Objective The immune rejection mediated by CD4 + T cell and antigen presenting macrophages is the leading cause of corneal transplantation failure. Bone marrow-derived mesenchymal stem cells (BM-MSCs) possess robust immunomodulatory potentials, and have been shown by us and others to promote corneal allograft survival. However, the immunological mechanism underlying the protective effects of BM-MSCs remains unclear. Therefore, in the current study, this mechanism was investigated in a BM-MSC-treated rat model of corneal allograft rejection, in the hope to facilitate the search for novel interventional targets to corneal allograft rejection.

Objectives Although several studies have shown that cigarette smoking is associated with thyroid stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb), the exact relationship between smoking and thyroid function is controversial. As little is known about the effects of smoking on TSH, TPOAb and TgAb in Chinese residents. This study aimed to evaluate the association between cigarette smoking and TSH, TPOAb and TgAb in ten-city residents of China.

The blood-brain barrier (BBB) is a dynamic and complex interface between blood and the central nervous system (CNS). It protects the brain by preventing toxic substances from entering the brain but also limits the entry of therapeutic agents. ATP-binding cassette (ABC) efflux transporters are critical for the functional barrier and present a formidable impediment to brain delivery of therapeutic agents including antibiotics. The aim of this study was to investigate the possible involvement of multidrug resistance-associated protein 1 and 4 (MRP1 and MRP4), two ABC transporters, in benzylpenicillin efflux transport using wild-type (WT) MDCKII cells and cells overexpressing those human transporters, as well as non-selective and selective inhibitors. We found that inhibiting MRP1 or MRP4 significantly increased [ 3 H]benzylpenicillin uptake in MDCKII-WT, -MRP1 or –MRP4 cells. Similar results were also found in HepG2 cells, which highly express MRP1 and MRP4, and hCMEC/D3 cells which express MRP1. The results indicate that human and canine MRP1 and MRP4 are involved in benzylpenicillin efflux transport. They could be potential therapeutic targets for improving the efficacy of benzylpenicillin for treating CNS infections since both MRP1 and MRP4 express at human blood-brain barrier.

Powerful shovel-like forelimbs with special shape, structure and biological materials enable mole cricket to digging efficiently. During digging, the tip of the claw needs to wedge into the soil, and the base needs to withstand considerable anti-shear force. In this study, we analysed the structural characteristics, material composition and mechanical properties of the claw teeth using scanning electron microscopy, plasma atomic emission spectroscopy, nanoindentation and finite element analysis. The results show that the tips of claw teeth have a dense and homogeneous structure and a higher hardness and contents of Mn and Zn compared with the base. The structure of the base of claw teeth has an obvious laminar structure and higher fracture resistance. Moreover, it is speculated from the simulation results that basal position of the claw teeth is tough enough to withstand high stress, and the presence of the ribs effectively improves the mechanical stability and load-bearing capacity of the teeth during excavation. The results of this study can provide inspiration for the design of efficient mechanical components and agricultural implements.

Learning a powerful representation for a class with few labeled samples is a challenging problem. Although some state-of-the-art few-shot learning algorithms perform well based on meta-learning, they only focus on novel network architecture and fail to take advantage of the knowledge of every classification task. In this paper, to accomplish this goal, it proposes to combine the channel attention and spatial attention module (C-SAM), the C-SAM can mine deeply more effective information using samples of different classes that exist in different tasks. The residual network is used to alleviate the loss of the underlying semantic information when the network is deeper. Finally, a relation network including a C-SAM is applied to act as a classifier, which avoids learning more redundant information and compares the relation between difference samples. The experiment was carried out using the proposed method on six datasets, such as mini imagenet, Omniglot, Caltech-UCSD Birds, describable textures dataset, Stanford Dogs and Stanford Cars. The experimental results show that the C-SAM outperforms many state-of-the-art few-shot classification methods.