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BACKGROUND: Experimental autoimmune thyroiditis (EAT) is a widely used animal model to study the pathogenesis and treatment of autoimmune thyroid diseases. Yiqi Jiedu Xiaoying Decoction (YJXD) is a traditional Chinese medicine formula with potential immunomodulatory effects. In this study, we investigated the therapeutic effects of YJXD on EAT in rats and explored its underlying mechanisms. METHODS: Female Wistar rats were induced to develop EAT by immunization with thyroglobulin (Tg) and taken sodium iodide water (0.05%) and then treated with YJXD or sodium selenite. HE staining was used to observe the pathological changes of thyroid tissue in EAT rats. Th17 and Treg cell frequencies were analyzed by flow cytometry, and the expression levels of Th17- and Treg-related cytokines and thyroid autoantibody were determined by enzyme-linked immunosorbent assay (ELISA). The expression of Th17- and Treg-related transcriptional factors was detected by real-time polymerase chain reaction (RT-PCR) and Immunohistochemistry (IHC). RESULTS: Our results demonstrated that treatment with YJXD significantly attenuated the severity of EAT, as evidenced by reduced thyroid gland inflammatory infiltration and decreased serum thyroglobulin autoantibody levels. Importantly, YJXD treatment effectively modulated the Th17/Treg cell balance by suppressing Th17 cell differentiation and promoting Treg cell expansion. Moreover, YJXD was also found to regulate the expression levels of Th17- and Tregrelated cytokines and transcriptional factors, further supporting its immunomodulatory effects in EAT. CONCLUSION: YJXD exerted therapeutic effects on EAT by regulating the Th17/Treg cell balance, modulating the production of Th17- and Treg-related cytokines and the expression of transcriptional factors.
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In molecular dynamics simulations, the limited time step size has been a barrier to simulating long-time behaviors. Implicit time integration methods allow markedly larger time steps than the standard explicit time method, although they have major drawbacks such as overheads solving linear systems and instability of Newton iterations. To overcome these issues, we propose a semi-implicit time integration scheme, the semi-implicit Hessian correction (SimHec) scheme, for overdamped Langevin dynamics. The method focuses on the Hessian matrices of bonded and nonbonded interactions, where components with large negative Hessian eigenvalues are cut off in the linear approximation of momentum equations to avoid instability. The narrow band Hessian matrix enables an efficient parallelized linear solution with an overlapping approximation. We tested SimHec for the interdomain fluctuations in adenylate kinase and the powerstroke transition of myosin II using a coarse-grained protein model. SimHec reproduced the same dynamics as the explicit method, although the transition dynamics tended to be accelerated and fluctuations in bonded potentials were slightly reduced. These deviations were corrected using a hybrid method, SimHec-H, which adds explicit time steps after the semi-implicit time step. The proposed scheme allowed us to use time steps 50-200 times larger than those in explicit time integration, which resulted in a speedup factor of 7-30 taking the overhead into account.
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By tracking echocardiography images more accurately and stably, we can better assess myocardial functions. In this paper, we propose a new tracking method with deformable Regions of Interest (ROIs) aiming at rational pattern matching. For this purpose we defined multiple tracking points for an ROI and regarded these points as nodes in the Meshfree Method to interpolate displacement fields. To avoid unreasonable distortion of the ROI caused by noise and perturbation in echo images, we introduced a stabilization technique based on a nonlinear strain energy function. Examples showed that the combination of our new tracking method and stabilization technique provides competitive and stable tracking.
