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Chronic wounds are characterized with excessive biofluid and persistent infection. Therefore, there is an urgent desire to develop a multifunctional wound dressing that can meet the extreme requirements including effective antibacterial and powerful wound microenvironment regulation and protection function to promote wounds heal quickly. In this study, a multifunctional composite dressing (HA-AMP/SF/Alg/Rb-BG-AIEgens) was synthesized by combining a mesoporous bioactive glass framework loaded with AIEgens (Rb-BG-AIEgens) with cross-linked antimicrobial peptide grafted hyaluronic acid (HA-AMP), sodium alginate (Alg), and silk fibroin (SF). It is important to note that the Rb-BG-AIEgens can achieve real-time and sensitive bacterial detection. HA-AMP can achieve broad spectrum antibacterial and avoid the residue of drug-resistant bacteria. The HA-AMP/SF/Alg/Rb-BG-AIEgens dressing can up-regulate related proliferative proteins, thereby promoting regeneration of tissue and the rapid healing of chronic wounds. With good biocompatibility and antibacterial ability, HA-AMP/SF/Alg/Rb-BG-AIEgens dressing has great potential to become a next generation wound dressing for clinical biological fluid management and chronic bacterial infection treatment.
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Objectives: To detect the expression of circular RNA (circRNA) circINTS4 in triple-negative breast cancer (TNBC) and to analyze the relationship between the expression of circRNA circINTS4 and the clinicopathological characteristics and chemotherapy resistance of patients with TNBC. Methods: Bioinformatics was used to predict that circINTS4 and POM121 could bind to miR-129-5p, and dual luciferase reporter genes proved that circINTS4 could bind to miR-129-5p and miR-129-5p could bind to POM121. RNA immunoprecipitation (RIP) and RNA pull-down experiments confirmed that circINTS4 binds to miR-129-5p. The correlation among circINTS4, miR-129-5p, and POM121 was detected by qRT-PCR. Results: In ADR-resistant TNB cells, circINTS4 was significantly up-regulated, miR-129-5p was down-regulated, and POM121 protein expression was significantly up-regulated. Experimental results showed that circINTS4 knockdown inhibited proliferation, migration, invasion, and autophagy. Knocking down miR-129-5p or overexpression of POM121 reversed the inhibitory effect of sh-circints4 on the development of ADR-resistant TNBC cells. In addition, CIRCINTS4 regulates POM121 expression by sponge-adsorbed miR-129-5p. CIRCINTS4 knockdown prevents ADR-resistant tumor growth by regulating the miR-129-5p/POM121 axis in vivo. Conclusions: CircRNA circINTS4 may act as the ceRNA of miR-129-5p to regulate the expression of target gene POM121, thereby promoting the progress of TNBC molecular mechanism and providing scientific basis for circINTS4 as a new molecular target for clinical diagnosis and drug resistance therapy of TNBC.
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Alzheimer disease (AD) is mainly manifested as insidious onset, chronic progressive cognitive decline and non-cognitive neuropsychiatric symptoms, which seriously affects the quality of life of the elderly and causes a very large burden on society and families. This paper uses graph theory to analyze the constructed brain network, and extracts the node degree, node efficiency, and node betweenness centrality parameters of the two modal brain networks. The T test method is used to analyze the difference of graph theory parameters between normal people and AD patients, and brain regions with significant differences in graph theory parameters are selected as brain network features. By analyzing the calculation principles of the conventional convolutional layer and the depth separable convolution unit, the computational complexity of them is compared. The depth separable convolution unit decomposes the traditional convolution process into spatial convolution for feature extraction and point convolution for feature combination, which greatly reduces the number of multiplication and addition operations in the convolution process, while still being able to obtain comparisons. Aiming at the special convolution structure of the depth separable convolution unit, this paper proposes a channel pruning method based on the convolution structure and explains its pruning process. Multimodal neuroimaging can provide complete information for the quantification of Alzheimer's disease. This paper proposes a cascaded three-dimensional neural network framework based on single-modal and multi-modal images, using MRI and PET images to distinguish AD and MCI from normal samples. Multiple three-dimensional CNN networks are used to extract recognizable information in local image blocks. The high-level two-dimensional CNN network fuses multi-modal features and selects the features of discriminative regions to perform quantitative predictions on samples. The algorithm proposed in this paper can automatically extract and fuse the features of multi-modality and multi-regions layer by layer, and the visual analysis results show that the abnormally changed regions affected by Alzheimer's disease provide important information for clinical quantification.
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Some studies evaluated the association of factor V Leiden (FVL) with sepsis risk and mortality risk. However, the results were conflicting. Thus, we performed a meta-analysis to address the association between FVL and sepsis. PubMed and EMBASE databases were searched to find relevant studies. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were estimated using random effects model. Five case-control studies and 3 cohort studies were included. Overall, no significant association between FVL and sepsis risk was observed (OR = 0.93; 95% CI 0.74-1.15; P = .49). In addition, there was no significant association between FVL and sepsis-related mortality (OR = 1.17; 95% CI 0.73-1.88; P = .52). In the subgroup analysis, no increased sepsis risk and mortality risk were found in caucasian population. This meta-analysis suggested that FVL was not a risk factor for sepsis and sepsis mortality.
