An Intelligent Prediction Model for Target Protein Identification in Hepatic Carcinoma Using Novel Graph Theory and ANN Model

Hepatocellular carcinoma(HCC)is one major cause of cancer-related mortality around the world.However,at advanced stages of HCC,systematic treatment options are currently limited.As a result,new pharmacological targetsmust be discovered regularly,and then tailored medicines against HCC must be developed.In this research,we used biomarkers of HCC to collect the protein interaction network related to HCC.Initially,DC(Degree Centrality)was employed to assess the importance of each protein.Then an improved Graph Coloring algorithm was used to rank the target proteins according to the interaction with the primary target protein after assessing the top ranked proteins related to HCC.Finally,physio-chemical proteins are used to evaluate the outcome of the top ranked proteins.The proposed graph theory and machine learning techniques have been compared with six existing methods.In the proposed approach,16 proteins have been identified as potential therapeutic drug targets for Hepatic Carcinoma.It is observable that the proposed method gives remarkable performance than the existing centrality measures in terms of Accuracy,Precision,Recall,Sensitivity,Specificity and F-measure.

Materials design and sensing mechanism of novel calix[6]arene composite for sensitively detecting amine drugs

In order to improve the co nvenie nce and sensitivity of amphetamines drug testing and reduce the threat of drugs to humans,we have designed a QCM gas sensor to detect amine-containing drugs.The sensing material is designed based on the chemical nature of amine drugs.The sensing mechanism is derived from a reve rsible Schiff base interaction between the amino group of the drug and the carbonyl group of the novel calix[6]arene derivatives as well as the hydrogen bond interaction between amino group and hydroxyl.The new composite material was well characterized by different analytical techniques including 1 H nuclear magnetic resonance(1 H-NMR),fourier transform infrared spectroscopy(FT-IR),scanning electro nic microscopy(SEM),transmission electron microscope(TEM),Raman spectra,powder X-ray diffraction,etc.The sensing experiments were conducted by coating the composite onto quartz crystal microbalance(QCM)transducers.The experimental results indicated that the novel calixarene derivatives and their GO complexes based on the design have excellent selectivity,high sensitivity and repeatability toβ-phenylethylamine.