[Inhibitory effect of Genipin on uncoupling protein-2 and energy metabolism of androgen-independent prostate cancer cells].

OBJECTIVE: To explore whether the inhibitory effect of Genipin on uncoupling protein-2 (UCP-2) in mitochondria is involved in energy metabolism of androgen-independent PC3 prostate cancer cells. METHODS: PC3 prostate cancer cells were cultured and treated with Genipin at the concentrations of 40, 80, and 160 µmol/L for 48 hours. Then the proliferation of the cells was detected by MTT assay, the expression of UCP-2 mRNA determined by RT-PCR, and the content of intracellular pyruvic acid (PA) and the activity of succinate dehydrogenase (SDH) in the mitochondria measured by visible spectrophotometry. RESULTS: With the increased concentration of Genipin, the proliferative activity of the PC-3 cells, the expression level of UCP-2 mRNA, the content of intracellular PA and the activity of SDH in the cells were all decreased, namely, with the enhanced inhibitory effect of Genipin on UCP-2, a trend of reduction was observed in the proliferation of the cells, intracellular PA content, and SDH activity in the mitochondria. CONCLUSION: Genipin is involved in the energy metabolism of androgen-independent PC3 prostate cancer cells by reducing the content of intracellular PA and the activity of SDH in the mitochondria, which may be associated with its inhibitory effect on UCP-2.

A novel MRI-based diagnostic model for predicting placenta accreta spectrum.

Objective To develop and evaluate a diagnostic model based on MRI signs for predicting placenta accreta spectrum. Materials and Methods A total of 155 pregnant women were included in this study, randomly divided into 104 cases in the training set and 51 cases in the validation set. There were 93 Non-PAS cases, and 62 cases in the PAS group. The training set included 62 Non-PAS cases and 42 PAS cases. Clinical factors and MRI signs were collected for univariate analysis. Then, binary logistic regression analysis was used to develop independent diagnostic models with clinical relevant risk factors or MRI signs, as well as those combining clinical risk factors and MRI signs. The ROC curve analysis was used to evaluate the diagnostic performance of each diagnostic model. Finally, the validation was performed with the validation set. Results In the training set, four clinical factors (gestity, parity, uterine surgery history, placental position) and 11 MRI features (T2-dark bands, placental bulge, T2 hypointense interface loss, myometrial thinning, bladder wall interruption, focal exophytic mass, abnormal placental bed vascularization, placental heterogeneity, asymmetric placental thickening/shape, placental ischemic infarction, abnormal intraplacental vascularity) were considered as risk factors for PAS. The AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.779, 0.854, and 0.874, respectively. In the validation set, the AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.655, 0.728, and 0.735, respectively. Conclusion Diagnosis model based on MRI features in this study can well predict placenta accreta spectrum.

Prediction of histopathologic grades of myxofibrosarcoma with radiomics based on magnetic resonance imaging.

PURPOSE: To develop a radiomics-based model from preoperative magnetic resonance imaging (MRI) for predicting the histopathological grades of myxofibrosarcoma. METHODS: This retrospective study included 54 patients. The tumors were classified into high-grade and low-grade myxofibrosarcoma. The tumor size, signal intensity heterogeneity, margin, and surrounding tissue were evaluated on MRI. Using the least absolute shrinkage and selection operator (LASSO) algorithms, 1037 radiomics features were obtained from fat-suppressed T2-weighted images (T2WI), and a radiomics signature was established. Using multivariable logistic regression analysis, three models were built to predict the histopathologic grade of myxofibrosarcoma. A radiomics nomogram represents the integrative model. The three models' performance was evaluated using the receiver operating characteristics (ROC) and calibration curves. RESULTS: The high-grade myxofibrosarcoma had greater depth (P = 0.027), more frequent heterogeneous signal intensity at T2WI (P = 0.015), and tail sign (P = 0.014) than the low-grade tumor. The area under curve (AUC) of these conventional MRI features models was 0.648, 0.656, and 0.668, respectively. Seven radiomic features were selected by LASSO to construct the radiomics signature model, with an AUC of 0.791. The AUC of the integrative model based on radiomics signature and conventional MRI features was 0.875. The integrative model's calibration curve and insignificant Hosmer-Lemeshow test statistic (P = 0.606) revealed good calibration. CONCLUSION: An integrative model using radiomics signature and three conventional MRI features can preoperatively predict low- or high-grade myxofibrosarcoma.

Phase separation of polymer-dispersed liquid crystals on a chemically patterned substrate.

The surface-induced structure formation of polymer-dispersed liquid crystals (PDLCs) on a chemically patterned substrate was studied for the first time. The patterns on the substrate were successfully transferred to the PDLC film, resulting in alternating LC-rich and polymer-rich phases. This simple approach offers a new means of organizing micrometer-sized LC domains into well-ordered structures in a polymer matrix of PDLCs.

Self-assembly of gradient concentric rings via solvent evaporation from a capillary bridge.

A drop of solution containing nonvolatile solute is allowed to evaporate from a sphere-on-flat geometry. Left behind is a striking pattern of gradient concentric rings with unprecedented regularity. The center-to-center distance between adjacent rings, lambda(C-C), and the height of the ring, h(d), are strongly affected by the concentration of the solution and the properties of the solvent. The nature of the formation of regular gradient ring patterns during the course of irreversible solvent evaporation is revealed through theoretical calculations based on the mass conservation of the solution.