Citations

Abstract Membrane curvature is closely associated with spatial distribution of lipids and curvature can influence the formation of lipid rafts in biological membranes. However, it is still unclear how the curvature elasticity plays a role on the asymmetric distribution of lipids across the membrane leaflets, especially, during the process of the raft domain growth. Using supported lipid membranes on wedge‐shaped substrates with alternating positive and negative curvatures, curvature‐mediated asymmetry of lipid raft domains is observed across the membrane leaflets accompanied by glycolipid receptor (GM 1 and GT 1 b) localization. The raft domains initially appear only in a membrane leaflet possessing negative curvatures. In the presence of the interleaflet coupling, they evolve to generate the transverse registry across the membrane bilayer. It is shown that a human recombinant antibody rHIgM12 is co‐localized with the rafts formed at the peaks and valleys of the wedge substrate, indicating that the spatial distribution of its receptor (GT 1 b) is indeed manifested by the site‐specific formation of asymmetric raft domains through the curvature elasticity. The platform can be used to explore the mechanism for the leaflet asymmetry and lipid sorting in terms of the membrane curvature, the composition, and the receptor presentation.

Level of Evidence : 5 Technical Efficacy Stage : 3 J. Magn. Reson. Imaging 2018;47:1169–1171.

Abstract Infection is a common cause of death in patients with advanced cirrhosis. We aimed to develop a predictive model in Child–Turcotte–Pugh (CTP) class C cirrhotics hospitalized with infection for optimizing treatment and improving outcomes. Clinical information was retrospectively abstracted from 244 patients at Tianjin Third Central Hospital, China (cohort 1). Factors associated with mortality were determined using logistic regression. The model for predicting 90-day mortality was then constructed by decision tree analysis. The model was further validated in 91 patients at Mayo Clinic, Rochester, MN (cohort 2) and 82 patients at Seoul St. Mary's Hospital, Korea (cohort 3). The predictive performance of the model was compared with that of the CTP, model for end-stage liver disease (MELD), MELD-Na, Chronic Liver Failure–Sequential Organ Failure Assessment, and the North American consortium for the Study of End-stage Liver Disease (NACSELD) models. The 3-month mortality was 58%, 58%, and 54% in cohort 1, 2, and 3, respectively. In cohort 1, respiratory failure, renal failure, international normalized ratio, total bilirubin, and neutrophil percentage were determinants of 3-month mortality, with odds ratios of 16.6, 3.3, 2.0, 1.1, and 1.03, respectively (P < .05). These parameters were incorporated into the decision tree model, yielding area under receiver operating characteristic (AUROC) of 0.804. The model had excellent reproducibility in the U.S. (AUROC 0.808) and Korea cohort (AUROC 0.809). The proposed model has the highest AUROC and best Youden index of 0.488 and greatest overall correctness of 75%, compared with other models evaluated. The proposed model reliably predicts survival of advanced cirrhotics with infection in both Asian and U.S. populations.

Disruption of epigenetic mechanisms has been intimately linked to the etiology of human cancer. Understanding how these epigenetic mechanisms (including DNA methylation [5mC], hydroxymethylation [5hmC], and histone post‐translational modifications) work in concert to drive cancer initiation and progression remains unknown. Hepatocellular carcinoma (HCC) is increasing in frequency in Western countries but lacks efficacious treatments. The epigenome of HCC remains understudied. To better understand the epigenetic underpinnings of HCC, we performed a genome‐wide assessment of 5mC, 5hmC, four histone modifications linked to promoter/enhancer function (H3K4me1, H3K27ac, H3K4me3, and H3K27me3), and transcription across normal, cirrhotic, and HCC liver tissue. Implementation of bioinformatic strategies integrated these epigenetic marks with each other and with transcription to provide a comprehensive epigenetic profile of how and when the liver epigenome is perturbed during progression to HCC. Our data demonstrate significant deregulation of epigenetic regulators combined with disruptions in the epigenome hallmarked by profound loss of 5hmC, locus‐specific gains in 5mC and 5hmC, and markedly altered histone modification profiles, particularly remodeling of enhancers. Data integration demonstrates that these marks collaborate to influence transcription (e.g., hyper‐5hmC in HCC‐gained active enhancers is linked to elevated expression) of genes regulating HCC proliferation. Two such putative epigenetic driver loci identified through our integrative approach, COMT and FMO3 , increase apoptosis and decrease cell viability in liver‐derived cancer cell lines when ectopically re‐expressed. Conclusion : Altogether, integration of multiple epigenetic parameters is a powerful tool for identifying epigenetically regulated drivers of HCC and elucidating how epigenome deregulation contributes to liver disease and HCC.

A microfluidic device was designed to efficiently fragment chromatin for downstream epigenetic assays.