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Owing to the promising ability of saving hardware cost and spectrum resources, integrated sensing and communication (ISAC) is regarded as a revolutionary technology for future sixth-generation (6G) networks. The mono-static ISAC systems considered in most of existing works can only achieve limited sensing performance due to the single observation angle and easily blocked transmission links, which motivates researchers to investigate cooperative ISAC networks. In order to further improve the degrees of freedom (DoFs) of cooperative ISAC networks, the transmitter-receiver selection, i.e., base station (BS) mode selection problem, is meaningful to be studied. However, to our best knowledge, this crucial problem has not been extensively studied in existing works. In this paper, we consider the joint BS mode selection, transmit beamforming, and receive filter designs for cooperative cell-free ISAC networks, where multi-BSs cooperatively serve communication users and detect targets. An efficient joint beamforming design algorithm and three different heuristic BS mode selection methods are proposed to solve the non-convex NP-hard problem. Simulation results demonstrates the advantages of cooperative ISAC networks, the importance of BS mode selection, and the effectiveness of proposed algorithms., Comment: Accepted by WCNC

Integrated sensing and communication (ISAC) is widely recognized as a pivotal enabling technique for the advancement of future wireless networks. This paper aims to efficiently exploit the inherent sparsity of echo signals for the multi-input-multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) based ISAC system. A novel joint receive echo processing and transmit beamforming design is presented to achieve this goal. Specifically, we first propose a compressive sensing (CS)-assisted estimation approach to facilitate ISAC receive echo processing, which can not only enable accurate recovery of target information, but also allow substantial reduction in the number of sensing subcarriers to be sampled and processed. Then, based on the proposed CS-assisted processing method, the associated transmit beamforming design is formulated with the objective of maximizing the sum-rate of multiuser communications while satisfying the transmit power budget and ensuring the received signal-to-noise ratio (SNR) for the designated sensing subcarriers. In order to address the formulated non-convex problem involving high-dimensional variables, an effective iterative algorithm employing majorization minimization (MM), fractional programming (FP), and the nonlinear equality alternative direction method of multipliers (neADMM) with closed-form solutions has been developed. Finally, extensive numerical simulations are conducted to verify the effectiveness of the proposed algorithm and the superior performance of the introduced sparsity exploitation strategy., Comment: 13 pages, 6 Figures, submitted to IEEE Trans

Reconfigurable intelligent surface (RIS) is a revolutionary technology for sixth-generation (6G) networks owing to its ability to manipulate wireless environments. As a frequency-selective device, RIS can only effectively shape the propagation of signals within a certain frequency band. Due to this frequency-selective property, the deployment of RIS in cellular networks will introduce a complicated base station (BS)-RIS-user association issue since adjacent BSs operate at different frequency bands. In this paper, with the consideration of the frequency-selective characteristics of RIS, we aim to jointly optimize BS-RIS-user association, active beamforming at BSs, and passive beamforming of RIS to maximize the sum-rate of a RIS-assisted cellular network. We first leverage $l_0$-norm to efficiently integrate BS-RIS-user association with active and passive beamforming. Then, we adopt fractional programming (FP) and block coordinate descent (BCD) methods to deal with logarithmic and fractional parts and decouple the joint association and beamforming design problem into several sub-problems. Efficient algorithms which combine $l_0$-norm approximation, majorization-minimization (MM), and alternating direction method of multipliers (ADMM) are developed to alternately solve the sub-problems. Extensive simulation results illustrate the importance of BS-RIS-user association optimization in RIS-assisted cellular networks and verify the effectiveness of the proposed joint association and beamforming design algorithm., Comment: Submitted to IEEE Journal

Dual-function radar-communication (DFRC) systems, which can efficiently utilize the congested spectrum and costly hardware resources by employing one common waveform for both sensing and communication (S&C), have attracted increasing attention. While the orthogonal frequency division multiplexing (OFDM) technique has been widely adopted to support high-quality communications, it also has great potentials of improving radar sensing performance and providing flexible S&C. In this paper, we propose to jointly design the dual-functional transmit signals occupying several subcarriers to realize multi-user OFDM communications and detect one moving target in the presence of clutter. Meanwhile, the signals in other frequency subcarriers can be optimized in a similar way to perform other tasks. The transmit beamforming and receive filter are jointly optimized to maximize the radar output signal-to-interference-plus-noise ratio (SINR), while satisfying the communication SINR requirement and the power budget. An majorization minimization (MM) method based algorithm is developed to solve the resulting non-convex optimization problem. Numerical results reveal the significant wideband sensing gain brought by jointly designing the transmit signals in different subcarriers, and demonstrate the advantages of our proposed scheme and the effectiveness of the developed algorithm., Comment: 6pages, 3 figures, accepted by Globecom

Symbol-level precoding (SLP), which converts the harmful multi-user interference (MUI) into beneficial signals, can significantly improve symbol-error-rate (SER) performance in multi-user communication systems. While enjoying symbolic gain, however, the complicated non-linear symbol-by-symbol precoder design suffers high computational complexity exponential with the number of users, which is unaffordable in realistic systems. In this paper, we propose a novel low-complexity grouped SLP (G-SLP) approach and develop efficient design algorithms for typical max-min fairness and power minimization problems. In particular, after dividing all users into several groups, the precoders for each group are separately designed on a symbol-by-symbol basis by only utilizing the symbol information of the users in that group, in which the intra-group MUI is exploited using the concept of constructive interference (CI) and the inter-group MUI is also effectively suppressed. In order to further reduce the computational complexity, we utilize the Lagrangian dual, Karush-Kuhn-Tucker (KKT) conditions and the majorization-minimization (MM) method to transform the resulting problems into more tractable forms, and develop efficient algorithms for obtaining closed-form solutions to them. Extensive simulation results illustrate that the proposed G-SLP strategy and design algorithms dramatically reduce the computational complexity without causing significant performance loss compared with the traditional SLP schemes., Comment: 15 pages, 10 figures, submitted to IEEE

The surface glycoprotein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was used to develop coronavirus disease 2019 (COVID-19) vaccines. However, SARS-CoV-2, especially the S protein, has undergone rapid evolution and mutation, which has remained to be determined. Here, we analyzed and compared the early (12 237) and the current (more than 10 million) SARS-CoV-2 strains to identify the mutation features and geographical distribution of the S gene and S protein. Results showed that in the early strains, most of the loci were with relative low mutation frequency except S: 23403 (4486 strains), while in the current strains, there was a surge in the mutation strains and frequency, with S: 23403 constantly being the highest one, but tremendously increased to approximately 1050 times. Furthermore, D614 (S: 23403) was one of the most highly frequent mutations in the S protein of Omicron as of March 2022, and most of the mutant strains were still from the United States, and the United Kingdom. Further analysis demonstrated that in the receptor-binding domain, most of the loci with low mutation frequency in the early strains, while S: 22995 was nowadays the most prevalent loci with 3 122 491 strains in the current strains. Overall, we compare the mutation features of the S region in SARS-CoV-2 strains between the early and the current stains, providing insight into further studies in concert with emerging SARS-CoV-2 variants for COVID-19 vaccines. © 2022 Wiley Periodicals LLC.

Although m6A modifications are associated with tumor progression, and anti-tumor immune responses, the role of m6A regulators in HPV-related carcinogenesis has not been well resolved. To provide evidence for the role of m6A regulators in HPV-related carcinogenesis and identify potential therapeutic targets for HPV-related cancers, integrative analyses of m6A regulators in 1,485 head and neck squamous cell carcinoma (HNSC) patients and 507 cervical squamous cell carcinoma (CESC) patients was performed and identified that an m6A regulator, METTL3, was highly expressed in tumors and was related to the poor prognosis in HNSC and CESC. In HPV-positive tumors, METTL3 was positively associated with tumor HPV status, such as HPV integration status, E6 and unspliced-E6 expression, and p16 expression. Further analysis demonstrated that METTL3high status was negatively correlated with tumor immune cell infiltrations and facilitated the expression of immunosuppressive immune checkpoint molecules (i.e., PD-L1). Cell-derived xenograft models demonstrated that METTL3 inhibitor combined with anti-PD1 therapy promoted immunotherapy of CESC in vivo. Overall, this study identified that METTL3high status, is associated with poor prognosis and HPV status, and serves as a mediator of the immunosuppressive tumor microenvironment in HPV-associated cancer, which provides a promising therapeutic target for anti-cancer immunotherapy. © The author(s).

Background: rs13405728 was identified as one of the most prevalent susceptibility loci for polycystic ovary syndrome (PCOS) in Han Chinese and Caucasian women. However, the target genes and potential mechanisms of the rs13405728 locus remain to be determined. Methods: Three-dimensional (3D) genome interactions from the ovary tissue were characterized via high-through chromosome conformation capture (Hi-C) and Capture Hi-C technologies to identify putative targets at the rs13405728 locus. Combined analyses of eQTL, RNA-Seq, DNase-Seq, ChIP-Seq, and sing-cell sequencing were performed to explore the molecular roles of these target genes in PCOS. PCOS-like mice were applied to verify the expression patterns. Results: Generally, STON1 and FSHR were identified as potential targets of the rs13405728 locus in 3D genomic interactions with epigenomic regulatory peaks, with STON1 (P=0.0423) and FSHR (P=0.0013) being highly expressed in PCOS patients. STON1 co-expressed genes were associated with metabolic processes (P=0.0008) in adipocytes (P=0.0001), which was validated in the fat tissue (P<0.0001) and ovary (P=0.0035) from fat-diet mice. The immune system process (GO:0002376) was enriched in FSHR co-expressed genes (P=0.0002) and PCOS patients (P=0.0002), with CD4 high expression in PCOS patients (P=0.0316) and PCOS-like models (P=0.0079). Meanwhile, FSHR expression was positively correlated with CD4 expression in PCOS patients (P=0.0252) and PCOS-like models (P=0.0178). Furthermore, androgen receptor (AR) was identified as the common transcription factor for STON1 and FSHR and positively correlated with the expression of STON1 (P=0.039) and FSHR (P=4e-06) in ovary tissues and PCOS-like mice. Conclusion: Overall, we identified STON1 and FSHR as potential targets for the rs13405728 locus and their roles in the processes of adipocyte metabolism and CD4 immune expression in PCOS, which provides 3D genomic insight into the pathogenesis of PCOS. © Copyright © 2021 Cao, Wei, Liu

Background: rs13405728 was identified as one of the most prevalent susceptibility loci for polycystic ovary syndrome (PCOS) in Han Chinese and Caucasian women. However, the target genes and potential mechanisms of the rs13405728 locus remain to be determined. Methods: Three-dimensional (3D) genome interactions from the ovary tissue were characterized via high-through chromosome conformation capture (Hi-C) and Capture Hi-C technologies to identify putative targets at the rs13405728 locus. Combined analyses of eQTL, RNA-Seq, DNase-Seq, ChIP-Seq, and sing-cell sequencing were performed to explore the molecular roles of these target genes in PCOS. PCOS-like mice were applied to verify the expression patterns. Results: Generally, STON1 and FSHR were identified as potential targets of the rs13405728 locus in 3D genomic interactions with epigenomic regulatory peaks, with STON1 (P=0.0423) and FSHR (P=0.0013) being highly expressed in PCOS patients. STON1 co-expressed genes were associated with metabolic processes (P=0.0008) in adipocytes (P=0.0001), which was validated in the fat tissue (P<0.0001) and ovary (P=0.0035) from fat-diet mice. The immune system process (GO:0002376) was enriched in FSHR co-expressed genes (P=0.0002) and PCOS patients (P=0.0002), with CD4 high expression in PCOS patients (P=0.0316) and PCOS-like models (P=0.0079). Meanwhile, FSHR expression was positively correlated with CD4 expression in PCOS patients (P=0.0252) and PCOS-like models (P=0.0178). Furthermore, androgen receptor (AR) was identified as the common transcription factor for STON1 and FSHR and positively correlated with the expression of STON1 (P=0.039) and FSHR (P=4e-06) in ovary tissues and PCOS-like mice. Conclusion: Overall, we identified STON1 and FSHR as potential targets for the rs13405728 locus and their roles in the processes of adipocyte metabolism and CD4 immune expression in PCOS, which provides 3D genomic insight into the pathogenesis of PCOS. © Copyright © 2021 Cao, Wei, Liu

Optimally extracting the advantages available from reconfigurable intelligent surfaces (RISs) in wireless communications systems requires estimation of the channels to and from the RIS. The process of determining these channels is complicated by the fact that the RIS is typically composed of passive elements without any data processing capabilities, and thus the channels must be estimated indirectly by a non-colocated device, typically a controlling base station. In this article, we examine channel estimation for RIS-based systems from a fundamental viewpoint. We study various possible channel models and the identifiability of the models as a function of the available pilot data and behavior of the RIS during training. In particular, we consider situations with and without line-of-sight propagation, single- and multiple-antenna configurations for the users and base station, correlated and sparse channel models, single-carrier and wideband OFDM scenarios, availability of direct links between the users and base station, exploitation of prior information, as well as a number of other special cases. We further conduct numerical comparisons of achievable performance for various channel models using the relevant Cramer-Rao bounds.

Background: rs13405728 was identified as one of the most prevalent susceptibility loci for polycystic ovary syndrome (PCOS) in Han Chinese and Caucasian women. However, the target genes and potential mechanisms of the rs13405728 locus remain to be determined. Methods: Three-dimensional (3D) genome interactions from the ovary tissue were characterized via high-through chromosome conformation capture (Hi-C) and Capture Hi-C technologies to identify putative targets at the rs13405728 locus. Combined analyses of eQTL, RNA-Seq, DNase-Seq, ChIP-Seq, and sing-cell sequencing were performed to explore the molecular roles of these target genes in PCOS. PCOS-like mice were applied to verify the expression patterns. Results: Generally, STON1 and FSHR were identified as potential targets of the rs13405728 locus in 3D genomic interactions with epigenomic regulatory peaks, with STON1 (P=0.0423) and FSHR (P=0.0013) being highly expressed in PCOS patients. STON1 co-expressed genes were associated with metabolic processes (P=0.0008) in adipocytes (P=0.0001), which was validated in the fat tissue (P<0.0001) and ovary (P=0.0035) from fat-diet mice. The immune system process (GO:0002376) was enriched in FSHR co-expressed genes (P=0.0002) and PCOS patients (P=0.0002), with CD4 high expression in PCOS patients (P=0.0316) and PCOS-like models (P=0.0079). Meanwhile, FSHR expression was positively correlated with CD4 expression in PCOS patients (P=0.0252) and PCOS-like models (P=0.0178). Furthermore, androgen receptor (AR) was identified as the common transcription factor for STON1 and FSHR and positively correlated with the expression of STON1 (P=0.039) and FSHR (P=4e-06) in ovary tissues and PCOS-like mice. Conclusion: Overall, we identified STON1 and FSHR as potential targets for the rs13405728 locus and their roles in the processes of adipocyte metabolism and CD4 immune expression in PCOS, which provides 3D genomic insight into the pathogenesis of PCOS. © Copyright © 2021 Cao, Wei, Liu

The recently emerged symbol-level precoding (SLP) technique has been regarded as a promising solution in multi-user wireless communication systems, since it can convert harmful multi-user interference (MUI) into beneficial signals for enhancing system performance. However, the tremendous computational complexity of conventional symbol-level precoding designs severely hinders the practical implementations. In order to tackle this difficulty, we propose a novel deep learning (DL) based approach to efficiently design the symbol-level precoders. Particularly, in this correspondence, we consider a multi-user multi-input single-output (MU-MISO) downlink system. An efficient precoding neural network (EPNN) is introduced to optimize the symbol-level precoders for maximizing the minimum quality-of-service (QoS) of all users under the power constraint. Simulation results demonstrate that the proposed EPNN based SLP design can dramatically reduce the computing time at the price of slight performance loss compared with the conventional convex optimization based SLP design., Comment: 5 pages, 5 figures, 2 tables, submitted to IEEE Transactions on Vehicular Technology

Di Xiao,1,2,&ast; Jun-Yan Liu,3,&ast; Si-Min Zhang,4,&ast; Rang-Ru Liu,1,5 Ji-Ye Yin,1,6 Xue-Yao Han,4 Xi Li,1,6 Wei Zhang,1,6,7 Xiao-Ping Chen,1,6 Hong-Hao Zhou,1,6,7 Li-Nong Ji,4 Zhao-Qian Liu1,6,7 1Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, People’s Republic of China; 2Department of pharmacy, Xiangya Hospital, Central South University, Changsha, People’s Republic of China; 3Department of orthopaedics, Xiangya Hospital, Central South University, Changsha, People’s Republic of China; 4Department of Endocrinology and Metabolism, The People’s Hospital of Peking University, Beijing, People’s Republic of China; 5Key Laboratory of Tropical Diseases and Translational Medicine of the Ministry of Education & Hainan Provincial Key Laboratory of Tropical Medicine, Hainan Medical College, Haikou, People’s Republic of China; 6Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, Changsha, People’s Republic of China; 7National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhao-Qian Liu; Li-Nong Ji Email liuzhaoqian63@126.com; jiln@gmail.comObjective: Individual differences in glycemic response to metformin in antidiabetic treatment exist widely. Although some associated genetic variations have been discovered, they still cannot accurately predict metformin response. In the current study, we set out to investigate novel genetic variants affecting metformin response in Chinese type 2 diabetes (T2D) patients.Methods: A two-stage study enrolled 500 T2D patients who received metformin, glibenclamide or a combination of both were recruited from 2009 to 2012 in China. Change of HbA1c, adjusted by clinical covariates, was used to evaluate glycemic response to metformin. Selected single nucleotide polymorph