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Abstract Point cloud data is a large collection of high dimensional 3D points with 3D coordinates and attributes, which has been one of the mainstream representations for emerging 3D applications, such as virtual reality, autonomous vehicles, and robotics. Due to the large‐scale unstructured high‐dimensional nature of point clouds, point cloud processing, transmitting and analysing has been challenging issues in multimedia signal processing and communication. Deep learning is a powerful tool to learn statistical knowledge from massive data. Advances in artificial intelligence, especially deep learning models are offering new opportunities for point cloud processing, compression and analysis. This special issue aims at promoting cutting‐edge research on deep learning‐based point cloud processing, including object detection, segmentation, registration, compression, and visual quality assessment.

ABSTRACTThis study aimed to conduct a bibliometric analysis in the field of bladder cancer (BC) immunotherapy, and explore the research trends, hotspots and frontiers from 2000 to 2022. VOSviewer software was used to analyze the collaborative relationships between authors, institutions, countries/regions, and journals through citation, co-authorship, and co-citation analysis, to identify research hotspots and frontiers in this field. Researchers based in the United States of America have published a total of 627 papers with 27,308 citations. Indeed, the USA ranked first among the top 10 most active countries and showed the most extensive collaboration with other countries. The University of Texas MD Anderson CANC CTR has published 58 articles, making it the top most institution in terms of published articles and active collaborative research. Kamat AM and Lamm DL were the most active and co-cited authors with 28 papers and 980 co-citations, respectively. Chang Yuan and Xu le were the most active collaborative authors with a total link strength of 195. The J UROLOGY was the most active and frequently co-cited journal, with 100 papers and 6,668 co-citations. Studies of BC immunotherapy can be broadly classified into three categories: “basic research”, “clinical trial”, and “prognosis”. Our findings provide an overview of the research priorities and future directions of BC immunotherapy. Tumor microenvironment and immune checkpoint inhibitors (ICIs) of BC, as well as the combination of ICIs with other drugs, may become the main direction of future research.

Abstract Chemotherapy is one of the most important treatments for cancer therapy. However, chemotherapy resistance is a big challenge in cancer treatment. Due to chemotherapy resistance, drugs become less effective or no longer effective at all. In recent years, long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been found to be associated with the development of chemotherapy resistance, suggesting that MALAT1 may be an important target to overcome chemotherapy resistance. In this review, we introduced the main mechanisms of chemotherapy resistance associated with MALAT1, which may provide new approaches for cancer treatment.