Decreased circulating Fas ligand in patients with familial combined hyperlipidemia or carotid atherosclerosis Normalization by atorvastatin

AbstractObjectivesWe sought to study whether patients with familial combined hyperlipidemia (FCH) or carotid atherosclerosis have modified circulating solubilized Fas ligand (sFasL) levels, as well as the potential modifications by atorvastatin. We also examined the effect of atorvastatin on FasL expression and sFasL release in cytokine-stimulated cultured human endothelial cells (ECs).BackgroundIn normal situations, FasL is expressed in most cells, including ECs. Proinflammatory stimuli can downregulate its expression in ECs and facilitate the vascular infiltration of inflammatory cells.MethodsWe have measured sFasL plasma levels (by ELISA) in 58 patients with FCH, 14 normocholesterolemic patients with carotid atherosclerosis, and 15 healthy volunteers. We analyzed FasL expression (by Western blot analysis) and sFasL release in cultured ECs stimulated with tumor necrosis factor (TNF)-alpha.ResultsSolubilized FasL levels were decreased in hyperlipidemic patients (49 pg/ml), as compared with healthy volunteers (123 pg/ml, p < 0.0001). Patients were randomized to atorvastatin (n = 28) or bezafibrate (n = 30) during 12 months. Atorvastatin treatment increased sFasL concentrations (111 pg/ml, p < 0.0001), reaching normal values. However, treatment with bezafibrate only marginally affected sFasL (85 pg/ml, p < 0.05). Solubilized FasL was also diminished in patients with carotid atherosclerosis (39 pg/ml), and intensive treatment with atorvastatin normalized sFasL levels (90 pg/ml, p = 0.02). Finally, atorvastatin prevented the diminution of FasL expression and sFasL release elicited by TNF-alpha in cultured ECs.ConclusionsPatients with FCH or carotid atherosclerosis have decreased circulating sFasL levels, probably indicating endothelial dysfunction, but treatment with atorvastatin restored normal blood levels. These data provide a novel effect of atorvastatin and add support for the well-known anti-inflammatory properties of statins

Extracellular Tuning of Mitochondrial Respiration Leads to Aortic Aneurysm

Marfan syndrome (MFS) is an autosomal dominant disorder of the connective tissue caused by mutations in the FBN1 (fibrillin-1) gene encoding a large glycoprotein in the extracellular matrix called fibrillin-1. The major complication of this connective disorder is the risk to develop thoracic aortic aneurysm. To date, no effective pharmacologic therapies have been identified for the management of thoracic aortic disease and the only options capable of preventing aneurysm rupture are endovascular repair or open surgery. Here, we have studied the role of mitochondrial dysfunction in the progression of thoracic aortic aneurysm and mitochondrial boosting strategies as a potential treatment to managing aortic aneurysms.Fondo de Investigacion Sanitaria del Instituto de Salud Carlos III (PI16/188, PI19/855), the European Regional D evelopment Fund, and the European Commission through H2020-EU.1.1, European Research Council grant ERC-2016-StG 715322-EndoMitTalk, and Gobierno de Espana SAF2016-80305P. This work was partially supported by Comunidad de Madrid (S2017/BMD 3867 RENIM-CM) and cofinanced by the European Structural and Investment Fund. M.M. is supported by the Miguel Servet Program (CP 19/014, Fundacion de Investigacion del Hospital 12 de Octubr

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration