Functional Genomics Profiling of Bladder Urothelial Carcinoma MicroRNAome as a Potential Biomarker.

Though bladder urothelial carcinoma is the most common form of bladder cancer, advances in its diagnosis and treatment have been modest in the past few decades. To evaluate miRNAs as putative disease markers for bladder urothelial carcinoma, this study develops a process to identify dysregulated miRNAs in cancer patients and potentially stratify patients based on the association of their microRNAome phenotype to genomic alterations. Using RNA sequencing data for 409 patients from the Cancer Genome Atlas, we examined miRNA differential expression between cancer and normal tissues and associated differentially expressed miRNAs with patient survival and clinical variables. We then correlated miRNA expressions with genomic alterations using the Wilcoxon test and REVEALER. We found a panel of six miRNAs dysregulated in bladder cancer and exhibited correlations to patient survival. We also performed differential expression analysis and clinical variable correlations to identify miRNAs associated with tobacco smoking, the most important risk factor for bladder cancer. Two miRNAs, miR-323a and miR-431, were differentially expressed in smoking patients compared to nonsmoking patients and were associated with primary tumor size. Functional studies of these miRNAs and the genomic features we identified for potential stratification may reveal underlying mechanisms of bladder cancer carcinogenesis and further diagnosis and treatment methods for urothelial bladder carcinoma

Papillary Thyroid Carcinoma Variants are Characterized by Co-dysregulation of Immune and Cancer Associated Genes.

Papillary thyroid carcinoma (PTC) variants exhibit different prognosis, but critical characteristics of PTC variants that contribute to differences in pathogenesis are not well-known. This study aims to characterize dysregulated immune-associated and cancer-associated genes in three PTC subtypes to explore how the interplay between cancer and immune processes causes differential prognosis. RNA-sequencing data from The Cancer Genome Atlas (TCGA) were used to identify dysregulated genes in each variant. The dysregulation profiles of the subtypes were compared using functional pathways clustering and correlations to relevant clinical variables, genomic alterations, and microRNA regulation. We discovered that the dysregulation profiles of classical PTC (CPTC) and the tall cell variant (TCPTC) are similar and are distinct from that of the follicular variant (FVPTC). However, unique cancer or immune-associated genes are associated with clinical variables for each subtype. Cancer-related genes MUC1, FN1, and S100-family members were the most clinically relevant in CPTC, while APLN and IL16, both immune-related, were clinically relevant in FVPTC. RAET-family members, also immune-related, were clinically relevant in TCPTC. Collectively, our data suggest that dysregulation of both cancer and immune associated genes defines the gene expression landscapes of PTC variants, but different cancer or immune related genes may drive the phenotype of each variant

The Landscape of Long Non-Coding RNA Dysregulation and Clinical Relevance in Muscle Invasive Bladder Urothelial Carcinoma.

Bladder cancer is one of the most common cancers in the United States, but few advancements in treatment options have occurred in the past few decades. This study aims to identify the most clinically relevant long non-coding RNAs (lncRNAs) to serve as potential biomarkers and treatment targets for muscle invasive bladder cancer (MIBC). Using RNA-sequencing data from 406 patients in The Cancer Genome Atlas (TCGA) database, we identified differentially expressed lncRNAs in MIBC vs. normal tissues. We then associated lncRNA expression with patient survival, clinical variables, oncogenic signatures, cancer- and immune-associated pathways, and genomic alterations. We identified a panel of 20 key lncRNAs that were most implicated in MIBC prognosis after differential expression analysis and prognostic correlations. Almost all lncRNAs we identified are correlated significantly with oncogenic processes. In conclusion, we discovered previously undescribed lncRNAs strongly implicated in the MIBC disease course that may be leveraged for diagnostic and treatment purposes in the future. Functional analysis of these lncRNAs may also reveal distinct mechanisms of bladder cancer carcinogenesis

Atrial cardiomyopathy: from cell to bedside

Atrial cardiomyopathy refers to structural and electrical remodelling of the atria, which can lead to impaired mechanical function. While historical studies have implicated atrial fibrillation as the leading cause of cardioembolic stroke, atrial cardiomyopathy may be an important, underestimated contributor. To date, the relationship between atrial cardiomyopathy, atrial fibrillation, and cardioembolic stroke remains obscure. This review summarizes the pathogenesis of atrial cardiomyopathy, with a special focus on neurohormonal and inflammatory mechanisms, as well as the role of adipose tissue, especially epicardial fat in atrial remodelling. It reviews the current evidence implicating atrial cardiomyopathy as a cause of embolic stroke, with atrial fibrillation as a lagging marker of an increased thrombogenic atrial substrate. Finally, it discusses the potential of antithrombotic therapy in embolic stroke with undetermined source and appraises the available diagnostic techniques for atrial cardiomyopathy, including imaging techniques such as echocardiography, computed tomography, and magnetic resonance imaging as well as electroanatomic mapping, electrocardiogram, biomarkers, and genetic testing. More prospective studies are needed to define the relationship between atrial cardiomyopathy, atrial fibrillation, and embolic stroke and to establish a prompt diagnosis and specific treatment strategies in these patients with atrial cardiomyopathy for the secondary and even primary prevention of embolic stroke

Functional Form and Spatial Dependence in Dynamic Panels

Wharton-SMU Research Centr

Self-supervised learning-based general laboratory progress pretrained model for cardiovascular event detection

The inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained due to their limited patient size and episodic observations. This study employed self-supervised learning (SSL) to pretrain a generalized laboratory progress (GLP) model that captures the overall progression of six common laboratory markers in prevalent cardiovascular cases, with the intention of transferring this knowledge to aid in the detection of specific cardiovascular event. GLP implemented a two-stage training approach, leveraging the information embedded within interpolated data and amplify the performance of SSL. After GLP pretraining, it is transferred for TVR detection. The proposed two-stage training improved the performance of pure SSL, and the transferability of GLP exhibited distinctiveness. After GLP processing, the classification exhibited a notable enhancement, with averaged accuracy rising from 0.63 to 0.90. All evaluated metrics demonstrated substantial superiority (p < 0.01) compared to prior GLP processing. Our study effectively engages in translational engineering by transferring patient progression of cardiovascular laboratory parameters from one patient group to another, transcending the limitations of data availability. The transferability of disease progression optimized the strategies of examinations and treatments, and improves patient prognosis while using commonly available laboratory parameters. The potential for expanding this approach to encompass other diseases holds great promise.Comment: published in IEEE Journal of Translational Engineering in Health & Medicin

Intrinsic Correlation between Hardness and Elasticity in Polycrystalline Materials and Bulk Metallic Glasses

Though extensively studied, hardness, defined as the resistance of a material to deformation, still remains a challenging issue for a formal theoretical description due to its inherent mechanical complexity. The widely applied Teter's empirical correlation between hardness and shear modulus has been considered to be not always valid for a large variety of materials. Here, inspired by the classical work on Pugh's modulus ratio, we develop a theoretical model which establishes a robust correlation between hardness and elasticity for a wide class of materials, including bulk metallic glasses, with results in very good agreement with experiment. The simplified form of our model also provides an unambiguous theoretical evidence for Teter's empirical correlation.Comment: 10 pages, 4 figures and 3 table

Towards General-Purpose Text-Instruction-Guided Voice Conversion

This paper introduces a novel voice conversion (VC) model, guided by text instructions such as "articulate slowly with a deep tone" or "speak in a cheerful boyish voice". Unlike traditional methods that rely on reference utterances to determine the attributes of the converted speech, our model adds versatility and specificity to voice conversion. The proposed VC model is a neural codec language model which processes a sequence of discrete codes, resulting in the code sequence of converted speech. It utilizes text instructions as style prompts to modify the prosody and emotional information of the given speech. In contrast to previous approaches, which often rely on employing separate encoders like prosody and content encoders to handle different aspects of the source speech, our model handles various information of speech in an end-to-end manner. Experiments have demonstrated the impressive capabilities of our model in comprehending instructions and delivering reasonable results.Comment: Accepted to ASRU 202

Atrial cardiomyopathy: from cell to bedside.

Atrial cardiomyopathy refers to structural and electrical remodelling of the atria, which can lead to impaired mechanical function. While historical studies have implicated atrial fibrillation as the leading cause of cardioembolic stroke, atrial cardiomyopathy may be an important, underestimated contributor. To date, the relationship between atrial cardiomyopathy, atrial fibrillation, and cardioembolic stroke remains obscure. This review summarizes the pathogenesis of atrial cardiomyopathy, with a special focus on neurohormonal and inflammatory mechanisms, as well as the role of adipose tissue, especially epicardial fat in atrial remodelling. It reviews the current evidence implicating atrial cardiomyopathy as a cause of embolic stroke, with atrial fibrillation as a lagging marker of an increased thrombogenic atrial substrate. Finally, it discusses the potential of antithrombotic therapy in embolic stroke with undetermined source and appraises the available diagnostic techniques for atrial cardiomyopathy, including imaging techniques such as echocardiography, computed tomography, and magnetic resonance imaging as well as electroanatomic mapping, electrocardiogram, biomarkers, and genetic testing. More prospective studies are needed to define the relationship between atrial cardiomyopathy, atrial fibrillation, and embolic stroke and to establish a prompt diagnosis and specific treatment strategies in these patients with atrial cardiomyopathy for the secondary and even primary prevention of embolic stroke

Folate cycle enzyme MTHFD1L confers metabolic advantages in hepatocellular carcinoma

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