Noncoding mutations cause super-enhancer retargeting resulting in protein synthesis dysregulation during B cell lymphoma progression.

Whole-genome sequencing of longitudinal tumor pairs representing transformation of follicular lymphoma to high-grade B cell lymphoma with MYC and BCL2 rearrangements (double-hit lymphoma) identified coding and noncoding genomic alterations acquired during lymphoma progression. Many of these transformation-associated alterations recurrently and focally occur at topologically associating domain resident regulatory DNA elements, including H3K4me3 promoter marks located within H3K27ac super-enhancer clusters in B cell non-Hodgkin lymphoma. One region found to undergo recurrent alteration upon transformation overlaps a super-enhancer affecting the expression of the PAX5/ZCCHC7 gene pair.

Segmental analysis of liver cirrhosis with different etiologies: a study based on iodine mixed imaging in port-venous phase.

Background: Computed tomography (CT) in port-venous phase can display the intra-hepatic vessels, and may provide the possibility for segment function evaluation for cirrhosis.

Purpose: To assess the value of iodine mixed imaging of dual-source dual-energy CT in port-venous phase in segmental evaluation of liver cirrhosis with different etiologies.

Material And Methods: Patients diagnosed with liver cirrhosis were enrolled.

Diagnostic potential of myocardial early systolic lengthening for patients with suspected non-ST-segment elevation acute coronary syndrome.

Background: During early systole, ischemic myocardium with reduced active force experiences early systolic lengthening (ESL). This study aimed to explore the diagnostic potential of myocardial ESL in suspected non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients with normal wall motion and left ventricular ejection fraction (LVEF).

Methods: Overall, 195 suspected NSTE-ACS patients with normal wall motion and LVEF, who underwent speckle tracking echocardiography (STE) before coronary angiography, were included in this study.

mA RNA modification regulates innate lymphoid cell responses in a lineage-specific manner.

Innate lymphoid cells (ILCs) can quickly switch from a quiescent state to an active state and rapidly produce effector molecules that provide critical early immune protection. How the post-transcriptional machinery processes different stimuli and initiates robust gene expression in ILCs is poorly understood. Here, we show that deletion of the N-methyladenosine (mA) writer protein METTL3 has little impact on ILC homeostasis or cytokine-induced ILC1 or ILC3 responses but significantly diminishes ILC2 proliferation, migration and effector cytokine production and results in impaired antihelminth immunity.

Specific regulation of BACH1 by the hotspot mutant p53 reveals a distinct gain-of-function mechanism.

Although the gain of function (GOF) of p53 mutants is well recognized, it remains unclear whether different p53 mutants share the same cofactors to induce GOFs. In a proteomic screen, we identified BACH1 as a cellular factor that recognizes the p53 DNA-binding domain depending on its mutation status. BACH1 strongly interacts with p53 but fails to effectively bind wild-type p53 or other hotspot mutants in vivo for functional regulation.

RNA exosome drives early B cell development via noncoding RNA processing mechanisms.

B cell development is linked to successful V(D)J recombination, allowing B cell receptor expression and ultimately antibody secretion for adaptive immunity. Germline noncoding RNAs (ncRNAs) are produced at immunoglobulin (Ig) loci during V(D)J recombination, but their function and posttranscriptional regulation are incompletely understood. Patients with trichohepatoenteric syndrome, characterized by RNA exosome pathway component mutations, exhibit lymphopenia, thus demonstrating the importance of ncRNA surveillance in B cell development in humans.

Mechanism of noncoding RNA-associated N-methyladenosine recognition by an RNA processing complex during IgH DNA recombination.

Immunoglobulin heavy chain (IgH) locus-associated G-rich long noncoding RNA (SμGLT) is important for physiological and pathological B cell DNA recombination. We demonstrate that the METTL3 enzyme-catalyzed N-methyladenosine (mA) RNA modification drives recognition and 3' end processing of SμGLT by the RNA exosome, promoting class switch recombination (CSR) and suppressing chromosomal translocations. The recognition is driven by interaction of the MPP6 adaptor protein with nuclear mA reader YTHDC1.

A ChIP-exo screen of 887 Protein Capture Reagents Program transcription factor antibodies in human cells.

Antibodies offer a powerful means to interrogate specific proteins in a complex milieu. However, antibody availability and reliability can be problematic, whereas epitope tagging can be impractical in many cases. To address these limitations, the Protein Capture Reagents Program (PCRP) generated over a thousand renewable monoclonal antibodies (mAbs) against human presumptive chromatin proteins.

Noncoding RNA processing by DIS3 regulates chromosomal architecture and somatic hypermutation in B cells.

Noncoding RNAs are exquisitely titrated by the cellular RNA surveillance machinery for regulating diverse biological processes. The RNA exosome, the predominant 3' RNA exoribonuclease in mammalian cells, is composed of nine core and two catalytic subunits. Here, we developed a mouse model with a conditional allele to study the RNA exosome catalytic subunit DIS3.

Proteasomal Regulation of Mammalian SPT16 in Controlling Transcription.

FACT (cilitates hromatin ranscription), an essential and evolutionarily conserved heterodimer from yeast to humans, controls transcription and is found to be upregulated in various cancers. However, the basis for such upregulation is not clearly understood. Our recent results deciphering a new ubiquitin-proteasome system regulation of the FACT subunit SPT16 in orchestrating transcription in yeast hint at the involvement of the proteasome in controlling FACT in humans, with a link to cancer.

Noncoding RNA transcription alters chromosomal topology to promote isotype-specific class switch recombination.

B cells undergo two types of genomic alterations to increase antibody diversity: introduction of point mutations into immunoglobulin heavy- and light-chain ( and ) variable regions by somatic hypermutation (SHM) and alteration of antibody effector functions by changing the expressed IgH constant region exons through IgH class switch recombination (CSR). SHM and CSR require the B cell-specific activation-induced cytidine deaminase (AID) protein, the transcription of germline noncoding RNAs, and the activity of the 3' regulatory region (3'RR) super-enhancer. Although many transcription regulatory elements (e.

3D Modeling of Esophageal Development using Human PSC-Derived Basal Progenitors Reveals a Critical Role for Notch Signaling.

Pluripotent stem cells (PSCs) could provide a powerful system to model development of the human esophagus, whose distinct tissue organization compared to rodent esophagus suggests that developmental mechanisms may not be conserved between species. We therefore established an efficient protocol for generating esophageal progenitor cells (EPCs) from human PSCs. We found that inhibition of TGF-ß and BMP signaling is required for sequential specification of EPCs, which can be further purified using cell-surface markers.

Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors.

The origin and specification of human dendritic cells (DCs) have not been investigated at the clonal level. Through the use of clonal assays, combined with statistical computation, to quantify the yield of granulocytes, monocytes, lymphocytes and three subsets of DCs from single human CD34 progenitor cells, we found that specification to the DC lineage occurred in parallel with specification of hematopoietic stem cells (HSCs) to the myeloid and lymphoid lineages. This started as a lineage bias defined by specific transcriptional programs that correlated with the combinatorial 'dose' of the transcription factors IRF8 and PU.

Nuclear Proximity of Mtr4 to RNA Exosome Restricts DNA Mutational Asymmetry.

The distribution of sense and antisense strand DNA mutations on transcribed duplex DNA contributes to the development of immune and neural systems along with the progression of cancer. Because developmentally matured B cells undergo biologically programmed strand-specific DNA mutagenesis at focal DNA/RNA hybrid structures, they make a convenient system to investigate strand-specific mutagenesis mechanisms. We demonstrate that the sense and antisense strand DNA mutagenesis at the immunoglobulin heavy chain locus and some other regions of the B cell genome depends upon localized RNA processing protein complex formation in the nucleus.

Electrospun Nanofibres Containing Antimicrobial Plant Extracts.

Over the last 10 years great research interest has been directed toward nanofibrous architectures produced by electrospinning bioactive plant extracts. The resulting structures possess antimicrobial, anti-inflammatory, and anti-oxidant activity, which are attractive for biomedical applications and food industry. This review describes the diverse approaches that have been developed to produce electrospun nanofibres that are able to deliver naturally-derived chemical compounds in a controlled way and to prevent their degradation.

Discovering a critical transition state from nonalcoholic hepatosteatosis to nonalcoholic steatohepatitis by lipidomics and dynamical network biomarkers.

Nonalcoholic fatty liver disease (NAFLD) is a major risk factor for type 2 diabetes and metabolic syndrome. However, accurately differentiating nonalcoholic steatohepatitis (NASH) from hepatosteatosis remains a clinical challenge. We identified a critical transition stage (termed pre-NASH) during the progression from hepatosteatosis to NASH in a mouse model of high fat-induced NAFLD, using lipidomics and a mathematical model termed dynamic network biomarkers (DNB).

Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study.

Diagnosing phenotypes of single-sample individuals by edge biomarkers.

Network or edge biomarkers are a reliable form to characterize phenotypes or diseases. However, obtaining edges or correlations between molecules for an individual requires measurement of multiple samples of that individual, which are generally unavailable in clinical practice. Thus, it is strongly demanded to diagnose a disease by edge or network biomarkers in one-sample-for-one-individual context.

Edge biomarkers for classification and prediction of phenotypes.

In general, a disease manifests not from malfunction of individual molecules but from failure of the relevant system or network, which can be considered as a set of interactions or edges among molecules. Thus, instead of individual molecules, networks or edges are stable forms to reliably characterize complex diseases. This paper reviews both traditional node biomarkers and edge biomarkers, which have been newly proposed.

MCentridFS: a tool for identifying module biomarkers for multi-phenotypes from high-throughput data.

Systematically identifying biomarkers, in particular, network biomarkers, from high-throughput data is an important and challenging task, and many methods for two-class comparison have been developed to exploit information of high-throughput data. However, as the high-throughput data with multi-phenotypes are available, there is a great need to develop effective multi-classification models. In this study, we proposed a novel approach, called MCentridFS (Multi-class Centroid Feature Selection), to systematically identify responsive modules or network biomarkers for classifying multi-phenotypes from high-throughput data.

EdgeMarker: Identifying differentially correlated molecule pairs as edge-biomarkers.

Biomarker discovery is one of the major topics in translational biomedicine study based on high-throughput biological data analysis. Traditional methods focus on differentially expressed genes (or node-biomarkers) but ignore non-differentials. However, non-differentially expressed genes also play important roles in the biological processes and the rewired interactions / edges among non-differential genes may reveal fundamental difference between variable conditions.

Deciphering early development of complex diseases by progressive module network.

There is no effective cure nowadays for many complex diseases, and thus it is crucial to detect and further treat diseases in earlier stages. Generally, the development and progression of complex diseases include three stages: normal stage, pre-disease stage, and disease stage. For diagnosis and treatment, it is necessary to reveal dynamical organizations of molecular modules during the early development of the disease from the pre-disease stage to the disease stage.