BACKGROUND: An important initial step in developing a tissue engineering artificial salivary gland organoid is to find an ideal scaffold. To find other new biomaterials should to be further studied.OBJECTIVE: To obtain an acellular matrix from tracheae of rabbits and SD rats, and to investigate its biocompatibility as a primary step toward developing a tissue engineering artificial salivary gland organoid.DESIGN, TIME AND SETTING: A randomized controlled animal study, which was performed at the Key Laboratory of Transplantation Engineering and Immunology of Ministry of Health, West China Hospital of Sichuan University from February 2003 to May 2005.MATERIALS: A modified detergent and enzyme link extraction procedure was performed to remove cells from SD rats and rabbits tracheae. The histology, topography of inner-surface and biocompatibility were studied on both acellular tracheae.METHODS: Eighteen SD rats were randomly divided into 2 groups. One group was planted acellular trachea of SD rats. Other group consisted of acellular trachea of rabbits. On the third generations, submandibular gland cells were inoculated on two acellular tracheae and cultured on PGA membrane; while, cells in the control group were inoculated on 12-well culture plate, and cell/scaffold complex was cultured at the same time.MAIN OUTCOME MEASURES: The structure and topography of inner-surface of the acellular tracheae matrixes were observed both by light and scanning electron microscopy. The inflammatory response of the tissue around acellular tracheae implanted under the skin of cheek was evaluated at 1, 4, 12 weeks. The numbers of cells grown on the acellular tracheae and PGA film were counted at 1, 2, 3, 4, 5, 6, 7 days. At 1, 3, 5, 7 days, the mean values of metabolic activity test and the amylase activities of supernatants of the cells/scaffold complexes were examined.RESULTS: The cells were completely removed from both tracheae. No evident inflammatory response was found in tissues around two kinds of acellular tracheae implanted under the skin of cheek. The number of submandibular gland cells (SSG) grown on the two kinds of naturally derived biomaterials was much more than grown on PGA (P<0.05). The mean values of metabolic activity test and the amylase activities of supernatants containing cell/acellular matrixes were much higher than that of cell/PGA (P<0.05).CONCLUSION: The acelhilar tracheae matrixes made by our laboratory can be used as scaffold in the study of tissue engineering artificial salivary gland organoid.

BACKGROUND: Seed cells with good proliferation and enough amounts are need in reconstructing artificial salivary gland in vitro. However, adult stem cells are difficult to be isolated from normal submandibular gland.OBJECTIVE: To in vitro isolate submandibular gland stem/progenitor cells for cloning culture using animal models of damaged gland tissue.DESIGN, TIME AND SETTING: Cytological in vitro experiment was performed at the Gu.izhou Provincial Key Laboratory of Cell Tissue Engineering, Zunyi Medical College from March 2006 to January 2007.MATERIALS: A total of 10 male Sprague Dawley rats aged 8 weeks were supplied by the Animal Center, Third Military Medical University of Chinese PLA.METHODS: The model of tissue damaged submandibular gland in 10 rats was made by deligation. One week later, the gland tissue was obtained to harvest submandibular gland stem/progenitor cells by enzyme digestion in vitro. Following 10-14 days of primary culture, small round cells were collected, purified and subcultured for monoclonal culture.MAIN OUTCOME MEASURES: Immunocytochemical staining and immunofluorescence staining results were measured in submandibular gland stem/progenitor cells. Growth curve was drawn to analyze the proliferation of submandibular gland stem/progenitor cells in vitro.RESULTS: Cells expressing laminin showed stem cell characteristics. Positive expression of CD29 suggested high-adherent and high-proliferative stem cell properties. Positive expression of keratin-19 indicated epithelium-derived submandibular gland stem/progenitor cells. Growth curve was near to "S" shape, and in vitro culture and proliferation was active.CONCLUSION: Submandibular gland stem/progenitor cells had the characteristics of tissue stem cells. They might be as a kind of seed cells for tissue engineered artificial salivary gland in further research.

Objective:To construct a combined radiomics model based on preoperative enhanced computed tomography (CT) examination for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and provide biological explanations for the radiomics model.Methods:The retrospective cohort study was conducted. The messenger RNA (mRNA) of 424 HCC patients, the clinicopathological data of 39 HCC patients entered into the Cancer Genome Atlas database from its establishment until January 2023, and the clinicopathological data of 53 HCC patients who were admitted to the Gansu Provincial People′s Hospital from January 2020 to January 2023 were collected. The 92 HCC patients were randomly divided into a training dataset of 64 cases and a test dataset of 28 cases with a ratio of 7∶3 based on a random number table method. The CT images of patients in the arterial phase and portal venous phase as well as the corresponding clinical data were analyzed. The 3Dslicer software (version 5.0.3) was used to register the CT images in the arterial phase and portal venous phase and delineate the three-dimensional regions of interest. The original images were preprocessed and the corresponding features were extracted by the open-source software FAE (version 0.5.5). After selecting features using the Least Absolute Shrinkage and Selection Operator, the radiomics model was constructed and the radiomics score (R-score) was calculated. The nomogram was constructed by integrating clinical parameters, imaging features and R-score based on Logistic regression. The gene modules related to radiomics model were obtained and subjected to enrichment analysis by conducting weighted gene co-expression network analysis and correlation analysis. Observation indicators: (1) comparison of clinical characteristics of patients with different MVI properties; (2) establishment of MVI risk model; (3) evaluation of MVI risk model; (4) clustering of gene modules; (5) functional enrichment of feature-correlated gene modules. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Comparison of count data was conducted using the chi-square test. The intra-/inter-class correlation coefficient (ICC) was used to assess the inter-observer consistency of radiomics feature extracted by different observers. ICC >0.75 indicated a good consistency in feature extraction. The Logistic regression model was used for univariate and multivariate analyses. The receiver operating characteristic curve was drawn, and the area under curve (AUC), the decision curve and the calibration curve were used to evaluate the diagnostic efficacy and clinical practicality of the model. Results:(1) Comparison of clinical characteristics of patients with different MVI properties. Of 92 HCC patients, there were 47 cases with MVI-positive and 45 cases with MVI-negative, and there were significant differences in hepatitis, tumor diameter, peritumoral enhancement, intratumoral arteries, pseudocapsule and smoothness of tumor margin between them ( χ2=5.308, 9.977, 47.370, 32.368, 21.105, 31.711, P<0.05). (2) Establishment of MVI risk model. A total of 1 781 features were extrac-ted from arterial and portal venous phases of the intratumoral and peritumoral regions. After feature dimension reduction, 8 radiomics features were selected from arterial and portal venous phases to construct the combined model. Results of multivariate analysis showed that peritumoral enhancement, intratumoral arteries, pseudocapsule, smoothness of tumor margins, and R-score were independent risk factors for MVI in patients with HCC [ hazard ratio=0.049, 0.017, 0.017, 0.021, 2.539, 95% confidence interval ( CI) as 0.005-0.446, 0.001-0.435, 0.001-0.518, 0.001-0.473, 1.220-5.283, P<0.05]. A nomogram model was constructed incorporating peritumoral enhancement, intratumoral arteries, pseudocapsule, smoothness of tumor margins, and R-score. (3) Evaluation of the MVI risk model. The AUC of radiomics model was 0.923 (95% CI as 0.887-0.944) and 0.918 (95% CI as 0.894-0.945) in the training dataset and test dataset, respectively. The AUC of nomogram model, incorpora-ting both the R-score and radiomics features, was 0.973 (95% CI as 0.954-0.988) and 0.962 (95% CI as 0.942-0.987) in the training dataset and test dataset, respectively. Results of decision curve showed that the nomogram had better clinical utility compared to the R-score. Results of calibration curve showed good consistency between the actual observed outcomes and the nomogram or the R-score. (4) Clustering of gene module. Results of weighted gene co-expression network analysis showed that 8 gene modules were obtained. (5) Functional enrichment of feature-related gene modules. Results of correlation analysis showed 4 gene modules were significantly associated with radiomics features. The radiomics features predicting of MVI may be related to pathways such as the cell cycle, neutrophil extracellular trap formation, and PPAR signaling pathway. Conclusions:The combined radiomics model based on preoperative enhanced CT imaging can predict the MVI status of HCC. By obtaining mRNA gene expression profiles associated with radiomics features, a biological interpretation of the radiomics model is provided.

Objective To explore the value of model established with radiomics features based on contrast enhanced arterial phase CT and model with radiogenomics for predicting prognosis of ovarian serous cystadenocarcinoma(OSC).Methods Enhanced arterial phase CT images of 110 OSC patients were retrospectively collected from 2 centers and The Cancer Imaging Archive(TCIA)database.The radiomics features were extracted,among those related to prognosis were selected to establish a radiomics Cox regression model.Genes data of 399 OSC patients were obtained from The Cancer Genome Atlas(TCGA)database,and genes related to the radiomics features included in the above radiomics model were identified with high Pearson correlation coefficient,and then enrichment gene analyses were performed.For 57 OSC cases with complete enhanced CT and gene data,the hub genes which had the highest connectivity with radiomics prognosis predicting model were detected using Cox regression and protein-protein interaction(PPI).Furthermore,a radiogenomics prognosis predicting model was established with the hub genes.The efficiencies of these 2 models for predicting prognosis of OSC patients were analyzed.Results Finally,the radiomics model included 5 OSC prognosis-related radiomics features,with C-index of 0.782 and 0.735 in corresponding training and test set,respectively.Meanwhile,the radiogenomics model included 30 prognostic hub genes,with C-index of 0.673 and 0.659 in corresponding training and test set,respectively.The survival rates of patients with better predicted prognosis according to radiomics model and radiogenomics model were both higher compared with the others(both P＜0.05).Totally 1 135 mRNA genes were found being associated with radiomics model,including biological behaviors such as cell adhesion,and signaling pathways such as PI3K-Akt,extracellular matrix receptor interaction pathway and type 1 diabetes pathway.Conclusion The radiomics model was effective for predicting prognosis of OSC patients.Analysis of mRNA bioinformatics in OSC patients might provide biological interpretations for the radiomics model.