Clinical phenotypes of acute heart failure based on signs and symptoms of perfusion and congestion at emergency department presentation and their relationship with patient management and outcomes

Objective To compare the clinical characteristics and outcomes of patients with acute heart failure (AHF) according to clinical profiles based on congestion and perfusion determined in the emergency department (ED). Methods and results Overall, 11 261 unselected AHF patients from 41 Spanish EDs were classified according to perfusion (normoperfusion = warm; hypoperfusion = cold) and congestion (not = dry; yes = wet). Baseline and decompensation characteristics were recorded as were the main wards to which patients were admitted. The primary outcome was 1-year all-cause mortality; secondary outcomes were need for hospitalisation during the index AHF event, in-hospital all-cause mortality, prolonged hospitalisation, 7-day post-discharge ED revisit for AHF and 30-day post-discharge rehospitalisation for AHF. A total of 8558 patients (76.0%) were warm+ wet, 1929 (17.1%) cold+ wet, 675 (6.0%) warm+ dry, and 99 (0.9%) cold+ dry; hypoperfused (cold) patients were more frequently admitted to intensive care units and geriatrics departments, and warm+ wet patients were discharged home without admission. The four phenotypes differed in most of the baseline and decompensation characteristics. The 1-year mortality was 30.8%, and compared to warm+ dry, the adjusted hazard ratios were significantly increased for cold+ wet (1.660; 95% confidence interval 1.400-1.968) and cold+ dry (1.672; 95% confidence interval 1.189-2.351). Hypoperfused (cold) phenotypes also showed higher rates of index episode hospitalisation and in-hospital mortality, while congestive (wet) phenotypes had a higher risk of prolonged hospitalisation but decreased risk of rehospitalisation. No differences were observed among phenotypes in ED revisit risk. Conclusions Bedside clinical evaluation of congestion and perfusion of AHF patients upon ED arrival and classification according to phenotypic profiles proposed by the latest European Society of Cardiology guidelines provide useful complementary information and help to rapidly predict patient outcomes shortly after ED patient arrival

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

Despite the growing number of binary black hole coalescences confidently 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 the 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 have already been identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total source-frame mass M > 70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz emitted gravitational-wave 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 a conservative upper limit for the merger rate density of high-mass binaries with eccentricities 0 < e ≤ 0.3 at 16.9 Gpc−3 yr−1 at the 90% confidence level

Open data from the third observing run of LIGO, Virgo, KAGRA, and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages

Studying the role of synchronized and chaotic spiking neural ensembles in neural information processing

[eng] The brain is characterized by performing many diverse processing tasks ranging from elaborate processes such as pattern recognition, memory or decision making to more simple functionalities such as linear filtering in image processing. Understanding the mechanisms by which the brain is able to produce such a different range of cortical operations remains a fundamental problem in neuroscience. Here we show a study about which processes are related to chaotic and synchronized states based on the study of in-silico implementation of Stochastic Spiking Neural Networks (SSNN). The measurements obtained reveal that chaotic neural ensembles are excellent transmission and convolution systems since mutual information between signals is minimized. At the same time, synchronized cells (that can be understood as ordered states of the brain) can be associated to more complex nonlinear computations. In this sense, we experimentally show that complex and quick pattern recognition processes arise when both synchronized and chaotic states are mixed. These measurements are in accordance with in vivo observations related to the role of neural synchrony in pattern recognition and to the speed of the real biological process. We also suggest that the high-level adaptive mechanisms of the brain that are the Hebbian and non-Hebbian learning rules can be understood as processes devoted to generate the appropriate clustering of both synchronized and chaotic ensembles. The measurements obtained from the hardware implementation of different types of neural systems suggest that the brain processing can be governed by the superposition of these two complementary states with complementary functionalities (nonlinear processing for synchronized states and information convolution and parallelization for chaotic)

Hardware implementation of stochastic spiking neural networks

[eng] Spiking Neural Networks, the last generation of Artificial Neural Networks, are characterized by its bioinspired nature and by a higher computational capacity with respect to other neural models. In real biological neurons, stochastic processes represent an important mechanism of neural behavior and are responsible of its special arithmetic capabilities. In this work we present a simple hardware implementation of spiking neurons that considers this probabilistic nature. The advantage of the proposed implementation is that it is fully digital and therefore can be massively implemented in Field Programmable Gate Arrays. The high computational capabilities of the proposed model are demonstrated by the study of both feed-forward and recurrent networks that are able to implement high-speed signal filtering and to solve complex systems of linear equations

A New Stochastic Computing Methodology for Efficient Neural Network Implementation

[eng] This paper presents a new methodology for the hardware implementation of neural networks (NNs) based on probabilistic laws. The proposed encoding scheme circumvents the limitations of classical stochastic computing (based on unipolar or bipolar encoding) extending the representation range to any real number using the ratio of two bipolar-encoded pulsed signals. Furthermore, the novel approach presents practically a total noise-immunity capability due to its specific codification. We introduce different designs for building the fundamental blocks needed to implement NNs. The validity of the present approach is demonstrated through a regression and a pattern recognition task. The low cost of the methodology in terms of hardware, along with its capacity to implement complex mathematical functions (such as the hyperbolic tangent), allows its use for building highly reliable systems and parallel computing

CIBER-CLAP (CIBERCV Cardioprotection Large Animal Platform): A multicenter preclinical network for testing reproducibility in cardiovascular interventions

Despite many cardioprotective interventions have shown to protect the heart against ischemia/reperfusion injury in the experimental setting, only few of them have succeeded in translating their findings into positive proof-of-concept clinical trials. Controversial and inconsistent experimental and clinical evidence supports the urgency of a disruptive paradigm shift for testing cardioprotective therapies. There is a need to evaluate experimental reproducibility before stepping into the clinical arena. The CIBERCV (acronym for Spanish network-center for cardiovascular biomedical research) has set up the “Cardioprotection Large Animal Platform” (CIBER-CLAP) to perform experimental studies testing the efficacy and reproducibility of promising cardioprotective interventions based on a pre-specified design and protocols, randomization, blinding assessment and other robust methodological features. Our first randomized, control-group, open-label blinded endpoint experimental trial assessing local ischemic preconditioning (IPC) in a pig model of acute myocardial infarction (n = 87) will be carried out in three separate sets of experiments performed in parallel by three laboratories. Each set aims to assess: (A) CMR-based outcomes; (B) histopathological-based outcomes; and (C) protein-based outcomes. Three core labs will assess outcomes in a blinded fashion (CMR imaging, histopathology and proteomics) and 2 methodological core labs will conduct the randomization and statistical analysis.Groups part of the CIBERCV receive competitive structural funding from the Insituto de Salud Carlos III (ISCiii) through the Ministry of Science, Innovation and Universities (MICINN). X.R. has received support from the SEC-CNIC CARDIOJOVEN fellowship program.Peer reviewe

ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo

Published online: May 25, 2022To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue’s cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN’s scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown.Andrew M. K. Law, Jiamin Chen, Yolanda Colino-Sanguino, Laura Rodriguez de la Fuente, Guocheng Fang, Susan M. Grimes, Hongxu Lu, Robert J. Huang, Sarah T. Boyle, Jeron Venhuizen, Lesley Castillo, Javad Tavakoli, Joanna N. Skhinas, Ewan K. A. Millar, Julia Beretov, Fernando J. Rossello, Joanne L. Tipper, Christopher J. Ormandy, Michael S. Samuel, Thomas R. Cox, Luciano Martelotto, Dayong Jin, Fatima Valdes-Mora, Hanlee P. Ji, and David Gallego-Orteg