to occur at Ni3+ centers in MI-NiAl-LDH, and the current response depended linearly on the Glyp concentration from 10.0 nmol/L to 1.0 µmol/L (R2 = 0.9906), with the limit of detection (LOD) being 3.1 nmol/L (S/N = 3). An exceptional discriminating capability with tolerance for other similar organophosphorus compounds was achieved. Molecular imprinting (N and P residues) affected the electronic structure of NiAl-LDH, triggering the formation of highly active NiOOH sites at relatively lower anodic potentials and substantially enhancing the electrocatalytic oxidation ability of the NiAl-LDH interface toward the C-N bonds in Glyp. In combination with the surface enrichment effect of MI-NiAl-LDH toward template molecules, the electrochemical oxidation signal intensity of Glyp increased significantly, with a greater peak separation from interfering molecules. These results challenge the common belief that the excellent performance of inorganic-framework molecularly imprinted interfaces arises from their specific adsorption of template molecules, providing new insight into the development of high-performance organic-pollutant-sensing electrodes.

Effects of agricultural land use on the differentiation of nitrifier communities and functional patterns from natural terrestrial ecosystems.

Human activities severely affect the global nitrogen (N) cycle. Croplands receive intensive N fertilization; consequently, cropland and natural ecosystem differentiation often results in community and functional variation in N-transforming microbes, including nitrifiers, which perform nitrification central to N cycle. However, evidence of such variation is mostly limited to ammonia oxidizers (AO) in local fields, excluding soil heterogeneity and nitrite-oxidizing bacteria (NOB); the variation under diverse climatic and soil conditions is not comprehensively understood. We conducted a large-scale survey of 131 cropland and natural sites in China. The community patterns of ammonia-oxidizing bacteria (AOB) and NOB differed significantly between croplands and some natural ecosystems, whereas ammonia-oxidizing archaea (AOA) were not affected by ecosystem type. The AOB population and nitrification potential (NP) were significantly higher in agroecosystems than in natural systems except wetlands. Fewer co-occurrence interactions involving nitrifiers were observed in croplands than in natural ecosystems except forests, systematically indicating the ecological diversification of nitrifiers in potential microbial associations among these habitats. Ecosystem type, pH, organic matter (OM), total phosphorus (TP), mean annual temperature (MAT) and mean annual precipitation (MAP) were primary drivers of nitrifier community and functional shifts. This study provides the first large-scale evidence of overall nitrifier community (i.e., AOA, AOB and NOB) and potential functional shifts between agroecosystems and natural environments, enabling predictions of terrestrial N cycle under foreseeable natural land use conversions and global climate change.

Significant loss of soil inorganic carbon at the continental scale.

Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate soil carbonate dissolution and CO2 release. However, to date, few studies have addressed these processes. Here, we use meta-analysis and nationwide-survey datasets to investigate changes in soil inorganic carbon (SIC) stocks in China. We observe an overall decrease in SIC stocks in topsoil (0-30 cm) (11.33 g C m-2 yr-1) from the 1980s to the 2010s. Total SIC stocks have decreased by ∼8.99 ± 2.24% (1.37 ± 0.37 Pg C). The average SIC losses across China (0.046 Pg C yr-1) and in cropland (0.016 Pg C yr-1) account for ∼17.6%-24.0% of the terrestrial C sink and 57.1% of the soil organic carbon sink in cropland, respectively. Nitrogen deposition and climate change have profound influences on SIC cycling. We estimate that ∼19.12%-19.47% of SIC stocks will be further lost by 2100. The consumption of SIC may offset a large portion of global efforts aimed at ecosystem carbon sequestration, which emphasizes the importance of achieving a better understanding of the indirect coupling mechanisms of nitrogen and carbon cycling and of effective countermeasures to minimize SIC loss.

Distribution and Assembly Processes of Soil Fungal Communities along an Altitudinal Gradient in Tibetan Plateau.

In soil ecosystems, fungi exhibit diverse biodiversity and play an essential role in soil biogeochemical cycling. Fungal diversity and assembly processes across soil strata along altitudinal gradients are still unclear. In this study, we investigated the structure and abundance of soil fungal communities among soil strata and elevational gradients on the Tibetan Plateau using Illumina MiSeq sequencing of internal transcribed spacer1 (ITS1). The contribution of neutral and niche ecological processes were quantified using a neutral community model and a null model-based methodology. Our results showed that fungal gene abundance increased along altitudinal gradients, while decreasing across soil strata. Along with altitudinal gradients, fungal α-diversity (richness) decreased from surface to deeper soil layers, while ß-diversity showed weak correlations with elevations. The neutral community model showed an excellent fit for neutral processes and the lowest migration rate (R2 = 0.75). The null model showed that stochastic processes dominate in all samples (95.55%), dispersal limitations were dominated at the surface layer and decreased significantly with soil strata, while undominated processes (ecological drift) show a contrary trend. The log-normal model and the null model (ßNTI) correlation analysis also neglect the role of niche-based processes. We conclude that stochastic dispersal limitations, together with ecological drifts, drive fungal communities.

MicroRNA-552 Accelerates the Progression of Gastric Cancer by Targeting FOXO1 and Regulating PI3K/AKT Pathway.

The specific function of microRNA-552 (miR-552) has been investigated in several malignancies, except gastric cancer (GC). Therefore, this study was performed to determine the role of miR-552 in GC.GC tissues and adjacent non-tumor tissues were collected to determine the expressions of miR-552. Quantitative real-time polymerase chain reaction assays (RT-qPCR) and Western blot analysis were carried out to measure expression levels. The regulatory mechanism of miR-552 was explored by (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) MTT Assay, and Transwell assays. The binding site between miR-552 and FOXO1 was verified by dual-luciferase reporter assays. Upregulation of miR-552 expression was detected and associated with worse clinical outcomes in GC. Furthermore, high miR-552 expression predicted poor prognosis in GC patients. Functionally, upregulation of miR-552 promoted cell viability, metastasis, epithelial-mesenchymal transition (EMT), and phosphatidylinositol 3-kinase and protein kinase B (PI3K/AKT) pathway in GC. In addition, miR-552 was confirmed to target forkhead box O1 (FOXO1) directly and inversely regulate its expression in GC. Upregulation of FOXO1 reversed the carcinogenesis of miR-552 in GC. In conclusion, miR-552 serves as a tumor promoter in GC through targeting FOXO1 and regulating EMT and PI3K/AKT pathway.

Soil moisture and texture primarily control the soil nutrient stoichiometry across the Tibetan grassland.

Soil nutrient stoichiometry and its environmental controllers play vital roles in understanding soil-plant interaction and nutrient cycling under a changing environment, while they remain poorly understood in alpine grassland due to lack of systematic field investigations. We examined the patterns and controls of soil nutrients stoichiometry for the top 10cm soils across the Tibetan ecosystems. Soil nutrient stoichiometry varied substantially among vegetation types. Alpine swamp meadow had larger topsoil C:N, C:P, N:P, and C:K ratios compared to the alpine meadow, alpine steppe, and alpine desert. In addition, the presence or absence of permafrost did not significantly impact soil nutrient stoichiometry in Tibetan grassland. Moreover, clay and silt contents explained approximately 32.5% of the total variation in soil C:N ratio. Climate, topography, soil properties, and vegetation combined to explain 10.3-13.2% for the stoichiometry of soil C:P, N:P, and C:K. Furthermore, soil C and N were weakly related to P and K in alpine grassland. These results indicated that the nutrient limitation in alpine ecosystem might shifts from N-limited to P-limited or K-limited due to the increase of N deposition and decrease of soil P and K contents under the changing climate conditions and weathering stages. Finally, we suggested that soil moisture and mud content could be good predictors of topsoil nutrient stoichiometry in Tibetan grassland.

Pedogenic knowledge-aided modelling of soil inorganic carbon stocks in an alpine environment.

Accurate estimation of soil carbon is essential for accounting carbon cycling on the background of global environment change. However, previous studies made little contribution to the patterns and stocks of soil inorganic carbon (SIC) in large scales. In this study, we defined the structure of the soil depth function to fit vertical distribution of SIC based on pedogenic knowledge across various landscapes. Soil depth functions were constructed from a dataset of 99 soil profiles in the alpine area of the northeastern Tibetan Plateau. The parameters of depth functions were mapped from environmental covariates using random forest. Finally, SIC stocks at three depth intervals in the upper 1m depth were mapped across the entire study area by applying predicted soil depth functions at each location. The results showed that the soil depth functions were able to improve accuracy for fitting the vertical distribution of the SIC content, with a mean determination coefficient of R2=0.93. Overall accuracy for predicted SIC stocks was assessed on training samples. High Lin's concordance correlation coefficient values (0.84-0.86) indicate that predicted and observed values were in good agreement (RMSE: 1.52-1.67kgm-2 and ME: -0.33 to -0.29kgm-2). Variable importance showed that geographic position predictors (longitude, latitude) were key factors predicting the distribution of SIC. Terrain covariates were important variables influencing the three-dimensional distribution of SIC in mountain areas. By applying the proposed approach, the total SIC stock in this area is estimated at 75.41Tg in the upper 30cm, 113.15Tg in the upper 50cm and 190.30Tg in the upper 1m. We concluded that the methodology would be applicable for further prediction of SIC stocks in the Tibetan Plateau or other similar areas.

Characterization of the spatial variability of soil available zinc at various sampling densities using grouped soil type information.

The influence of anthropogenic activities and natural processes involved high uncertainties to the spatial variation modeling of soil available zinc (AZn) in plain river network regions. Four datasets with different sampling densities were split over the Qiaocheng district of Bozhou City, China. The difference of AZn concentrations regarding soil types was analyzed by the principal component analysis (PCA). Since the stationarity was not indicated and effective ranges of four datasets were larger than the sampling extent (about 400 m), two investigation tools, namely F3 test and stationarity index (SI), were employed to test the local non-stationarity. Geographically weighted regression (GWR) technique was performed to describe the spatial heterogeneity of AZn concentrations under the non-stationarity assumption. GWR based on grouped soil type information (GWRG for short) was proposed so as to benefit the local modeling of soil AZn within each soil-landscape unit. For reference, the multiple linear regression (MLR) model, a global regression technique, was also employed and incorporated the same predictors as in the GWR models. Validation results based on 100 times realization demonstrated that GWRG outperformed MLR and can produce similar or better accuracy than the GWR approach. Nevertheless, GWRG can generate better soil maps than GWR for limit soil data. Two-sample t test of produced soil maps also confirmed significantly different means. Variogram analysis of the model residuals exhibited weak spatial correlation, rejecting the use of hybrid kriging techniques. As a heuristically statistical method, the GWRG was beneficial in this study and potentially for other soil properties.

Precise estimation of soil organic carbon stocks in the northeast Tibetan Plateau.

There is a need for accurate estimate of soil organic carbon (SOC) stocks for understanding the role of alpine soils in the global carbon cycle. We tested a method for mapping digitally the continuous distribution of the SOC stock in three dimensions in the northeast of the Tibetan Plateau. The approach integrated the spatial distribution of the mattic epipedon which is a special surface horizon widespread and rich in organic matter in Tibetan grasslands. Prediction models resulted in high prediction accuracy. An average SOC stock in the mattic epipedon was estimated to be 4.99 kg m(-2) in a mean depth of 14 cm. The amounts of SOC in the mattic epipedon, the upper 30 cm and 50 cm accounted for about 21%, 80% and 89%, respectively, of the total SOC stock in the upper 1 m depth. Compared with previous estimates, our approach resulted in more reliable predictions. The mattic epipedon was proven to be an important factor for modelling the realistic distribution of the SOC stock in Tibetan grasslands. Vegetation-related covariates have the most important influence on the distribution of the mattic epipedon and the SOC stock in the alpine grassland soils of northeast Tibetan Plateau.

Predictive Mapping of Topsoil Organic Carbon in an Alpine Environment Aided by Landsat TM.

The objective of this study was to examine the reflectance of Landsat TM imagery for mapping soil organic Carbon (SOC) content in an Alpine environment. The studied area (ca. 3*104 km2) is the upper reaches of the Heihe River at the northeast edge of the Tibetan plateau, China. A set (105) of topsoil samples were analyzed for SOC. Boosted regression tree (BRT) models using Landsat TM imagery were built to predict SOC content, alone or with topography and climate covariates (temperature and precipitation). The best model, combining all covariates, was only marginally better than using only imagery. Imagery alone was sufficient to build a reasonable model; this was a bit better than only using topography and climate covariates. The Lin's concordance correlation coefficient values of the imagery only model and the full model are very close, larger than the topography and climate variables based model. In the full model, SOC was mainly explained by Landsat TM imagery (65% relative importance), followed by climate variables (20%) and topography (15% of relative importance). The good results from imagery are likely due to (1) the strong dependence of SOC on native vegetation intensity in this Alpine environment; (2) the strong correlation in this environment between imagery and environmental covariables, especially elevation (corresponding to temperature), precipitation, and slope aspect. We conclude that multispectral satellite data from Landsat TM images may be used to predict topsoil SOC with reasonable accuracy in Alpine regions, and perhaps other regions covered with natural vegetation, and that adding topography and climate covariables to the satellite data can improve the predictive accuracy.

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Isolation and characterization of a proteinaceous α-amylase inhibitor AAI-CC5 from Streptomyces sp. CC5, and its gene cloning and expression.

An α-amylase inhibitor producing Streptomyces sp. strain CC5 was isolated from soil. A proteinaceous α-amylase inhibitor AAI-CC5 was purified from strain CC5. AAI-CC5 specifically inhibited mammalian α-amylases. The molecular weight of the inhibitor was determined to be 8,212 Da by MALDI-TOF Mass Spectrum. The N-terminal 15 amino acid residues of the purified AAI-CC5 were DTGSPAPECVEYFQS, which is dissimilar to other reported proteinaceous α-amylase inhibitors. AAI-CC5 is a pH insensitive and heat-stable protein, and cannot be hydrolysed by trypsin. AAI-CC5 was cloned and expressed in Escherichia coli BL21 (DE3) with a hexa-histidine tag on the C terminal. AAI-CC5 shared 82 % identity with Parvulustat. The recombinant α-amylase inhibitor was purified to homogeneity by one-step affinity chromatography using Ni(2+)-NTA resin with molecular mass of 9,404 Da. Steady state kinetics studies of α-amylase and the inhibitor revealed an irreversible, non-competitive inhibition mechanism with IC50 and Ki value of 6.43 ×1 10(-11) and 4.45 × 10(-11) M respectively. These results suggest this novel α-amylase inhibitor possessed powerful inhibitory activity for α-amylase, and it may be a candidate in research of diabetes therapy and obesity treatment.

Potassium hydroxide-ethylene diamine tetraacetic acid method for the rapid preparation of small-scale PCR template DNA from actinobacteria.

Genomic DNA extraction from Gram-positive bacteria is a laborious and time-consuming process. A rapid and convenient method was established to extract genomic DNA from a single colony as a PCR template. KOH-EDTA is used as a lysis buffer to disrupt the cell envelope, releasing genomic DNA, and Tris-HCl (pH = 4) is then added to neutralize the lysate. The lysate can be used directly as a template for PCR amplification. 16S rDNA was successfully amplified from Gram-positive bacteria from the genera of Bacillus, Streptomyces, Micromonospora, Nonomuraea, Microbispora, and Staphylococcus. Amplification of the trpB gene indicated that this method could also be applied to the amplification of functional genes. Compared to colony PCR methods without KOH-EDTA, this method is extremely fast and efficient, and it is applicable to high-throughput PCR amplifications.

[Clinical study of perineural invasion in patients with rectal cancer].

OBJECTIVE: To investigate the clinical significance of perineural invasion(PNI) in rectal cancer. METHODS: Clinical data of 204 patients undergoing resection of low rectal cancer from January 2003 to January 2005 at the First People's Hospital of Chenzhou were analyzed retrospectively. Paraffin sections of surgical specimens from all the patients who underwent resection of low rectal cancer were stained with HE. PNI-positive was defined as infiltration of carcinoma cell into the perineurium or neural fascia. The association of PNI with clinicopathologic features and prognosis of rectal cancer was analyzed. RESULTS: PNI was positive in 31.9%(65/204) of the patients. The tumor size, depth of invasion, lymph node metastasis, TNM stage, tumor growth pattern, histologic grade, tumor resection were significantly associated with PNI. The overall survival time of the PNI-positive patients was shorter than that of the PNI-negative patients[(43.8±1.5) months vs.(57.2±1.5) months, P<0.01]. Furthermore, the overall survival time of the PNI-positive stage II( patients was shorter than that of the stage III( patients [(46.5±3.2) months vs. (55.7±1.2) months, P<0.05]. CONCLUSION: PNI can be used as one of the indicators to predict the prognosis of patients with rectal cancer.

Assessment of bioaccessibility and exposure risk of arsenic and lead in urban soils of Guangzhou City, China.

Soil ingestion is an important human exposure pathway of heavy metals in urban environments with heavy metal contaminated soils. This study aims to assess potential health risks of heavy metals in soils sampled from an urban environment where high frequency of human exposure may be present. A bioaccessibility test is used, which is an in vitro gastrointestinal (IVG) test of soluble metals under simulated physiological conditions of the human digestion system. Soil samples for assessing the oral bioaccessibility of arsenic (As) and lead (Pb) were collected from a diverse range of different land uses, including urban parks, roadsides, industrial sites and residential areas in Guangzhou City, China. The soil samples contained a wide range of total As (10.2 to 61.0 mg kg(-1)) and Pb (38.4 to 348 mg kg(-1)) concentrations. The bioaccessibility of As and Pb in the soil samples were 11.3 and 39.1% in the stomach phase, and 1.9 and 6.9% in the intestinal phase, respectively. The As and Pb bioaccessibility in the small intestinal phase was significantly lower than those in the gastric phase. Arsenic bioaccessibility was closely influenced by soil pH and organic matter content (r (2) = 0.451, p < 0.01) in the stomach phase, and by organic matter, silt and total As contents (r (2) = 0.604, p < 0.001) in the intestinal phase. The general risk of As and Pb intake for children from incidental ingestion of soils is low, compared to their maximum doses, without causing negative human health effects. The exposure risk of Pb in the soils ranked in the order of: industrial area/urban parks > residential area/road side. Although the risk of heavy metal exposure from direct ingestion of urban soils is relatively low, the risk of inhalation of fine soil particulates in the air remains to be evaluated.