Learning Unified Anchor Graph for Joint Clustering of Hyperspectral and LiDAR Data.

The joint clustering of multimodal remote sensing (RS) data poses a critical and challenging task in Earth observation. Although recent advances in multiview subspace clustering have shown remarkable success, existing methods become computationally prohibitive when dealing with large-scale RS datasets. Moreover, they neglect intrinsic nonlinear and spatial interdependencies among heterogeneous RS data and lack generalization ability for out-of-sample data, thereby restricting their applicability. This article introduces a novel unified framework called anchor-based multiview kernel subspace clustering with spatial regularization (AMKSC). It learns a scalable anchor graph in the kernel space, leveraging contributions from each modality instead of seeking a consensus full graph in the feature space. To ensure spatial consistency, we incorporate a spatial smoothing operation into the formulation. The method is efficiently solved using an alternating optimization strategy, and we provide theoretical evidence of its scalability with linear computational complexity. Furthermore, an out-of-sample extension of AMKSC based on multiview collaborative representation-based classification is introduced, enabling the handling of larger datasets and unseen instances. Extensive experiments on three real heterogeneous RS datasets confirm the superiority of our proposed approach over state-of-the-art methods in terms of clustering performance and time efficiency. The source code is available at https://github.com/AngryCai/AMKSC.

A pyroptosis-related lncRNA-based prognostic index for hepatocellular carcinoma by relative expression orderings.

Background: Hepatocellular carcinoma (HCC) is an invasive malignant tumor, and pyroptosis makes an important contribution to the pathology and progression of liver cancer. Many prognostic models have been proposed for HCC based on the quantitative expression level of candidate genes, which are unsuitable for clinical application due to their vulnerability against experimental batch effects. The aim of this study was to develop a novel pyroptosis-related long non-coding RNA (lncRNA)-based prognostic index (PLPI) for HCC based on relative expression orderings (REOs). Methods: Firstly, the pyroptosis-related lncRNAs were identified through the Wilcoxon rank-sum test and gene co-expression analyses. Then, the novel prognostic model PLPI was constructed by pyroptosis-related lncRNA pairs, which were identified by multiple machine learning algorithms. Gene set enrichment, somatic mutation, and drug sensitivity analyses were conducted to measure the differences between high- and low-risk patients. Multiple immune analyses were used to explore the association between PLPI and the immunological microenvironment. Results: In this study, a novel prognostic model PLPI based on 10 pyroptosis-related lncRNA pairs was constructed, which was proven to be an independent prognostic risk factor. The receiver operating characteristic (ROC) curves showed that the model had a good prognostic ability in the training, testing, and external set, respectively [5-year area under the curve (AUC) =0.73, 5-year AUC =0.81, 4-year AUC =0.79]. The results of survival, somatic mutation, and immune analyses showed that the patients in the low-risk group had a better prognosis, lower rates of somatic mutation, and better immune cell infiltration. Personalized chemotherapeutic drugs were also identified for the patients with HCC. Conclusions: The novel PLPI not only greatly predicted the prognosis of patients with HCC but could also offer novel ideas and approaches for the therapeutic management of HCC.

LncRNA EBLN3P Accelerates Cell Proliferation and Invasion of Colon Cancer through Modulating the miR-519d-3p/ZFP91 Axis.

Purpose: The study aims to explore the roles and underlying mechanisms of long noncoding RNAs endogenous bornavirus-like nucleoprotein (lncRNA EBLN3P) in colon cancer, emphasizing the potential impact of these insights on advancing colon cancer treatment strategies. By shedding light on lncRNA EBLN3P's involvement, this research could contribute to the development of novel therapeutic approaches, enhancing the efficacy of interventions for colon cancer patients. Methods: We employed quantitative reverse transcription polymerase chain reaction to assess the levels of lncRNA EBLN3P, zinc finger protein (ZFP91), and miR-519d-3p, alongside CCK-8 and EdU assays for cell proliferation, flow cytometry for apoptosis, and Transwell and wound healing assays for migration and invasion. The in vivo function of lncRNA EBLN3P was investigated through a xenograft model, and protein levels were evaluated via Western blot analysis. Results: LncRNA EBLN3P was found to be upregulated in colon cancer tissues and cells, promoting cell proliferation and metastasis while inhibiting apoptosis. Downregulation of lncRNA EBLN3P reduced tumor size, volume, and weight in a mouse model. MiR-519d-3p, which negatively interacts with lncRNA EBLN3P, was found to be downregulated in colon cancer tissues and cell lines. Its upregulation hindered cancer cell proliferation and metastasis while enhancing apoptosis. ZFP91, a binding partner of miR-519d-3p, was upregulated in colon cancer and inversely related to miR-519d-3p levels. Rescue experiments indicated that the effects of lncRNA EBLN3P silencing could be reversed by miR-519d-3p suppression, but were mitigated by ZFP91 downregulation. Conclusion: LncRNA EBLN3P facilitates colon cancer progression via the miR-519d-3p/ZFP91 axis, presenting a novel understanding of lncRNA EBLN3P's role and offering potential therapeutic insights for colon cancer treatment. This study fills a critical gap by linking lncRNA EBLN3P with the miR-519d-3p/ZFP91 axis in the context of colon cancer, thereby broadening our understanding of the molecular mechanisms underlying colon cancer progression.

UPLC-Q-TOF/MS-Based Serum Metabolomics Reveals Potential Anti-tumor Mechanism of Banxia Xiexin Decoction in Colorectal Cancer Mice.

OBJECTIVE: To clarify the potential mechanism of Banxia Xiexin Decoction (BXD) on colorectal cancer (CRC) from the perspective of metabolomics. METHODS: Forty male C57BL/6 mice were randomly divided into normal control (NC), azoxymethane/dextran sulfate sodium (AOM/DSS) model, low-dose BXD (L-BXD), high-dose BXD (H-BXD) and mesalamine (MS) groups according to a random number table, 8 mice in each group. Colorectal cancer model was induced by AOM/DSS. BXD was administered daily at doses of 3.915 (L-BXD) and 15.66 g/kg (H-BXD) by gavage for consecutive 21 days, and 100 mg/kg MS was used as positive control. Following the entire modeling cycle, colon length of mice was measured and quantity of colorectal tumors were counted. The spleen and thymus index were determined by calculating the spleen/thymus weight to body weight. Inflammatory cytokine and changes of serum metabolites were analyzed by enzyme-linked immunosorbent assay kits and ultra performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-Q/TOF-MS), respectively. RESULTS: Notably, BXD supplementation protected against weight loss, mitigated tumor formation, and diminished histologic damage in mice treated with AOM/DSS (P<0.05 or P<0.01). Moreover, BXD suppressed expression of serum inflammatory enzymes, and improved the spleen and thymus index (P<0.05). Compared with the normal group, 102 kinds of differential metabolites were screened in the AOM/DSS group, including 48 potential biomarkers, involving 18 main metabolic pathways. Totally 18 potential biomarkers related to CRC were identified, and the anti-CRC mechanism of BXD was closely related to D-glutamine and D-glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, nitrogen metabolism and so on. CONCLUSION: BXD exerts partial protective effects on AOM/DSS-induced CRC by reducing inflammation, protecting organism immunity ability, and regulating amino acid metabolism.

A prognostic model based on tumor microenvironment-related lncRNAs predicts therapy response in pancreatic cancer.

Pancreatic cancer is an aggressive malignant tumor with high mortality and a low survival rate. The immune and stromal cells that infiltrate in the tumor microenvironment (TME) significantly impact immunotherapy and drug responses. Therefore, we identify the TME-related lncRNAs to develop a prognostic model for predicting the therapy efficacy in pancreatic cancer patients. Firstly, we identified differentially expressed genes (DEGs) for weighted gene co-expression network analysis (WGCNA) to identify the TME-related module eigengenes. According to the module eigengenes, the TME-related prognostic lncRNAs were screened through the univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses to construct a prognostic risk score (RS) model. Next, the predictive power of this model was evaluated by the time-dependent receiver operating characteristic (ROC) curve and Kaplan-Meier analyses. In addition, functional enrichment, immune cell infiltration, and somatic mutation analyses were performed. Finally, tumor immune dysfunction and exclusion (TIDE) score and drug sensitivity analyses were applied to predict therapy response. In this study, 11 TME-related prognostic lncRNAs were identified to develop the prognostic RS model. According to the RS, the low-risk patients had a better prognosis, lower rates of somatic mutation, lower TIDE scores, and higher sensitivity to gemcitabine and paclitaxel compared to high-risk patients. The findings above suggested that low-risk patients may benefit more from immunotherapy, and high-risk patients may benefit more from chemotherapy. Within this study, we established a prognostic RS model based on 11 TME-related lncRNAs, which may help improve clinical decision-making.

Albiflorin alleviates DSS-induced ulcerative colitis in mice by reducing inflammation and oxidative stress.

Objectives: To clarify therapeutic potential of albiflorin and its intrinsic mechanisms against dextran sulfate sodium (DSS)-induced Ulcerative colitis (UC) mice. Materials and Methods: Sixty male C57BL/6 mice were randomly divided into five groups: negative control, positive, albiflorin low-dose group, albiflorin high-dose group and treatment control (Salicylazosulfapyridine "SASP", 100 mg/kg) group. Acute colitis was induced in all groups except NC by administration of 3% DSS for 7 days. Albiflorin and SASP were administered via the intragastric route twice a day for 7 days. The changes of colon tissue were assessed by disease activity index (DAI), HE staining, and ELISA. Adrenodoxin expressions of UC colon tissues were evaluated by immunohistochemistry. Western blotting was performed to investigate related protein of the NF-κB and mitogen-activated protein kinase (MAPK) signaling pathways. Results: It has been found that the albiflorin shares similar influences as the SASP in ameliorating the DSS-induced UC. The reduced DAI and alleviated colon tissue damage were observed in albiflorin intervened groups. Moreover, albiflorin significantly inhibited myeloperoxidase activities and attenuated immuno-inflammatory response and elevated Foxp3 mRNA in colon tissue. Furthermore, investigations revealed that albiflorin could inhibit adrenodoxin isoform and activate activated phosphorylated NF-κB p65 and IκBα, which consequently suppressed phosphorylated p38 MAPK, extracellular regulated protein kinase (ERK), and c-Jun N-terminal kinase (JNK). Conclusion: These findings showed that albiflorin could alleviate DSS-induced murine colitis by activating inhibiting NF-κB and MAPK signaling pathways. It might be a potential therapeutic reagent for UC treatment.

A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer.

Colon cancer (CC) is a common malignant tumor worldwide, and ferroptosis plays a vital role in the pathology and progression of CC. Effective prognostic tools are required to guide clinical decision-making in CC. In our study, gene expression and clinical data of CC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed ferroptosis-related lncRNAs using the differential expression and gene co-expression analysis. Then, univariate and multivariate Cox regression analyses were used to identify the effective ferroptosis-related lncRNAs for constructing the prognostic model for CC. Gene set enrichment analysis (GSEA) was conducted to explore the functional enrichment analysis. CIBERSORT and single-sample GSEA were performed to investigate the association between our model and the immune microenvironment. Finally, three ferroptosis-related lncRNAs (XXbac-B476C20.9, TP73-AS1, and SNHG15) were identified to construct the prognostic model. The results of the validation showed that our model was effective in predicting the prognosis of CC patients, which also was an independent prognostic factor for CC. The GSEA analysis showed that several ferroptosis-related pathways were significantly enriched in the low-risk group. Immune infiltration analysis suggested that the level of immune cell infiltration was significantly higher in the high-risk group than that in the low-risk group. In summary, we established a prognostic model based on the ferroptosis-related lncRNAs, which could provide clinical guidance for future laboratory and clinical research on CC.

Small RNA Sequencing Revealed that miR4415, a Legume-Specific miRNA, was Involved in the Cold Acclimation of Ammopiptanthus nanus by Targeting an L-Ascorbate Oxidase Gene and Regulating the Redox State of Apoplast.

MicroRNAs (miRNAs) are small endogenous single-stranded RNAs that regulate plant growth, development, and environmental stress response posttranscriptionally. Ammopiptanthus nanus, a rare evergreen broad-leaved shrub in the temperate area of Central Asia, can tolerate freezing stress as low as -30 degrees centigrade in winter, and miRNA might be involved in the cold acclimation which enables A. nanus to obtain tolerance to freezing stress. Systematic identification and functional analysis of the miRNAs involved in the cold acclimation in A. nanus may promote understanding of the miRNA-mediated gene regulation network underlying cold acclimation. Here, based on small RNA and degradome sequencing, 256 miRNAs and 1,808 miRNA-target pairs were identified in A. nanus. A total of 39 cold-responsive miRNAs were identified, of which 29 were upregulated and ten were downregulated. These cold-responsive miRNAs may participate in the cold acclimation by regulating redox homeostasis (miR398, miR4415, and miR408), calcium signaling (miR5225 and miR5211), growth and development (miR159 and miR390), and small RNA-mediated gene silencing (miR168 and miR1515). We found that miR4415, a legume-specific miRNA, is involved in the cold acclimation of A. nanus by targeting an L-ascorbate oxidase gene and then regulating the redox state of the apoplast. Our study provides important data for understanding the regulatory role of miRNA in the cold acclimation of A. nanus.

Exploring Long Non-Coding RNAs Associated with IP3/DAG Signaling Pathway as Potential Biomarkers Involved in Mast Cell Degranulation in Chronic Spontaneous Urticaria with 2-Year Follow-Up.

PURPOSE: Chronic spontaneous urticaria (CSU) pathogenesis involves mast cell degranulation induced by the inositol 1,4,5-trisphosphate/diacylglycerol (IP3/DAG) pathway, but the condition lacks specific biomarkers. This study was performed to investigate long non-coding RNA (lncRNA) expression profiles, identify those associated with IP3/DAG pathway, and assess their diagnostic and prognostic value for CSU. METHODS: Ten samples were selected from CSU and control groups, and microarray was performed to screen differentially expressed (DE) lncRNAs and mRNAs. Bioinformatic and co-expression network analyses were used to identify lncRNAs associated with IP3/DAG pathway. Quantitative real-time polymerase chain reaction was used to validate lncRNA expression levels. Combined with disease characteristics and serum indices detected with enzyme-linked immunosorbent assays, Spearman analysis and logistic regression were applied to analyze lncRNA-associated disease risk. Receiver operating characteristic (ROC) curves and 2-year follow-up data were applied to evaluate lncRNA diagnostic and prognostic value. RESULTS: A total of 678 up- and 573 downregulated DE lncRNAs and 609 up- and 176 downregulated DE mRNAs were identified. Seven lncRNAs (upregulated T264761, T280622, ENST00000587970, T224062, ENST00000562459, and his-1_RNA_dna; downregulated ENST00000417930) were associated with the IP3/DAG pathway. D-dimer and histamine levels were significantly different between the two groups. Correlation analysis showed that his-1_RNA_dna positively correlated with the frequency of symptom appearance, while his-1_RNA_dna, ENST00000417930, T264761, and T280622 negatively correlated with the maximum wheal diameter. Regression analysis showed T264761 was associated with CSU risk. ROC analysis showed that the specificity of T264761 was 90%, with an area under the curve of 0.666. In follow-up, the rate of well-controlled disease in the low T264761 expression group was 82.61%. CONCLUSION: This study established lncRNA and mRNA expression profiles in CSU and identified lncRNAs associated with IP3/DAG pathway, which is mechanistically involved in this disease. T264761 may be a novel biomarker for CSU, but further study is needed to confirm its specific mechanism.

Using Vehicle-to-Vehicle Communication to Improve Traffic Safety in Sand-dust Environment.

Sand-dust environment affects drivers' perceptions of surrounding traffic conditions, resulting in unsafe operations. From an ergonomics perspective, such adverse effects could be alleviated by environment control as well as the assistance of machines. Vehicle-to-vehicle (V2V) communication appears to be an important component of machines in future traffic systems, which could support the driving task. In order to explore what influences V2V communication would generate on traffic systems, this paper proposes a car-following model accounting for V2V communication in a sand-dust environment. The results indicate that V2V communication helps to reduce the fluctuations of acceleration, headway, and velocity, when a small perturbation is added to the traffic flow in sand-dust environment. If a vehicle in the traffic flow stops suddenly, the number of crumped vehicles decreases with V2V communication taken into account. Furthermore, the residual velocities of the crumped vehicles decrease, which means the severity of collision is suppressed. It is concluded that V2V communication can play an active role in the improvement of traffic safety in a sand-dust environment.

Effect of Imitation Phenomenon on Two-lane Traffic Safety in Fog Weather.

A neighboring lane's vehicles are potentially important influence factors of traffic safety. In fog weather, drivers will automatically imitate the behaviors demonstrated by other vehicles in the neighboring lane. To illustrate the effect of the imitation phenomenon on traffic safety, this paper develops an extended two-lane car-following model in fog weather. Numerical simulations are carried out to study the effect of imitation on multiple-vehicle collision induced by a sudden stop, as well as perturbation propagation when a small perturbation is added to the uniform traffic flow. The results indicate that the number of collisions depends on the influence coefficient of neighboring lane's vehicles, sensitivity, headway and initial velocity. Furthermore, the number of crumpled vehicles decreases when the imitation phenomenon is taken into account. In addition, lower vehicular velocity in the neighboring lane can reduce the magnitude of acceleration and fluctuation of headway. The perturbation can be absorbed under certain given conditions regarding the imitation phenomenon. Therefore, traffic safety can be improved by considering the effect of the imitation phenomenon on two-lane traffic flow in fog weather. The findings in this study can provide a theoretical reference for the development of multi-lane intermittent release measures in fog weather.

Systematic genetic analyses of genome-wide association study data reveal an association between the key nucleosome remodeling and deacetylase complex and bipolar disorder development.

BACKGROUND: Genome-wide association studies (GWASs) are used to identify genetic variants for association with bipolar disorder (BD) risk; however, each GWAS can only reveal a small fraction of this association. This study systematically analyzed multiple GWAS data sets to provide further insights into potential causal BD processes by integrating the results of Psychiatric Genomics Consortium Phase I (PGC-I) for BD with core human pathways and functional networks. METHODS: The i-Gsea4GwasV2 program was used to analyze data from the PGC-I GWAS for BD (the pathways came from Reactome), as well as the nominally significant pathways. We established a gene network of the significant pathways and performed a gene set analysis for each gene cluster of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) GWAS data for the volumes of the intracranial region and seven subcortical regions. RESULTS: A total of 30 of 1816 Reactome pathways were identified and showed associations with BD risk. We further revealed 22 interconnected functional and topologically interacting clusters (Clusters 0-21) that were associated with BD risk. Moreover, we obtained brain transcriptome data from BrainSpan and found significant associations between common variants of the genes in Cluster 1 with the hippocampus (HIP; P = .026; family-wise error [FWE] correction) and amygdala (AMY; P = .016; FEW correction) in Cluster 8 with HIP (P = .022; FWE correction). The genes in Cluster 1 were enriched for the transcriptional co-expression profile in the prenatal AMY, and core genes (CDH4, MTA2, RBBP4, and HDAC2) were identified to be involved in regulating early brain development. CONCLUSION: This study demonstrated that the HIP and AMY play a central role in neurodevelopment and BD risk.