A Note On the Rank of the Optimal Matrix in Symmetric Toeplitz Matrix Completion Problem

We consider the symmetric Toeplitz matrix completion problem, whose matrix under consideration possesses specific row and column structures. This problem, which has wide application in diverse areas, is well-known to be computationally NP-hard. This note provides an upper bound on the objective of minimizing the rank of the symmetric Toeplitz matrix in the completion problem based on the theorems from the trigonometric moment problem and semi-infinite problem. We prove that this upper bound is less than twice the number of linear constraints of the Toeplitz matrix completion problem. Compared with previous work in the literature, ours is one of the first efforts to investigate the bound of the objective value of the Toeplitz matrix completion problem

A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application

Graph clustering, which aims to divide the nodes in the graph into several distinct clusters, is a fundamental and challenging task. In recent years, deep graph clustering methods have been increasingly proposed and achieved promising performance. However, the corresponding survey paper is scarce and it is imminent to make a summary in this field. From this motivation, this paper makes the first comprehensive survey of deep graph clustering. Firstly, the detailed definition of deep graph clustering and the important baseline methods are introduced. Besides, the taxonomy of deep graph clustering methods is proposed based on four different criteria including graph type, network architecture, learning paradigm, and clustering method. In addition, through the careful analysis of the existing works, the challenges and opportunities from five perspectives are summarized. At last, the applications of deep graph clustering in four domains are presented. It is worth mentioning that a collection of state-of-the-art deep graph clustering methods including papers, codes, and datasets is available on GitHub. We hope this work will serve as a quick guide and help researchers to overcome challenges in this vibrant field.Comment: 13 pages, 13 figure

Study on Fabrication and Stability of Starch-Lycium barbarum Complex

In this investigation, the starch-Lycium barbarum complex (CS-LB) was fabricated using corn starch (CS) and Lycium barbarum (LB) through a high-speed shear method. The stability of the guest molecules was also explored. The influence of shear time, rotational speed, and LB to CS mass ratio on Lycium barbarum pigment (LP) content and its stability were investigated. The CS-LB was characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), infrared spectroscopy (FT-IR), and thermogravimetric analysis (TGA). It was found that the content of LP in the product was 0.99±0.03 mg per gram when the shear time was 1.5 hours, the rotational speed was 12000 r/min, and the mass ratio of LB to CS was 3:1. The SEM results illustrated that the products had an agglomerated morphology. The XRD results showed that the crystal domain of starch particles was destroyed and transformed into amorphous structures due to the high-speed shear treatment, but the CS-LP crystalline structure changed into a V-type, which was promoted by the interaction between CS and active components of LB. The FT-IR results showed that the absorption peak at 3421 cm−1 shifted, indicating that CS and LB were bound through hydrogen bonds. The TGA results showed that the thermal stability of the product was also enhanced, with a mass retention rate of 36% at 600 ℃ for the composite. Thus, the CS-LB could be effectively fabricated by high-speed shear treatment. Additionally, it was found that the composite could effectively reduce the effects of temperature, oxygen, and light on the stability of guest molecules in stability experiments. The shelf-life of guest molecules was also extended, enabling them to perform their related functions better

Epigenetic modifications in KDM lysine demethylases associate with survival of early-stage NSCLC

BACKGROUND: KDM lysine demethylase family members are related to lung cancer clinical outcomes and are potential biomarkers for chemotherapeutics. However, little is known about epigenetic alterations in KDM genes and their roles in lung cancer survival. METHODS: Tumor tissue samples of 1230 early-stage non-small cell lung cancer (NSCLC) patients were collected from the five independent cohorts. The 393 methylation sites in KDM genes were extracted from epigenome-wide datasets and analyzed by weighted random forest (Ranger) in discovery phase and validation dataset, respectively. The variable importance scores (VIS) for the sites in top 5% of both discovery and validation sets were carried forward for Cox regression to further evaluate the association with patient's overall survival. TCGA transcriptomic data were used to evaluate the correlation with the corresponding DNA methylation. RESULTS: DNA methylation at sites cg11637544 in KDM2A and cg26662347 in KDM1A were in the top 5% of VIS in both discovery phase and validation for squamous cell carcinomas (SCC), which were also significantly associated with SCC survival (HRcg11637544 = 1.32, 95%CI, 1.16-1.50, P = 1.1 × 10-4; HRcg26662347 = 1.88, 95%CI, 1.37-2.60, P = 3.7 × 10-3), and correlated with corresponding gene expression (cg11637544 for KDM2A, P = 1.3 × 10-10; cg26662347 for KDM1A P = 1.5 × 10-5). In addition, by using flexible criteria for Ranger analysis followed by survival classification tree analysis, we identified four clusters for adenocarcinomas and five clusters for squamous cell carcinomas which showed a considerable difference of clinical outcomes with statistical significance. CONCLUSIONS: These findings highlight the association between somatic DNA methylation in KDM genes and early-stage NSCLC patient survival, which may reveal potential epigenetic therapeutic targets

COVID-19 vaccination willingness among people living with HIV in Shijiazhuang, China: a cross-sectional survey

ObjectivesThe COVID-19 pandemic imposed an enormous disease and economic burden worldwide. SARS-CoV-2 vaccination is essential to containing the pandemic. People living with HIV (PLWH) may be more vulnerable to severe COVID-19 outcomes; thus, understanding their vaccination willingness and influencing factors is helpful in developing targeted vaccination strategies.MethodsA cross-sectional study was conducted between 15 June and 30 August 2022 in Shijiazhuang, China. Variables included socio-demographic characteristics, health status characteristics, HIV-related characteristics, knowledge, and attitudes toward COVID-19 vaccination and COVID-19 vaccination status. Multivariable logistic regression was used to confirm factors associated with COVID-19 vaccination willingness among PLWH.ResultsA total of 1,428 PLWH were included, with a 90.48% willingness to receive the COVID-19 vaccination. PLWH were more unwilling to receive COVID-19 vaccination for those who were female or had a fair/poor health status, had an allergic history and comorbidities, were unconvinced and unsure about the effectiveness of vaccines, were unconvinced and unsure about the safety of vaccines, were convinced and unsure about whether COVID-19 vaccination would affect ART efficacy, or did not know at least a type of domestic COVID-19 vaccine. Approximately 93.00% of PLWH have received at least one dose of the COVID-19 vaccine among PLWH, and 213 PLWH (14.92%) reported at least one adverse reaction within 7 days.ConclusionIn conclusion, our study reported a relatively high willingness to receive the COVID-19 vaccination among PLWH in Shijiazhuang. However, a small number of PLWH still held hesitancy; thus, more tailored policies or guidelines from the government should be performed to enhance the COVID-19 vaccination rate among PLWH

Population Differences in Transcript-Regulator Expression Quantitative Trait Loci

Gene expression quantitative trait loci (eQTL) are useful for identifying single nucleotide polymorphisms (SNPs) associated with diseases. At times, a genetic variant may be associated with a master regulator involved in the manifestation of a disease. The downstream target genes of the master regulator are typically co-expressed and share biological function. Therefore, it is practical to screen for eQTLs by identifying SNPs associated with the targets of a transcript-regulator (TR). We used a multivariate regression with the gene expression of known targets of TRs and SNPs to identify TReQTLs in European (CEU) and African (YRI) HapMap populations. A nominal p-value of <1×10−6 revealed 234 SNPs in CEU and 154 in YRI as TReQTLs. These represent 36 independent (tag) SNPs in CEU and 39 in YRI affecting the downstream targets of 25 and 36 TRs respectively. At a false discovery rate (FDR) = 45%, one cis-acting tag SNP (within 1 kb of a gene) in each population was identified as a TReQTL. In CEU, the SNP (rs16858621) in Pcnxl2 was found to be associated with the genes regulated by CREM whereas in YRI, the SNP (rs16909324) was linked to the targets of miRNA hsa-miR-125a. To infer the pathways that regulate expression, we ranked TReQTLs by connectivity within the structure of biological process subtrees. One TReQTL SNP (rs3790904) in CEU maps to Lphn2 and is associated (nominal p-value = 8.1×10−7) with the targets of the X-linked breast cancer suppressor Foxp3. The structure of the biological process subtree and a gene interaction network of the TReQTL revealed that tumor necrosis factor, NF-kappaB and variants in G-protein coupled receptors signaling may play a central role as communicators in Foxp3 functional regulation. The potential pleiotropic effect of the Foxp3 TReQTLs was gleaned from integrating mRNA-Seq data and SNP-set enrichment into the analysis

Type 2 Diabetes Modifies the association of Cad Genomic Risk Variants With Subclinical atherosclerosis

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS: Using a Bonferroni-corrected significance threshold of CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC

Powerful, Scalable and Resource-Efficient Meta-Analysis of Rare Variant Associations in Large Whole Genome Sequencing Studies

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples

A Framework For Detecting Noncoding Rare-Variant associations of Large-Scale Whole-Genome Sequencing Studies

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 toPMed samples. We also analyze five non-lipid toPMed traits