Resorting to a neural network approach we refined several representative and sophisticated global nuclear mass models within the latest atomic mass evaluation (AME2012). In the training process, a quite robust algorithm named the Levenberg–Marquardt (LM) method is employed to determine the weights and biases of the neural network. As a result, this LM neural network approach demonstrates a very useful tool for further improving the accuracy of mass models. For a simple liquid drop formula the root mean square (rms) deviation between the predictions and the 2353 experimental known masses are sharply reduced from 2.455 MeV to 0.235 MeV, and for the other revisited mass models, the rms is remarkably improved by about 30%.
This study aims to investigate the clinical significance of serum autoantibodies against MDM2 and c-Myc and evaluate their feasibility in the immunodiagnosis of lung cancer. 50 sera samples with 43 available paired lung cancer tissue and adjacent normal tissue slides with follow up information and 44 sera from normal human controls (NHC) were used in the research group. Another 62 lung cancer sera and 43 NHC sera were used in the validation group. The results of IHC showed that MDM2 and c-Myc protein were overexpressed in lung cancer tissues compared to adjacent normal tissues (p < 0.001). Likewise, significantly higher levels of serum autoantibodies against MDM2 and c-Myc were found in lung cancer compared to NHC both in research and validation groups. Further analysis on IHC and ELISA results showed that serum level of autoantibodies against these two TAAs were positively associated with tissue staining scores (both p < 0.05). The area under curve (AUC) values of anti-MDM2 and anti-cMyc autoantibodies for discriminating lung cancers from NHC were 0.698 and 0.636 in research group, 0.777 and 0.815 in the validation group, respectively. Both anti-MDM2 and anti-c-Myc autoantibodies can discriminate stage I lung cancer patients from NHC with AUC values of 0.703 and 0.662. Kaplan-Meier analysis showed that higher level of serum anti-c-Myc autoantibodies was significantly related to shortened disease-free survival (DFS) (p = 0.041). In conclusion, our finding suggested that serum MDM2 and c-Myc autoantibodies may have the potential to serve as non-invasive diagnostic biomarkers in patients with lung cancer.
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