Myoglobin for Detection of High-Risk Patients with Acute Myocarditis

There is an unmet need for accurate and practical screening to detect myocarditis. We sought to test the hypothesis that the extent of acute myocarditis, measured by late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR), can be estimated based on routine blood markers. A total of 44 patients were diagnosed with acute myocarditis and included in this study. There was strong correlation between myoglobin and LGE (rs = 0.73 [95% CI 0.51; 0.87], p < 0.001), while correlation was weak between LGE and TnT-hs (rs = 0.37 [95% CI 0.09; 0.61], p = 0.01). Receiver operating curve (ROC) analysis determined myoglobin ≥ 87 μg/L as cutoff to identify myocarditis (92% sensitivity, 80% specificity). The data were reproduced in an established model of coxsackievirus B3 myocarditis in mice (n = 26). These data suggest that myoglobin is an accurate marker of acute myocarditis. Graphical Abstract Receiver operating curve analysis determined myoglobin ≥ 87 μg/L as cutoff to identify myocarditis and these data were reproduced in an established model of coxsackievirus B3 myocarditis in mice: CMRI, cardiac magnetic resonance imaging; Mb, myoglobin; LGE, late gadolinium enhancement; ROC, receiver operating curve analysis

Sex and age differences in sST2 in cardiovascular disease

AimsThe goal of this study was to determine whether sex and age differences exist for soluble ST2 (sST2) for several cardiovascular diseases (CVDs).MethodsWe examined sST2 levels using an ELISA kit for myocarditis (n = 303), cardiomyopathy (n = 293), coronary artery disease (CAD) (n = 239), myocardial infarct (MI) (n = 159), and congestive heart failure (CHF) (n = 286) and compared them to controls that did not have CVDs (n = 234).ResultsMyocarditis occurred in this study in relatively young patients around age 40 while the other CVDs occurred more often in older individuals around age 60. We observed a sex difference in sST2 by age only in myocarditis patients (men aged 38, women 46, p = 0.0002), but not for other CVDs. Sera sST2 levels were significantly elevated compared to age-matched controls for all CVDs: myocarditis (p ≤ 0.0001), cardiomyopathy (p = 0.0009), CAD (p = 0.03), MI (p = 0.034), and CHF (p &lt; 0.0001) driven by elevated sST2 levels in females for all CVDs except myocarditis, which was elevated in both females (p = 0.002) and males (p ≤ 0.0001). Sex differences in sST2 levels were found for myocarditis and cardiomyopathy but no other CVDs and were higher in males (myocarditis p = 0.0035; cardiomyopathy p = 0.0047). sST2 levels were higher in women with myocarditis over 50 years of age compared to men (p = 0.0004) or women under 50 years of age (p = 0.015). In cardiomyopathy and MI patients, men over 50 had significantly higher levels of sST2 than women (p = 0.012 and p = 0.043, respectively) but sex and age differences were not detected in other CVDs. However, women with cardiomyopathy that experienced early menopause had higher sST2 levels than those who underwent menopause at a natural age range (p = 0.02).ConclusionWe found that sex and age differences in sera sST2 exist for myocarditis, cardiomyopathy, and MI, but were not observed in other CVDs including CAD and CHF. These initial findings in patients with self-reported CVDs indicate that more research is needed into sex and age differences in sST2 levels in individual CVDs

Simultaneous, Multi-Wavelength Variability Characterization of the Free-Floating Planetary Mass Object PSO J318.5-22

We present simultaneous HST WFC3 + Spitzer IRAC variability monitoring for the highly-variable young ($\sim$20 Myr) planetary-mass object PSO J318.5-22. Our simultaneous HST + Spitzer observations covered $\sim$2 rotation periods with Spitzer and most of a rotation period with HST. We derive a period of 8.6$\pm$0.1 hours from the Spitzer lightcurve. Combining this period with the measured $v sin i$ for this object, we find an inclination of 56.2$\pm 8.1^{\circ}$. We measure peak-to-trough variability amplitudes of 3.4$\pm$0.1$\%$ for Spitzer Channel 2 and 4.4 - 5.8$\%$ (typical 68$\%$ confidence errors of $\sim$0.3$\%$) in the near-IR bands (1.07-1.67 $\mu$m) covered by the WFC3 G141 prism -- the mid-IR variability amplitude for PSO J318.5-22 one of the highest variability amplitudes measured in the mid-IR for any brown dwarf or planetary mass object. Additionally, we detect phase offsets ranging from 200--210$^{\circ}$ (typical error of $\sim$4$^{\circ}$) between synthesized near-IR lightcurves and the Spitzer mid-IR lightcurve, likely indicating depth-dependent longitudinal atmospheric structure in this atmosphere. The detection of similar variability amplitudes in wide spectral bands relative to absorption features suggests that the driver of the variability may be inhomogeneous clouds (perhaps a patchy haze layer over thick clouds), as opposed to hot spots or compositional inhomogeneities at the top-of-atmosphere level.Comment: 48 pages, 22 figures, accepted to A

A Novel Circulating MicroRNA for the Detection of Acute Myocarditis.

The diagnosis of acute myocarditis typically requires either endomyocardial biopsy (which is invasive) or cardiovascular magnetic resonance imaging (which is not universally available). Additional approaches to diagnosis are desirable. We sought to identify a novel microRNA for the diagnosis of acute myocarditis. To identify a microRNA specific for myocarditis, we performed microRNA microarray analyses and quantitative polymerase-chain-reaction (qPCR) assays in sorted CD4+ T cells and type 17 helper T (Th17) cells after inducing experimental autoimmune myocarditis or myocardial infarction in mice. We also performed qPCR in samples from coxsackievirus-induced myocarditis in mice. We then identified the human homologue for this microRNA and compared its expression in plasma obtained from patients with acute myocarditis with the expression in various controls. We confirmed that Th17 cells, which are characterized by the production of interleukin-17, are a characteristic feature of myocardial injury in the acute phase of myocarditis. The microRNA mmu-miR-721 was synthesized by Th17 cells and was present in the plasma of mice with acute autoimmune or viral myocarditis but not in those with acute myocardial infarction. The human homologue, designated hsa-miR-Chr8:96, was identified in four independent cohorts of patients with myocarditis. The area under the receiver-operating-characteristic curve for this novel microRNA for distinguishing patients with acute myocarditis from those with myocardial infarction was 0.927 (95% confidence interval, 0.879 to 0.975). The microRNA retained its diagnostic value in models after adjustment for age, sex, ejection fraction, and serum troponin level. After identifying a novel microRNA in mice and humans with myocarditis, we found that the human homologue (hsa-miR-Chr8:96) could be used to distinguish patients with myocarditis from those with myocardial infarction. (Funded by the Spanish Ministry of Science and Innovation and others.).Supported by a grant (PI19/00545, to Dr. Martín) from the Ministry of Science and Innovation through the Carlos III Institute of Health–Fondo de Investigación Sanitaria; by a grant from the Biomedical Research Networking Center on Cardiovascular Diseases (to Drs. Martín, Sánchez-Madrid, and Ibáñez); by grants (S2017/BMD-3671-INFLAMUNE-CM, to Drs. Martín and Sánchez-Madrid; and S2017/BMD-3867-RENIM-CM, to Dr. Ibáñez) from Comunidad de Madrid; by a grant (20152330 31, to Drs. Martín, Sánchez-Madrid, and Alfonso) from Fundació La Marató de TV3; by grants (ERC-2011-AdG 294340-GENTRIS, to Dr. Sánchez-Madrid; and ERC-2018-CoG 819775-MATRIX, to Dr. Ibáñez) from the European Research Council; by grants (SAF2017-82886R, to Dr. Sánchez-Madrid; RETOS2019-107332RB-I00, to Dr. Ibáñez; and SAF2017-90604-REDT-NurCaMeIn and RTI2018-095928-BI00, to Dr. Ricote) from the Ministry of Science and Innovation; by Fondo Europeo de Desarrollo Regional (FEDER); and by a 2016 Leonardo Grant for Researchers and Cultural Creators from the BBVA Foundation to Dr. Martín. The National Center for Cardiovascular Research (CNIC) is supported by the Carlos III Institute of Health, the Ministry of Science and Innovation, the Pro CNIC Foundation, and by a Severo Ochoa Center of Excellence grant (SEV-2015-0505). Mr. Blanco-Domínguez is supported by a grant (FPU16/02780) from the Formación de Profesorado Universitario program of the Spanish Ministry of Education, Culture, and Sports. Ms. Linillos-Pradillo is supported by a fellowship (PEJD-2016/BMD-2789) from Fondo de Garantía de Empleo Juvenil de Comunidad de Madrid. Dr. Relaño is supported by a grant (BES-2015-072625) from Contratos Predoctorales Severo Ochoa para la Formación de Doctores of the Ministry of Economy and Competitiveness. Dr. Alonso-Herranz is supported by a fellowship from La Caixa–CNIC. Dr. Caforio is supported by Budget Integrato per la Ricerca dei Dipartimenti BIRD-2019 from Università di Padova. Dr. Das is supported by grants (UG3 TR002878 and R35 HL150807) from the National Institutes of Health and the American Heart Association through its Strategically Focused Research Networks.S

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho

From Data to Software to Science with the Rubin Observatory LSST

editorial reviewedThe Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M&gt;70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0&lt;e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects