Helper T Cell (CD4(+)) Targeted Tacrolimus Delivery Mediates Precise Suppression of Allogeneic Humoral Immunity

Antibody-mediated rejection (ABMR) is a major cause of dysfunction and loss of transplanted kidney. The current treatments for ABMR involve nonspecific inhibition and clearance of T/B cells or plasma cells. However, the prognosis of patients following current treatment is poor. T follicular helper cells (Tfh) play an important role in allograft-specific antibodies secreting plasma cell (PC) development. Tfh cells are therefore considered to be important therapeutic targets for the treatment of antibody hypersecretion disorders, such as transplant rejection and autoimmune diseases. Tacrolimus (Tac), the primary immunosuppressant, prevents rejection by reducing T cell activation. However, its administration should be closely monitored to avoid serious side effects. In this study, we investigated whether Tac delivery to helper T (CD4(+)) cells using functionalized mesoporous nanoparticles can block Tfh cell differentiation after alloantigen exposure. Results showed that Tac delivery ameliorated humoral rejection injury in rodent kidney graft by suppressing Tfh cell development, PC, and donor-specific antibody (DSA) generation without causing severe side effects compared with delivery through the drug administration pathway. This study provides a promising therapeutic strategy for preventing humoral rejection in solid organ transplantation. The specific and controllable drug delivery avoids multiple disorder risks and side effects observed in currently used clinical approaches

Elevated Serum IL-21 Levels Are Associated With Stable Immune Status in Kidney Transplant Recipients and a Mouse Model of Kidney Transplantation

Allograft rejection after renal transplantation remains a challenge to overcome. Interleukin (IL)-21, a cytokine with pleiotropic effects, maintains immune homeostasis post-transplantation. Here, we report higher levels of IL-21 in kidney transplant recipients with non-rejection (NR) than in recipients with T cell-mediated rejection (TCMR, P \u3c 0.001) and antibody-mediated rejection (ABMR, P = 0.005). We observed a negative correlation between IL-21 and creatinine (Cr) levels (P = 0.016). The receiving operating characteristic (ROC) curve showed a promising diagnostic value of IL-21 to identify acute rejection with an area under the curve (AUC) of 0.822 (P \u3c 0.001). In contrast, exogenous administration of IL-21 accelerated acute rejection in a comparative translational kidney transplant (KT) mouse model. Reduced IL-21 levels in the peripheral blood were observed in KT mice after IL-21 injection. Further analysis revealed that increased IL-21 levels in the spleen induced proliferation of CD4+ T cells and CD19+ B cells after IL-21 treatment. Our findings suggest a critical function of IL-21 in kidney transplantation and the potential involvement of the IL-21/IL-21R pathway in acute rejection management

Numerical Simulation Research Considering the Influence of Bridge Deck Cross Slope on Wind Performance of π-Type Composite Beam Cable-Stayed Bridge with a Symmetric Elevation Arrangement

Based on a symmetrical cable-stayed bridge, the wind resistance performance of a proposed π-type composite beam is analyzed, and the influence of changing the bridge deck cross slope ratio on the static and dynamic wind characteristics is emphatically studied. The purpose is to provide a design reference for the preliminary wind resistance study of the cable-stayed bridge. The CFD (Computational Fluid Dynamics) numerical calculation method is used to solve the vibration problem of wind-bridge coupling with the help of the software Fluent. It is found that variation of four deck cross slope rates 0%, 1.5%, 2%, and 2.5% has large effects on the static wind coefficient and flutter critical wind speed of a π-type combination beam. In the range of a −3–3° wind attack angle, the static wind drag coefficient will be decreased as the beam deck cross slope rate increases, and in which the drag coefficient at 0% slope rate is the largest. Within the discounted wind speed 13, changing the bridge deck cross slope has little effect on the aerodynamic derivatives of a π-type composite beam. However, the beam deck slope increases the critical wind speed of the bridge, and the critical wind speed at 2.5% is the largest of the four deck slope rates. In addition, it is found that the beam leeward surface keeps generating up and down vortices when the incoming flow wind speed is in the range of 2.5–4.0 m/s, which led the beam to be under vertical vortex vibration, and further research is needed on vibration suppression measures

Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection

RGB-D saliency detection aims to accurately localize salient regions using the complementary information of a depth map. Global contexts carried by the deep layer are key to salient objection detection, but they are diluted when transferred to shallower layers. Besides, depth maps may contain misleading information due to the depth sensors. To tackle these issues, in this paper, we propose a new cross-modal cross-scale network for RGB-D salient object detection, where the global context information provides global guidance to boost performance in complex scenarios. First, we introduce a global guided cross-modal and cross-scale module named G2CMCSM to realize global guided cross-modal cross-scale fusion. Then, we employ feature refinement modules for progressive refinement in a coarse-to-fine manner. In addition, we adopt a hybrid loss function to supervise the training of G2CMCSNet over different scales. With all these modules working together, G2CMCSNet effectively enhances both salient object details and salient object localization. Extensive experiments on challenging benchmark datasets demonstrate that our G2CMCSNet outperforms existing state-of-the-art methods

Swin Transformer-Based Edge Guidance Network for RGB-D Salient Object Detection

Salient object detection (SOD), which is used to identify the most distinctive object in a given scene, plays an important role in computer vision tasks. Most existing RGB-D SOD methods employ a CNN-based network as the backbone to extract features from RGB and depth images; however, the inherent locality of a CNN-based network limits the performance of CNN-based methods. To tackle this issue, we propose a novel Swin Transformer-based edge guidance network (SwinEGNet) for RGB-D SOD in which the Swin Transformer is employed as a powerful feature extractor to capture the global context. An edge-guided cross-modal interaction module is proposed to effectively enhance and fuse features. In particular, we employed the Swin Transformer as the backbone to extract features from RGB images and depth maps. Then, we introduced the edge extraction module (EEM) to extract edge features and the depth enhancement module (DEM) to enhance depth features. Additionally, a cross-modal interaction module (CIM) was used to integrate cross-modal features from global and local contexts. Finally, we employed a cascaded decoder to refine the prediction map in a coarse-to-fine manner. Extensive experiments demonstrated that our SwinEGNet achieved the best performance on the LFSD, NLPR, DES, and NJU2K datasets and achieved comparable performance on the STEREO dataset compared to 14 state-of-the-art methods. Our model achieved better performance compared to SwinNet, with 88.4% parameters and 77.2% FLOPs. Our code will be publicly available