Understanding and recognition of the right ventricular function and dysfunction via a numerical study

The role played by the right ventricular (RV) dysfunction has long been underestimated in clinical practice. Recent findings are progressively confirming that when the RV efficiency deteriorates both the right and the left circulation is (significantly) affected, but studies dedicated to a detailed description of RV hemodynamic role still lack. In response to such a gap in knowledge, this work proposes a numerical model that for the first time evaluates the effect of isolated RV dysfunction on the whole circulation. Lumped parameter modelling was applied to represent the physio-pathological hemodynamics. Different grades of impairment were simulated for three dysfunctions i.e., systolic, diastolic, and combined systolic and diastolic. Hemodynamic alterations (i.e., of blood pressure, flow, global hemodynamic parameters), arising from the dysfunctions, are calculated and analysed. Results well accord with clinical observations, showing that RV dysfunction significantly affects both the pulmonary and systemic hemodynamics. Successful verification against in vivo data proved the clinical potentiality of the model i.e., the capability of identifying the degree of RV impairment for given hemodynamic conditions. This study aims at contributing to the improvement of RV dysfunction recognition and treatment, and to the development of tools for the clinical management of pathologies involving the right heart

Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west african populations.

Background Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC. Methods Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis. Results Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages. Conclusions The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance

Glycans in Sera of Amyotrophic Lateral Sclerosis Patients and Their Role in Killing Neuronal Cells

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease caused by degeneration of upper and lower motor neurons. To date, glycosylation patterns of glycoproteins in fluids of ALS patients have not been described. Moreover, the aberrant glycosylation related to the pathogenesis of other neurodegenerative diseases encouraged us to explore the glycome of ALS patient sera. We found high levels of sialylated glycans and low levels of core fucosylated glycans in serum-derived N-glycans of patients with ALS, compared to healthy volunteer sera. Based on these results, we analyzed the IgG Fc N297-glycans, as IgG are major serum glycoproteins affected by sialylation or core fucosylation and are found in the motor cortex of ALS patients. The analyses revealed a distinct glycan, A2BG2, in IgG derived from ALS patient sera (ALS-IgG). This glycan increases the affinity of IgG to CD16 on effector cells, consequently enhancing Antibody-Dependent Cellular Cytotoxicity (ADCC). Therefore, we explore whether the Fc-N297-glycans of IgG may be involved in ALS disease. Immunostaining of brain and spinal cord tissues revealed over-expression of CD16 and co-localization of intact ALS-IgG with CD16 and in brain with activated microglia of G93A-SOD1 mice. Intact ALS-IgG enhanced effector cell activation and ADCC reaction in comparison to sugar-depleted or control IgG. ALS-IgG were localized in the synapse between brain microglia and neurons of G93A-SOD1 mice, manifesting a promising in vivo ADCC reaction. Therefore, glycans of ALS-IgG may serve as a biomarker for the disease and may be involved in neuronal damage

Ventricular wall stress and wall shear stress homeostasis predicts cardiac remodeling during pregnancy: A modeling study

Pregnancy is a unique and dynamic process characterized by significant changes in the maternal cardiovascular system that are required to satisfy the increased maternal and fetal metabolic demands. Profound structural and hemodynamic adaptations occur during healthy pregnancy that allows the mother to maintain healthy hemodynamics and provide an adequate uteroplacental blood circulation to ensure physiological fetal development. Investigating these adaptations is crucial for understanding the physiology of pregnancy and may provide important insights for the management of high-risk pregnancies. However, no previous modeling studies have investigated the maternal cardiac structural changes that occur during gestation. This study, therefore, had two aims. The first was to develop a lumped parameter model of the whole maternal circulation that is suitable for studying global hemodynamics and cardiac function at different stages of gestation. The second was to test the hypothesis that myofiber stress and wall shear stress homeostasis principles can be used to predict cardiac remodeling that occurs during normal pregnancy. Hemodynamics and cardiac variables predicted from simulations with and without controlled cardiac remodeling algorithms were compared and evaluated with reference clinical data. While both models reproduced the hemodynamic variations that arise in pregnancy, importantly, we show that the structural changes that occur with pregnancy could be predicted by assuming invariant homeostatic “target” values of myocardial wall stress and chamber wall shear stress

An Empirical Investigation of the Relationship between Trade and Structural Change

This paper investigates the role of international trade in the increase in the employment share of non-tradable sectors (services and construction). Borrowing insights from the vast theoretical literature on the determinants of structural change, we build an empirical model allowing to distinguish between long-run and short-run effects. We use this model to investigate the relative importance of the main traditional demand-side and supply-side channels of structural change, assessing, in this context, the role of trade variables. To this end, we use an unbalanced panel of countries for the period 1960-2011 from the EU-KLEMS and the GGDC 10- sector databases. Our preliminary results suggest that both Engelian income effects, i.e. the so-called demand-side drivers, and relative productivity, i.e. the supply-side channel, are relevant drivers of structural change. We show that the import and export shares are positively and negatively related, respectively, with the employment shifts to non-tradable sectors in the long run, in particular, for mature and transition economies. In the short run, a positive and significant relationship between the import share and structural shifts towards tradable sectors emerges

Ventricular outflow tract obstruction: An in-silico model to relate the obstruction to hemodynamic quantities in cardiac paediatric patients

Background Right (R) or left (L) ventricular outflow tract (VOT) obstruction can be either a dynamic phenomenon or a congenital anatomic lesion, which requires a prompt and optimal timing of treatment to avoid a pathological ventricular remodelling. Objective To develop a simple and reliable numerical tool able to relate the R/L obstruction size with the pressure gradient and the cardiac output. To provide indication of the obstruction severity and be of help in the clinical management of patients and designing the surgical treatment for obstruction mitigation. Methods Blood flow across the obstruction is described according to the classical theory of one-dimensional flow, with the obstruction uniquely characterized by its size. Hemodynamics of complete circulation is simulated according to the lumped parameter approach. The case of a 2 years-old baby is reproduced, with the occlusion placed in either the R/or the L/VOT. Conditions from wide open to almost complete obstruction are reproduced. Results Both R/LVOT obstruction in the in-silico model resulted in an increased pressure gradient and a decreased cardiac output, proportional to the severity of the VOT obstruction and dependent on the R/L location of the obstruction itself, as it is clinically observed. Conclusion The in-silico model of ventricular obstruction which simulates pressure gradient and/or cardiac output agrees with clinical data, and is a first step towards the creation of a tool that can support the clinical management of patients from diagnosis to surgical treatments

Distensibility of Deformable Aortic Replicas Assessed by an Integrated In-Vitro and In-Silico Approach

The correct estimation of the distensibility of deformable aorta replicas is a challenging issue, in particular when its local characterization is necessary. We propose a combined in-vitro and in-silico approach to face this problem. First, we tested an aortic silicone arch in a pulse-duplicator analyzing its dynamics under physiological working conditions. The aortic flow rate and pressure were measured by a flow meter at the inlet and two probes placed along the arch, respectively. Video imaging analysis allowed us to estimate the outer diameter of the aorta in some sections in time. Second, we replicated the in-vitro experiment through a Fluid-Structure Interaction simulation. Observed and computed values of pressures and variations in aorta diameters, during the cardiac cycle, were compared. Results were considered satisfactory enough to suggest that the estimation of local distensibility from in-silico tests is reliable, thus overcoming intrinsic experimental limitations. The aortic distensibility (AD) is found to vary significantly along the phantom by ranging from 3.0 × 10−3 mmHg−1 in the ascending and descending tracts to 4.2 × 10−3 mmHg−1 in the middle of the aortic arch. Interestingly, the above values underestimate the AD obtained in preliminary tests carried out on straight cylindrical samples made with the same material of the present phantom. Hence, the current results suggest that AD should be directly evaluated on the replica rather than on the samples of the adopted material. Moreover, tests should be suitably designed to estimate the local rather than only the global distensibility