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Orai family are a calcium channel of cell membrane extracellular Ca

Thymic stromal lymphopoietin presents in two distinct isoforms: short-form (sfTSLP) and long-form (lfTSLP). lfTSLP promotes inflammation, whereas sfTSLP inhibits inflammation, in allergic asthma. However, little is known about the regulation of lfTSLP and sfTSLP during allergic attack in the asthma airway epithelium. Here, we report that small ubiquitin-like modifier (SUMOylation) was enhanced in house dust mite-induced allergic asthma airway epithelium. Inhibition of SUMOylation significantly alleviated airway T-helper cell type 2 inflammation and lfTSLP expression. Mechanistically, chromobox 4 (CBX4), a SUMOylation E3 ligase, enhanced lfTSLP mRNA translation, but not sfTSLP, through the RNA-binding protein muscle excess (MEX)-3B. MEX-3B promoted lfTSLP translation by binding the lfTSLP mRNA through its K homology domains. Furthermore, CBX4 regulated MEX-3B transcription in human bronchial epithelial cells through enhancing SUMOylation concentrations of the transcription factor TFII-I. In conclusion, we demonstrate an important mechanism whereby CBX4 promotes MEX-3B transcription through enhancing TFII-I SUMOylation and MEX-3B enhances the expression of lfTSLP through binding to the lfTSLP mRNA and promoting its translation. Our findings uncover a novel target of CBX4 for therapeutic agents for lfTSLP-mediated asthma.

The Variational Principle (VP) is designed to generate non-folding grids (diffeomorphisms) with prescribed Jacobian determinant (JD) and curl. The solution pool of the original VP is based on an additive formulation and, consequently, is not invariant in the diffeomorphic Lie algebra. The original VP works well when the prescribed pair of JD and curl is calculated from a diffeomorphism, but not necessarily when the prescribed JD and curl are unknown to come from a diffeomorphism. In spite of that, the original VP works effectively in 2D grid generations. To resolve this issue, in this paper, we describe a new version of VP (revised VP), which is based on the composition of transformations and, therefore, is invariant in the Lie algebra. The revised VP seems to have overcome the inaccuracy of the original VP in 3D grid generations. In the following sections, the mathematical derivations are presented. It is shown that the revised VP can calculate the inverse transformation of a known diffeomorphism. Its inverse consistency and transitivity of transformations are also demonstrated numerically. Finally, a new definition of averaging diffeomorphisms based on the revised VP is proposed.

Medical image segmentation annotated by experts provides the labeled data sets for many scientific researches. However, due to the unevenly experienced backgrounds of the experts and limited numbers of patients with certain diseases or illnesses, not only do such labeled data sets have smaller samples but their quality and normality also can range in wide variabilities and be ambiguous. In practice, these segmentations are usually assigned to be the ground truths for the scientific studies, so it may undermine the trustworthiness of the resulting findings. Therefore, it is meaningful to consider how to give a more unified opinion of the annotations among different experts. In this paper, a novel approach to form normal distributions of segmentation is proposed based on multiple doctors’ annotations for the same patient. The proposed approach is developed through the following steps: (1) utilize a framework(7) of averaging images to construct an averaged annotation based on different given annotations; (2) determine the image registration deformations from the averaged annotation to the given annotations; (3) build a joint multivariate Gaussian distribution over the logorithm of Jacobian determinants and curls of the registration deformations; lastly, (4) simulate a normal distribution of segmentation by the joint Gaussian distribution of registration deformation. This work translates the problem of forming a normal distribution of the image segmentation into a problem of forming joint Gaussian distribution of image registration deformations, which the latter can be reasoned by Jacobian determinant (models local size of pixel cells) and curl (models local rotation of pixel cells) information. In the following sections, a detailed walk-through of the proposed approach is provided along with its analytical mathematics and numerical examples for its effectiveness. A synthetic example of 3 manually defined label image is made to show how to construct a mean label image, and an example of a real cancer image annotated by 3 doctors demonstrates the formation of the normal distribution and the effectiveness of the propose method.

Background: Thymic stromal lymphopoietin (TSLP) is present in two distinct isoforms, short-form (sfTSLP) and long-form (lfTSLP). lfTSLP promotes inflammation while sfTSLP inhibits inflammation in allergic asthma. However, little is known about the regulation of lfTSLP and sfTSLP during allergic attack in asthma airway epithelium. Methods and Results: Here, we report that SUMOylation was enhanced in HDM-induced allergic asthma airway epithelium. Inhibition of SUMOylation significantly alleviated airway Th2 inflammation and lfTSLP expression. Mechanistically, CBX4, a SUMOylation E3 ligase, enhanced lfTSLP, but not sfTSLP, mRNA translation through the RNA binding protein, MEX-3B. MEX-3B promoted lfTSLP translation through binding of its KH domains to the lfTSLP mRNA. Furthermore, CBX4 regulated MEX-3B transcription in HBE through enhancing SUMOylation levels of the transcription factor, TFII-I. Conclusion: We demonstrate an important mechanism whereby CBX4 promotes MEX-3B transcription through enhancing TFII-I SUMOylation, and MEX-3B enhances the expression of lfTSLP through binding to the lfTSLP mRNA and promoting its translation. Our findings uncover a novel target of CBX4 for therapeutic agents to lfTSLP-mediated asthma.

Background Up-regulation of aerobic glycolysis has been reported as a characterization of asthma and facilitates airway inflammation. We has been previously reported that short isoform thymic stromal lymphopoietin (sTSLP) could reduce inflammation in asthmatic airway epithelial cells. Here we wanted to investigate whether the inhibition of sTSLP on asthma is related to aerobic glycolysis. Methods Asthmatic model was established in challenging Male BALB/c mice and 16-HBE (human bronchial epithelial) cell line with house dust mite (HDM). Indicators of glycolysis were assessed to measure whether involve in sTSLP regulating airway epithelial cells inflammation in asthmatic model in vivo and in vitro. Results sTSLP decreased inflammation of asthmatic airway and aerobic glycolysis in mice. HDM or long isoform thymic stromal lymphopoietin (lTSLP) promoted HIF-1α expression and aerobic glycolysis by miR-223 to target and inhibit VHL (von Hippel-Lindau) expression 16-HBE. Inhibition of aerobic glycolysis restrained HDM- and lTSLP-induced inflammatory cytokines production. sTSLP along had almost no potential to alter aerobic glycolysis of 16-HBE. But sTSLP decreased LDHA (lactate dehydrogenase A) and LD (Lactic acid) levels in BALF, and HIF-1α and LDHA protein levels in airway epithelial cells of asthma mice model. lTSLP and sTSLP both induced formation of TSLPR and IL-7R receptor complex, and lTSLP obviously facilitated phosphorylation of JAK1, JAK2 and STAT5, while sTSLP induced a little phosphorylation of JAK1 and STAT5. Conclusion We identified a novel mechanism that lTSLP could promote inflammatory cytokines production by miR-223/VHL/HIF-1α pathway to upregulate aerobic glycolysis in airway epithelial cells in asthma. This pathway is suppressed by sTSLP through occupying binding site of lTSLP in TSLPR and IL-7R receptor complex.

The natural configuration of an intrinsically curved and twisted filament is uniquely a helix so that it can be referred to as a helical filament. We find that confining a helical filament on a cylinder can create a bistable state. When c_{0}R=0.5, where c_{0} is the intrinsic curvature of filament and R is the radius of cylinder, the phase diagram for the stability of a helix contains three regimes. Regime I has a small intrinsic twisting rate (ITR) and exhibits a bistable state which consists of two isoenergic helices. In regime II, the filament has a moderate ITR and the bistable state consists of a metastable low-pitch helix and a stable nonhelix. In regime III, the helix is unstable, owing to a large ITR. A similar phenomenon occurs when c_{0}R∼0.5. Monte Carlo simulation confirms these conclusions and indicates further that there are bistable nonhelices in regime III. This bistable system offers a prospective green material since the wide range of parameters and distinctive configurations for bistable states favor its realization and application.

We find that the excluded volume interaction (EVI) can accelerate an abrupt transition in extension for an intrinsically curved two-dimensional semiflexible biopolymer. It makes the transition much sharper, reduces the critical force remarkably, and the larger the persistent length or the intrinsic curvature, the larger the reduction in critical force. The transition is caused by a collective change in bending angles associated with removing cusps owing to thermal fluctuation. Our results reveal that EVI can excite a cooperative behavior, straighten more bonds simultaneously so cause a sharper transition. The transition is dominated by the mechanical force because the specific heat does not divergence. Our findings suggest that an intrinsically curved biopolymer can act as a switch or sensor in some biological processes.

Avasimibe (Ava) is an acetyl-CoA acetyltransferase 1 (ACAT1) specific inhibitor and an established medicine for atherosclerosis, owing to its excellent and safe anti-inflammation effects in humans. However, its efficacy in asthma has not yet been reported. We first administered varying concentrations of avasimibe to house dust mite (HDM)-induced asthmatic mice; results showed that 20 mg/kg avasimibe most significantly reduced IL-4 and IL-5 production in bronchoalveolar lavage fluid (BALF) and total IgE in serum, and the avasimibe treatment also exhibited lower mucus secretion, decreased goblet and basal cells but increased ciliated cells compared to the HDM group. And the redistribution of adherens junction (AJ) proteins induced by HDM was far more less upon avasimibe administration. However, avasimibe did not reduce the cholesterol ester ratio in lung tissues or intracellular cholesterol ester, which is avasimibe’s main effect. Further analysis confirmed that avasimibe impaired epithelial basal cell proliferation independent of regulating cholesterol metabolism and we analyzed datasets using the Gene Expression Omnibus (GEO) database and then found that the KRT5 gene (basal cell marker) expression is correlated with the β-catenin gene. Moreover, we found that β-catenin localized in cytomembrane upon avasimibe treatment. Avasimibe also reduced β-catenin phosphorylation in the cytoplasm and inactivated the Wnt/β-catenin signaling pathway induced by HDMs, thereby alleviating the airway epithelial barrier disruption. Taken together, these findings indicated that avasimibe has potential as a new therapeutic option for allergic asthma.

Epithelial barrier dysfunction is involved in the pathogenesis of asthma. Previous studies show that SUMOylation can regulate epithelial junction molecule localization. However, the role of SUMOylation in epithelial barrier dysfunction in asthma remains unclear. This study found that inhibition of SUMOylation attenuates house dust mite (HDM)-induced epithelial barrier dysfunction. The SUMOylation levels of junction molecules were determined by co-immunoprecipitation (CO-IP) and proximity ligation assay (PLA). HDM treatment significantly enhanced SUMOylation levels of β-catenin, while no effect was seen on ZO-1, Occludin, and E-cadherin SUMOylation levels. Inhibition of β-catenin SUMOylation through 2-D08 treatment or SUMOylation modification site mutant (K233A) promoted its membrane localization and repressed Wnt/β-catenin signaling. Further, we identified that CBX4, an E3 ligase, mediated SUMOylation of β-catenin. Knockdown of CBX4 promoted β-catenin membrane localization and improved epithelial barrier function. In vivo analysis showed that AAV6-shCBX4-mediated knockdown of CBX4 attenuated HDM-induced allergic airway inflammation and epithelial barrier dysfunction. The findings showed that inhibiting β-catenin SUMOylation by targeting CBX4 mitigated HDM-induced epithelial barrier dysfunction in asthma.

RationaleThymic stromal lymphopoietin (TSLP) is present in two distinct isoforms, short-form (sfTSLP) and long-form (lfTSLP). lfTSLP promotes inflammation while sfTSLP inhibits inflammation in allergic asthma. However, little is known about the regulation of lfTSLP and sfTSLP during allergic attack in asthma airway epithelium.Methods and ResultsHere, we report that SUMOylation was enhanced in HDM-induced allergic asthma airway epithelium. Inhibition of SUMOylation significantly alleviated airway Th2 inflammation and lfTSLP expression. Mechanistically, CBX4, a SUMOylation E3 ligase, enhanced lfTSLP, but not sfTSLP, mRNA translation through the RNA binding protein, MEX-3B. MEX-3B promoted lfTSLP translation through binding of its KH domains to the lfTSLP mRNA. Furthermore, CBX4 regulated MEX-3B transcription in HBE through enhancing SUMOylation levels of the transcription factor, TFII-I.ConclusionWe demonstrate an important mechanism whereby CBX4 promotes MEX-3B transcription through enhancing TFII-I SUMOylation, and MEX-3B enhances the expression of lfTSLP through binding to the lfTSLP mRNA and promoting its translation. Our findings uncover a novel target of CBX4 for therapeutic agents to lfTSLP-mediated asthma.

Accurate registration of medical images is vital for doctor’s diagnosis and quantitative analysis. In this paper, we propose a new unsupervised learning network SA-VoxelMorph for 3D deformable medical image registration. In this paper, we design a novel network architecture SAU-Net by introducing a new Binary Spatial Attention Module (BSAM) into skip connection of 3D U-Net, which can make full use of the spatial information extracted from the encoding and corresponding decoding stage. Moreover, from variational method, control function can better control the generation of registration field $\phi$. Therefore, we also propose a new registration loss function with novel smoothing term based on optimal control method to generate better $\phi$. We verify our method on two datasets including ADNI and PPMI, and obtain excellent results on magnetic resonance image (MRI) registration with higher average Dice scores and better diffeomorphic registration fields compared with other state-of-the-art methods. The experimental results show the method can achieve better performance in brain MRI registration.

We explore the effects of two typical torques on the mechanical property of the helical configuration for an intrinsically straight filament or biopolymer either in three-dimensional space or on a cylinder. One torque is parallel to the direction of a uniaxial applied force, and is coupled to the cross section of the filament. We obtain some algebraic equations for the helical configuration and find that the boundary conditions are crucial. In three-dimensional space, we show that the extension is always a monotonic function of the applied force. On the other hand, for a filament confined on a cylinder, the twisting rigidity and torque coupled to the cross section are irrelevant in forming a helix if the filament is isotropic and under free boundary condition. However, the twisting rigidity and the torque coupled to the cross section become crucial when the Euler angle at two ends of the filament are fixed. Particularly, the extension of a helix can subject to a first-order transition so that in such a condition a biopolymer can act as a switch or sensor in some biological processes. We also present several phase diagrams to provide the conditions to form a helix.

Accurate segmentation of brain tissue in magnetic resonance images (MRI) is a difficult task due to different types of brain abnormalities. In this paper, we review the deformation method focus on the construction of diffeomorphisms to generate the 2D MRI image grids and extend it to the 3D MRI images, address clearly a new formation of the deformation problem for moving domains and construction of diffeomorphisms through a completely different approach. The idea is to control directly the first order differential operators including the Jacobian determinant (JD), divergence (DIV), and curl vector (CV) generated by the 2D and 3D MRI image grids and use them as CNN channels with other modalities (T1-weighted, T1-IR, and T2-FLAIR) or single T1-weighted modality to improve the performance of brain segmentation. More importantly, we discuss the influence of three optimization parameters to the generation of the 2D and 3D MRI image grids by both theoretical analysis and the numerical experiments. We test this method on the IBSR dataset and MRBrainS18 dataset based on VoxResNet and verify the influence of three parameters on the accuracy of MRI brain segmentation. Finally, we also compare the segmentation performance of our method in three networks, including 2D U-Net, 3D U-Net, and VoxResNet. We believe the proposed method can advance the performance in brain segmentation and clinical diagnosis.

We study the mechanical property of a two-dimensional free rotating chain (FRC). We find that at low force and with a scaled bond length, the relation between extension and applied force of a FRC obeys the same linear law as that of a free jointed chain (FJC), agreeing with the conclusion that free of applied force the end-to-end distances of two models have the same power law. But beginning from a moderate force, the two models become very different even with a scaled bond length. Especially, when the bond angle is small, the relative extension of a FRC is always smaller than that of a FJC; but with a large bond angle the relative extension of a FRC becomes larger than that of a FJC. Moreover, the extension of FJC is a smooth function of applied force, but the extension of a long FRC can subject to a first order transition when the bond angle is large.

Deformable medical image registration is vital for doctor's diagnosis and quantitative analysis. In this paper, we propose a novel unsupervised learning model (denoted as BSADM) for 3D diffeomorphic medical image registration. Inspired by spatial attention module, we propose a new network architecture BSAU-Net by introducing a novel Binary Spatial Attention Module (BSAM) into skip connection, which can take full advantages of the spatial information extracted from the encoding path and corresponding decoding path. In addition, from variational method in differential geometry, monitor function f is used to control the Jacobian determinant (JD) of registration field ɸ. So, we also propose a novel orientation-consistent regularization loss to penalize the local regions with negative Jacobian determinant, which further encourages the diffeomorphic property of the transformations. We verify our method on two datasets including ADNI and PPMI dataset, and obtain excellent improvement on magnetic resonance (MR) image registration with higher average Dice scores and better diffeomorphic registration.

Background: Asthma is a complex and heterogeneous disease. Autophagy, process of self-protection in cells, is an intracellular process when cells are being attacked by certain stress. Our team focused upon the disruption of airways epithelial barrier in asthma, and we interested in whether autophagy played a key role in asthma. Methods: 400U HDM was used to treat HBECs and established asthmatic mice model. Western blotting, RT-PCR and immunofluorescence were mainly used to detect autophagy process in vivo and in vitro. One way ANOVA and Mann Whitney test were used for statistic. Results: After treated with HDM, expression of LC3ab increased in vivo and in vitro. Using Rapamycin, 3-MA and Chloroquine to treat HBECs, then we surprisingly found that HDM disrupts epithelial barrier through incomplete autophagy. To find out the connection between asthma and autophagy, we chose known autophagy related genes to determine the association between autophagy and disruption of airway epithelial barrier. Atg5 and atg12 were chosen because these two genes varied upon the time dependent manner. Knocked down the expression of atg5 or atg12 by siRNA, the expression of TSLP, which can induce the disruption of airway epithelial barrier, remarkably reduced. Conclusions: These results demonstrated that HDM induced inflammatory in airway epithelium through autophagy, and then knocked down autophagy related genes alleviated the inflammatory in HBECs.

We find that a moderate intrinsic twisting rate (ITR) can induce a bistable state for a force-free two-dimensional intrinsically curved filament. There are two different configurations of equal energy in a bistable state so that the filament is clearly different from its three-dimensional counterpart. The smaller the ITR or the larger the intrinsic curvature (IC), the clearer the distinction between two isoenergetic configurations and the longer the filament. In bistable states, the relationship between length and ITR is approximately a hyperbola and relationship between IC and critical ITR is approximately linear. Thermal fluctuation can result in a shift between two isoenergetic configurations, but large bending and twisting rigidities can prevent the shift and maintain the filament in one of these two configurations. Moreover, a filament can have a metastable state and at a finite temperature such a filament has the similar property as that of a filament with bistable state.

Recently deep learning-based networks have achieved advanced performance in medical image segmentation. However, the development of deep learning is slow in magnetic resonance image (MRI) segmentation of normal brain tissues. In this paper, inspired by channel attention module, we propose a new architecture, Binary Channel Attention U-Net (BCAU- Net), by introducing a novel Binary Channel Attention Module (BCAM) into skip connection of U-Net, which can take full advantages of the channel information extracted from the encoding path and corresponding decoding path. To better aggregate multiscale spatial information of the feature map, spatial pyramid pooling (SPP) modules with different pooling operations are used in BCAM instead of original average-pooling and max-pooling operations. We verify this model on two datasets including IBSR and MRBrainS18, and obtain better performance on MRI brain segmentation compared with other methods. We believe the proposed method can advance the performance in brain segmentation and clinical diagnosis.

We study the effects of the intrinsic curvature (IC), intrinsic twist rate (ITR), anisotropic bending rigidities, sequence disorder, and temperature (T) on the persistence length (l_{p}) of a two- or three-dimensional semiflexible biopolymer. We develop some general expressions to evaluate exactly these effects. We find that a moderate IC alone reduces l_{p} considerably. Our results indicate that the centerline of the filament keeps as a helix in a rather large range of T when ITR is small. However, a large ITR can counterbalance the effect of IC and the result is insensitive to the twist rigidity. Moreover, a weak randomness in IC and ITR can result in an "overexpanded" state. Meanwhile, when ITR is small, l_{p} is not a monotonic function of T but can have either minimum or maximum at some T, and in the two-dimensional case the maximum is more obvious than that in the three-dimensional case. These results reveal that to obtain a proper size at a finite T for an intrinsically curved semiflexible biopolymer, proper values of bending rigidities and ITR are necessary but a large twist rigidity may be only a by-product. Our findings are instructive in controlling the size of a semiflexible biopolymer in organic synthesis since the mean end-to-end distance and radius of gyration of a long semiflexible biopolymer are proportional to l_{p}.

Optimization of loss function is one of the research directions in medical image registration. A loss function of registration is the sum of two terms: a similarity term Lsim (Φ) and a smoothing term Lsmooth(Φ). From variational method in differential geometry, control function is essential to generate better registration field Φ. Here, we propose a new registration loss function with novel smoothing terms using VoxelMorph based on control function and Laplacian operator. We divide the process into two steps. The first step is based on Laplacian operator. We replace the gradient of registration field Φ in Lsmooth (Φ) by the Laplacian of Φ. In the second step, we add the term control function F to the Lsmooth (Φ) in the first step, which is the key contribution of our method. We verify our method on two datasets including ADNI and IBSR, and obtain excellent improvement on MR image registration, with better convergence and gets higher average Dice and lower percentage of non-positive Jacobian locations compared with original loss function.

This work explores the ground-state of an elastic model for an intrinsically curved semiflexible biopolymer. We find that the two- and three-dimensional systems have exactly the same mechanical property and show that the signed curvature of the model is nowhere continuous so that the standard variational technique fails in continuous model. Moreover, we show that the ground-state configuration of the model is a sawtooth line, and find that the relative extension of the corresponding discrete model is z r = cos [ 2 c 0 / ( 4 + f ) ] when c0

An analysis of more than eight years of data from vaccination forums on mothering.com shows that the antivaccination movement is well-organized and widely dispersed, and that it emerged long before concerns about immunity were expressed. The findings are evidence of a formidable challenge to the social norms surrounding vaccination.