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Segmentation of mitral valve is not only important for clinical diagnosis, but also has far-reaching impact on prevention and prognosis of the disease by experts and doctors. In this paper, the multi-channel cross fusion transformer based U-Net network model (MCCT-UNet) is proposed according to the classical U-Net architecture. First, the jump connection part of MCCT-UNet is designed by using a multi-channel cross-fusion based attention mechanism module (MCCT) instead of the original jump connection, and this module fuses the feature maps from different scales in different stages of the encoder. Second, the optimization of the feature fusion method is proposed in the decoding stage by designing the cross-compression excitation sub-module (C-SENet) to replace the simple feature splicing, and the C-SENet is used to bridge the inconsistency of the semantic hierarchy by effectively combining the deeper information in the encoding stage with the shallower information. This two modules can establish a close connection between the encoder and decoder by exploring multi-scale global contextual information to solve the semantic divide problem, thus it significantly improves the segmentation performance of the network. The experimental results show that the improvement is effective, and the MCCT-UNet model outperforms the other 9 network models. Specifically, the MCCT-UNet achieved a Dice coefficient of 0.8734, an IoU of 0.7854, and an accuracy of 0.9977, demonstrating significant improvements over the compared models.

Brain metastases are a leading cause of cancer-related mortality. However, progress in their treatment has been limited over the past decade, due to an incomplete understanding of the underlying biological mechanisms. Employing accurate in vitro and in vivo models to recapitulate the complexities of brain metastasis offers the most promising approach to unravel the intricate cellular and physiological processes involved. Here, we present a comprehensive review of the currently accessible models for studying brain metastasis. We introduce a diverse array of in vitro and in vivo models, including cultured cells using the Transwell system, organoids, microfluidic models, syngeneic models, xenograft models, and genetically engineered models. We have also provided a concise summary of the merits and limitations inherent to each model while identifying the optimal contexts for their effective utilization. This review serves as a comprehensive resource, aiding researchers in making well-informed decisions regarding model selection that align with specific research questions.

Background: Cell-assisted lipotransfer (CAL), a modified adipose-derived stromal/stem cells (ADSCs)-based approach for autologous fat grafting that is an ideal option for soft tissue augmentation, has many shortcomings in terms of retention and adverse effects. The objective of our study was to improve the treatment efficacy of CAL by adding fibroblasts. Methods: ADSCs and fibroblasts were isolated from human adipose and dermal tissues, with fibroblasts identified by immunofluorescence and ADSCs identified by the multilineage differentiation method. We performed cell proliferation, apoptosis, migration, adipogenic, and hemangioendothelial differentiation experiments, qPCR and Western blotting analysis in co-cultures of fibroblasts and ADSCs. Subsequently, we conducted animal experiments with BALB/c nude mice. Masson's staining, immunofluorescence staining and ultrasound were used to analyze the occurrence of adverse reactions of the grafted fat, and CT and three-dimensional reconstruction were used to accurately evaluate the volume of the grafted fat. Results: We found that the co-culture of fibroblasts and ADSCs promoted their mutual proliferation, adipogenic differentiation, hemangioendothelial differentiation and proliferation and migration of HUVECs. Fibroblasts inhibit the apoptosis of ADSCs. Moreover, in animal experiments, the autografted adipose group combined with ADSCs and fibroblasts had the least occurrence of oily cysts, and fat had the best form of survival. Conclusions: We enhanced adipocyte regeneration and angiogenesis in ADSCs and fibroblast cells after adding fibroblasts to conventional CAL autologous fat grafts. In turn, the volume retention rate of the grafted fat is improved, and the adverse reactions are reduced.

As the emerging contaminants, the environmental risks of drug-derived pollutants have attracted extensive attention. Citalopram (CTP) and mirtazapine (MTP) are commonly used as modern antidepressant drugs. Previous studies had proved that CTP and MTP entered the aquatic environment, but less reported the negative effects of the drugs on aquatic organisms. Herein, the effects on the feeding rate of Daphnia magna (D. magna) induced by psychotropic drugs CTP and MTP were investigated, which the possible mechanisms were analyzed with the oxidative stress and damage. Generally, the feeding rates of exposed D. magna under all concentrations of CTP and 1.03 mg/L of MTP were significantly decreased after exposure (p

MicroRNAs bind to the 3′ untranslated regions of mRNAs, affecting translation, tumorigenesis, and apoptosis. This study evaluated the role of TYMS (rs1059394, C > T, and rs2847153, G > A), RYR3 (rs1044129, G > A), KIAA0423 (rs1053667, T > C), and GOLGA7 (rs11337, G > T) polymorphisms for assessment of glioma risk and prognosis among the Chinese Han population. Five single-nucleotide polymorphisms were assessed in 605 glioma patients and 1,300 controls. We found a significant correlation between rs1059394 and glioma susceptibility in the homozygote and dominant genetic models (TT versus CC, odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.52–0.97, p = 0.03; CT+TT versus CC, OR = 0.74, 95% CI = 0.55–0.99, p = 0.04). The results of the Kaplan-Meier and log rank tests revealed that the rs11337 GG genotype correlated with better overall survival of glioma patients (p = 0.017) than the GT genotype. Multivariate Cox regression analysis results also showed that the rs11337 GT genotype correlated with worse overall survival (p = 0.017, hazard ratio [HR] = 1.25, 95% CI = 1.04–1.5) than the GG genotype. These results suggest that GOLGA7 (rs11337) polymorphism may play a role in the prognosis of glioma patients and that TYMS (rs1059394) is associated with glioma risk. Keywords: GOLGA7, rs11337, polymorphism, cancer risk, prognosis, microRNA-binding site