Enabling More Users to Benefit from Near-Field Communications: From Linear to Circular Array

Massive multiple-input multiple-output (MIMO) for 5G is evolving into the extremely large-scale antenna array (ELAA) to increase the spectrum efficiency by orders of magnitude for 6G communications. ELAA introduces spherical-wave-based near-field communications, where channel capacity can be significantly improved for single-user and multi-user scenarios. Unfortunately, the near-field region at large incidence/emergence angles is greatly reduced with the widely studied uniform linear array (ULA). Thus, many randomly distributed users may fail to benefit from near-field communications. In this paper, we leverage the rotational symmetry of uniform circular array (UCA) to provide uniform and enlarged near-field regions at all angles, enabling more users to benefit from near-field communications. Specifically, by exploiting the geometrical relationship between UCA and users, the near-field beamforming technique for UCA is developed. Based on the analysis of near-field beamforming, we reveal that UCA is able to provide a larger near-field region than ULA in terms of the effective Rayleigh distance. Moreover, a concentric-ring codebook is designed to realize efficient codebook-based beamforming in the near-field region. In addition, we find out that UCA could generate orthogonal near-field beams along the same direction when the focal point of the near-field beam is exactly the zeros of other beams, which has the potential to further improve spectrum efficiency in multi-user communications compared with ULA. Simulation results are provided to verify the effectiveness of theoretical analysis and feasibility of UCA to enable more users to benefit from near-field communications by broadening the near-field region.Comment: Accepted by IEEE TWC. In this paper, the rotational symmetry of UCA is leveraged to provide uniform and enlarged near-field regions, enabling more users to benefit from near-field communications. Simulation codes will be provided to reproduce the results in this paper: http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.htm

Systematical Detection of Significant Genes in Microarray Data by Incorporating Gene Interaction Relationship in Biological Systems

Many methods, including parametric, nonparametric, and Bayesian methods, have been used for detecting differentially expressed genes based on the assumption that biological systems are linear, which ignores the nonlinear characteristics of most biological systems. More importantly, those methods do not simultaneously consider means, variances, and high moments, resulting in relatively high false positive rate. To overcome the limitations, the SWang test is proposed to determine differentially expressed genes according to the equality of distributions between case and control. Our method not only latently incorporates functional relationships among genes to consider nonlinear biological system but also considers the mean, variance, skewness, and kurtosis of expression profiles simultaneously. To illustrate biological significance of high moments, we construct a nonlinear gene interaction model, demonstrating that skewness and kurtosis could contain useful information of function association among genes in microarrays. Simulations and real microarray results show that false positive rate of SWang is lower than currently popular methods (T-test, F-test, SAM, and Fold-change) with much higher statistical power. Additionally, SWang can uniquely detect significant genes in real microarray data with imperceptible differential expression but higher variety in kurtosis and skewness. Those identified genes were confirmed with previous published literature or RT-PCR experiments performed in our lab

PAK1IP1, a ribosomal stress-induced nucleolar protein, regulates cell proliferation via the p53–MDM2 loop

Cell growth and proliferation are tightly controlled via the regulation of the p53–MDM2 feedback loop in response to various cellular stresses. In this study, we identified a nucleolar protein called PAK1IP1 as another regulator of this loop. PAK1IP1 was induced when cells were treated with chemicals that disturb ribosome biogenesis. Overexpression of PAK1IP1 inhibited cell proliferation by inducing p53-dependent G1 cell-cycle arrest. PAK1IP1 bound to MDM2 and inhibited its ability to ubiquitinate and to degrade p53, consequently leading to the accumulation of p53 levels. Interestingly, knockdown of PAK1IP1 in cells also inhibited cell proliferation and induced p53-dependent G1 arrest. Deficiency of PAK1IP1 increased free ribosomal protein L5 and L11 which were required for PAK1IP1 depletion-induced p53 activation. Taken together, our results reveal that PAK1IP1 is a new nucleolar protein that is crucial for rRNA processing and plays a regulatory role in cell proliferation via the p53–MDM2 loop

Dendritic cell vaccines in breast cancer: Immune modulation and immunotherapy

Breast cancer (BC) is the most common cancer in women worldwide. Although substantial progress has been made in the diagnosis and treatment of breast cancer, the efficacy and side effects of traditional treatment methods are still unsatisfactory. In recent years, immunotherapy including tumor vaccine has achieved great success in the treatment of BC. Dendritic cells (DCs) are multifunctional antigen-presenting cells that play an important role in the initiation and regulation of innate and adaptive immune responses. Numerous studies have shown that DC-based treatments might have a potential effect on BC. Among them, the clinical study of DC vaccine in BC has demonstrated considerable anti-tumor effect, and some DC vaccines have entered the stage of clinical trials. In this review, we summarize the immunomodulatory effects and related mechanisms of DC vaccine in breast cancer as well as the progress of clinical trials to propose possible challenges of DC vaccines and new development directions

MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data

MotivationSingle nucleotide variant (SNV) detection procedures are being utilized as never before to analyze the recent abundance of high-throughput DNA sequencing data, both on single and multiple sample datasets. Building on previously published work with the single sample SNV caller genotype model selection (GeMS), a multiple sample version of GeMS (MultiGeMS) is introduced. Unlike other popular multiple sample SNV callers, the MultiGeMS statistical model accounts for enzymatic substitution sequencing errors. It also addresses the multiple testing problem endemic to multiple sample SNV calling and utilizes high performance computing (HPC) techniques.ResultsA simulation study demonstrates that MultiGeMS ranks highest in precision among a selection of popular multiple sample SNV callers, while showing exceptional recall in calling common SNVs. Further, both simulation studies and real data analyses indicate that MultiGeMS is robust to low-quality data. We also demonstrate that accounting for enzymatic substitution sequencing errors not only improves SNV call precision at low mapping quality regions, but also improves recall at reference allele-dominated sites with high mapping quality.Availability and implementationThe MultiGeMS package can be downloaded from https://github.com/cui-lab/[email protected] informationSupplementary data are available at Bioinformatics online

Kisspeptin Receptor GPR54 Promotes Adipocyte Differentiation and Fat Accumulation in Mice

GPR54, Kisspeptin-1 receptor (KISS1R), a member of rhodopsin family, plays a critical role in puberty development and has been proposed to be involved in regulation of energy metabolism. This study aims to explore the function of GPR54 in adipogenesis, lipid metabolism, and obesity in addition to its effect through hormones. Results showed that when fed a high-fat diet, the weight growth of castrated or ovariectomized Gpr54−/− mice was significantly slower than that of WT control, together with a lower triglyceride concentration. The ratio of white adipose tissue was lower, and average size of adipocytes was smaller in Gpr54−/− mice. Meanwhile, there were less adipose tissue macrophages (ATMs), especially pro-inflammatory macrophages. Expression of inflammatory related genes also indicated that inflammatory response caused by obesity was not as drastic in Gpr54−/− mice as in WT mice. Liver triglyceride in Gpr54−/− mice was reduced, especially in female mice. On the other hand, oil drop formation was accelerated when hepatocytes were stimulated by kisspeptin-10 (Kp-10). Primary mesenchymal stem cells (MSCs) of Gpr54−/− mice were less likely to differentiate into adipocytes. When stimulated by Kp-10, 3T3-L1 cell differentiation into adipocytes was accelerated and triglyceride synthesis was significantly promoted. These data indicated that GPR54 could affect obesity development by promoting adipocyte differentiation and triglyceride accumulation. To further elucidate the mechanism, genes related to lipid metabolism were analyzed. The expression of genes involved in lipid synthesis including PPARγ, ACC1, ADIPO, and FAS was significantly changed in Gpr54−/− mice. Among them PPARγ which also participate in adipocyte differentiation displayed a marked reduction. Moreover, phosphorylation of ERK, which involved in GPR54 signaling, was significantly decreased in Gpr54−/− mice, suggesting that GPR54 may promote lipid synthesis and obesity development by activating MAP kinase pathway. Therefore, in addition to the involvement in hormone regulation, our study demonstrated that GPR54 directly participates in obesity development by promoting adipocyte differentiation and fat accumulation. This provided evidence of involvement of GPR54 in lipid metabolism, and revealed new potentials for the identification and development of novel drug targets for metabolic diseases

Study on the Mechanical and Toughness Behavior of Epoxy Nano-Composites with Zero-Dimensional and Two-Dimensional Nano-Fillers

The mechanical properties of epoxy resin can be enhanced by adding nanofillers into its matrix. This study researches and compares the impacts of adding nanofillers with different dimensions, including two-dimensional boron nitride and zero-dimensional silica, on the mechanical and toughness properties of epoxy resin. At low fractions (0–2.0 wt%), 2DBN/epoxy composites have a higher Young’s modulus, fracture toughness and critical strain energy release rate compared to SiO2/epoxy composites. However, the workability deteriorated drastically for BN/epoxy composites above a specific nanofiller concentration (2.0–3.0 wt%). BN prevents crack growth by drawing and bridging. SiO2 enhances performance by deflecting the crack direction and forming voids. Additionally, the dimension and content of nanofiller also influence glass transition temperature and storage modulus significantly