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Yuyun Ye, Yifan Zhao, Yong Sun, Jie Cao Department of Pharmaceutics, School of Pharmacy, Qingdao University, Qingdao, 266021, People’s Republic of ChinaCorrespondence: Jie Cao; Yong Sun, Email caojie0829@qdu.edu.cn; sunyong@qdu.edu.cnAbstract: Photodynamic therapy (PDT), combining photosensitizers (PSs) and excitation light at a specific wavelength to produce toxic reactive oxygen species, has been a novel and promising approach to cancer treatment with non-invasiveness, spatial specificity, and minimal systemic toxicity, compared with conventional cancer treatment. Recently, numerous basic research and clinical research have demonstrated the potential of PDT in the treatment of a variety of malignant tumors, such as esophageal cancer, bladder cancer, and so on. Metal-organic framework (MOF) has been developed as a new type of nanomaterial with the advantages of high porosity, large specific surface area, adjustable pore size, and easy functionalization, which could serve as carriers to load PSs or increase the accumulation of PSs in target cells during PDT. Moreover, active MOFs have the potential to construct multifunctional systems, which are conducive to refining the tumor microenvironment (TME) and implementing combination therapy to improve PDT efficacy. Hence, a comprehensive and in-depth depiction of the whole scene of the recent development of MOFs-based PDT in cancer treatment is desirable. This review summarized the recent research strategies of MOFs-based PDT in antitumor therapy from the perspective of MOFs functions, including active MOFs, inactive MOFs, and their further combination therapies in clinical antitumor treatment. In addition, the bottlenecks and obstacles in the application of MOFs in PDT are also described.Keywords: photodynamic therapy, metal-organic framework, tumor microenvironment, active MOFs, inactive MOFs

In order to meet the emerging demands of high-fidelity video services, a new video coding standard — High Efficiency Video Coding (HEVC) is developed to improve the compression performance of high definition (HD) videos and save half of the bitrate for the same perceptual video quality compared with H.264/Advanced Video Coding (AVC). Rate control still plays a significant role in HD video data transmission via the communication channel. However, R-lambda model based HEVC rate control algorithm does not take the relationship between the encoding complexity and Human Visual System (HVS) into account, what’s more, the convergence speed of Least Mean Square (LMS) algorithm is slow. In this paper, an adaptive gradient information and Broyden Fletcher Goldfarb Shanno (BFGS) based R-lambda model (GBRL) is proposed for the inter frame rate control, where the gradient based on Sobel operator can effectively measure the frame-content complexity and BFGS algorithm converges speedily than LMS algorithm. Experimental results show that the proposed GBRL method can achieve bitrate error reduction and peak signal to noise ratio (PSNR) improvement especially for the sequences with large motion, compared to the state-of-the-art rate control methods. In addition, if the optimal initial quantization parameter (QP) prediction model based on linear regression can be incorporated into the proposed GBRL method, the performance of rate control can be further improved.