ObjectiveTo compare planning quality,treatment efficiency and delivery accuracy for initial treated nasopharyngeal carcinoma (NPC) with step & shoot intensity modulated radiation therapy (ssIMRT) and volumetric modulated arc therapy (VMAT).These results will help make a clinic choice of the therapeutical technique.MethodsTwenty-six NPC cases were planned with the same dose prescription and objective constrains by means of 9-field ss-IMRT and VMAT respectively.Compare:( 1 ) plan dosimetric distribution,conformity index and homogeneity index of the targets,the average dose,maximum dose and interested dose-volume histograms of organs at risk (OAR) et al;(2) delivery times of the therapy plans ;(3) the accuracy of treatment plans dose verification.ResultsBoth therapeutical plans can achieve the clinic dosimetric demands.Compared to ss-IMRT,VMAT had less inferior target coverage.The CI and HI of the PGTV was 0.57 and 0.08 ( ss-IMRT),0.48 and 0.12 (VMAT) respectively ( t =-4.52,- 8.33,P =0.000,0.000).Except of brain stem,VMAT had higher mean dose and maximum dose of OARs than ss-IMRT (t=-9.57 - -3.71,P=0.000 -0.001).The spinal cord D1cc and parotids D50％ were increased by 11.9％ and 6.5％ averagely.The treatment times of ss-IMRT and VMAT were 803.7 s and 389.3 s respectively (t =24.12,P =0.000),while V MAT decreasing by 51.6％.The pass ratios of γ (3mm,3％ ) from the dose verification were 99.4％ (ss-IMRT) and 98.0％ (VMAT) respectively ( t =5.19,P =0.000).ConclusionsThe dose distribution of VMAT for initial treated nasopharyngeal carcinoma can achieve the clinic demands,but slightly worse than 9-field ss-IMRT.VMAT has the advantage of high efficiency and dosimetric accuracy.

Objective To study the mechanism of ferulic acid(FA)on hepatic fibrosis(HF)based on network pharmacology,and establish an in vitro model of rat hepatic stellate Cell-T6(HSC-T6)according to the results.Methods The potential targets of FA were screened through PubChem,swisstargetprediction and pharmmapper,and overlapped with the FA targets screened in disgenet,genecards and OMIM.Then,protein protein interaction(PPI)was analyzed by using string platform.Gene ontology(go)and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis were carried out for key targets by using R64 4.0.3,and the"component target disease"network diagram was constructed by Cytoscape 3.7.2 software.Based on this,the proliferation of HSC-T6 was detected by cell counting kit-8(CCK-8)method,and the grouping was determined:blank group and low-dose group(100 μg·mL-1 FA),medium dose group(200 μg·mL-1 FA),high dose group(400 μg·mL-1 FA)and positive control group(200 μg·mL-1 colchicine),the migration ability of HSC-T6 was detected by scratch test,and the content of HSC-T6 was detected by enzyme linked immunosorbent assay(ELISA)α-Alpha smooth muscle actin,α-Flow cytometry was used to detect the changes of HSC-T6 cycle,quantitative real time polymerase chain reaction(qRT-PCR)was used to detect the relative expression of JAK2 and STAT3 mRNA,and Western Blot was used to detect the molecular expression of JAK2 and STAT3 protein.Results 254 intersection targets of FA and HF were obtained.The core targets were signal transducer and activvator of Transcription(STAT3),albumin(ALB),protein kinase B(AKT1),tumor suppressor protein p53(TP53),epidermal growth factor receptor(EGFR)and caspase-3(CASP3).KEGG analysis showed that the action pathway of FA on HF mainly involved phosphatidylinositol 3 kinase protein kinase B(PI3K-Akt),vascular endothelial growth factor(VEGF),Janus kinase/signal transducer and activator of transcription(JAK/STAT)Tumor necrosis factor(TNF)and other pathways.The experimental results showed that in CCK-8 experiment,scratch experiment and ELISA experiment,compared with the blank group,the cell proliferation rate,migration ability and the expression of α-SMA protein decreased significantly(P<0.05).Compared with the blank group,the cycle arrest rate of low,medium and high dose groups and positive control group increased significantly(P<0.05).Compared with the blank group,the molecular weight and mRNA expression of JAK2 and STAT3 protein in low,medium and high dose groups and positive control group decreased gradually(P<0.05).Conclusion FA has the characteristics of multi-channel and multi-target.FA may inhibit the apoptosis of hepatic stellate cell(HSC)by down regulating JAK2 and STAT3 targets.

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers.The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.

As a representative member of the Rho family, RhoA plays an important role in the oncogenesis and development of malignant tumors. According to previous studies, RhoA functions as a key regulator in mediating actin polymerization, cytoskeletal structure remodeling, cell polarity changes, epithelial-mesenchymal transition and so on. RhoA can promote multiple malignant phenotypes of tumor cells, such as migration, invasion, etc. At present, mainstream research believes that RhoA functions as oncogene in the carcinogenesis of tumors. Downregulated RhoA can inhibit tumor growth and progression, which can be used as a potential target for clinical anti-tumor therapy.