No abstract

The function of triggering receptor expressed on myeloid cell-like transcript 2 (TLT2) has not been characterized and their role in pulmonary tuberculosis (TB) remains unclear. In this study, we found that surface TLT2 was up-regulated in human monocytes of patients with active TB compared to healthy subjects. In vitro, TLT2 expression was induced in human monocyte cell line THP-1 cells after bacillus Calmette-Guérin (BCG) or Mycobacterium tuberculosis (Mtb) H37Rv infection. Knockdown of TLT2 by siRNA transfection suppressed IL-6 expression, whereas over-expression of TLT2 increased IL-6 production in THP-1 cells infected by H37Rv. TLT2 + CD14 + monocytes produced higher level of IL-6 compared to TLT2 − subset in active TB patients. Western blot and immunocoprecipitation revealed that TLT2 interacted with kinase JAK1/JAK2/Tyk2 to enhance STAT3 phosphorylation. Moreover, we showed that tyrosine residues 297 and 315 of TLT2 cytoplasmic domain were involved in STAT3 activation. In monocyte/CD4 + T cell co-culture assay, blockage of TLT2 fusion protein facilitated IFN-γ production by CD4 + T cells. Plate count assay showed that monocyte-mediated bacterial killing was promoted by TLT2 fusion protein. In vivo treatment with TLT-2 fusion protein reduced IL-6 production by macrophage but increased IFN-γ production by CD4 + T cell in H37Rv and BCG infected mice. Furthermore, TLT2 fusion protein attenuated inflammation, and reduced bacterial load in lung of infected mice. Together, these findings demonstrate that TLT2 negatively regulates Th1 response against mycobacterial infection, which promotes IL-6 production through JAK/STAT3 signal pathway.

In order to effectively improve the efficiency of hospital public management, we designed a hospital management index system based on deep learning model and analysed the application effect of reverse broadcast neural network model in hospital. The results show that in the performance analysis of the model, compared with other classical algorithms, the constructed model has the highest accuracy and the shortest delay. The weight analysis of each index in the model shows that the weight of rational utilization rate of beds in tertiary public hospitals is the highest, and the weight of rational utilization rate of beds in secondary public hospitals is the highest. The further analysis of the model training effect shows that the actual value of most output indexes is consistent with the predicted value, and the residual error of the predicted value is close to 0.