1.Molecular design and immunogenicity of a multiple-epitope foot-and-mouth disease virus antigen, adjuvants, and DNA vaccination.
Mingxiao MA ; Ningyi JIN ; Gefen YIN ; Huijun LU ; Chang LI ; Kuoshi JIN ; Zuyi QU
Chinese Journal of Biotechnology 2009;25(4):514-519
We designed and constructed a fuse expression gene OAAT and staphylococcal enterotoxin A (SEA) on the basis of the OAAT designed and constructed which consists of the structural protein VP1 genes from serotypes A and O FMDV, 5 major VP1 immunodominant epitopes from two genotypes of Asia1 serotype, and 3 Th2 epitopes originating from the non-structural protein, 3ABC gene and structural protein VP4 gene. The recombinant plasmids pEA was constructed using SEA as a genetic adjuvant. Expressions of target gene from the pEA in Hela cell were verified by IFA and Western blotting. The experiment of BALB/c mice immunized with the DNA vaccines showed that pA and pEA could induce simultaneously specific antibodies against serotypes A, Asia1, and O FMDV, and the highest antibody titres were found in the pEA and inactivated vaccine groups compared to pA vaccinating mice. Compared with the control, the levels of IL-2, IFN-gamma, IL-4, and IL-10 expression by splenic lymphocytes from mice immunized with pA and pEA were significantly increased. In addition, we found that the levels of IL-2, IFN-gamma and IL-4 from the mice immunized with pEA was higher than mice immunized with pA did. The results of viral challenge in guinea pigs showed the pA, pEA and inactivated vaccine provided full protection in 2/4, 2/4, 3/4, 3/4 and 4/4, 4/4 guinea pigs from challenge with FMDV O/NY00 and Asial/YNBS/58, respectively. The results demonstrated fuse protein OAAT and SEA may be potential immunoge against FMDV, furthermore, SEA may be an effective genetic adjuvant for DNA vaccine.
Adjuvants, Immunologic
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genetics
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Animals
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Antigens, Viral
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immunology
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Capsid Proteins
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genetics
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immunology
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Enterotoxins
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genetics
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immunology
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Epitopes
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immunology
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Foot-and-Mouth Disease
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immunology
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prevention & control
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Foot-and-Mouth Disease Virus
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immunology
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Guinea Pigs
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HeLa Cells
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Humans
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Mice
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Mice, Inbred BALB C
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Peptide Fragments
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genetics
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immunology
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Vaccines, DNA
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immunology
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Viral Structural Proteins
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genetics
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immunology
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Viral Vaccines
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immunology
2.Prediction of vessels encapsulating tumor clusters pattern in hepatocellular carcinoma based on Gd-EOB-DTPA enhanced MRI
Jiyun ZHANG ; Xueqin ZHANG ; Tao ZHANG ; Maotong LIU ; Lei XU ; Qi QU ; Mengtian LU ; Zixin LIU ; Zuyi YAN
Journal of Practical Radiology 2024;40(2):235-239
Objective To investigate the value of qualitative and quantitative characteristics of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced MRI in preoperative prediction of vessels encapsulating tumor clusters(VETC)pattern in hepatocellular carcinoma(HCC).Methods A total of 234 patients diagnosed with HCC by pathology were analyzed retrospectively.A total of 101 VETC-positive HCC patients and 133 VETC-negative HCC patients were included.All patients were divided into training group and validation group according to 7︰3.The training group data were used to construct a prediction model for VETC-positive HCC.Receiver operating characteristic(ROC)curve was drawn and the area under the curve(AUC)was calculated to verify the diagnostic efficiency of the model.Calibration curve was drawn to verify the calibration of the model.Results Multivariate logistic regression analysis predicted the independent risk factors for VETC-positive HCC:portal phase peripheral washout[odds ratio(OR)6.493],necrosis or severe ischemia(OR 4.756),targetoid transitional phase or hepatobiliary phase(OR 0.307),and lesion to liver signal intensity ratio(LLR)on arterial phase(OR 0.074).The AUC of the training group in predicting VETC-positive HCC was 0.790[95%confidence interval(CI)0.720-0.859].The AUC of the validation group in predicting VETC-positive HCC was 0.779(95%CI 0.668-0.889).The calibration curve diagram showed that the calibration curve(the slope was 0.91)almost coincides with the ideal curve,indicating that the prediction model had better calibration.Conclusion The qualitative and quantitative characteristics of Gd-EOB-DTPA enhanced MRI can be used to predict VETC-positive HCC preoperatively,the independent risk factors of VETC include portal phase peripheral washout,necrosis or severe ischemia,targetoid transitional phase or hepatobiliary phase,and LLR on arterial phase.
3.Scoring model of MRI features for predicting proliferative hepatocellular carcinoma
Mengtian LU ; Xueqin ZHANG ; Tao ZHANG ; Qi QU ; Zuyi YAN ; Chunyan GU ; Lei XU ; Jifeng JIANG
Chinese Journal of Medical Imaging Technology 2024;40(6):874-879
Objective To observe the value of the scoring model of MRI features for predicting proliferative hepatocellular carcinoma(HCC).Methods Data of 241 patients with pathologically confirmed HCC,including 90 cases of proliferative HCC and 151 cases of non-proliferative HCC were analyzed retrospectively.Univariate and multivariate logistic regression were used to compare the clinical and MRI findings evaluated according to liver imaging reporting and data system version 2018 between groups.The independent predictive factors of proliferative HCC were screened,and scores were assigned according to the weight,then a scoring model was constructed.Receiver operating characteristic(ROC)curve was drawn,and the area under the curves(AUC)were calculated to assess the predictive efficacy of this model.The patients were divided into high and low proliferation risk subgroups based on the optimal score thresholds.The recurrence free survival(RFS)rates and early RFS rates were compared between groups and subgroups.Results MRI showed tumor corona enhancement,arterial phase annular hyper-enhancement,intratumoral vessels,much focus parenchymal low enhancement and irregular tumor margins were all independent predictive factors for proliferative HCC(OR=3.287,2.362,4.542,2.997,2.379,all P<0.05),which were then were scored with 7,5,9,7 and 5,respectively,with a total score of 0-33.AUC of the obtained scoring model for predicting proliferative HCC was 0.818.Taken 9 points as the optimal score thresholds,97 cases were assigned into high proliferation subgroup and 144 into low proliferation risk subgroups).Significant differences of RFS rates and early RFS rates were found between groups and subgroups(all P<0.05).Conclusion MRI features scoring model could effectively predict proliferative HCC.