Decomposition of some pointed Hopf algebras given by the canonical Nakayama automorphism

Every finite dimensional Hopf algebra is a Frobenius algebra, with Frobenius homomorphism given by an integral. The Nakayama automorphism determined by it yields a decomposition with degrees in a cyclic group. For a family of pointed Hopf algebras, we determine necessary and sufficient conditions for this decomposition to be strongly graded.Comment: 8 page

Twisted Tensor Products of Kn with Km

We find three families of twisting maps of Km with Kn, where K is a field, and we make a detailed study of its properties. One of them is related to truncated quiver algebras, the second one consists of deformations of the first and the third one requires m = n and yields algebras isomorphic to Mn(K).Fil: Arce, Jack. Pontificia Universidad Católica del Perú. Sección Matemáticas; PerúFil: Guccione, Jorge Alberto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaFil: Guccione, Juan Jose. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderón; ArgentinaFil: Valqui, Christian. Pontificia Universidad Católica del Perú. Sección Matemáticas; Perú. Instituto de Matemática y Ciencias Afines; Per

Demonstration of Einstein-Podolsky-Rosen Steering Using Hybrid Continuous- and Discrete-Variable Entanglement of Light

Einstein-Podolsky-Rosen steering is known to be a key resource for one-sided device-independent quantum information protocols. Here we demonstrate steering using hybrid entanglement between continuous- and discrete-variable optical qubits. To this end, we report on suitable steering inequalities and detail the implementation and requirements for this demonstration. Steering is experimentally certified by observing a violation by more than 5 standard deviations. Our results illustrate the potential of optical hybrid entanglement for applications in heterogeneous quantum networks that would interconnect disparate physical platforms and encodings

Metabolic Changes Associated with Different Levels of Energy Deficits in Mediterranean Buffaloes during the Early Lactation Stage: Type and Role of the Main Lipid Fractions Involved

Simple Summary The mobilization of lipids from adipose tissue increases fatty acids and ketone bodies levels. The & beta;-hydroxybutyrate is the main ketone body used to diagnose ketosis, a metabolic disorder of the transition period, in ruminants. Nevertheless, a specific cut-off for the ketosis of & beta;-hydroxybutyrate in buffaloes and the plasma lipid fractions related to ketone bodies have not been established. The relative concentrations of not only total plasma lipids but also lipid fractions such as phospholipids, free fatty acids, triglycerides, and cholesterol esters are influenced by the mobilization of lipids. Each of these fractions has a different role in animal metabolism, influencing energy redistribution and cell metabolism and function. The present study reveals the relationship between lipid fractions and changes in metabolism and inflammation that is related to variations in lipid classes according to different levels of energy deficits in the early lactation of Mediterranean buffaloes. Furthermore, buffaloes defined as at risk of ketosis showed similarities, with ketotic cows suggesting the necessity of further investigations in these ruminants. Cell function and energy redistribution are influenced by lipid classes (phospholipids (PLs), free fatty acids (FFAs), triglycerides (TGs), and cholesterol esters (CEs)). The aim of this study was to investigate metabolic alterations that are related to changes in lipid classes according to different levels of energy deficits in early lactating Mediterranean buffaloes (MBs). Sixty-three MBs were enrolled at the beginning of lactation using an observational study with a cross-sectional experimental design. Serum & beta;-hydroxybutyrate (BHB) levels were used to group the animals into a healthy group (Group H; n = 38; BHB < 0.70 mmol/L) and hyperketonemia risk group (Group K; n = 25; BHB & GE; 0.70 mmol/L). Statistical analysis was performed using a linear model that included the effect of the group and body condition score to assess differences in fatty acid (FA) concentrations. A total of 40 plasma FAs were assessed in each lipid class. Among the FAs, eight PLs, seven FFAs, four TGs, and four CEs increased according to BHB levels, while three FFAs, three TGs, and one CE decreased. The changes among lipid class profiles suggested the influence of inflammatory response, liver metabolism, and the state of body lipid reserves. In addition, the possible similarities of buffaloes at risk of hyperketonemia with ketotic cows suggest the necessity of further investigations in these ruminants

Patient-specific analysis of ascending thoracic aortic aneurysm with the living heart human model

In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs

Using machine learning to characterize heart failure across the scales

Heart failure is a progressive chronic condition in which the heart undergoes detrimental changes in structure and function across multiple scales in time and space. Multiscale models of cardiac growth can provide a patient-specific window into the progression of heart failure and guide personalized treatment planning. Yet, the predictive potential of cardiac growth models remains poorly understood. Here, we quantify predictive power of a stretch-driven growth model using a chronic porcine heart failure model, subject-specific multiscale simulation, and machine learning techniques. We combine hierarchical modeling, Bayesian inference, and Gaussian process regression to quantify the uncertainty of our experimental measurements during an 8-week long study of volume overload in six pigs. We then propagate the experimental uncertainties from the organ scale through our computational growth model and quantify the agreement between experimentally measured and computationally predicted alterations on the cellular scale. Our study suggests that stretch is the major stimulus for myocyte lengthening and demonstrates that a stretch-driven growth model alone can explain 52.7% of the observed changes in myocyte morphology. We anticipate that our approach will allow us to design, calibrate, and validate a new generation of multiscale cardiac growth models to explore the interplay of various subcellular-, cellular-, and organ-level contributors to heart failure. Using machine learning in heart failure research has the potential to combine information from different sources, subjects, and scales to provide a more holistic picture of the failing heart and point toward new treatment strategies

Left Ventricle Biomechanics of Low-Flow, Low-Gradient Aortic Stenosis: A Patient-Specific Computational Model

This study aimed to create an imaging-derived patient-specific computational model of low-flow, low-gradient (LFLG) aortic stenosis (AS) to obtain biomechanics data about the left ventricle. LFLG AS is now a commonly recognized sub-type of aortic stenosis. There remains much controversy over its management, and investigation into ventricular biomechanics may elucidate pathophysiology and better identify patients for valve replacement. ECG-gated cardiac computed tomography images from a patient with LFLG AS were obtained to provide patient-specific geometry for the computational model. Surfaces of the left atrium, left ventricle (LV), and outflow track were segmented. A previously validated multi-scale, multi-physics computational human heart model was adapted to the patient-specific geometry, yielding a model consisting of 91,000 solid elements. This model was coupled to a virtual circulatory system and calibrated to clinically measured parameters from echocardiography and cardiac catheterization data. The simulation replicated key physiologic parameters within 10% of their clinically measured values. Global LV systolic myocardial stress was 7.1 ± 1.8&nbsp;kPa. Mean stress of the basal, middle, and apical segments were 7.7 ± 1.8&nbsp;kPa, 9.1 ± 3.8&nbsp;kPa, and 6.4 ± 0.4&nbsp;kPa, respectively. This is the first patient-specific computational model of LFLG AS based on clinical imaging. Low myocardial stress correlated with low ejection fraction and eccentric LV remodeling. Further studies are needed to understand how alterations in LV biomechanics correlates with clinical outcomes of AS

Serum metabolomics assessment of etiological processes predisposing ketosis in water buffalo during early lactation

Metabolic disorders as ketosis are manifestations of the animal's inability to manage the increase in energy requirement during early lactation. Generally, buffaloes show a different response to higher metabolic demands than other ruminants with a lower incidence of metabolic problems, although ketosis is one of the major diseases that may decrease the productivity in buffaloes. The aim of this study was to characterize the metabolic profile of Mediterranean buffaloes (MB) associated with 2 different levels of beta-hydroxybutyrate (BHB). Sixty-two MB within 50 days in milk (DIM) were enrolled and divided into 2 groups according to se -rum BHB concentration: healthy group (37 MB; BHB &lt;0.70 mmol/L; body condition score: 5.00; parity: 3.78; and DIM: 30.70) and group at risk of hyperketonemia (25 MB; BHB &gt;= 0.70 mmol/L; body condition score: 4.50; parity: 3.76; and DIM: 33.20). The statistical analysis was conducted by one-way ANOVA and un-paired 2-sample Wilcoxon tests. Fifty-seven metabolites were identified and among them, 12 were significant or tended to be significant. These metabolites were related to different metabolic changes such as mobilization of body resources, ruminal fermentations, urea cycle, thy-roid hormone synthesis, inflammation, and oxidative stress status. These findings are suggestive of metabolic changes related to subclinical ketosis status that should be further investigated to better characterize this dis-ease in the MB

Proteomic changes in the milk of water buffaloes (Bubalus bubalis) with subclinical mastitis due to intramammary infection by Staphylococcus aureus and by non-aureus staphylococci

Subclinical mastitis by Staphylococcus aureus (SAU) and by non-aureus staphylococci (NAS) is a major issue in the water buffalo. To understand its impact on milk, 6 quarter samples with &gt;3,000,000 cells/ mL (3 SAU-positive and 3 NAS-positive) and 6 culture-negative quarter samples with &lt;50,000 cells/ mL were investigated by shotgun proteomics and label-free quantitation. A total of 1530 proteins were identified, of which 152 were significantly changed. SAU was more impacting, with 162 vs 127 differential proteins and higher abundance changes (P &lt; 0.0005). The 119 increased proteins had mostly structural (n = 43, 28.29%) or innate immune defence functions (n = 39, 25.66%) and included vimentin, cathelicidins, histones, S100 and neutrophil granule proteins, haptoglobin, and lysozyme. The 33 decreased proteins were mainly involved in lipid metabolism (n = 13, 59.10%) and included butyrophilin, xanthine dehydrogenase/oxidase, and lipid biosynthetic enzymes. The same biological processes were significantly affected also upon STRING analysis. Cathelicidins were the most increased family, as confirmed by western immunoblotting, with a stronger reactivity in SAU mastitis. S100A8 and haptoglobin were also validated by western immunoblotting. In conclusion, we generated a detailed buffalo milk protein dataset and defined the changes occurring in SAU and NAS mastitis, with potential for improving detection (ProteomeXchange identifier PXD012355)