Silk fibroin/collagen composite hydrogels with different matrix stiffness influence the growth and phenotype of human mammary epithelial cells / 生理学报

Extracellular matrix (ECM) stiffness is closely related to the physiological and pathological states of breast tissue. The current study was aimed to investigate the effect of silk fibroin/collagen composite hydrogels with adjustable matrix stiffness on the growth and phenotype of normal breast epithelial cells. In this study, the enzymatic reaction of horseradish peroxidase (HRP) with hydrogen peroxide (H2O2) was used to change the degree of cross-linking of the silk fibroin solution. The rotational rheometer was used to characterize the composite hydrogel's biomechanical properties. Human normal mammary epithelial cell line MCF-10A were inoculated into composite hydrogels with various stiffness (19.10-4 932.36 Pa) to construct a three dimensional (3D) culture system of mammary epithelial cells. The CCK-8 assay was applied to detect the cell proliferation rate and active states in each group. Hematoxylin-Eosin (HE) staining and whole-mount magenta staining were used for histological evaluation of cell morphology and distribution. The results showed that with the increase of matrix stiffness, MCF-10A cells exhibited inhibited proliferation rate, decreased formation of acinus structures and increased branching structures. Meanwhile, with the increase of matrix stiffness, the polarity of MCF-10A cells was impeded. And the increase of matrix stiffness up-regulated the expression levels of mmp-2, mmp-3, and mmp-9 in MCF-10A cells. Among the genes related to epithelial-mesenchymal transition (EMT), the expression level of the epithelial marker gene E-cadherin was significantly down-regulated, while the interstitial cell marker gene Vimentin was up-regulated, and the expression levels of Snail, Wnt5b and Integrin β1 in the Wnt pathway were up-regulated. These results suggest that the silk fibroin/collagen composite hydrogels with adjustable matrix stiffness regulates the proliferation and the phenotype of MCF-10A cells. The effects of increased matrix stiffness may be closely related to the changes of the polar structures and function of MCF-10A cells, as well as the occurrence of ECM-remodeling and EMT.

Effect of Vaccarin on atherosclerosis in mouse model and its mechanism / 中国药理学通报

Aim To investigate the effect of vaccarin on mouse atherosclerosis in vivo and the underlying mechanism. Methods AopE mice aged 6 to 8 weeks old were used to establish the atherosclerosis model. Oil red O staining was used to determine the lipid levels in aorta and aortic root. Enzyme linked immunosorbent assay (ELISA) was used to detect the levels of serum inflammatory factors. Results Vaccarin could effectively reduce the levels of blood glucose and blood pressure in AopE

Permeability to blood-brain burrier of / 解剖学报

Objective To investigate the optimal time and mechanism of nerve growth factor(NGF)crossing the blood-brain barrier (BBB) under cerebral ischemia in rats through focal cerebral ischemia experiments in rats, and to provide a new way for the clinical application of NGF. Methods A total of 65 healthy Sprague-Dawlay (SD) male rats were prepared by using a modified suture method to prepare focal cerebral ischemia models. Rats were injected with

Application of recurrent neural network in prognosis of peritoneal dialysis / 北京大学学报(医学版)

OBJECTIVE@#Deep learning models, including recurrent neural network (RNN) and gated recurrent unit (GRU), were used to construct the clinical prognostic prediction models for peritoneal dialysis (PD) patients based on routine clinical data. The performance of the RNN and GRU were compared with logistic regression (LR), which is commonly used in medical researches. The possible underlining clinical implications based on the result from the GRU model were also investigated.@*METHODS@#We used the clinical data from the PD center of Peking University Third Hospital as the data source. Both the baseline data at the beginning of dialysis, and the follow-up and prognostic data of the patients were used by the RNN and GRU prediction models. The hyper-parameters were tuned based on the 10-fold cross-validation. The risk prediction performance of each model was evaluated via area under the receiver operation characteristic curve (AUROC), recall rate and F1-score on the testset.@*RESULTS@#A total of 656 patients with the 261 occurrences of death were included in the experiment. The total number of all diagnostic records were 13 091. The results on the testset showed that the AUROC of the LR model, RNN model, and GRU model was 0.701 4, 0.786 0, and 0.814 7, respectively. The predictive performances of the GRU and RNN models were significantly better than that of the LR model. The performances of the GRU and RNN models assessed by recall rate and F1-score were also significantly better than that of the LR model, in which the GRU model reached the best performance. In addition, the recall rates were different among different causes of death or by different prediction time windows.@*CONCLUSION@#The recurrent neural network model, especially the GRU model, is more effective in predicting PD patients' prognosis as compared with the LR model. This new model may be helpful for clinicians to provide timely intervention, thus improving the quality of care of PD.