Previous studies used BA and BEI structures as stimuli to infer that syntax-first models seemed not applicable in Chinese. However, there were inconsistent results of both within same structures and between different structures. Since sentence structures of stimuli were non-canonical as well as lacking wide representativeness in Chinese, we examined the processing mechanism of a more representative structure in Chinese, QING (QING + NP₁ + V + NP₂) structure in the current study. Four conditions, including correct sentences (CORRECT), semantic-violated sentences (SEMANTIC), syntactic-violated sentences (SYNTACTIC), and combined violated sentences (COMBINED), were composed by manipulating the V between NP₁ and NP₂. Results with respect to three types of violation were as follows. In the initial phrase (100–300 ms), there existed an interaction between SEMANTIC consistency and the SYNTACTIC category. In the intermediate phrase (300–500 ms), the interaction continued with similar negative waves evoked by three types of violated sentences. In the final phrase (500–700 ms), both SYNTACTIC or COMBINED evoked obvious negative waves. The current research of Qing structure provided new evidence for the processing mechanism of Chinese sentence patterns. Specifically, we found that the interactive model rather than the syntax-first model may apply to the processing of this specific structure of Chinese sentences and compared the results with those reported in previous studies that examined other types of sentence structures.

Unlike in English, the role of phonology in word recognition in Chinese is unclear. In this event-related potential experiment, we investigated the role of phonology in reading both high- and low-frequency two-character compound Chinese words. Participants executed semantic and homophone judgment tasks of the same precede-target pairs. Each pair of either high- or low-frequency words were either unrelated (control condition) or related semantically or phonologically (homophones). The induced P200 component was greater for low- than for high-frequency word-pairs both in semantic and phonological tasks. Homophones in the semantic judgment task and semantically-related words in the phonology task both elicited a smaller N400 than the control condition, word frequency-independently. However, for low-frequency words in the phonological judgment task, it was found that the semantically related pairs released a significantly larger P200 than the control condition. Thus, the semantic activation of both high- and low-frequency words may be no later than phonological activation.

In the present study, a comparison of the biological processes and gene ontology (GO) in human hepatocellular carcinoma (HCC) with high expression (fold change ≥2) of amelogenin Y-linked (AMELY)-activated upstream regulation networks with non-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) with low expression of activated networks was performed. The principle biological processes involved in non-tumor hepatitis/cirrhotic tissues include positive regulation of mismatch repair, regulation of transcription from RNA polymerase II promoters, negative regulation of cell-cell adhesion, protein ubiquitinatin and protein catabolism. The main biological processes involved in the development of HCC include positive regulation of calcium ion transport into the cytosol, cell proliferation, DNA replication, fibroblast proliferation, immune response, microtubule polymerization and protein secretion. Specific transcription from RNA polymerase II promoters, regulation of angiogenesis, cell growth, protein metabolism, Wnt receptor signaling pathways, negative regulation of endothelial cell differentiation, microtubule depolymerization, peptidase activity and progression through the cell cycle are also involved. Positive regulation of transcription is involved in both processes. An activated AMELY-coupled upstream positive regulation of immune response-mediated protein secretion to Wnt signaling and calcium into cytosol-induced regulation of cell growth and angiogenesis in HCC is proposed. The AMELY upstream regulation molecular network model was constructed with BUB1B, CST6, ESM1, HOXA5, LEF1, MAPT, MYBL2, NOTCH3, PLA2G1B, PROK1, ROBO1, SCML2 and UBE2C in HCC from a Gene Expression Omnibus (GEO) dataset by gene regulation network inference methods and our programming methods.

Studies were done on analysis of biological processes in the same high expression (fold change ≥2) activatedPTHLHfeedback-mediated cell adhesion gene ontology (GO) network of human hepatocellular carcinoma (HCC) compared with the corresponding low expression activated GO network of no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection). ActivatedPTHLHfeedback-mediated cell adhesion network consisted of anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolism, cell adhesion, cell differentiation, cell-cell signaling, G-protein-coupled receptor protein signaling pathway, intracellular transport, metabolism, phosphoinositide-mediated signaling, positive regulation of transcription, regulation of cyclin-dependent protein kinase activity, regulation of transcription, signal transduction, transcription, and transport in HCC. We proposed activatedPTHLHcoupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network. Our hypothesis was verified by the different activatedPTHLHfeedback-mediated cell adhesion GO network of HCC compared with the corresponding inhibited GO network of no-tumor hepatitis/cirrhotic tissues, or the same compared with the corresponding inhibited GO network of HCC. ActivatedPTHLHcoupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network includedBUB1B, GNG10, PTHR2, GNAZ, RFC4, UBE2C, NRXN3, BAP1, PVRL2, TROAP,andVCANin HCC from GEO dataset using gene regulatory network inference method and our programming.