Objective To investigate the effects of exosomes derived from human dental pulp mes-enchymal stem cells ( hDPSC-exosomes) on the maturation and function of dendritic cells ( DC) stimulated by lipopolysaccharide ( LPS ) , and to evaluate their regulatory effects on the immune system. Methods Adult permanent teeth-derived dental pulp mesenchymal stem cells were cultured in vitro to extract exosomes in the cell culture medium. The morphology and sizes of the exosomes were observed under transmission electron microscopy. Expression of CD9 and CD63 on the surface of the exosomes was detected by Western blot. PBS, LPS and LPS+hDPSC-exosomes were respectively used to stimulate mouse bone marrow-derived dendritic cells (DC2. 4) for 24 h. A blank control group was set up accordingly. Expression of co-stimulato-ry molecules and cytokine secretion were detected by flow cytometry and ELISA, respectively. Expression of TLR2, TLR4 and NF-κB at mRNA level was detected by RT-PCR. Changes in the functions of DC were evaluated by mixed lymphocyte reaction ( MLR) . Results Adult permanent teeth-derived dental pulp mes-enchymal stem cells were successfully isolated. Up-regulated CD73 and CD90, and down-regulated CD45 were detected on the surface of the cells. Under electron microscopy ( SEM ) , hDPSC-exosomes showed round or oval microcapsule bodies about 50-80 nm in diameter with positive surface markers of CD9 and CD63. hDPSCs-exosomes could significantly reduce the LPS-induced expression of co-stimulatory molecules CD11c and CD86 on DC surface. Moreover, hDPSCs-exosomes increased TGF-β expression and decreased IL-4. They could also significantly inhibit the proliferation of splenic lymphocytes that was induced by DC af-ter LPS stimulation. Compared with the blank control group, hDPSC-exosomes could promote the expression of TLR2 and TLR4 on DC surface and up-regulate the expression of NF-κB. Conclusions This study showed that hDPSC-exosomes could inhibit the activation and functional maturation of DC, promote the de-velopment towards tolerant DC through TLR-NF-κB signaling pathway, and induce immune tolerance to regu-late immune balance.

Subject recruitment is a key component that affects the progress and results of clinical trials, and generally conducted with eligibility criteria (includes inclusion criteria and exclusion criteria). The semantic category analysis of eligibility criteria can help optimizing clinical trials design and building automated patient recruitment system. This study explored the automatic semantic categories classification of Chinese eligibility criteria based on artificial intelligence by academic shared task. We totally collected 38 341 annotated eligibility criteria sentences and predefined 44 semantic categories. A total of 75 teams participated in competition, with 27 teams having submitted system outputs. Based on the results, we found out that most teams adopted mixed models. The mainstream resolution was applying pre-trained language models capable of providing rich semantic representation, which were combined with neural network models and used to fine-tune the models with reference to classifier tasks, and finally improved classification performance could be obtained by ensemble modeling. The best-performing system achieved a macro
Artificial Intelligence ; China ; Humans ; Language ; Natural Language Processing ; Neural Networks, Computer