Different "nongrain" activities affect the accumulation of heavy metals and their source-oriented health risks on cultivated lands.

"Nongrain" production on cultivated land is one of the primary environmental issues in China. Different "nongrain" activities may introduce different pollution sources to the local environment, leading to variations in heavy metal contents in soil, which can profoundly impact national food security. In this study, three typical "nongrain" regions (Nanxun (NX), Xiaoshan (XS) and Lin'an (LA)) with intensive aquaculture, tea planting and flower (seedling) growth on cultivated land around the Hangzhou metropolitan area were selected to address the spatial heterogeneity of accumulation levels, sources and source-oriented health risks of heavy metals in soil. The results showed that Hg was the main pollutant in NX and XS, while Cd and As were the major contaminants in LA. Aquiculture and sericultural industries (37.43%), natural sources (23.59%) and industrial activities (38.99%) were the major sources in NX; atmospheric deposition (37.73%), flower and seedling planting (23.49%) and metal-related industries (35.16%) were the major sources in XS; and atmospheric deposition (28.06%), excessive application of fertilizers and pesticides during tea planting (43.47%) and natural sources (28.47%) were the major sources in LA. The major risk population, area, exposure route and hazardous elements were children, LA, ingestion and As and Cr, respectively. From the perspective of source-based health risk assessment, in addition to natural sources that are difficult to intervene in, industrial activities, especially leather and wood process industries, metal-related industries and excessive fertilizer and pesticide application during tea planting contributed the most to the total health risk, which explained 67%, 41% and 42%, respectively, of the total risk in NX, XS and LA. High health risks are present in sources with heavy loadings of hazardous heavy metals (As and Cr); thus, to protect human health, the corresponding high-risk anthropogenic pollution sources in different "nongrain" areas need to be controlled.

Quantitative heterogeneous source apportionment of toxic metals through a hybrid method in spatial random fields.

Toxic metals in soils pose hazards to food security and human health. Accurate source apportionment provides foundation for pollution prevention. In this study, a novel hybrid method that combines positive matrix factorization, Bayesian maximum entropy and integrative predictability criterion is proposed to provide a new perspective for exploring the heterogeneity of pollution sources in spatial random fields. The results suggest that Cd, As and Cu are the predominant pollutants, with exceedance rates of 27%, 12% and 11%, respectively. The new method demonstrates superiority in predicting toxic metals when combined major and all sources as auxiliary information., with the improvements of 44% and 46%, respectively, Although the major sources identified with the hybrid method are the primary contributors to the accumulation of toxic metals (e.g. coal combustion for Hg, traffic emission for Pb and Zn, industrial activities for As, agricultural activities for Cd and Cu and natural sources for Cr and Ni), the impact of nonmajor sources on toxic metal sin specific regions should not be ignored (e.g. industrial activities on Ni, Pb and Zn in the north and natural sources on Cd, Cu, As, Pb and Zn in the south). For better pollution control, specific local sources should be considered.

Processing toxic metal source proxies appropriately for better spatial heterogeneity source apportionment.

Soil toxic metals have strong spatial heterogeneity, and their sources vary among regions. Thus, this study integrated the Catreg and geographically weighted regression (GWR) models to quantitatively extract the main source proxies (numerical and categorical variables were analyzed simultaneously) for different toxic metals and analyze the spatial heterogeneity of the distributions of these sources. Pb, Cd and Hg were the predominant toxic metals in soil. Of the samples with Pb, Cd and Hg, 84.12 %, 68.03 % and 41.57 % exceeded the background values, and 5.36 %, 6.42 % and 5.43 % were moderately contaminated according to the geoaccmulation index, respectively. Industrial activities, with relative importance values of 17.82 %, 31.54 % and 26.51 % for Cd, Hg and Pb, respectively, were the predominant source of these metals especially, in their high-content cluster areas (central urban areas). Soil available phosphorus was another important factor (relative importance values of 13.03 %, 13.41 % and 25.55 % for Cd, Hg and Pb, respectively), and agricultural activities (especially the overuse of phosphoric fertilizers) were identified as an anthropogenic source of these toxic metals. Soil parent material had the greatest influence on As and Cr, with relative importance values of 19.88 % and 19.09 %, respectively, especially in their high-content accumulation area (the eastern coastal area), indicating that these toxic metals mainly come from natural sources. Slope had important impacts on toxic metal accumulation (relative importance values of 17.48 %, 21.22 %, 12.40 % and 16.13 % for Cd, Hg, Cr and As, respectively) by influencing industrial distribution and pollutant migration. By changing the soil adsorption capacity, soil organic matter (explaining 13.01 % of Pb) and soil pH (explaining 14.58 % of As and 12.40 % of Cr) strongly influenced toxic metal accumulation. This study highlights the benefits of the integrated Catreg-GWR model for analyzing multiple spatially heterogeneous environmental data types (numerical and categorical variables), providing a potential foundation for local pollution prevention.

Pollution threshold assessment and risk area delineation of heavy metals in soils through the finite mixture distribution model and Bayesian maximum entropy theory.

Pollution threshold and high-risk area determination for heavy metals is important for effectively developing pollution control strategies. Based on heavy metal contents in 3627 dense samples, an integrated framework combining the finite mixture distribution model and Bayesian maximum entropy (BME) theory was proposed to assess pollution thresholds, contamination levels and risk areas in an uncertain environment for soil heavy metals. The results showed that the average heavy metal contents were in the order Zn > Cr > Pb > Cu > Ni > As > Cd > Hg, with strong/moderate variation, and the corresponding pollution thresholds were 158.39, 84.29, 47.84, 49.75, 28.95, 18.01, 0.49 and 0.16 mg/kg, respectively. The thresholds were consistently greater than the Zhejiang Province backgrounds but lower than the national risk screening values, except for Cd. Approximately 27.9% of the samples were classified as contaminated at various levels, and they were distributed in the northern, northwestern and eastern regions of the study area. Additionally, 3.73%, 5.34% and 8.22% of the total area were classified as at-risk areas under confidence levels of 95%, 90% and 75%, respectively, through BME theory. The findings provide a reasonable classification system and suggestions for heavy metal pollution management and control.

Contamination assessment, health risk evaluation, and source identification of heavy metals in the soil-rice system of typical agricultural regions on the southeast coast of China.

To quantitatively assess heavy metal accumulation and potential ecological and human health risks as well as analyze the sources of metals in a typical soil-rice system located on the southeast coast of China, 120 topsoil samples and corresponding rice grain samples were collected across the study area. The concentrations of As, Cd, Pb, Cr, Hg, Zn, Cu, and Ni were analyzed. The results revealed that Hg, Cd, and Cu were the main pollutants in soils. Besides, according to geo-accumulation value of Hg, 18.3% of samples were at or above moderate contamination levels. Additionally, the soil was in moderate ecological risk from combined heavy metal pollution, and 49.7% and 27.0% of this risk could be attributed to Hg and Cd pollution, respectively, due to their high toxic-response factors. For the rice samples, Cd content showed the highest biological accumulation coefficient value (40.8%) in rice grains and was slightly greater than its maximum allowable value (MAV) (0.2 mg/kg) in 7.5% of samples, whereas the other metals were all lower than their corresponding MAVs. Heavy metal exposure (especially As exposure) via rice consumption causes significant carcinogenic and non-carcinogenic risks to adults, and non-carcinogenic risk to children, while the carcinogenic risk to children was at tolerable level. Greater rice consumption might be responsible for the greater health risk to adults than children. Natural sources (loaded heavily with Cr and Ni) such as lithogenic components and soil parent materials, agricultural activities (loaded heavily with Cd, Cu, and Zn), especially excessive use of pesticides and fertilizers, and industrial activities (loaded heavily with Hg, Pb, and As) including vehicle emissions, coal combustion, and those of the textile and chemical industries were identified as the main sources. Effective regulations should be enforced to guarantee the safety of farm produce and protect ecological and human health in the study area.

Contamination assessment and source apportionment of heavy metals in agricultural soil through the synthesis of PMF and GeogDetector models.

Heavy metal pollution in soils has attracted great attention worldwide in recent decades. Selecting Hangzhou as a case study location, this research proposed the synthesis application of positive matrix factorization (PMF) and GeogDetector models for quantitative analysis of pollution sources, which is the basis for subsequent soil pollution prevention and remediation. In total, 2150 surface soil samples were collected across the study area. Although the mean concentrations of As, Cd, Cr, Hg, and Pb in the soils were lower than the National Environmental Quality Standards for Soils in China, the mean contents of As and Cd were higher than their corresponding local background values by approximately 1.31 and 1.59 times, respectively, indicating that heavy metals have been enriched in topsoil. Agricultural activities, industrial activities, and soil parent materials were the main sources of heavy metal pollution in the soils, accounting for 63.4%, 19.8%, and 16.8% of the total heavy metal accumulation, respectively. Cr was derived mainly from soil parent materials (80.72%). Cd was closely associated with agricultural activities (73.68%), such as sewage irrigation and application of fertilizer. Mercury was mainly attributed to industrial activities (92.38%), such as coal mining and smelting. As was related to agricultural (57.83%) and natural (35.56%) sources, and Pb was associated with industrial (42.42%) and natural (41.83%) sources. The new synthesis models are useful for estimating the source apportionment of heavy metals in soils.

Identifying the sources and spatial patterns of potentially toxic trace elements (PTEs) in Shanghai suburb soils using global and local regression models.

Destructive development of suburban areas in some metropolises has exposed suburban soils to high risk of potentially toxic trace elements (PTEs) enrichment, which also threatens human and ecosystem health. This study investigated the pollution status, sources and spatial patterns of four PTEs (Pb, Cd, Cr and As) in 1805 soil samples collected from the suburbs of Shanghai in 2015. Nineteen potential sources, including: 6 soil property factors, 10 proximity factors and 3 topography factors, were selected to help explain the PTEs aggregation using logistic regression models from global and local perspectives. The statistical results of PTEs concentration revealed that Cd showed the highest pollution risk in local soils, which was followed by As. Soil property was the primary factor affecting the PTEs (except Cr) enrichment, both identified by global models and local models. The local model particularly emphasized the significant correlation between soil property and PTEs in most parts of the outer suburbs and southeastern inner suburbs. Some proximity factors such as distance to district center and water were negatively correlated with Cd pollution and some topography factors such as elevation and slope were closely related to As pollution. It is worth noting that in the coastal areas, especially Chongming Island, there were obvious PTEs depositions in the soil near the estuary. This study helps to identify the sources of anthropogenic contamination and geogenic enrichment of the four PTEs and their spatial patterns, playing an essential role in formulating regional environmental policies for coastal cities.

Improved heavy metal mapping and pollution source apportionment in Shanghai City soils using auxiliary information.

Soil heavy metal pollution can be a serious threat to human health and the environment. The accurate mapping of the spatial distribution of soil heavy metal pollutant concentrations enables the detection of high pollution areas and facilitates pollution source apportionment and control. To make full use of auxiliary soil properties information and show that they can improve mapping, a synthesis of the Bayesian Maximum Entropy (BME) theory and the Geographically Weighted Regression (GWR) model is proposed and implemented in the study of the Shanghai City soils (China). The results showed that, compared to traditional techniques, the proposed BME-GWR synthesis has certain important advantages: (a) it integrates heavy metal measurements and auxiliary information on a sound theoretical basis, and (b) it performs better in terms of both prediction accuracy and implementation flexibility (including the assimilation of multiple data sources). Based on the heavy metal concentration maps generated by BME-GWR, we found that the As, Cr and Pb concentration levels are high in the eastern part of Shanghai, whereas high Cd concentration levels were observed in the northwestern part of the city. Organic carbon and pH were significantly correlated with most of the heavy metals in Shanghai soils. We concluded that Cd pollution is mainly the result of agricultural activities, and that the Cr pollution is attributed to natural sources, whereas Pb and As have compound pollution sources. Future studies should investigate the implementation of BME-GWR in the case of space-time heavy metal mapping and its ability to integrate human activity information and soil category variables.

The association between heavy metal soil pollution and stomach cancer: a case study in Hangzhou City, China.

Stomach cancer (SC) is a severe health burden, with nearly half of the world's cases found in China. Noticeably, the emissions of heavy metals into the environment have increased alongside rapid urbanization and industrialization in China. However, as regards carcinogenic associations, the relationship between heavy metals and SC is yet unclear. Based on 9378 newly diagnosed SC cases in Hangzhou City from 2009 to 2012, this work is concerned with the quantitative characterization of the spatial distribution pattern of SC incidence and its geographical association with soil heavy metals by means of a novel geographical model. The results show that (a) Cd is one of the severe soil pollutants in Hangzhou; (b) higher SC incidence clusters are in central Hangzhou, whereas lower clusters are found in the northeast and southwest with a male to female incidence ratio about 2.2:1; (c) although when considered separately, the heavy metals in this work do not have a considerable impact on the distribution of SC incidence in Hangzhou City, nevertheless, the joint effects of multiple heavy metals have significant impacts on SC risk. The present work calls for a rigorous quantitative assessment of the integrated heavy metal soil pollution and its effects on SC incidence.

The spatio-temporal distribution and risk factors of thyroid cancer during rapid urbanization-A case study in China.

BACKGROUND: Incidences of thyroid cancer (TC) have been increasing worldwide in recent decades. In this research, we aimed to analyze the spatiotemporal pattern of TC and explore relevant environmental risk factors in Hangzhou (HZ), which is rapidly urbanizing and home to the highest TC incidence in China. METHODS: Spatial scan statistic was employed to analyze the spatiotemporal pattern of TC in HZ from 2008 to 2012. The geographically weighted regression model (GWR) was implemented to explore environmental risk factors. Its performance was compared to the traditional ordinary least squares model (OLS). RESULTS: A total of 7147 TC cases (5385 female and 1762 male) were diagnosed in HZ from 2008 to 2012. High TC clusters were detected in the northeast, urban areas and expanded outwards while low clusters were located in the southwest rural areas. The GWR model generally performed better than the OLS in analyzing the associations between TC incidence and environmental factors. The industrial density, chemical oxygen demand of wastewater (COD) and the percentage of building area had a strong positive influence on the TC in the northeastern suburb areas of HZ, while the elevation, slope and the percentage of forest area had a significant negative correlation with TC in the middle, rural areas of HZ. Meanwhile, the accessibility to health care might have an impact on the TC incidence. CONCLUSION: High clusters were mostly located in the northeastern urban areas and showed an expansion process from the center urban area to the suburb area, especially for female TC. Intensive industrial activities and the emission of organic pollutants, which positively correlated with the high TC clusters in the northeast suburb areas of HZ, should get proper attention.

Contribution of industrial density and socioeconomic status to the spatial distribution of thyroid cancer risk in Hangzhou, China.

BACKGROUND: The thyroid cancer (TC) incidence in China has increased dramatically during the last three decades. Typical in this respect is the case of Hangzhou city (China), where 7147 new TC cases were diagnosed during the period 2008-2012. Hence, the assessment of the TC incidence risk increase due to environmental exposure is an important public health matter. METHODS: Correlation analysis, Analysis of Variance (ANOVA) and Poisson regression were first used to evaluate the statistical association between TC and key risk factors (industrial density and socioeconomic status). Then, the Bayesian maximum entropy (BME) theory and the integrative disease predictability (IDP) criterion were combined to quantitatively assess both the overall and the spatially distributed strength of the "exposure-disease" association. RESULTS: Overall, higher socioeconomic status was positively correlated with higher TC risk (Pearson correlation coefficient=0.687, P<0.01). Compared to people of low socioeconomic status, people of median and high socioeconomic status showed higher TC risk: the Relative Risk (RR) and associated 95% confidence interval (CI) were found to be, respectively, RR=2.29 with 95% CI=1.99 to 2.63, and RR=3.67 with 95% CI=3.22 to 4.19. The "industrial density-TC incidence" correlation, however, was non-significant. Spatially, the "socioeconomic status-TC" association measured by the corresponding IDP coefficient was significant throughout the study area: the mean IDP value was -0.12 and the spatial IDP values were consistently negative at the township level. It was found that stronger associations were distributed among residents mainly on a stripe of land from northeast to southwest (consisting mainly of sub-district areas). The "industrial density-TC" association measured by its IDP coefficient was spatially non-consistent. CONCLUSIONS: Socioeconomic status is an important indicator of TC risk factor in Hangzhou (China) whose effect varies across space. Hence, socioeconomic status shows the highest TC risk effect in sub-district areas.

Improving Spatiotemporal Breast Cancer Assessment and Prediction in Hangzhou City, China.

Breast cancer (BC) is the main cause of death of female cancer patients in China. Mainstream mapping techniques, like spatiotemporal ordinary kriging (STOK), generate disease incidence maps that improve our understanding of disease distribution. Yet, the implementation of these techniques experiences substantive and technical complications (due mainly to the different characteristics of space and time). A new spatiotemporal projection (STP) technique that is free of the above complications was implemented to model the space-time distribution of BC incidence in Hangzhou city and to estimate incidence values at locations-times for which no BC data exist. For comparison, both the STP and the STOK techniques were used to generate BC incidence maps in Hangzhou. STP performed considerably better than STOK in terms of generating more accurate incidence maps showing a closer similarity to the observed incidence distribution, and providing an improved assessment of the space-time BC correlation structure. In sum, the inter-connections between space, time, BC incidence and spread velocity established by STP allow a more realistic representation of the actual incidence distribution, and generate incidence maps that are more accurate and more informative, at a lower computational cost and involving fewer approximations than the incidence maps produced by mainstream space-time techniques.

[Geographic spatial pattern of digestive system cancers in Yiwu city].

OBJECTIVE: To analyze the geographic spatial patterns and risk areas of main digestive system cancers in Yiwu city. METHODS: Newly diagnosed cases of esophageal, gastric and colorectal cancer during 2010-2014 were obtained from Yiwu Center for Disease Control and Prevention (CDC). The household registration population data in 2013 were obtained from public security bureau. Hierarchy clustering and partitioning regionalization method was used to generate geographic units. Global Moran's I was used to evaluate whether cancer incidence was significantly clustered in space, Anselin Local Moran's I was used to identify statistically significant hot spots, cold spots, and spatial outliers, and Spatial Scan Statistics was implemented to analyze the relative risk of cancers in different areas. RESULTS: The 5-year average incidence of esophageal, gastric and colorectal cancers were 9.99/100 000, 34.01/100 000 and 31.46/100 000, respectively. Males showed significantly higher incidence than females. The incidence was heterogeneous throughout the study area. Spatial Scan analysis revealed that southern Yiwu presented a significantly higher male esophageal cancer (RR=1.78) and gastric cancer (RR=1.87) risk. The central area of Yiwu showed a significantly lower female esophageal cancer risk (RR=0.00) and male stomach cancer risk (RR=0.63) and the northern Yiwu exhibited a significantly lower female colorectal cancer risk (RR=0.48). CONCLUSIONS: The incidence of main digestive tract cancers shows a heterogeneous distribution in Yiwu city.

Soil Landscape Pattern Changes in Response to Rural Anthropogenic Activity across Tiaoxi Watershed, China.

Soil sealing (loss of soil resources due to extensive land covering for the purpose of house building, road construction etc.) and subsequent soil landscape pattern changes constitute typical environmental problems in many places worldwide. Previous studies concentrated on soil sealing in urbanized regions, whereas rural areas have not been given sufficient attention. Accordingly, this paper studies soil landscape pattern dynamics (i.e., landscape pattern changes in response to rural anthropogenic activities) in the Tiaoxi watershed (Zhejiang province, eastern China), in which surface sealing is by far the predominant component of human forcing with respect to environmental change. A novel approach of quantifying the impacts of rural anthropogenic activities on soil resources is presented. Specifically, quantitative relationships were derived between five soil landscape pattern metrics (patch density, edge density, shape index, Shannon's diversity index and aggregation index) and three rural anthropogenic activity indicators (anthropogenic activity intensity, distance to towns, and distance to roads) at two landscape block scales (3 and 5 km) between 1985 and 2010. The results showed that the Tiaoxi watershed experienced extensive rural settlement expansion and high rates of soil sealing. Soil landscapes became more fragmented, more irregular, more isolated, and less diverse. Relationships between soil landscape pattern changes and rural anthropogenic activities differed with the scale (spatial and temporal) and variable considered. In particular, the anthropogenic activity intensity was found to be the most important indicator explaining social development intensity, whereas the other two proximity indicators had a significant impact at certain temporal interval. In combination with scale effects, spatial dependency (correlation) was shown to play a key role that should be carefully taken into consideration in any relevant environmental study. Overall, the findings of this work suggest that soil sealing can be a critical human forcing issue with considerable consequences deserving serious attention by the experts, the public and the government alike.

Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China.

Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008-2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008-2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

A Geographic Analysis about the Spatiotemporal Pattern of Breast Cancer in Hangzhou from 2008 to 2012.

BACKGROUND: Breast cancer (BC) is the most common female malignant tumor. Previous studies have suggested a big incidence disparity among different cities in China. The present work selected a typical city, Hangzhou, to study BC incidence disparity within the city. METHODS: Totally, 8784 female breast cancer cases were obtained from the Hangzhou Center for Disease Control and Prevention during the period 2008-2012. Analysis of Variance and Poisson Regression were the statistical tools implemented to compare incidence disparity in the space-time domain (reference group: township residents during 2008, area: subdistrict, town, and township, time frame: 2008-2012), space-time scan statistics was employed to detect significant spatiotemporal clusters of BC compared to the null hypothesis that the probability of cases diagnosed at a particular location was equal to the probability of cases diagnosed in the whole study area. Geographical Information System (GIS) was used to generate BC spatial distribution and cluster maps at the township level. RESULTS: The subdistrict populations were found to have the highest and most stable BC incidence. Although town and township populations had a relatively low incidence, it displayed a significant increasing trend from 2008 to 2012. The BC incidence distribution was spatially heterogeneous and clustered with a trend-surface from the southwest low area to the northeast high area. High clusters were located in the northeastern Hangzhou area, whereas low clusters were observed in the southwestern area during the time considered. CONCLUSIONS: Better healthcare service and lifestyle changes may be responsible for the increasing BC incidence observed in towns and townships. One high incidence cluster (Linping subdistrict) and two low incidence clusters (middle Hangzhou) were detected. The low clusters may be attributable mainly to developmental level disparity, whereas the high cluster could be associated with other risk factors, such as environmental pollution.

Urban-rural disparity of breast cancer and socioeconomic risk factors in China.

Breast cancer is one of the most commonly diagnosed cancers worldwide. The primary aim of this work is the study of breast cancer disparity among Chinese women in urban vs. rural regions and its associations with socioeconomic factors. Data on breast cancer incidence were obtained from the Chinese cancer registry annual report (2005-2009). The ten socioeconomic factors considered in this study were obtained from the national population 2000 census and the Chinese city/county statistical yearbooks. Student's T test was used to assess disparities of female breast cancer and socioeconomic factors in urban vs. rural regions. Pearson correlation and ordinary least squares (OLS) models were employed to analyze the relationships between socioeconomic factors and cancer incidence. It was found that the breast cancer incidence was significantly higher in urban than in rural regions. Moreover, in urban regions, breast cancer incidence remained relatively stable, whereas in rural regions it displayed an annual percentage change (APC) of 8.55. Among the various socioeconomic factors considered, breast cancer incidence exhibited higher positive correlations with population density, percentage of non-agriculture population, and second industry output. On the other hand, the incidence was negatively correlated with the percentage of population employed in primary industry. Overall, it was observed that higher socioeconomic status would lead to a higher breast cancer incidence in China. When studying breast cancer etiology, special attention should be paid to environmental pollutants, especially endocrine disruptors produced during industrial activities. Lastly, the present work's findings strongly recommend giving high priority to the development of a systematic nationwide breast cancer screening program for women in China; with sufficient participation, mammography screening can considerably reduce mortality among women.

[Hierarchical regionalization for spatial epidemiology: a case study of thyroid cancer incidence in Yiwu, Zhejiang].

OBJECTIVE: Sporadic cases occurring in mall geographic unit could lead to extreme value of incidence due to the small population bases, which would influence the analysis of actual incidence. METHODS: This study introduced a method of hierarchy clustering and partitioning regionalization, which integrates areas with small population into larger areas with enough population by using Geographic Information System (GIS) based on the principles of spatial continuity and geographical similarity (homogeneity test). This method was applied in spatial epidemiology by using a data set of thyroid cancer incidence in Yiwu, Zhejiang province, between 2010 and 2013. RESULTS: Thyroid cancer incidence data were more reliable and stable in the new regionalized areas. Hotspot analysis (Getis-Ord) on the incidence in new areas indicated that there was obvious case clustering in the central area of Yiwu. CONCLUSION: This method can effectively solve the problem of small population base in small geographic units in spatial epidemiological analysis of thyroid cancer incidence and can be used for other diseases and in other areas.

[Reappraisal of the impacts of human Runt-related transcription factor gene 3 expression on differentiation and prognosis of gastric cancer].

OBJECTIVE: To investigate the expression of Runt-related transcription factor gene 3(RUNX3) in gastric cancer and its impact on the outcome of gastric cancer patients. METHODS: By using immunohistochemistry staining and western blot assay, the expression of RUNX3 protein in 66 cases of gastric cancer with various clinicopathologic characteristics were detected, and the effects of RUNX3 protein expression on the outcome of patients undergone surgical resection were evaluated. RESULTS: (1) The expression rate of RUNX3 protein in gastric cancer lesions was 60.6% (40/66), and RUNX3 protein was mainly expressed in the cytoplasm of cancer cells. RUNX3 protein expression in tumor tissues was significantly higher than that in non-tumor tissues. (2) RUNX3 protein expression was correlated with tumor differentiation (P=0.025) and Lauren's classification (P=0.034), but had no relationship with the TNM stage (P=0.085). (3) In sharp contrast, the median survival time of patients who had tumors with negative and positive RUNX3 protein expression were 2478 and 2187 days respectively (P=0.016). CONCLUSIONS: RUNX3 protein influences the differentiation of gastric cancer. The role of RUNX3 protein as a tumor-suppressor in tumorigenesis and differentiation of gastric carcinoma need to be further evaluated.

Applying proteomic methodologies to analyze the effect of methionine restriction on proliferation of human gastric cancer SGC7901 cells.

BACKGROUND: Methionine dependence is a feature unique to cancer cells, exhibited as inability to grow in a methionine-depleted environment supplemented with homocysteine, the immediate metabolic precursor of methionine. However, the molecular mechanisms by which methionine restriction inhibits cancer cells growth have not been elucidated. The effect of methionine restriction on the protein expression in gastric cancer cells was studied. METHODS: SGC7901 cells were treated with M-H+ medium for 5 days, which was followed by analysis of total cellular protein from cells by a combination of 2-DE and MS. Then the differential expressional levels of partially identified proteins were determined by Western blot analysis. RESULTS: The well-resolved, reproducible 2-DE patterns of SGC7901 cells cultured in M+H- or M-H+ medium were established. The 10 differential proteins between pairs of gastric cancer cells SGC7901 cultured either in M+H- medium or M-H+ medium, were identified by MALDI-TOF/TOF MS, and the differential expression levels of 2 identified proteins were confirmed. CONCLUSION: These data will be valuable for further study of the molecular mechanisms by which methionine restriction induces cell cycle arrest and apoptosis in human gastric cancer.