Assessing the relationship between molecular rejection and parenchymal injury in heart transplant biopsies

[Abstract] Background: The INTERHEART study (ClinicalTrials.gov #NCT02670408) used genome-wide microarrays to detect rejection in endomyocardial biopsies; however, many heart transplants with no rejection have late dysfunction and impaired survival. We used the microarray measurements to develop a molecular classification of parenchymal injury. Methods: In 1320 endomyocardial biopsies from 645 patients previously studied for rejection-associated transcripts, we measured the expression of 10 injury-induced transcript sets: 5 induced by recent injury; 2 reflecting macrophage infiltration; 2 normal heart transcript sets; and immunoglobulin transcripts, which correlate with time. We used archetypal clustering to assign injury groups. Results: Injury transcript sets correlated with impaired function. Archetypal clustering based on the expression of injury transcript sets assigned each biopsy to 1 of 5 injury groups: 87 Severe-injury, 221 Late-injury, and 3 with lesser degrees of injury, 376 No-injury, 526 Mild-injury, and 110 Moderate-injury. Severe-injury had extensive loss of normal transcripts (dedifferentiation) and increase in macrophage and injury-induced transcripts. Late-injury was characterized by high immunoglobulin transcript expression. In Severe- and Late-injury, function was depressed, and short-term graft failure was increased, even in hearts with no rejection. T cell-mediated rejection almost always had parenchymal injury, and 85% had Severe- or Late-injury. In contrast, early antibody-mediated rejection (AMR) had little injury, but late AMR often had the Late-injury state. Conclusions: Characterizing heart transplants for their injury state provides new understanding of dysfunction and outcomes and demonstrates the differential impact of T cell-mediated rejection versus AMR on the parenchyma. Slow deterioration from AMR emerges as a major contributor to late dysfunction

A GAL4-Driver Line Resource for Drosophila Neurobiology

We established a collection of 7,000 transgenic lines of Drosophila melanogaster. Expression of GAL4 in each line is controlled by a different, defined fragment of genomic DNA that serves as a transcriptional enhancer. We used confocal microscopy of dissected nervous systems to determine the expression patterns driven by each fragment in the adult brain and ventral nerve cord. We present image data on 6,650 lines. Using both manual and machine-assisted annotation, we describe the expression patterns in the most useful lines. We illustrate the utility of these data for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy. The GAL4 lines allow expression of exogenous genes in distinct, small subsets of the adult nervous system. The set of DNA fragments, each driving a documented expression pattern, will facilitate the generation of additional constructs for manipulating neuronal function

A GAL4-driver line resource for Drosophila neurobiology.

We established a collection of 7,000 transgenic lines of Drosophila melanogaster. Expression of GAL4 in each line is controlled by a different, defined fragment of genomic DNA that serves as a transcriptional enhancer. We used confocal microscopy of dissected nervous systems to determine the expression patterns driven by each fragment in the adult brain and ventral nerve cord. We present image data on 6,650 lines. Using both manual and machine-assisted annotation, we describe the expression patterns in the most useful lines. We illustrate the utility of these data for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy. The GAL4 lines allow expression of exogenous genes in distinct, small subsets of the adult nervous system. The set of DNA fragments, each driving a documented expression pattern, will facilitate the generation of additional constructs for manipulating neuronal function

2019 HRS expert consensus statement on evaluation, risk stratification, and management of arrhythmogenic cardiomyopathy: Executive summary

Arrhythmogenic cardiomyopathy (ACM) is an arrhythmogenic disorder of the myocardium not secondary to ischemic, hypertensive, or valvular heart disease. ACM incorporates a broad spectrum of genetic, systemic, infectious, and inflammatory disorders. This designation includes, but is not limited to, arrhythmogenic right/left ventricular cardiomyopathy, cardiac amyloidosis, sarcoidosis, Chagas disease, and left ventricular noncompaction. The ACM phenotype overlaps with other cardiomyopathies, particularly dilated cardiomyopathy with arrhythmia presentation that may be associated with ventricular dilatation and/or impaired systolic function. This expert consensus statement provides the clinician with guidance on evaluation and management of ACM and includes clinically relevant information on genetics and disease mechanisms. PICO questions were utilized to evaluate contemporary evidence and provide clinical guidance related to exercise in arrhythmogenic right ventricular cardiomyopathy. Recommendations were developed and approved by an expert writing group, after a systematic literature search with evidence tables, and discussion of their own clinical experience, to present the current knowledge in the field. Each recommendation is presented using the Class of Recommendation and Level of Evidence system formulated by the American College of Cardiology and the American Heart Association and is accompanied by references and explanatory text to provide essential context. The ongoing recognition of the genetic basis of ACM provides the opportunity to examine the diverse triggers and potential common pathway for the development of disease and arrhythmia

Fly Light Split-GAL4 Driver Collection

<p>The data presented on this site are the work of the <a href="http://janelia.org/team-project/fly-light" target="_blank">Janelia FlyLight Project Team</a> and the laboratories of <a href="http://www.janelia.org/lab/rubin-lab" target="_blank">Gerald M. Rubin</a>. </p><p>The split-GAL4 lines can be requested from the Janelia fly facility by performing a search and adding the desired lines to your cart. You will then be able to use the FlyBank website to tell us where to send them. For additional help ordering lines, please contact us at <a href="mailto:flybank.janelia.org">flybank.janelia.org</a></p><p>In publications, please attribute the data presented on this site to one of the following papers, as follows: <br><br>For the overall strategy and methods used to produce the split-GAL4 lines for the mushroom body neurons: <br>Aso, Y., Hattori, D., Yu, Y., Johnston, R. M., Iyer, N., Ngo, T. B., Dionne, H., Abbott, L. F., Axel, R., Tanimoto, H. & Rubin, G. M. . The neuronal architecture of the mushroom body provides a logic for associative learning. <a href="http://elifesciences.org/content/3/e04577" target="_blank">eLife (2014) 3:e04577</a><br><br>For split-GAL4 lines for the Lobula Columnar (LC) visual projection neurons:<br>Wu, M., Nern, A., Williamson, W. R., Morimoto, M. M., Reiser, M. B., Card, G. M. & Rubin, G. M. Visual projection neurons in the Drosophila lobula link feature detection to distinct behavioral programs. under review<br><br>For refinement of the split-GAL4 vectors and methodology: <br>Pfeiffer, B. D., Ngo, T. T., Hibbard, K. L., Murphy, C., Jenett, A., Truman, J. W. & Rubin, G. M. Refinement of tools for targeted gene expression in Drosophila. <a href="http://www.genetics.org/content/186/2/735.long" target="_blank">Genetics (2010) 186: 735-55</a>. <br><br>For Multicolor Flp-out (MCFO) technique and single cell labeling:<br>Nern, A., Pfeiffer, B.D., and Rubin, G.M. Optimized tools for multicolor stochastic labeling reveal diverse stereotyped cell arrangements in the fly visual system. <a href="http://www.pnas.org/content/112/22/E2967.long" target="_blank">Proc Natl Acad Sci USA (2015) 112: E2967-2976</a>. <br><br>Split-GAL4 lines were designed based on the expression patterns of GAL4 driver lines in the adult nervous system: <br>The Janelia collection of lines is described in Jenett, A., Rubin, G.M., Ngo, T.-T. B., Shepherd, D., Murphy, C., Dionne, H., Pfeiffer, B.D., Cavallaro, A., Hall, D., Jeter, J., Iyer, N., Fetter, D., Hausenfluck, J.H., Peng, H., Trautman, E., Svirskas, R., Myers, G.W., Iwinski, Z.R., Aso, Y., DePasquale, G.M., Enos, A., Hulamm, P., Lam, S.C.B., Li, H-H., Laverty, T., Long, F., Qu, L., Murphy, S.D., Rokicki, K., Safford, T., Shaw, K., Simpson, J.H., Sowell, A., Tae, S., Yu, Y., Zugates, C.T. A GAL4-Driver Line Resource for Drosophila Neurobiology. <a href="http://www.cell.com/cell-reports/fulltext/S2211-1247(12)00292-6" target="_blank">Cell Reports (2012) 2: 991-1001</a> <br><br>The VT collection of lines is described in Kvon, E.Z., Kazmar, T., Stampfel, G., Yanez-Cuna, J.O., Pagani, M., Schernhuber, K., Dickson, B.J., and Stark, A. Genome-scale functional characterization of Drosophila developmental enhancers in vivo. <a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13395.html" target="_blank">Nature (2014) 512: 91-95</a> and Barry J. Dickson, unpublished data. <br><br>For opening and viewing h5j and LSM stacks:<br>Use <a href="http://fiji.sc/" target="_blank">Fiji</a> (<a href="http://fiji.sc/" target="_blank">http://fiji.sc</a>). Fiji has a built-in plugin (H5J_Loader_Plugin-1.0.4) for opening stack in h5j format, a "visually lossless" compression format.</p