Programmed cell death ligand 1 (PD-L1) is an immunosuppressive molecule expressed on tumor cells. By interacting with programmed cell death-1 (PD-1) on T cells, it inhibits immune responses. Because PD-L1 expression on cancer cells increases their chemoresistance, we investigated the correlation between PD-L1 and multidrug resistance 1/ P-glycoprotein (MDR1/P-gp) expression in breast cancer cells. Analysis of breast cancer tissues using tissue microarrays revealed a significant correlation between PD-L1 and MDR1/P-gp protein levels. Increased expression of PD-L1 was associated with lymph node metastasis and histological tumor grade. In addition, interaction of PD-L1 with PD-1 induced phosphorylation of AKT and ERK, resulting in the activation of PI3K/AKT and MAPK/ERK pathways and increased MDR1/P-gp expression in breast cancer cells. The PD-1/PD-L1 interaction also increased survival of breast cancer cells incubated with doxorubicin. These findings suggest that the PD-1/PD-L1 inhibition may increase chemotherapy efficacy by inhibiting the MDR1/P-gp expression in breast cancer cells.
In this paper, we prove the existence and general energy decay rate of global solution to the mixed problem for nondissipative multi-valued hyperbolic differential inclusionswith memory boundary conditions on a portion of the boundary and acoustic boundary conditions on the rest of it. For the existence of solutions, we prove the global existence of weak solution by using Galerkin's method and compactness arguments. For the energy decay rates, we first consider the general nonlinear case of h satisfying a smallness condition, and prove the general energy decay rate by using perturbed modified energy method. Then, we consider the linear case of h: h(∇u) = −∇φ · (a∇u) and prove the general decay estimates of equivalent energy.
Anderson acceleration (AA) has a long history of use and a strong recent interest due to its potential ability to dramatically improve the linear convergence of the fixed-point iteration. Most authors are simply using and analyzing the stationary version of Anderson acceleration (sAA) with a constant damping factor or without damping. Little attention has been paid to nonstationary algorithms. However, damping can be useful and is sometimes crucial for simulations in which the underlying fixed-point operator is not globally contractive.The role of this damping factor has not been fully understood. In the present work, we consider the non-stationary Anderson acceleration algorithm with optimized damping (AAoptD) in each iteration to further speed up linear and nonlinear iterations by applying one extra inexpensive optimization. We analyze this procedure and develop an efficient and inexpensive implementation scheme. We also show that, compared with the stationary Anderson acceleration with fixed window size sAA(m), optimizing the damping factors is related to dynamically packaging sAA(m) and sAA(1) in each iteration (alternating window size m is another direction of producing non-stationary AA). More-
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