Article in JACC. Basic to translational science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 75% of its field
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literature
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
10 authors at 3 institutions in 2 countries.
Derrick AkpaluDepartment of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia.
Gale NewmanDepartment of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia.
Mark BriceDepartment of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia.
Mike PowellDepartment of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia.
Rajesh SinghDepartment of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia.
Alexander QuarshieClinical Research Center, Morehouse School of Medicine, Atlanta, Georgia.
Elizabeth OfiliClinical Research Center, Morehouse School of Medicine, Atlanta, Georgia.
James FongerCardioScout LLC, Atlanta, Georgia.
Nic ChronosCardiology Care Clinic of Lake Oconee, Eatonton, Georgia.
David FeldmanDivision of Cardiology University of Cincinnati Medical Center, Cincinnati, Ohio.
Morehouse School of Medicine · USEaton (United States) · USUniversity of Cincinnati Medical Center · US
Funding
Research Desogn and Biostatistics CoreU54MD007588 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI MAYBERRY, ROBERT M · 2012 to 2018
$24.8M
TRANSPLANTATION OF EXOSOMES FROM HYPOXIA-PRECONDITIONED ADIPOSE-DERIVED STEM CELLS PROMOTES ANGIOGENESIS IN ISCHEMIC HEARTG12MD007602 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI BOND, VINCENT C · 2012 to 2017
$18.4M
TISSUE CULTURE MODEL FOR RETINITIS PIGMENTOSA--A MOLECULAR APPROACHR25GM058268 · NIGMS · MOREHOUSE SCHOOL OF MEDICINE · PI HARRIS-HOOKER, SANDRA, STILES, JONATHAN K. · 1998 to 2023
$16.5M
Adrenergically Mediated Remodeling in Nonischemic Heart FailureR01HL084498 · NHLBI · OHIO STATE UNIVERSITY · PI FELDMAN, DAVID SETH · 2007 to 2012
$1.8M
Effect of Diet on Inflammation in Sicke Cell MiceR21HL092358 · NHLBI · MOREHOUSE SCHOOL OF MEDICINE · PI HIBBERT, JACQUELINE M · 2009 to 2010
This study investigated the release and proteomic profile of tissue factor microparticles (TFMPs) prospectively (up to 6 months) following a myocardial infarction (MI) in a chronic porcine model to establish their utility in tracking cellular level activities that predict physiologic outcomes. Our animal groups (n = 6 to 8 each) consisted of control, noninfarcted (negative control); infarcted only (positive control); and infarcted animals treated with cardiac resynchronization therapy (CRT) and a β-blocker (BB) (metoprolol succinate). The authors found different protein profiles in TFMPs between the control, infarcted only group, and the CRT + BB treated group with predictive impact on the outward phenotype of pathological remodeling after an MI within and between groups. This novel approach of monitoring cellular level activities by profiling the content of TFMPs has the potential of addressing a shortfall of the current crop of cardiac biomarkers, which is the inability to capture composite molecular changes associated with chronic maladaptive signaling in a spatial and temporal manner.
Indexed as
ADRB1, β1-adrenergic receptorADRB2, β2-adrenergic receptorAR, adrenergic receptorARRB1, β1-arrestinBB, β-blockercAMP, cyclic adenosine monophosphatechronic ischemic cardiomyopathyCRT, cardiac resynchronization therapyEDV, end-diastolic volumeEF, ejection fractionELISA, enzyme-linked immunosorbent assayESV, end-systolic volumeFACS, fluorescence-activated cell sortingGRK, G-protein receptor kinaseHSP, heat shock proteinHUVEC, human umbilical vein endothelial cellLVAd MV, left ventricular area around the mitral valve at diastoleLVAd PM, left ventricular area around the papillary muscle at diastoleLVAs MV, left ventricular area around the mitral valve at systoleLVAs PM, left ventricular area around the papillary muscle at systolematrix signalingMI, myocardial infarctionMP, microparticlemyocardial infarctionPCR, polymerase chain reactionTFMP, tissue factor–bearing microparticleTF, tissue factortissue factor-bearing microparticlesTnT, troponin TYucatan mini swineβAR signaling
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Matrix Signaling Subsequent to a Myocardial Infarction: A Proteomic Profile of Tissue Factor Microparticles. · full record | OpenQuestion