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Yu Z.,Qingdao University | Lu H.,Qingdao University | Si H.,Institute for Computational Science and Engineering | Liu S.,Qingdao University | And 6 more authors.
PLoS ONE | Year: 2015

Background: Lung cancer is an important and common cancer that constitutes a major public health problem, but early detection of small cell lung cancer can significantly improve the survival rate of cancer patients. A number of serum biomarkers have been used in the diagnosis of lung cancers; however, they exhibit low sensitivity and specificity. Methods: We used biochemical methods to measure blood levels of lactate dehydrogenase (LDH), Creactive protein (CRP), Na+, Cl-, carcino-embryonic antigen (CEA), and neuron specific enolase (NSE) in 145 small cell lung cancer (SCLC) patients and 155 non-small cell lung cancer and 155 normal controls. A gene expression programming (GEP) model and Receiver Operating Characteristic (ROC) curves incorporating these biomarkers was developed for the auxiliary diagnosis of SCLC. Results: After appropriate modification of the parameters, the GEP model was initially set up based on a training set of 115 SCLC patients and 125 normal controls for GEP model generation. Then the GEP was applied to the remaining 60 subjects (the test set) for model validation. GEP successfully discriminated 281 out of 300 cases, showing a correct classification rate for lung cancer patients of 93.75% (225/240) and 93.33% (56/60) for the training and test sets, respectively. Another GEP model incorporating four biomarkers, including CEA, NSE, LDH, and CRP, exhibited slightly lower detection sensitivity than the GEP model, including six biomarkers. We repeat the models on artificial neural network (ANN), and our results showed that the accuracy of GEP models were higher than that in ANN. GEP model incorporating six serum biomarkers performed by NSCLC patients and normal controls showed low accuracy than SCLC patients and was enough to prove that the GEP model is suitable for the SCLC patients. Conclusion: We have developed a GEP model with high sensitivity and specificity for the auxiliary diagnosis of SCLC. This GEP model has the potential for the wide use for detection of SCLC in less developed regions. © 2015 Yu et al.

Wang Y.,Institute for Computational Science and Engineering | Fu A.-P.,Institute for Computational Science and Engineering | Li H.-L.,Institute for Computational Science and Engineering | Tian F.-H.,Institute for Computational Science and Engineering | And 4 more authors.
Chemical Research in Chinese Universities | Year: 2011

The effects of two different amino acid catalysts on the stereoselectivities in the direct Mannich reactions of cyclohexanone, p-anisidine and p-nitrobenzaldehyde were studied with the aid of density functional theory. Transition states of the stereo-determining C-C bond-forming step with the addition of enamine intermediate to the imine for the L-proline(α-amino acid) and (R)-3-pyrrolidinecarboxylic acid(β-amino acid)-catalyzed processes were reported. B3LYP/6-31G** calculations provide a good explanation for the opposite syn vs. anti diastereoselectivities of these two different kinds of catalysts(syn-selectivity for the α-amino acid catalysts, anti-selectivity for the β-amino acid catalysts). Calculated and observed diastereomeric ratio and enantiomeric excess values are in reasonable agreement.

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