ALTERATION OF THE EPHA2/EPHRIN-A SIGNALING AXIS IN PSORIATIC EPIDERMIS

EphA2 is a receptor tyrosine kinase (RTK) that triggers keratinocyte differentiation upon activation and subsequently down-regulation by ephrin-A1 ligand. The objective for this study was to determine if the EphA2/ephrin-A1 signaling axis was altered in psoriasis, an inflammatory skin condition where keratinocyte differentiation is abnormal. Microarray analysis of skin biopsies from psoriasis patients revealed increased mRNA transcripts for several members of this RTK family in plaques, including the EphA1, EphA2 and EphA4 subtypes prominently expressed by keratinocytes. Of these, EphA2 showed the greatest up-regulation, a finding that was confirmed by quantitative RT-PCR, IHC analysis and ELISA. In contrast, psoriatic lesions exhibited reduced ephrin-A ligand immunoreactivity. Exposure of primary keratinocytes induced to differentiated in high calcium or a 3-dimensiosnal raft culture of human epidermis to a combination of growth factors and cytokines elevated in psoriasis increased EphA2 mRNA and protein expression while inducing S100A7 and disrupting differentiation. Pharmacological delivery of a soluble ephrin-A1 peptidomimetic ligand led to a reduction in EphA2 expression and ameliorated proliferation and differentiation in raft cultures exposed to EGF and IL-1α. These findings suggest that ephrin-A1-mediated down-regulation of EphA2 supports keratinocyte differentiation in the context of cytokine perturbation

Algebraic Comparison of Partial Lists in Bioinformatics

The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset

Supramolecular binding and separation of hydrocarbons within a functionalised porous metal-organic framework

Supramolecular interactions are fundamental to host-guest binding in chemical and biological processes. Direct visualisation of such supramolecular interactions within host-guest systems is extremely challenging but crucial for the understanding of their function. We report a comprehensive study combining neutron scattering with synchrotron X-ray and neutron diffraction, coupled with computational modelling, to define the detailed binding at a molecular level of acetylene, ethylene and ethane within the porous host NOTT-300. This study reveals the simultaneous and cooperative hydrogen-bonding, π···π stacking interactions and inter-molecular dipole interactions in the binding of acetylene and ethylene to give up to twelve individual weak supramolecular interactions aligned within the host to form an optimal geometry for intelligent, selective binding of hydrocarbons. We also report, for the first time, the cooperative binding of a mixture of acetylene and ethylene within the porous host together with the corresponding breakthrough experiment and analysis of mixed gas adsorption isotherms

A Regional Reduction in Ito and IKACh in the Murine Posterior Left Atrial Myocardium Is Associated with Action Potential Prolongation and Increased Ectopic Activity.

BACKGROUND: The left atrial posterior wall (LAPW) is potentially an important area for the development and maintenance of atrial fibrillation. We assessed whether there are regional electrical differences throughout the murine left atrial myocardium that could underlie regional differences in arrhythmia susceptibility. METHODS: We used high-resolution optical mapping and sharp microelectrode recordings to quantify regional differences in electrical activation and repolarisation within the intact, superfused murine left atrium and quantified regional ion channel mRNA expression by Taqman Low Density Array. We also performed selected cellular electrophysiology experiments to validate regional differences in ion channel function. RESULTS: Spontaneous ectopic activity was observed during sustained 1Hz pacing in 10/19 intact LA and this was abolished following resection of LAPW (0/19 resected LA, P<0.001). The source of the ectopic activity was the LAPW myocardium, distinct from the pulmonary vein sleeve and LAA, determined by optical mapping. Overall, LAPW action potentials (APs) were ca. 40% longer than the LAA and this region displayed more APD heterogeneity. mRNA expression of Kcna4, Kcnj3 and Kcnj5 was lower in the LAPW myocardium than in the LAA. Cardiomyocytes isolated from the LAPW had decreased Ito and a reduced IKACh current density at both positive and negative test potentials. CONCLUSIONS: The murine LAPW myocardium has a different electrical phenotype and ion channel mRNA expression profile compared with other regions of the LA, and this is associated with increased ectopic activity. If similar regional electrical differences are present in the human LA, then the LAPW may be a potential future target for treatment of atrial fibrillation

Probing pre-supernova mass loss in double-peaked Type Ibc supernovae from the Zwicky Transient Facility

Eruptive mass loss of massive stars prior to supernova (SN) explosion is key to understanding their evolution and end fate. An observational signature of pre-SN mass loss is the detection of an early, short-lived peak prior to the radioactive-powered peak in the lightcurve of the SN. This is usually attributed to the SN shock passing through an extended envelope or circumstellar medium (CSM). Such an early peak is common for double-peaked Type IIb SNe with an extended Hydrogen envelope but is uncommon for normal Type Ibc SNe with very compact progenitors. In this paper, we systematically study a sample of 14 double-peaked Type Ibc SNe out of 475 Type Ibc SNe detected by the Zwicky Transient Facility. The rate of these events is ~ 3-9 % of Type Ibc SNe. A strong correlation is seen between the peak brightness of the first and the second peak. We perform a holistic analysis of this sample's photometric and spectroscopic properties. We find that six SNe have ejecta mass less than 1.5 Msun. Based on the nebular spectra and lightcurve properties, we estimate that the progenitor masses for these are less than ~ 12 Msun. The rest have an ejecta mass > 2.4 Msun and a higher progenitor mass. This sample suggests that the SNe with low progenitor masses undergo late-time binary mass transfer. Meanwhile, the SNe with higher progenitor masses are consistent with wave-driven mass loss or pulsation-pair instability-driven mass loss simulations.Comment: Submitted to ApJ. Comments are welcome. arXiv admin note: text overlap with arXiv:2210.0572

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment