Targeting treatment of bladder cancer using PTK7 aptamer-gemcitabine conjugate

Xiang Wei,Peng Yongbo,Zeng Hongliang,Yu Chunping,Zhang Qun,Liu Biao,Liu Jiahao,Hu Xing,Wei Wensu,Deng Minhua,Wang Ning,Liu Xuewen,Xie Jianfei,Hou Weibin,Tang Jin,Long Zhi,Wang Long,Liu Jianye 한국생체재료학회 2023 생체재료학회지 Vol.27 No.00

Gemcitabine (GEM) is one of the first-line chemotherapies for bladder cancer (BC), but the GEMs cannot recognize cancer cells and have a low long-term response rate and high recurrence rate with side effects during the treatment of BC. Targeted transport of GEMs to mediate cytotoxicity to tumor and avoid the systemic side effects remains a challenge in the treatment of BC.Based on a firstly confirmed biomarker in BC-protein tyrosine kinase 7 (PTK7), which is overexpressed on the cell membrane surface in BC cells, a novel targeting system protein tyrosine kinase 7 aptamer-Gemcitabine conjugate (PTK7-GEMs) was designed and synthesized using a specific PTK7 aptamer and GEM through auto-synthesis method to deliver GEM against BC. In addition, the antitumor effects and safety evaluation of PTK7-GEMs was assessed with a series of in vitro and in vivo assays.PTK7-GEMs can specifically bind and enter to BC cells dependent on the expression levels of PTK7 and via the macropinocytosis pathway, which induced cytotoxicity after GEM cleavage from PTK7-GEMs respond to the intracellular phosphatase. Moreover, PTK7-GEMs showed stronger anti-tumor efficacy and excellent biosafety in three types of tumor xenograft mice models.These results demonstrated that PTK7-GEMs is a successful targeted aptamer-drug conjugates strategy (APDCs) to treat BC, which will provide new directions for the precision treatment of BC in the field of biomarker-oriented tumor targeted therapy.

Extracting phenolic compounds from aqueous solutions by cyclohexanone, a highly efficient extractant

Weibin Cai,Haihan Wang,Q. Gary Yang,Tiankun Liu,Yujun Wang 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.116 No.-

Methyl isobutyl ketone (MIBK) and diisopropyl ether (DIPE) are two commonly used extractants in industry,but their efficiency in extracting phenols, especially polyhydroxyphenols, is low. In the work, ahighly-efficient extractant was proposed to extract phenolic compounds, including polyhydroxyphenols. The interactions between three extractants, cyclohexanone (CYC), MIBK and DIPE, and phenols were analyzedby the COSMO-RS method and CYC shows stronger interactions with phenols than MIBK and DIPE. The results of Fourier-transform infrared spectroscopy (FTIR) show that strong hydrogen bonds areformed between CYC and phenolic compounds, in agreement with the results of the COSMO-RS method. The effects of concentration, temperature and pH values on the extractant performance were studied. Results showed that the performance of CYC is the best, followed by MIBK and DIPE, whose performanceis the worst. As CYC was used as the extractant, the distribution coefficients of the three phenolic compounds,phenol, resorcinol and phloroglucinol, are 96.7, 47.8, 13.0, respectively. These values are 35%,263%, and 160% larger than those of phenol, resorcinol and phloroglucinol, respectively, correspondingto MIBK. CYC is a highly-efficient extractant for the extraction of phenolic compounds, includingpolyhydroxyphenol.

A robust Correlation Filter based tracker with rich representation and a relocation component

( Menglei Jin ),( Weibin Liu ),( Weiwei Xing ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.10

Correlation Filter was recently demonstrated to have good characteristics in the field of video object tracking. The advantages of Correlation Filter based trackers are reflected in the high accuracy and robustness it provides while maintaining a high speed. However, there are still some necessary improvements that should be made. First, most trackers cannot handle multi-scale problems. To solve this problem, our algorithm combines position estimation with scale estimation. The difference from the traditional method in regard to the scale estimation is that, the proposed method can track the scale of the object more quickly and effective. Additionally, in the feature extraction module, the feature representation of traditional algorithms is relatively simple, and furthermore, the tracking performance is easily affected in complex scenarios. In this paper, we design a novel and powerful feature that can significantly improve the tracking performance. Finally, traditional trackers often suffer from model drift, which is caused by occlusion and other complex scenarios. We introduce a relocation component to detect object at other locations such as the secondary peak of the response map. It partly alleviates the model drift problem.

DA-Res2Net: a novel Densely connected residual Attention network for image semantic segmentation

( Xiaopin Zhao ),( Weibin Liu ),( Weiwei Xing ),( Xiang Wei ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.11

Since scene segmentation is becoming a hot topic in the field of autonomous driving and medical image analysis, researchers are actively trying new methods to improve segmentation accuracy. At present, the main issues in image semantic segmentation are intra-class inconsistency and inter-class indistinction. From our analysis, the lack of global information as well as macroscopic discrimination on the object are the two main reasons. In this paper, we propose a Densely connected residual Attention network (DA-Res2Net) which consists of a dense residual network and channel attention guidance module to deal with these problems and improve the accuracy of image segmentation. Specifically, in order to make the extracted features equipped with stronger multi-scale characteristics, a densely connected residual network is proposed as a feature extractor. Furthermore, to improve the representativeness of each channel feature, we design a Channel-Attention-Guide module to make the model focusing on the high-level semantic features and low-level location features simultaneously. Experimental results show that the method achieves significant performance on various datasets. Compared to other state-of-the-art methods, the proposed method reaches the mean IOU accuracy of 83.2% on PASCAL VOC 2012 and 79.7% on Cityscapes dataset, respectively.

A Framework for Human Motion Segmentation Based on Multiple Information of Motion Data

( Xiaofei Zan ),( Weibin Liu ),( Weiwei Xing ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.9

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.

Metalens for improving optical coherence tomography

Guo Songming,Feng Weibin,Long Yong,Liu Zhihao,Fu Xiao,Liang Haowen,Li Juntao 한국물리학회 2022 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.81 No.1

Optical coherence tomography is one of the most attractive new tomographic techniques, especially in the detection and imaging of biological tissues. For the detection and imaging of human corneas, the current ultra-high-resolution optical coherence tomography technology faces the challenge that the depth of focus is too short to scan the entire human cornea in a single amplitude scan. Here, we propose and design a silicon metalens to replace the objective lens in the sample arm of the optical coherence tomography system. In our simulation, a uniform focused beam with a depth of focus of 886 μm, an axial resolution of 3.1 μm and a lateral resolution of 2.2 μm can be generated by the metalens, which is under the excitation of broadband Gaussian light with wavelength coverage from 800 to 900 nm. This metalens fully satisfies the depth of focus and resolution requirements of the ultra-high-resolution optical coherence tomography system for human corneas, hence expands the application of optical coherence tomography in medical science for the benefit of mankind.