Polymorphism and Forensic Application of 11 Y-SNP in Guizhou Shui Ethnic Group / 法医学杂志

Objective To investigate the frequency distribution features of 11 Y-SNP of Guizhou Shui ethnic group, explore its genetic relationship with other ethnic groups and evaluate its forensic application value. Methods Multiplex amplification of the 11 Y-SNP of samples of 180 unrelated male individuals from Guizhou Shui ethnic group was performed with microsequencing technique. The frequency of haplogroup was calculated by direct counting method, and principal component analysis （PCA） of Guizhou Shui ethnic group and reference ethnic groups was performed by using Multi-variate statistical package （MVSP）. The Fst genetic distance between Guizhou Shui ethnic group and other ethnic groups was calculated with Arlequin v3.5. The phylogenetic tree was established with MEGA 4.0 software according to the Fst value. Results Six types of Y chromosome haplogroups were observed in total. Among which, the distribution frequency of O-M175 haplogroup was the highest （71.11%）, followed by C-M130 （25.00%）, and D-M174 （3.89%）. O1b-M268 （31.11%） and O2a2-IMS-JST021354 （28.33%） had a relatively high distribution frequency in O haplogroup. The paternal relationship between Guizhou Shui ethnic group and Guizhou Gelao ethnic group in the same language group was the closest. Conclusion The distribution of Y-SNP haplogroup of the Shui ethnic group in Guizhou has certain specificity, which can provide basic data for forensic biogeographic inference.

The optimal combination of serum tumor markers with bioinformatics in diagnosis of colorectal carcinoma / 浙江大学学报·医学版

<p><b>OBJECTIVE</b>To identify the optimal combination of serum tumor markers with bioinformatics in diagnosis of colorectal cancer.</p><p><b>METHODS</b>The serum levels of CEA, AFP, NSE, CA199, CA242, CA724, CA211 and TPA were detected in 128 patients with colorectal carcinoma and 113 health subjects. The serum tumor markers were evaluated with the area under curves. The optimal combination of serum tumor markers was selected and the diagnostic model with artificial neural network was established.</p><p><b>RESULTS</b>CEA, CA199, CA242, CA211, CA724 were selected for the optimal combination and the artificial neural network was built. The model was evaluated by a 5-cross validation approach. The model had a specificity of 95%, sensitivity of 83% and positive predictive value of 95% in diagnosis of colorectal carcinoma.</p><p><b>CONCLUSION</b>The combination of optimal serum tumor markers has a high sensitivity and specificity in diagnosis of colorectal carcinoma.</p>