Coronary Microvascular Angina: A State-of-the-Art Review

Up to 60-70% of patients, undergoing invasive coronary angiography due to angina and demonstrable myocardial ischemia with provocative tests, do not have any obstructive coronary disease. Coronary microvascular angina due to a dysfunction of the coronary microcirculation is the underlying cause in almost 50% of these patients, associated with a bad prognosis and poor quality of life. In recent years, progress has been made in the diagnosis and management of this condition. The aim of this review is to provide an insight into current knowledge of this condition, from current diagnostic methods to the latest treatments.Copyright © 2022 Spione, Arevalos, Gabani, Sabaté and Brugaletta

Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO₂ and water fluxes through combined in situ measurements and ecosystem modelling

Water stress is a defining characteristic of Mediterranean ecosystems, and is likely to become more severe in the coming decades. Simulation models are key tools for making predictions, but our current understanding of how soil moisture controls ecosystem functioning is not sufficient to adequately constrain parameterisations. <br><br> Canopy-scale flux data from four forest ecosystems with Mediterranean-type climates were used in order to analyse the physiological controls on carbon and water flues through the year. Significant non-stomatal limitations on photosynthesis were detected, along with lesser changes in the conductance-assimilation relationship. New model parameterisations were derived and implemented in two contrasting modelling approaches. <br><br> The effectiveness of two models, one a dynamic global vegetation model ("ORCHIDEE"), and the other a forest growth model particularly developed for Mediterranean simulations ("GOTILWA+"), was assessed and modelled canopy responses to seasonal changes in soil moisture were analysed in comparison with in situ flux measurements. <br><br> In contrast to commonly held assumptions, we find that changing the ratio of conductance to assimilation under natural, seasonally-developing, soil moisture stress is not sufficient to reproduce forest canopy CO₂ and water fluxes. However, accurate predictions of both CO₂ and water fluxes under all soil moisture levels encountered in the field are obtained if photosynthetic capacity is assumed to vary with soil moisture. This new parameterisation has important consequences for simulated responses of carbon and water fluxes to seasonal soil moisture stress, and should greatly improve our ability to anticipate future impacts of climate changes on the functioning of ecosystems in Mediterranean-type climates

Sig-Wasserstein GANs for Time Series Generation

Synthetic data is an emerging technology that can significantly accelerate the development and deployment of AI machine learning pipelines. In this work, we develop high-fidelity time-series generators, the SigWGAN, by combining continuous-time stochastic models with the newly proposed signature W1 metric. The former are the Logsig-RNN models based on the stochastic differential equations, whereas the latter originates from the universal and principled mathematical features to characterize the measure induced by time series. SigWGAN allows turning computationally challenging GAN min-max problem into supervised learning while generating high fidelity samples. We validate the proposed model on both synthetic data generated by popular quantitative risk models and empirical financial data. Codes are available at https://github.com/SigCGANs/Sig-WassersteinGANs.gi

Sig-Wasserstein GANs for Time Series Generation

Synthetic data is an emerging technology that can significantly accelerate the development and deployment of AI machine learning pipelines. In this work, we develop high-fidelity time-series generators, the SigWGAN, by combining continuous-time stochastic models with the newly proposed signature W1 metric. The former are the Logsig-RNN models based on the stochastic differential equations, whereas the latter originates from the universal and principled mathematical features to characterize the measure induced by time series. SigWGAN allows turning computationally challenging GAN min-max problem into supervised learning while generating high fidelity samples. We validate the proposed model on both synthetic data generated by popular quantitative risk models and empirical financial data. Codes are available at https://github.com/SigCGANs/Sig-WassersteinGANs.gi

Pulse processing routines for neutron time-of-flight data

A pulse shape analysis framework is described, which was developed for n_TOF-Phase3, the third phase in the operation of the n_TOF facility at CERN. The most notable feature of this new framework is the adoption of generic pulse shape analysis routines, characterized by a minimal number of explicit assumptions about the nature of pulses. The aim of these routines is to be applicable to a wide variety of detectors, thus facilitating the introduction of the new detectors or types of detectors into the analysis framework. The operational details of the routines are suited to the specific requirements of particular detectors by adjusting the set of external input parameters. Pulse recognition, baseline calculation and the pulse shape fitting procedure are described. Special emphasis is put on their computational efficiency, since the most basic implementations of these conceptually simple methods are often computationally inefficient.Comment: 13 pages, 10 figures, 5 table

The prion-like RNA-processing protein HNRPDL forms inherently toxic amyloid-like inclusion bodies in bacteria

BACKGROUND: The formation of protein inclusions is connected to the onset of many human diseases. Human RNA binding proteins containing intrinsically disordered regions with an amino acid composition resembling those of yeast prion domains, like TDP-43 or FUS, are being found to aggregate in different neurodegenerative disorders. The structure of the intracellular inclusions formed by these proteins is still unclear and whether these deposits have an amyloid nature or not is a matter of debate. Recently, the aggregation of TDP-43 has been modelled in bacteria, showing that TDP-43 inclusion bodies (IBs) are amorphous but intrinsically neurotoxic. This observation raises the question of whether it is indeed the lack of an ordered structure in these human prion-like protein aggregates the underlying cause of their toxicity in different pathological states. RESULTS: Here we characterize the IBs formed by the human prion-like RNA-processing protein HNRPDL. HNRPDL is linked to the development of limb-girdle muscular dystrophy 1G and shares domain architecture with TDP-43. We show that HNRPDL IBs display characteristic amyloid hallmarks, since these aggregates bind to amyloid dyes in vitro and inside the cell, they are enriched in intermolecular β-sheet conformation and contain inner amyloid-like fibrillar structure. In addition, despite their ordered structure, HNRPDL IBs are highly neurotoxic. CONCLUSIONS: Our results suggest that at least some of the disorders caused by the aggregation of human prion-like proteins would rely on the formation of classical amyloid assemblies rather than being caused by amorphous aggregates. They also illustrate the power of microbial cell factories to model amyloid aggregation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12934-015-0284-7) contains supplementary material, which is available to authorized users

Low Power Design of MPPT Circuit Using Power Down System in 65nm CMOS Process

In the field of light energy harvesting, a great amount of power is wasted when the voltage of the photovoltaic cells does not reach the maximum power point at which the storage will charge at its most efficient manner. The most common solution is to build a maximum power point tracking (MPPT) circuit. However, this still needs improvement with very low energy produced indoor. Thus, aiming to reduce the power consumption of the conventional MPPT system, this study implemented a power down system that turns off idle blocks; hence, improving the performance of the conventional MPPT circuit. From several MPPT techniques, this study implemented the Fractional Open Circuit Voltage Method (FOCV), which has a lower cost and simple circuitry, neglecting the use of a microcontroller. Conventional FOCV-based MPPT systems are composed of a sampling circuit that sets the maximum power point voltage (VMPP) from the sampled open circuit voltage (VOC); and a comparator which assures that the accurate VMPP is stored at the output. From the simulation results, the conventional MPPT consumed a power of 324µW from the PV cell, which is higher than the 255µW consumed by this system. Therefore, the implementation of a power down system saved 21.2% more power than that of the conventional FOCV-based MPPT system. The size of the overall layout implemented in 65nm CMOS technology is 70.955 µm x 34.09 µm