Effects of exercise training on cardiovascular adrenergic system

In heart failure (HF), exercise has been shown to modulate cardiac sympathetic hyperactivation which is one of the earliest features of neurohormonal derangement in this syndrome and correlates with adverse outcome. An important molecular alteration related to chronic sympathetic overstimulation in HF is represented by cardiac β-adrenergic receptor (β-AR) dysfunction. It has been demonstrated that exercise reverses β-AR dysfunction by restoring cardiac receptor membrane density and G-protein-dependent adenylyl cyclase activation. In particular, several evidence indicate that exercise reduces levels of cardiac G-protein coupled receptor kinase-2 (GRK2) which is known to be involved in both β1-AR and β2-AR dysregulation in HF. Similar alterations of β-AR system have been described also in the senescent heart. It has also been demonstrated that exercise training restores adrenal GRK2/α-2AR/catecholamine (CA) production axis. At vascular level, exercise shows a therapeutic effect on age-related impairment of vascular reactivity to adrenergic stimulation and restores β-AR-dependent vasodilatation by increasing vascular β-AR responsiveness and reducing endothelial GRK2 activity. Sympathetic nervous system overdrive is thought to account for >50% of all cases of hypertension and a lack of balance between parasympathetic and sympathetic modulation has been observed in hypertensive subjects. Non-pharmacological, lifestyle interventions have been associated with reductions in SNS overactivity and blood pressure in hypertension. Several evidence have highlighted the blood pressure lowering effects of aerobic endurance exercise in patients with hypertension and the significant reduction in sympathetic neural activity has been reported as one of the main mechanisms explaining the favorable effects of exercise on blood pressure control

Cervical dystonia patients display subclinical gait changes

Gait disorders in cervical dystonia (CD) are reported in patients under DBS or in severe cases complicated with spinal deformities

Rational Design, Synthesis, Characterization and Evaluation of Iodinated 4,4′-Bipyridines as New Transthyretin Fibrillogenesis Inhibitors

The 3,30,5,50-tetrachloro-2-iodo-4,40-bipyridine structure is proposed as a novel chemical scaold for the design of new transthyretin (TTR) fibrillogenesis inhibitors. In the frame of a proof-of-principle exploration, four chiral 3,30,5,50-tetrachloro-2-iodo-20-substituted-4,40- bipyridines were rationally designed and prepared from a simple trihalopyridine in three steps, including a Cu-catalysed Finkelstein reaction to introduce iodine atoms on the heteroaromatic scaold, and a Pd-catalysed coupling reaction to install the 20-substituent. The corresponding racemates, along with other five chiral 4,40-bipyridines containing halogens as substituents, were enantioseparated by high-performance liquid chromatography in order to obtain pure enantiomer pairs. All stereoisomers were tested against the amyloid fibril formation (FF) of wild type (WT)-TTR and two mutant variants, V30M and Y78F, in acid mediated aggregation experiments. Among the 4,40-bipyridine derivatives, interesting inhibition activity was obtained for both enantiomers of the 3,30,5,50-tetrachloro-20-(4-hydroxyphenyl)-2-iodo-4,40-bipyridine. In silico docking studies were carried out in order to explore possible binding modes of the 4,40-bipyridine derivatives into the TTR. The gained results point out the importance of the right combination of H-bond sites and the presence of iodine as halogen-bond donor. Both experimental and theoretical evidences pave the way for the utilization of the iodinated 4,40-bipyridine core as template to design new promising inhibitors of TTR amyloidogenesis

Combined Experimental and Numerical Investigation of the ECN Spray G under Different Engine-Like Conditions

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction. Foremost, the main scope of the activity was to identify the most accurate numerical set-up in terms of atomization ad secondary break-up models, thanks to a validation of the computed results against experimental data available for the ECN Spray G baseline condition. Specifically, attention was focused on spray penetration along with an analysis of spray morphology and effects of plume-to-plume interaction. Afterwards, the reference set-up was tested and validated under different operating conditions, characterized by detailed experimental measurements specifically provided for this work. In particular, Mie scattering and Schlieren techniques allowed the quasi-simultaneous acquisition of both vapor and liquid penetrations, while a customized image-processing procedure, developed in Matlab environment, was used for the outline of the spray contours of both fuel phases to measure the parameters characterizing the jet development. A robust reference numerical set-up was identified, capable to reproduce with good accuracy the injection process of a multi-hole GDI spray under the wide range of tested operating conditions

Carcinomas in inflammatory bowel disease: a narrative review on diagnostic imaging techniques

We aimed, therefore, to review the current evidence on imaging modalities and carcinomas overlapping IBD.Patients affected by inflammatory bowel diseases (IBD) are at increased risk for developing both gastrointestinal and extra-intestinal cancers. The subtype of IBD, namely Crohn's disease or ulcerative colitis, the location, the activity, the extent, and the duration of the disease determine this risk. Standardized surveillance programs based on imaging techniques exist only for colorectal cancer, where colonoscopy is the milestone of early detection. Clarification is needed on whether different imaging modalities might be adopted in the algorithms for screening and diagnosis of cancers in IBD patients.PubMed was searched up to July 2021 to identify relevant studies investigating the accuracy of imaging techniques in identifying carcinomas in IBD patients. The following text words and corresponding Medical Subject Heading/Entree terms were used: "imaging", "computed tomography", "magnetic resonance imaging", "inflammatory bowel disease", "adenocarcinoma" and "cancer".Currently dye-chromoendoscopy (DCE) is established as the gold standard diagnostic modality for the detection of dysplasia in IBD, with a demonstrated superiority compared to white-light endoscopy. Two main radiological patterns have been described at cross-sectional imaging for both colorectal cancer and small bowel adenocarcinoma. The first subtype is characterized by a tissue mass, while the second subtype recognizes a circumferential thickening with or without the stricturing of the lumen. The diagnostic sensitivity, specificity, and accuracy of cross-sectional imaging techniques for the detection of carcinomas in the context of IBD are largely unknown and scarcely investigated. The definition of surveillance programs based on different imaging methods is warranted

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, SomnivoreTM, for automated wake–sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and drug-treated rats (total n = 56), and pigeons (n = 5). Training and testing sets for validation were previously scored manually by 1–2 trained sleep technologists from each laboratory. F-measure was used to assess precision and sensitivity for statistical analysis of classifier output and human scorer agreement. The algorithm gave high concordance with manual visual scoring across all human data (wake 0.91 ± 0.01; N1 0.57 ± 0.01; N2 0.81 ± 0.01; N3 0.86 ± 0.01; REM 0.87 ± 0.01), which was comparable to manual inter-scorer agreement on all stages. Similarly, high concordance was observed across all rodent (wake 0.95 ± 0.01; NREM 0.94 ± 0.01; REM 0.91 ± 0.01) and pigeon (wake 0.96 ± 0.006; NREM 0.97 ± 0.01; REM 0.86 ± 0.02) data. Effects of classifier learning from single signal inputs, simple stage reclassification, automated removal of transition epochs, and training set size were also examined. In summary, we have developed a polysomnography analysis program for automated sleep-stage classification of data from diverse species. Somnivore enables flexible, accurate, and high-throughput analysis of experimental and clinical sleep studies

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

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 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<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