27 research outputs found
Cardiac defects of hypermobile Ehlers-Danlos syndrome and hypermobility spectrum disorders: a retrospective cohort study
BackgroundDefective connective tissue structure may cause individuals with hypermobile Ehlers-Danlos syndrome (hEDS) or hypermobility spectrum disorders (HSD) to develop cardiac defects.MethodsWe conducted a retrospective chart review of adult patients treated in the EDS Clinic from November 1, 2019, to June 20, 2022 to identify those with cardiac defects. Echocardiogram data were collected using a data collection service. All EDS Clinic patients were evaluated by a single physician and diagnosed according to the 2017 EDS diagnostic criteria. Patient demographic, family and cardiac history were extracted from self-reported responses from a REDCap clinical intake questionnaire. Patients with at least 1 available echocardiogram (ECHO) were selected for the study (nâ=â568).ResultsThe prevalence of aortic root dilation in patients with hEDS was 2.7% and for HSD was 0.6%, with larger measurements for males than females and with age. Based on self-reported cardiac history that was verified from the medical record, patients with hEDS with bradycardia (pâ=â0.034) or brain aneurysm (pâ=â0.015) had a significantly larger average adult aortic root z-score. In contrast, patients with HSD that self-reported dysautonomia (pâ=â0.019) had a significantly larger average aortic root z-score. The prevalence of diagnosed mitral valve prolapse in patients with hEDS was 3.5% and HSD was 1.8%. Variants of uncertain significance were identified in 16 of 84 patients that received genetic testing based on family history.ConclusionsThese data reveal a low prevalence of cardiac defects in a large cohort of well-characterized hEDS and HSD patients. Differences in cardiovascular issues were not observed between patients with hEDS vs. HSD; and our findings suggest that cardiac defects in patients with hEDS or HSD are similar to the general population
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 â„ 87 ÎŒg/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 â„ 87 ÎŒg/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 < 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 (20 Myr) planetary-mass object PSO J318.5-22.
Our simultaneous HST + Spitzer observations covered 2 rotation periods
with Spitzer and most of a rotation period with HST. We derive a period of
8.60.1 hours from the Spitzer lightcurve. Combining this period with the
measured for this object, we find an inclination of 56.2. We measure peak-to-trough variability amplitudes of
3.40.1 for Spitzer Channel 2 and 4.4 - 5.8 (typical 68
confidence errors of 0.3) in the near-IR bands (1.07-1.67 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 (typical error of 4) 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. MartĂn) from the Ministry of Science and Innovation through the Carlos III Institute of HealthâFondo de InvestigaciĂłn Sanitaria; by a grant from the Biomedical Research Networking Center on Cardiovascular Diseases (to Drs. MartĂn, SĂĄnchez-Madrid, and Ibåñez); by grants (S2017/BMD-3671-INFLAMUNE-CM, to Drs. MartĂn and SĂĄnchez-Madrid; and S2017/BMD-3867-RENIM-CM, to Dr. Ibåñez) from Comunidad de Madrid; by a grant (20152330 31, to Drs. MartĂn, SĂĄnchez-Madrid, and Alfonso) from FundaciĂł La MaratĂł de TV3; by grants (ERC-2011-AdG 294340-GENTRIS, to Dr. SĂĄnchez-Madrid; and ERC-2018-CoG 819775-MATRIX, to Dr. Ibåñez) from the European Research Council; by grants (SAF2017-82886R, to Dr. SĂĄnchez-Madrid; RETOS2019-107332RB-I00, to Dr. Ibåñez; 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. MartĂn. 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-DomĂnguez is supported by a grant (FPU16/02780) from the FormaciĂłn 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 GarantĂa de Empleo Juvenil de Comunidad de Madrid. Dr. Relaño is supported by a grant (BES-2015-072625) from Contratos Predoctorales Severo Ochoa para la FormaciĂłn de Doctores of the Ministry of Economy and Competitiveness. Dr. Alonso-Herranz is supported by a fellowship from La CaixaâCNIC. Dr. Caforio is supported by Budget Integrato per la Ricerca dei Dipartimenti BIRD-2019 from UniversitĂ 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
Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches
Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly
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>70 Mâ) 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<eâ€0.3 at 0.33 Gpcâ3 yrâ1 at 90\% confidence level