Cross-modal integration of bulk RNA-seq and single-cell RNA sequencing data to reveal T-cell exhaustion in colorectal cancer.

Colorectal cancer (CRC) is a relatively common malignancy clinically and the second leading cause of cancer-related deaths. Recent studies have identified T-cell exhaustion as playing a crucial role in the pathogenesis of CRC. A long-standing challenge in the clinical management of CRC is to understand how T cells function during its progression and metastasis, and whether potential therapeutic targets for CRC treatment can be predicted through T cells. Here, we propose DeepTEX, a multi-omics deep learning approach that integrates cross-model data to investigate the heterogeneity of T-cell exhaustion in CRC. DeepTEX uses a domain adaptation model to align the data distributions from two different modalities and applies a cross-modal knowledge distillation model to predict the heterogeneity of T-cell exhaustion across diverse patients, identifying key functional pathways and genes. DeepTEX offers valuable insights into the application of deep learning in multi-omics, providing crucial data for exploring the stages of T-cell exhaustion associated with CRC and relevant therapeutic targets.

The stabilization ability of NaA zeolite derived from fly ash for lead and cadmium in soil: Mechanisms and evaluation of effectiveness.

Developing technologies aimed at ecologically restoring is of great significance in addressing the problem of heavy metal pollution. In this study, NaA zeolites (FAZ) originated from fly ash with outstanding performance were prepared by alkali fusion hydrothermal method and used for the solidification and stabilization of heavy metals in soil. After systematic evaluation, it was found that FAZ may lower the leaching concentration of lead (Pb) in soil to <1 mg/kg and increase the stabilization rate of Pb to 80 % in the single Pb-contaminated soil, lower the leaching concentration of cadmium (Cd) in soil to <3 mg/kg and increase the stabilization rate of Cd to 60 % in the single Cd-contaminated soil, and lower the leaching concentration of Pb to 0.15 mg/kg and the leaching concentration of Cd to 0.74 mg/kg in PbCd complex polluted soil. Additionally, Pb stabilization rates reach 60 % and Cd stabilization rates reach 30 %, respectively. Ion exchange is primarily responsible for the adsorption and solidification of Pb and Cd in soil by FAZ. Generally, FAZ has a wide range of applications in the rehabilitation of contaminated soil and significantly lowers the level of heavy metal pollution in soil.

Development and validation of a multi-modality fusion deep learning model for differentiating glioblastoma from solitary brain metastases. / åŒºåˆ†èƒ¶è´¨æ¯ç»†èƒžç˜¤å’Œå•å‘æ€§è„‘è½¬ç§»ç˜¤çš„å¤šæ¨¡æ€èžåˆæ·±åº¦å­¦ä¹ æ¨¡åž‹çš„å¼€å‘å’ŒéªŒè¯.

OBJECTIVES: Glioblastoma (GBM) and brain metastases (BMs) are the two most common malignant brain tumors in adults. Magnetic resonance imaging (MRI) is a commonly used method for screening and evaluating the prognosis of brain tumors, but the specificity and sensitivity of conventional MRI sequences in differential diagnosis of GBM and BMs are limited. In recent years, deep neural network has shown great potential in the realization of diagnostic classification and the establishment of clinical decision support system. This study aims to apply the radiomics features extracted by deep learning techniques to explore the feasibility of accurate preoperative classification for newly diagnosed GBM and solitary brain metastases (SBMs), and to further explore the impact of multimodality data fusion on classification tasks. METHODS: Standard protocol cranial MRI sequence data from 135 newly diagnosed GBM patients and 73 patients with SBMs confirmed by histopathologic or clinical diagnosis were retrospectively analyzed. First, structural T1-weight, T1C-weight, and T2-weight were selected as 3 inputs to the entire model, regions of interest (ROIs) were manually delineated on the registered three modal MR images, and multimodality radiomics features were obtained, dimensions were reduced using a random forest (RF)-based feature selection method, and the importance of each feature was further analyzed. Secondly, we used the method of contrast disentangled to find the shared features and complementary features between different modal features. Finally, the response of each sample to GBM and SBMs was predicted by fusing 2 features from different modalities. RESULTS: The radiomics features using machine learning and the multi-modal fusion method had a good discriminatory ability for GBM and SBMs. Furthermore, compared with single-modal data, the multimodal fusion models using machine learning algorithms such as support vector machine (SVM), Logistic regression, RF, adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) achieved significant improvements, with area under the curve (AUC) values of 0.974, 0.978, 0.943, 0.938, and 0.947, respectively; our comparative disentangled multi-modal MR fusion method performs well, and the results of AUC, accuracy (ACC), sensitivity (SEN) and specificity(SPE) in the test set were 0.985, 0.984, 0.900, and 0.990, respectively. Compared with other multi-modal fusion methods, AUC, ACC, and SEN in this study all achieved the best performance. In the ablation experiment to verify the effects of each module component in this study, AUC, ACC, and SEN increased by 1.6%, 10.9% and 15.0%, respectively after 3 loss functions were used simultaneously. CONCLUSIONS: A deep learning-based contrast disentangled multi-modal MR radiomics feature fusion technique helps to improve GBM and SBMs classification accuracy.

SCInter: A comprehensive single-cell transcriptome integration database for human and mouse.

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.

Landscape and significance of human super enhancer-driven core transcription regulatory circuitry.

A core transcription regulatory circuitry (CRC) is an interconnected self-regulatory circuitry that is formed by a group of core transcription factors (TFs). These core TFs collectively regulate gene expression by binding not only to their own super enhancers (SEs) but also to the SEs of one another. For most human tissue/cell types, a global view of CRCs and core TFs has not been generated. Here, we identified numerous CRCs using two identification methods and detailed the landscape of the CRCs driven by SEs in large cell/tissue samples. The comprehensive biological analyses, including sequence conservation, CRC activity and genome binding affinity were conducted for common TFs, moderate TFs, and specific TFs, which exhibit different biological features. The local module located from the common CRC network highlighted the essential functions and prognostic performance. The tissue-specific CRC network was highly related to cell identity. Core TFs in tissue-specific CRC networks exhibited disease markers, and had regulatory potential for cancer immunotherapy. Moreover, a user-friendly resource named CRCdb (http://www.licpathway.net/crcdb/index.html) was developed, which contained the detailed information of CRCs and core TFs used in this study, as well as other interesting results, such as the most representative CRC, frequency of TFs, and indegree/outdegree of TFs.

Morphology regulation of zero-valent iron nanosheets supported on microsilica for promoting peroxymonosulfate activation.

Combing the assisted dispersion strategy of support with the wet chemical reduction method, a novel nano-zero valent iron/microsilica (nZVI/M) composite was successfully fabricated, where the 2D nZVI nanosheets were uniformly anchored and covered on the surface of microsilica. The introduction of microsilica notably relieved the agglomeration effect of nZVI nanosheets, which induced the improvement of specific surface area (45.68 m2/g) and pore volume (0.172 cm3/g), and thereby exposing more active sites for bisphenol A (BPA) removal. The optimized nZVI/M-0.6 displayed the superior catalytic performance in the presence of peroxymonosulfate (PMS) with the degradation rate of BPA reached above 97% within 3 min and a higher constant rate of 0.659 min-1, which was approximately 3.9 times as high as that of nZVI/PMS system. The homogeneously dispersion of nZVI nanosheets on microsilica benefited for the assembly of the pollutants and boosting the kinetics of the catalytic degradation process. As a highly efficient PMS activator, it could well maintain the catalytic activity in different real water samples. The quenching experiments verified that SO4•- played the dominate role for BPA removal. This work offered novel insights for designing and preparing iron-based persulfate activator for wastewater treatment.

CanMethdb: a database for genome-wide DNA methylation annotation in cancers.

MOTIVATION: DNA methylation within gene body and promoters in cancer cells is well documented. An increasing number of studies showed that cytosine-phosphate-guanine (CpG) sites falling within other regulatory elements could also regulate target gene activation, mainly by affecting transcription factors (TFs) binding in human cancers. This led to the urgent need for comprehensively and effectively collecting distinct cis-regulatory elements and TF-binding sites (TFBS) to annotate DNA methylation regulation. RESULTS: We developed a database (CanMethdb, http://meth.liclab.net/CanMethdb/) that focused on the upstream and downstream annotations for CpG-genes in cancers. This included upstream cis-regulatory elements, especially those involving distal regions to genes, and TFBS annotations for the CpGs and downstream functional annotations for the target genes, computed through integrating abundant DNA methylation and gene expression profiles in diverse cancers. Users could inquire CpG-target gene pairs for a cancer type through inputting a genomic region, a CpG, a gene name, or select hypo/hypermethylated CpG sets. The current version of CanMethdb documented a total of 38 986 060 CpG-target gene pairs (with 6 769 130 unique pairs), involving 385 217 CpGs and 18 044 target genes, abundant cis-regulatory elements and TFs for 33 TCGA cancer types. CanMethdb might help biologists perform in-depth studies of target gene regulations based on DNA methylations in cancer. AVAILABILITY AND IMPLEMENTATION: The main program is available at https://github.com/chunquanlipathway/CanMethdb. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Defect Engineering Modulated Iron Single Atoms with Assist of Layered Clay for Enhanced Advanced Oxidation Processes.

Single-atom catalysts (SACs) feature maximum atomic utilization efficiency; however, the loading amount, dispersibility, synthesis cost, and regulation of the electronic structure are factors that need to be considered in water treatment. In this study, kaolinite, a natural layered clay mineral, is applied as the support for g-C3 N4 and single Fe atoms (FeSA-NGK). The FeSA-NGK composite exhibits an impressive degradation performance toward the target pollutant (>98% degradation rate in 10 min), and catalytic stability across consecutive runs (90% reactivity maintained after three runs in a fluidized-bed catalytic unit) under peroxymonosulfate (PMS)/visible light (Vis) synergetic system. The introduction of kaolinite promotes the loading amount of single Fe atoms (2.57 wt.%), which is a 14.2% increase compared to using a bare catalyst without kaolinite, and improved the concentration of N vacancies, thereby optimizing the regulation of the electronic structure of the single Fe atoms. It is discovered that the single Fe atoms successfully occupied five coordinated N atoms and combined with a neighboring N vacancy. Consequently, this regulated the local electronic structure of single Fe atoms, which drives the electrons of N atoms to accumulate on the Fe centers. This study opens an avenue for the design of clay-based SACs for water purification.

Protrudent electron transfer channels on kaolinite modified iron oxide QDs/N vacancy graphitic carbon nitride driving superior catalytic oxidation.

Optimizing electron transfer channels and sufficiently exposing active sites to trigger an efficient Fenton-like reaction are vital for manipulating catalytic properties of water treatment. Herein, Fe2O3 quantum dots were prepared and integrated with composites of g-C3N4 and kaolinite with nitrogen (N) vacancies (FONGK-10) for bisphenol A (BPA) removal in a peroxymonosulfate (PMS)/visible light (Vis) system. X-ray absorption near-edge structures and extended X-ray absorption fine structures demonstrated interface's combined properties. In particular, the tight interfacial contact and introduction of N vacancies resulted in the formation of effective electron channels, which caused more effective separation of electron-hole pairs and an extended response time of 1.5 × 10-4 s. Furthermore, the introduction of kaolinite reduced the Fe2O3 particle size and accelerated PMS consumption. The k value in FONGK-10/PMS/Vis system was 4.5 times that of the FONGK-10/PMS and 27.5 times that of the FONGK-10/Vis system, and the synergetic system exhibited superior consecutive catalytic performance in a fluidized-bed catalytic unit, degrading ~100% of BPA in 200 min. The exposed electron channels significantly maintained the Fe(III)/Fe(II) stable dynamic cycle, thereby enhancing the activation of PMS and photocatalysis performance.

High-efficient mineralization of formaldehyde by three-dimensional "PIZZA"-like bismuth molybdate-titania/diatomite composite.

The application of TiO2-based photocatalysts in air pollution control has attracted much attention thanks to their advantageous green and sustainable performance. However, how to improve the degradation efficiency under visible light is still challenging. Herein, we report a ternary three-dimensional "PIZZA"-like Bi2MoO6-TiO2/diatomite (BTD) composite with high-efficient mineralization and recycling performance towards gaseous formaldehyde (HCHO) under visible light. The high-efficient adsorption-photocatalysis collaborative system with intimate interface combination is successfully established among Bi2MoO6 (BMO), TiO2 and diatomite. The HCHO mineralization rate constant of BTD-1:2 composite is up to around 4.03 times and 2.18 times higher than those of bare BMO and binary Bi2MoO6-TiO2 composite, respectively. It is indicated that the introduction of diatomite increases active sites and plays the vital role in the improvement of photocatalysis. In addition, the photogenerated holes (h+) and hydroxyl radical (OH) are proved to be the main active species for HCHO mineralization. Furthermore, there is a competitive adsorption relationship between water (H2O) molecules and HCHO molecules, and both H2O molecules and oxygen (O2) molecules participated in the reaction of HCHO mineralization based on in-situ DRIFTs spectra analysis. Our work would give a new perspective on gaseous HCHO purification.

TF-Marker: a comprehensive manually curated database for transcription factors and related markers in specific cell and tissue types in human.

Transcription factors (TFs) play key roles in biological processes and are usually used as cell markers. The emerging importance of TFs and related markers in identifying specific cell types in human diseases increases the need for a comprehensive collection of human TFs and related markers sets. Here, we developed the TF-Marker database (TF-Marker, http://bio.liclab.net/TF-Marker/), aiming to provide cell/tissue-specific TFs and related markers for human. By manually curating thousands of published literature, 5905 entries including information about TFs and related markers were classified into five types according to their functions: (i) TF: TFs which regulate expression of the markers; (ii) T Marker: markers which are regulated by the TF; (iii) I Marker: markers which influence the activity of TFs; (iv) TFMarker: TFs which play roles as markers and (v) TF Pmarker: TFs which play roles as potential markers. The 5905 entries of TF-Marker include 1316 TFs, 1092 T Markers, 473 I Markers, 1600 TFMarkers and 1424 TF Pmarkers, involving 383 cell types and 95 tissue types in human. TF-Marker further provides a user-friendly interface to browse, query and visualize the detailed information about TFs and related markers. We believe TF-Marker will become a valuable resource to understand the regulation patterns of different tissues and cells.

Cancer CRC: A Comprehensive Cancer Core Transcriptional Regulatory Circuit Resource and Analysis Platform.

A core transcriptional regulatory circuit (CRC) is a group of interconnected auto-regulating transcription factors (TFs) that form loops and can be identified by super-enhancers (SEs). Studies have indicated that CRCs play an important role in defining cellular identity and determining cellular fate. Additionally, core TFs in CRCs are regulators of cell-type-specific transcriptional regulation. However, a global view of CRC properties across various cancer types has not been generated. Thus, we integrated paired cancer ATAC-seq and H3K27ac ChIP-seq data for specific cell lines to develop the Cancer CRC (http://bio.liclab.net/Cancer_crc/index.html). This platform documented 94,108 cancer CRCs, including 325 core TFs. The cancer CRC also provided the "SE active core TFs analysis" and "TF enrichment analysis" tools to identify potentially key TFs in cancer. In addition, we performed a comprehensive analysis of core TFs in various cancer types to reveal conserved and cancer-specific TFs.

Large-scale and high-resolution mass spectrometry-based proteomics profiling defines molecular subtypes of esophageal cancer for therapeutic targeting.

Esophageal cancer (EC) is a type of aggressive cancer without clinically relevant molecular subtypes, hindering the development of effective strategies for treatment. To define molecular subtypes of EC, we perform mass spectrometry-based proteomic and phosphoproteomics profiling of EC tumors and adjacent non-tumor tissues, revealing a catalog of proteins and phosphosites that are dysregulated in ECs. The EC cohort is stratified into two molecular subtypes-S1 and S2-based on proteomic analysis, with the S2 subtype characterized by the upregulation of spliceosomal and ribosomal proteins, and being more aggressive. Moreover, we identify a subtype signature composed of ELOA and SCAF4, and construct a subtype diagnostic and prognostic model. Potential drugs are predicted for treating patients of S2 subtype, and three candidate drugs are validated to inhibit EC. Taken together, our proteomic analysis define molecular subtypes of EC, thus providing a potential therapeutic outlook for improving disease outcomes in patients with EC.

Alterations of RNA splicing patterns in esophagus squamous cell carcinoma.

Alternative splicing (AS) is an important biological process for regulating the expression of various isoforms from a single gene and thus to promote proteome diversity. In this study, RNA-seq data from 15 pairs of matched esophageal squamous cell carcinoma (ESCC) and normal tissue samples as well as two cell lines were analyzed. AS events with significant differences were identified between ESCC and matched normal tissues, which were re-annotated to find protein coding genes or non-coding RNAs. A total of 45,439 AS events were found. Of these, 6019 (13.25%) significant differentially AS events were identified. Exon skipping (SE) events occupied the largest proportion of abnormal splicing events. Fifteen differential splicing events with the same trends of ΔΨ values in ESCC tissues, as well in the two cell lines were found. Four pathways and 20 biological processes related to pro-metastasis cell junction and migration were significantly enriched for the differentially spliced genes. The upregulated splicing factor SF3B4, which regulates 92 gene splicing events, could be a potential prognostic factor of ESCC. Differentially spliced genes, including HNRNPC, VCL, ZNF207, KIAA1217, TPM1 and CALD1 are shown with a sashimi plot. These results suggest that cell junction- and migration-related biological processes are influenced by AS abnormalities, and aberrant splicing events can be affected by splicing factor expression changes. The involved splicing factor SF3B4 was found to be a survival-related gene in ESCC and is presumed to regulate AS in multiple cancers. In summary, we identified significant differentially expressed AS events which may be related to the development of ESCC.

MiRNA-Mediated Subpathway Identification and Network Module Analysis to Reveal Prognostic Markers in Human Pancreatic Cancer.

BACKGROUND: Pancreatic cancer (PC) remains one of the most lethal cancers. In contrast to the steady increase in survival for most cancers, the 5-year survival remains low for PC patients. METHODS: We describe a new pipeline that can be used to identify prognostic molecular biomarkers by identifying miRNA-mediated subpathways associated with PC. These modules were then further extracted from a comprehensive miRNA-gene network (CMGN). An exhaustive survival analysis was performed to estimate the prognostic value of these modules. RESULTS: We identified 105 miRNA-mediated subpathways associated with PC. Two subpathways within the MAPK signaling and cell cycle pathways were found to be highly related to PC. Of the miRNA-mRNA modules extracted from CMGN, six modules showed good prognostic performance in both independent validated datasets. CONCLUSIONS: Our study provides novel insight into the mechanisms of PC. We inferred that six miRNA-mRNA modules could serve as potential prognostic molecular biomarkers in PC based on the pipeline we proposed.

TP63, SOX2, and KLF5 Establish a Core Regulatory Circuitry That Controls Epigenetic and Transcription Patterns in Esophageal Squamous Cell Carcinoma Cell Lines.

BACKGROUND & AIMS: We investigated the transcriptome of esophageal squamous cell carcinoma (ESCC) cells, activity of gene regulatory (enhancer and promoter regions), and the effects of blocking epigenetic regulatory proteins. METHODS: We performed chromatin immunoprecipitation sequencing with antibodies against H3K4me1, H3K4me3, and H3K27ac and an assay for transposase-accessible chromatin to map the enhancer regions and accessible chromatin in 8 ESCC cell lines. We used the CRC_Mapper algorithm to identify core regulatory circuitry transcription factors in ESCC cell lines, and determined genome occupancy profiles for 3 of these factors. In ESCC cell lines, expression of transcription factors was knocked down with small hairpin RNAs, promoter and enhancer regions were disrupted by CRISPR/Cas9 genome editing, or bromodomains and extraterminal (BET) family proteins and histone deacetylases (HDACs) were inhibited with ARV-771 and romidepsin, respectively. ESCC cell lines were then analyzed by whole-transcriptome sequencing, immunoprecipitation, immunoblots, immunohistochemistry, and viability assays. Interactions between distal enhancers and promoters were identified and verified with circular chromosome conformation capture sequencing. NOD-SCID mice were given injections of modified ESCC cells, some mice where given injections of HDAC or BET inhibitors, and growth of xenograft tumors was measured. RESULTS: We identified super-enhancer-regulated circuits and transcription factors TP63, SOX2, and KLF5 as core regulatory factors in ESCC cells. Super-enhancer regulation of ALDH3A1 mediated by core regulatory factors was required for ESCC viability. We observed direct interactions between the promoter region of TP63 and functional enhancers, mediated by the core regulatory circuitry transcription factors. Deletion of enhancer regions from ESCC cells decreased expression of the core regulatory circuitry transcription factors and reduced cell viability; these same results were observed with knockdown of each core regulatory circuitry transcription factor. Incubation of ESCC cells with BET and HDAC disrupted the core regulatory circuitry program and the epigenetic modifications observed in these cells; mice given injections of HDAC or BET inhibitors developed smaller xenograft tumors from the ESCC cell lines. Xenograft tumors grew more slowly in mice given the combination of ARV-771 and romidepsin than mice given either agent alone. CONCLUSIONS: In epigenetic and transcriptional analyses of ESCC cell lines, we found the transcription factors TP63, SOX2, and KLF5 to be part of a core regulatory network that determines chromatin accessibility, epigenetic modifications, and gene expression patterns in these cells. A combination of epigenetic inhibitors slowed growth of xenograft tumors derived from ESCC cells in mice.

Characterization of super-enhancer-associated functional lncRNAs acting as ceRNAs in ESCC.

Long noncoding RNAs (lncRNAs) have important regulatory roles in cancer biology. Although some lncRNAs have well-characterized functions, the vast majority of this class of molecules remains functionally uncharacterized. To systematically pinpoint functional lncRNAs, a computational approach was proposed for identification of lncRNA-mediated competing endogenous RNAs (ceRNAs) through combining global and local regulatory direction consistency of expression. Using esophageal squamous cell carcinoma (ESCC) as model, we further identified many known and novel functional lncRNAs acting as ceRNAs (ce-lncRNAs). We found that most of them significantly regulated the expression of cancer-related hallmark genes. These ce-lncRNAs were significantly regulated by enhancers, especially super-enhancers (SEs). Landscape analyses for lncRNAs further identified SE-associated functional ce-lncRNAs in ESCC, such as HOTAIR, XIST, SNHG5, and LINC00094. THZ1, a specific CDK7 inhibitor, can result in global transcriptional downregulation of SE-associated ce-lncRNAs. We further demonstrate that a SE-associated ce-lncRNA, LINC00094 can be activated by transcription factors TCF3 and KLF5 through binding to SE regions and promoted ESCC cancer cell growth. THZ1 downregulated expression of LINC00094 through inhibiting TCF3 and KLF5. Our data demonstrated the important roles of SE-associated ce-lncRNAs in ESCC oncogenesis and might serve as targets for ESCC diagnosis and therapy.

Macrophage-Enriched lncRNA RAPIA: A Novel Therapeutic Target for Atherosclerosis.

OBJECTIVE: Despite the current antiatherosclerotic and antithrombotic therapies, the incidence of advanced atherosclerosis-associated clinical events remains high. Whether long noncoding RNAs (lncRNAs) affect the progression of atherosclerosis and whether they are potential targets for the treatment of advanced atherosclerosis are poorly understood. Approach and Results: The progression of atherosclerotic lesions was accompanied by dynamic alterations in lncRNA expression, as revealed by RNA sequencing and quantitative polymerase chain reaction. Among the dynamically changing lncRNAs, we identified a novel lncRNA, lncRNA Associated with the Progression and Intervention of Atherosclerosis (RAPIA), that was highly expressed in advanced atherosclerotic lesions and in macrophages. Inhibition of RAPIA in vivo not only repressed the progression of atherosclerosis but also exerted atheroprotective effects similar to those of atorvastatin on advanced atherosclerotic plaques that had already formed. In vitro assays demonstrated that RAPIA promoted proliferation and reduced apoptosis of macrophages. A molecular sponge interaction between RAPIA and microRNA-183-5p was demonstrated by dual-luciferase reporter and RNA immunoprecipitation assays. Rescue assays indicated that RAPIA functioned at least in part by targeting the microRNA-183-5p/ITGB1 (integrin ß1) pathway in macrophages. In addition, the transcription factor FoxO1 (forkhead box O1) could bind to the RAPIA promoter region and facilitate the expression of RAPIA. CONCLUSIONS: The progression of atherosclerotic lesions was accompanied by dynamic changes in the expression of lncRNAs. Inhibition of the pivotal lncRNA RAPIA may be a novel preventive and therapeutic strategy for advanced atherosclerosis, especially in patients resistant or intolerant to statins.

Multidimensional assembly of oxygen vacancy-rich amorphous TiO2-BiOBr-sepiolite composite for rapid elimination of formaldehyde and oxytetracycline under visible light.

Herein, a novel oxygen vacancy-rich amorphous TiO2-BiOBr-sepiolite composite was synthesized through a facile one-pot solvothermal method. Under visible light, it exhibited enhanced adsorption and photocatalytic removal activity towards gaseous formaldehyde, whose reaction rate constant is nearly 11.75, 3.44, 1.69, 2.18 and 6.27 times higher than those of amorphous TiO2, BiOBr, TiO2-BiOBr, oxygen vacancy-poor composite and P25, respectively. Moreover, it also displayed significantly improved photodegradation performance towards oxytetracycline under visible light. The improved photocatalytic activity is mainly ascribed to the synergy between the ternary heterogeneous structure and introduced oxygen vacancy, leading to the superior adsorption performance, extended visible-light adsorption scope and faster carriers' separation rate. The photogenerated holes are the dominant active species during the reaction process. Additionally, a plausible photocatalytic degradation pathway for oxytetracycline was also proposed. In general, this work provides a viable strategy of visible-light-driven photocatalyst for practical environmental remediation of indoor volatile organic compounds (VOCs) and pharmaceuticals and personal care products (PPCPs).

Identification of lncRNA-associated differential subnetworks in oesophageal squamous cell carcinoma by differential co-expression analysis.

Differential expression analysis has led to the identification of important biomarkers in oesophageal squamous cell carcinoma (ESCC). Despite enormous contributions, it has not harnessed the full potential of gene expression data, such as interactions among genes. Differential co-expression analysis has emerged as an effective tool that complements differential expression analysis to provide better insight of dysregulated mechanisms and indicate key driver genes. Here, we analysed the differential co-expression of lncRNAs and protein-coding genes (PCGs) between normal oesophageal tissue and ESCC tissues, and constructed a lncRNA-PCG differential co-expression network (DCN). DCN was characterized as a scale-free, small-world network with modular organization. Focusing on lncRNAs, a total of 107 differential lncRNA-PCG subnetworks were identified from the DCN by integrating both differential expression and differential co-expression. These differential subnetworks provide a valuable source for revealing lncRNA functions and the associated dysfunctional regulatory networks in ESCC. Their consistent discrimination suggests that they may have important roles in ESCC and could serve as robust subnetwork biomarkers. In addition, two tumour suppressor genes (AL121899.1 and ELMO2), identified in the core modules, were validated by functional experiments. The proposed method can be easily used to investigate differential subnetworks of other molecules in other cancers.