Objective:To investigate the predictive value of radiomics features derived from dynamic contrast-enhanced MRI (DCE-MRI) based on habitat imaging technology for pathological complete response after neoadjuvant therapy (NAT) for breast cancer.Methods:All patients were female, aged 25-67 years. Patients were stratified into training ( n=83) and validation ( n=36) sets via stratified random sampling (7∶3 ratio). Pathological complete remission (pCR) and non-pathological complete remission (non-pCR) were defined using the Miller-Payne grading system. All patients underwent DCE-MRI before NAT. ITK-Snap software was used to outline the region of interest (ROI), the imaging histological features of the entire tumor region were extracted and screened, a traditional imaging histological model for predicting post-NAT pCR (ROI overall model) was constructed; the tumor region was divided into three subregions using habitat imaging technology, and the imaging histological features within ROI subregion 1, ROI subregion 2, and ROI subregion 3 were extracted and screened, and the habitat imaging model for predicting post-NAT pCR were constructed (ROI subregion 1 model, ROI subregion 2 model, ROI subregion 3 model). Univariate logistic regression identified clinical predictors of pCR for clinical model construction. Combined models integrating clinical predictors and habitat imaging features were established. The efficacy of each model in predicting pCR after NAT in breast cancer was evaluated using receiver operating characteristic curves and area under the curve (AUC), and the efficacy of clinical application of the models was evaluated using decision curve analysis (DCA). Results:Of the 119 patients, 74 were pCR patients, with 52 in the training set and 22 in the validation set, and 45 were non-pCR patients, with 31 in the training set and 14 in the validation set. Logistic regression analysis showed that human epidermal growth factor receptor 2 status ( OR=0.254, 95% CI 0.093-0.697, P=0.008) was an independent predictor of pCR after NAT, and this was used to construct a clinical prediction model. The predictive efficacy of ROI subregion 1 model and ROI subregion 2 model in the habitat model was higher than that of the traditional imaging histology model (ROI overall model), with AUCs of 0.805, 0.748,0.728 for the training set and 0.776,0.718,0.708 for the validation set, respectively. The combined clinical prediction model for predicting pCR after NAT in breast cancer had AUCs of 0.877 and 0.818 for the training and validation sets, respectively. DCA showed a higher net benefit for the combined model than for the traditional imaging histology model and the habitat imaging histology model. Conclusion:Compared with the traditional method of extracting the entire tumor region, extracting radiomics features from DCE-MRI subregions based on habitat imaging technology can improve the predictive performance of NAT efficacy in breast cancer.

Objective:To investigate the predictive value of radiomics features derived from dynamic contrast-enhanced MRI (DCE-MRI) based on habitat imaging technology for pathological complete response after neoadjuvant therapy (NAT) for breast cancer.Methods:All patients were female, aged 25-67 years. Patients were stratified into training ( n=83) and validation ( n=36) sets via stratified random sampling (7∶3 ratio). Pathological complete remission (pCR) and non-pathological complete remission (non-pCR) were defined using the Miller-Payne grading system. All patients underwent DCE-MRI before NAT. ITK-Snap software was used to outline the region of interest (ROI), the imaging histological features of the entire tumor region were extracted and screened, a traditional imaging histological model for predicting post-NAT pCR (ROI overall model) was constructed; the tumor region was divided into three subregions using habitat imaging technology, and the imaging histological features within ROI subregion 1, ROI subregion 2, and ROI subregion 3 were extracted and screened, and the habitat imaging model for predicting post-NAT pCR were constructed (ROI subregion 1 model, ROI subregion 2 model, ROI subregion 3 model). Univariate logistic regression identified clinical predictors of pCR for clinical model construction. Combined models integrating clinical predictors and habitat imaging features were established. The efficacy of each model in predicting pCR after NAT in breast cancer was evaluated using receiver operating characteristic curves and area under the curve (AUC), and the efficacy of clinical application of the models was evaluated using decision curve analysis (DCA). Results:Of the 119 patients, 74 were pCR patients, with 52 in the training set and 22 in the validation set, and 45 were non-pCR patients, with 31 in the training set and 14 in the validation set. Logistic regression analysis showed that human epidermal growth factor receptor 2 status ( OR=0.254, 95% CI 0.093-0.697, P=0.008) was an independent predictor of pCR after NAT, and this was used to construct a clinical prediction model. The predictive efficacy of ROI subregion 1 model and ROI subregion 2 model in the habitat model was higher than that of the traditional imaging histology model (ROI overall model), with AUCs of 0.805, 0.748,0.728 for the training set and 0.776,0.718,0.708 for the validation set, respectively. The combined clinical prediction model for predicting pCR after NAT in breast cancer had AUCs of 0.877 and 0.818 for the training and validation sets, respectively. DCA showed a higher net benefit for the combined model than for the traditional imaging histology model and the habitat imaging histology model. Conclusion:Compared with the traditional method of extracting the entire tumor region, extracting radiomics features from DCE-MRI subregions based on habitat imaging technology can improve the predictive performance of NAT efficacy in breast cancer.

[Abstract] Objective: To establish a method for in vitro isolation and culture of T lymphocytes from peripheral blood of cynomolgus monkeys that induced by human CD3 antibody based on the foundation of protein homology of CD3 from human, cynomolgus monkey and porcine. Methods: The amino acid sequences of human, cynomolgus monkeys and porcine CD3 proteins were obtained from NCBI, and the sequence, homology and phylogenetic tree were analyzed by DNAMAN software. Western blotting was used to detect the expression of CD3 protein on T cell membranes from the three species. PBMCs of healthy cynomolgus were isolated and divided into three groups: group A was stimulated with anti-human CD3Ab alone, group B was stimulated with IL-2 alone, and group C was costimulated with human CD3Ab and IL-2. Cell morphology and growth status were observed under inverted microscope and the cell growth curve was plotted. Cell viability was detected by trypan blue staining and the expressions of CD3, CD4 and CD8 on T cell surface were detected by flow cytometry. Results: The homology of the amino acid sequence of human CD3 protein to cynomolgus monkey and porcine were 86.9% and 65.6% respectively. The expression levels of CD3 protein on cynomolgus and porcine T cell membrane were 79% and 17% contrast to human, respectively. Cells of group A did not proliferate. Proliferation, viability and CD3 expression [(93.8±3.6)% vs (70.3±4.7)%, P<0.01] in T cells of group C were significantly higher than those in group B. Growth curve of T cells in group C showed an S-shape, which is consistent with Logistic growth curve. T cells in group C exhibited high purity and expressed high level CD3; moreover, the CD8+T cell took a high proportion. Conclusion: The membrane of T lymphocytes from peripheral blood of cynomolgus can express CD3 protein that highly homological to human. Co-stimulation of human CD3Ab, IL-2 and 1% PHAcan induce the proliferation and differentiation of T lymphocytes of cynomolgus, and obtain T lymphocytes with good growth status, high proliferation ability and high purity.

Objective To develop paclitaxel-loaded polymeric micelles from poly (ε-caprolactone)-poly (ethylene glycol)-poly(ε-caprolactone) (PCL-PEG-PCL),and to evaluate in vitro cytotoxicity as well as in vivo antitumor activity against EMT-6 tumor breast cell.Methods Paclitaxel-loaded polymeric micelles were prepared by thin-film hydration and ultrasonic method.The physical status of paclitaxel inside the polymeric micelles was investigated by differential scanning calorimetry (DSC).In vitro cytotoxicity of paclitaxel-loaded polymeric micelles against EMT-6 cell line was assessed by MTT assay.In vivo anticancer activity was evaluated against EMT-6 tumorbearing mice,with commercially available Taxol injection as control.Results Paclitaxel-loaded polymeric micelles exhibited homogeneous spherical shapes with apparent core-shell morphology.The average diameter of paclitaxelloaded polymeric micelles was 93 nm.DSC study indicated that paclitaxel was in solid amorphous state after being encapsulated in the polymeric micelles.In vitro cytotoxicity demonstrated that the cytotoxic effect of paclitaxelloaded polymeric micelles was lower than that of Taxol injection at the same paclitaxel content.Paclitaxel-loaded polymeric micelles showed greater tumor growth-inhibition effect in vivo on EMT-6 breast tumor in comparison with that of Taxol injection,with tumor growth inhibition of 85.79％ and 63.37％,respectively (P＜0.05).Conculsions The prepared paclitaxel-loaded polymeric micelles showed high anti-tumoral efficacy and low toxicity,and might have the potential to be developed as an effective anticancer drug-delivery system for cancer chemotherapy.

Polymersomes have attracted tremendous attention as novel drug delivery systems because of their unique and superior structure,tunable membrane properties,colloidal stability,and ability in encapsulating a broad range of both water soluble and insoluble substances.In this paper,preparation method and criteria for the formation of polymersomes,their structure and characterization as well as amphiphilic block copolymers for vesicle formation are addressed.Moreover,research progress on polymersomes as drug delivery system in the field of therapeutic and diagnostic applications are reviewed in this paper.

AIM: To investigate the effects of sodium ferulate on cholesterol and triglyceride metabolism in atherosclerosis with hyperlipidemia.METHODS: The rabbit model of atherosclerosis was produced by feeding high lipid forages.RAW264.7 foam cell and HepG2 injured cell models were established by incubation with oxidized low density lipoprotein(ox-LDL).The atherosclerotic plaque area was measured,and serum lipids were detected.The cellular lipid accumulation was examined by oil red O staining.The cellular contents of total cholesterol and cholesterol ester were quantified by high performance liquid chromatography.The hepatic lipase(HL) mRNA expression was determined by RT-PCR.RESULTS:(1) Compared with hyperlipid group,the aorta atherosclerosis plaque area and the serum triglyceride level were significantly decreased in sodium ferulate-treated rabbits,but the serum cholesterol level showed little change.(2) Compared with ox-LDL group,the HL mRNA expression in HepG2 cells was enhanced significantly in sodium ferulate-treated group,but the cellular contents of total cholesterol and cholesterol ester in RAW264.7 foam cells showed little change.CONCLUSION: Sodium ferulate inhibits the formation of atherosclerotic plaque in high-cholesterol-fed rabbits aorta.This antiatherosclerotic function may reduce serum triglyceride level through enhancing the expression of HL mRNA without influencing serum cholesterol level and foam cell formation.