Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids.

BACKGROUND: Biliary atresia (BA) is a rare fatal liver disease in children, and the aim of this study was to develop a method to diagnose BA early. METHODS: We determined serum levels of matrix metalloproteinase-7 (MMP-7), the results of 13 liver tests, and the levels of 20 bile acids, and integrated computational models were constructed to diagnose BA. RESULTS: Our findings demonstrated that MMP-7 expression levels, as well as the results of four liver tests and levels of ten bile acids, were significantly different between 86 BA and 59 non-BA patients (P < 0.05). The computational prediction model revealed that MMP-7 levels alone had a higher predictive accuracy [area under the receiver operating characteristic curve (AUC) = 0.966, 95% confidence interval (CI): 0.942, 0.989] than liver test results and bile acid levels. The AUC was 0.890 (95% CI 0.837, 0.943) for liver test results and 0.825 (95% CI 0.758, 0.892) for bile acid levels. Furthermore, bile levels had a higher contribution to enhancing the predictive accuracy of MMP-7 levels (AUC = 0.976, 95% CI 0.953, 1.000) than liver test results. The AUC was 0.983 (95% CI 0.962, 1.000) for MMP-7 levels combined with liver test results and bile acid levels. In addition, we found that MMP-7 levels were highly correlated with gamma-glutamyl transferase levels and the liver fibrosis score. CONCLUSION: The innovative integrated models based on a large number of indicators provide a noninvasive and cost-effective approach for accurately diagnosing BA in children. Video Abstract (MP4 142103 KB).

[Enrichment Factors, Health Risk, and Source Identification of Heavy Metals in Agricultural Soils in Semi-arid Region of Hainan Island].

To understand the enrichment factors and pollution levels of heavy metals in agricultural soils in the semi-arid region of Hainan island, 1818 surface soil samples were collected in Gancheng Town and analyzed for their heavy metal contents and physicochemical composition. Correlation analysis was used to determine the heavy metal enrichment factors. The geo-accumulation index (Igeo), comprehensive ecological risk index (RI), and hazard index (HI), as well as carcinogenic risk (CR), were used to assess the degree of pollution and health risk. Positive matrix factorization (PMF) was used to determine the primary sources of pollution and priority sources. The average values of heavy metal contents in the topsoil were 22.7, 0.128, 33.4, 14.5, 0.032, 9.32, 32.5, and 43.3 mg·kg-1 for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, respectively. With the exception of Zn, the concentrations of other heavy metals in the topsoil were higher than the soil background values of Hainan, showing different degrees of heavy metal accumulation effect. The Igeo revealed that the major pollutant element in soils was As, followed by Cd and Cu. The RI showed that the proportion of soil samples that were high-risk level or worse was 29.4% of the total number of samples, among which As was the major source of risk. The health risk assessment results indicated that As, Cr, and Ni exposure presented carcinogenic risk for children with high CR values. Based on PMF, four major sources of heavy metals were identified in the study area. Hg was derived mainly from industrial sources, and As was closely associated with agricultural activities. Ni, Cu, Cr, and Zn were related to soil parent materials. Pb and Cd were associated with agricultural activities and traffic emissions. The PMF models combined with correlation analysis were useful for estimating the source apportionment of heavy metals in soils.

[Accumulation and Health Risk of Heavy Metals in Cereals, Vegetables, and Fruits of Intensive Plantations in Hainan Province].

The accumulation of some harmful elements in plants from intensive production systems pose a serious threat to human health. In this study, seven heavy metals(Cu, Pb, Zn, Cr, Cd, As, and Hg) and their distribution characteristics in the crops, vegetables, and fruits were analyzed alongside single factor evaluation and Nemero index analysis. Combined with dietary recommended consumption data from the Chinese Nutrition Society, the dietary exposure of heavy metals were further analyzed, and a consequent safety risk assessment was conducted. A total of 673 crop, vegetable, and fruit samples were collected from typical intensive production systems in Hainan Province. The results showed that the content of Cu, As, and Hg in the 673 plant samples was below the value of the national food standard. The exceed rates of Pb, Zn, Cr, and Cd were 2.67%, 3.71%, 2.53%, and 3.71%, respectively. The heavy metal comprehensive pollution degree of six species of plants showed the trend of leafy vegetables > tuber crops > non-leafy vegetables > legume crops > fruits > cereals. In particular, Cr in leafy vegetables showed significantly higher hazard quotients(HQ) than that in other types, and exceeded 1, suggesting a high potential health risk via the ingestion of heavy metals through leafy vegetables. The relatively lower hazard index(HI) values of tuber crops, non-leafy vegetables, legume crops, fruits, and cereals suggest that these types of plants are more suitable for intensive production systems.