Renifolin F is a prenylated chalcone isolated from Shuteria involucrata, a traditional minority ethnic medicine used to treat the respiratory diseases and asthma. Based on the effects of the original ...medicine plant, we established an in vivo mouse model of allergic asthma using ovalbumin (OVA) as an inducer to evaluate the therapeutic effects of Renifolin F. In the research, mice were sensitized and challenged with OVA to establish an allergic asthma model to evaluate the effects of Renifolin F on allergic asthma. The airway hyper-reactivity (AHR) to methacholine, cytokine levels, ILC2s quantity and mircoRNA-155 expression were assessed. We discovered that Renifolin F attenuated AHR and airway inflammation in the OVA-induced asthmatic mouse model by inhibiting the regulation of ILC2s in the lung, thereby, reducing the upstream inflammatory cytokines IL-25, IL-33 and TSLP; the downstream inflammatory cytokines IL-4, IL-5, IL-9 and IL-13 of ILC2s; and the co-stimulatory factors IL-2 and IL-7; as well as the expression of microRNA-155 in the lung. The findings suggest a therapeutic potential of Renifolin F on OVA-induced airway inflammation.
Facial expression is the main medium of information transmission in human communication, playing an important role in human's daily life. Facial expression recognition is still challenging due to the ...various obstacle, illumination, and posture. However, most of the existing works focus on deeper or wider network structures and rarely explores the high-level feature statistics. In this paper, we propose a second-order pooling convolution neural network to explore the correlation information between the facial features after deep network learning. At the final stage of the network, we add a new covariance pooling layer to replace the first-order pooling of standard convolution networks. In the pooling layer of covariance, the Newton iteration method is used to approximate the square root instead of EIG or SVD, which makes it more suitable for GPU. Due to the small amount of facial expression data, this paper uses different data augmentation methods to increase the amount of training data and improve the generalization ability of the model. The proposed method, data augmentation and second-order pooling (DASOP), was evaluated on the real-world affective faces database (RAFDB) and the static facial expressions in the wild (SFEW), yielding correct rates of 88.625% and 59.518%, respectively. We achieve state-of-the-art performance superior to existing methods.
Features and interaction between features of liver disease is of great significance for the classification of liver disease. Based on least absolute shrinkage and selection operator (LASSO) and ...interaction LASSO, the generalized interaction LASSO model is proposed in this paper for liver disease classification and compared with other methods. Firstly, the generalized interaction logistic classification model was constructed and the LASSO penalty constraints were added to the interactive model parameters. Then the model parameters were solved by an efficient alternating directions method of multipliers (ADMM) algorithm. The solutions of model parameters were sparse. Finally, the test samples were fed to the model and the classification results were obtained by the largest statistical probability. The experimental results of liver disorder dataset and India liver dataset obtained by the proposed methods showed that the coefficients of interaction features of the model were not zero, indicating that interaction
Person re-identification aims to retrieve the pedestrian across different cameras. It is still a challenging task for the intelligent visual surveillance system because of similar appearances, camera ...shooting angles, scene illumination, and pedestrian pose. In this paper, we propose a novel two-stream network named spatial segmentation network that learns both the global and local features in a unified framework for nonaligned person re-identification. One stream focuses on spatial feature learning using global adaptive average pooling in deep convolutional neural networks. Another stream is utilized to learn the fine local features by adopting horizontal average pooling without division that depends on the pose predictor. To assess the importance ranking of all features, we also obtain the performance of every part feature and global features. Our evaluation of the proposed method on Market-1501 acquires 94.51% Rank-1 and 90.78% mAP, that on DukeMTMC-re-ID acquires 87.52% Rank-1 and 84.82% mAP, and that on CHUK03-detected acquires 69.71% Rank-1 and 71.67% mAP; these findings verify the state-of-the-art performance of the proposed method.
Background
Tuberous sclerosis complex (TSC), belongs to autosomal dominant genetic disorder, which affects multiple organ systems in the body, including the skin, brain, lungs, kidneys, liver, and ...eyes. Mutations in TSC1 or TSC2 was proved to be associated with these conditions.
Methods
Gene‐panel Sequence of NGS was used to detect the mutation in a Chinese family. The research further investigates whether aberrant splicing and nonsense‐mediated mRNA degradation (NMD) could serve as a mechanism cause by TSC1 mutation. MINI‐Gene assay apply by pcMINI‐TSC1wt/mut plasmids delivered in HeLa and 293T cell lines. Recombinant plasmids expressing wild‐type and mutant‐type EGFP‐TSC1 were constructed and transiently transfected into human embryonic kidney cells 293T by lipofectamine. Real‐time PCR and Western Blot were performed to analyze the expression of mRNAs and proteins of EGFP‐TSC1 and NMD factor UPF1.
Results
The gene test verified a novel heterozygous TSC1 frameshift mutation (TSC1 c.1550_1551del) in the proband and her mother. From MINI‐Gene assay, the agarose gel showed that both the mutant and wild‐type mRNA possess two main bands, indicating two splicing modes, named band A and B, respectively. The mutation c.1550_1551del has not produced new splicing site, but there is a selective splicing in varying degree significantly after mutation. On the contrary, function validation assay showed that cells transfected with the mutant TSC1 plasmids expressed significantly lower TSC1 in mRNAs and proteins levels, compared with the wild‐type TSC1 plasmid transfection. A translation inhibitor cycloheximide and small interfering RNA of UPF1 (siRNA‐UPF1) increased mRNA or protein expression of TSC1 significantly in cells transfected with the mutant plasmids.
Conclusion
Our study demonstrated that the novel TSC1 frameshift mutation (TSC1 c.1550_1551del) trigger aberrant splicing and NMD simultaneously, causing decrease of hamartin, then, leading to tuberous sclerosis complex formation.
This paper verified a novel heterozygous TSC1 frameshift mutation（TSC1 c.1550_1551del）in a Chinese family of tuberous sclerosis complex. MINI‐Gene and function validation assay demonstrated that the novel TSC1 mutation triggered aberrant splicing and NMD simultaneously, caused decrease of hamartin, then resulted in tuberous sclerosis complex.
Facial expressions which contain rich behavioral information are the primary vehicle to express emotions. It is important to analyze people's emotions with computer to achieve human-computer ...interaction. Feature extraction is the most important factor affecting the recognition effect. However, the existing deep learning for expression recognition is mainly based on global feature extraction. Local feature extraction provides more fine-grained information than global features. To strengthen the local discrimination of the image and pay more attention to the small targets in the local region, we propose an innovative Adaptive Weight Based on Overlapping Blocks Network (AWOBNet) for learning feature representation. First, we spatially overlay the feature maps to obtain the local features of the face. Considering the correlation and proportion between different features, we model the correlation between feature channels after overlapping blocks. Moreover, a new adaptive weighting method is developed to enhance significant features. We evaluate the proposed network on two public datasets, including the Real-World Affective Faces Database (RAFDB) and the Static Facial Expressions in the Wild (SFEW), and show the performance using the visualization method. The accuracy rates of our method obtain 89.863% on RAFDB and 62.410% on SFEW, which is significantly higher than the existing technical level.
•Adaptive Weight Based on Overlapping Blocks Network for Facial Expression Recognition.•Feature map blocking to extract local features of the network to improve performance.•The relevant information between local features to achieve effective performance.•Performance of local network for facial expressions that are occluded and posture.
The present study was designed to investigate the effect of sinomenine (SIN), an alkaloid extracted from sinomenium acutum, on the antigen-induced activation of RBL-2H3. For this investigation, the ...RBL-2H3 cells were sensitized with dinitrophenyl (DNP)-specific IgE overnight in 1.0 ml of Eagle's MEM (EMEM), and varying doses of SIN were added to the culture medium for 30 min and challenged with dinitrophenyl-human serum albumin (DNP-HSA) to induce mast cell degranulation before supernatants were collected. The effects of SIN on antigen-induced release of β-hexosaminidase were measured by enzymatic assay, calcium influx by FACS, cytokines by ELISA, and signaling events by immunoblotting. The results showed that treatment with SIN was followed by a decrease in FcεRI-mediated mast cell release of β-hexosaminidase, production of IL-4 and TNF-α, phosphorylation of Gab2 (Scaffolding adapter Grb2-associated binder 2), Akt and p38 mitogen-activated protein kinase (MAPK). In addition, SIN had no effect on the phosphorylation of LAT and no significant difference on calcium mobilization was observed between control and SIN treated group. These results suggested that SIN might suppress the antigen-induced activation of RBL-2H3 cells via a Ca
2+ independent pathway.
Gab2 plays an important role in FcepsilonRI mediated signal events which lead to degranulation from mast cells. The present study was designed to investigate the effect of the synthetic Gab2 ...(scaffolding adapter Grb2-associated binder 2) siRNA on the antigen-induced activation of RBL-2H3 cells. A double stranded siRNA against Gab2-mRNA was synthesized and transfected into RBL-2H3 cells. After 6 h, cells were then sensitized with dinitrophenyl (DNP)-specific IgE overnight and challenged with dinitrophenyl-human serum albumin (DNP-HSA) to induce mast cell degranulation before supernatants were collected. Effects of Gab2 siRNA on antigen-induced release of beta-hexosaminidase and histamine, cytokine production and regulation of the proteins in the pathway were measured by enzymatic assay, EIA, ELISA and Western blotting. Treatment with Gab2 siRNA significantly decreased Gab2 expression, inhibited the FcepsilonRI-mediated mast cell release of beta-hexosaminidase and histamine, reduced the production of IL-4 and TNF-alpha and inhibited the phosphorylation of Akt, PKCdelta and p38 mitogen-activated protein kinase (MAPK). Data showed that Gab2 siRNA could suppress the antigen-induced activation of RBL-2H3 cells and suggested a possible mechanism through inhibition of signaling molecules downstream of Gab2 in the FcepsilonRI-mediated Ca(2+)-independent pathway. Furthermore, potential usefulness of Gab2 knock-down as a method for inhibition of mast cell-mediated allergic reactions was demonstrated.
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