Multiparametric cardiac magnetic resonance in patients with thalassemia intermedia: new insights from the E-MIOT network.

PURPOSE: In a relatively large cohort of thalassemia intermedia (TI) patients, we systematically investigated myocardial iron overload (MIO), function, and replacement fibrosis using cardiac magnetic resonance (CMR), we assessed the clinical determinants of global heart T2* values, and we explored the association between multiparametric CMR findings and cardiac complications. MATERIALS AND METHODS: We considered 254 beta-TI patients (43.14 ± 13.69 years, 138 females) consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia project. MIO was quantified by T2* technique and biventricular function and atrial areas by cine images. Macroscopic myocardial fibrosis was detected by late gadolinium enhancement technique. RESULTS: Compared to never/sporadically transfused patients, regularly transfused (RT)-TI patients exhibited significantly lower global heart T2* values, biventricular end-diastolic volume indexes, left ventricular mass index, and cardiac index. In RT-TI patients, age and serum ferritin levels were the strongest predictors of global heart T2* values. Independently from the transfusional state, cardiac T2* values were not associated with biventricular function. Of the 103 (40.6%) patients in whom the contrast medium was administrated, 27 (26.2%) had replacement myocardial fibrosis. Age, sex distribution, cardiac iron, and biventricular function parameters were comparable between patients without and without replacement myocardial fibrosis. Twenty-five (9.8%) patients had a history of cardiac complications (heart failure and arrhythmias). Increased age and replacement myocardial fibrosis emerged as significant risk markers for cardiac complications. CONCLUSIONS: In TI, regular transfusions are associated with less pronounced cardiac remodeling but increase the risk of MIO. Replacement myocardial fibrosis is a frequent finding associated with cardiac complications.

Time-shift selection for reservoir computing using a rank-revealing QR algorithm.

Reservoir computing, a recurrent neural network paradigm in which only the output layer is trained, has demonstrated remarkable performance on tasks such as prediction and control of nonlinear systems. Recently, it was demonstrated that adding time-shifts to the signals generated by a reservoir can provide large improvements in performance accuracy. In this work, we present a technique to choose the time-shifts by maximizing the rank of the reservoir matrix using a rank-revealing QR algorithm. This technique, which is not task dependent, does not require a model of the system and, therefore, is directly applicable to analog hardware reservoir computers. We demonstrate our time-shift selection technique on two types of reservoir computer: an optoelectronic reservoir computer and the traditional recurrent network with a t a n h activation function. We find that our technique provides improved accuracy over random time-shift selection in essentially all cases.

Reservoir computing with noise.

This paper investigates in detail the effects of measurement noise on the performance of reservoir computing. We focus on an application in which reservoir computers are used to learn the relationship between different state variables of a chaotic system. We recognize that noise can affect the training and testing phases differently. We find that the best performance of the reservoir is achieved when the strength of the noise that affects the input signal in the training phase equals the strength of the noise that affects the input signal in the testing phase. For all the cases we examined, we found that a good remedy to noise is to low-pass filter the input and the training/testing signals; this typically preserves the performance of the reservoir, while reducing the undesired effects of noise.

Synchronizing chaos using reservoir computing.

We attempt to achieve complete synchronization between a drive system unidirectionally coupled with a response system, under the assumption that limited knowledge on the states of the drive is available at the response. Machine-learning techniques have been previously implemented to estimate the states of a dynamical system from limited measurements. We consider situations in which knowledge of the non-measurable states of the drive system is needed in order for the response system to synchronize with the drive. We use a reservoir computer to estimate the non-measurable states of the drive system from its measured states and then employ these measured states to achieve complete synchronization of the response system with the drive.

National networking in rare diseases and reduction of cardiac burden in thalassemia major.

AIMS: A tailored chelation therapy guided by magnetic resonance imaging (MRI) is a strategy to improve the prognosis in iron-loaded patients, in many cases still hampered by limited MRI availability. In order to address this issue, the Myocardial Iron Overload in Thalassemia (MIOT) network was established in Italy and we aimed to describe the impact of 10-year activity of this network on cardiac burden in thalassemia major (TM). METHODS AND RESULTS: Within the MIOT network, 1746 TM patients (911 females; mean age 31.2 ± 9.1 years) were consecutively enrolled and prospectively followed by 70 thalassemia and 10 MRI centres. Patients were scanned using a multiparametric approach for assessing myocardial iron overload (MIO), biventricular function, and myocardial fibrosis. At the last MRI scan, a significant increase in global heart T2* values and a significantly higher frequency of patients with no MIO (all segmental T2* ≥20 ms) were detected, with a concordant improvement in biventricular function, particularly in patients with baseline global heart T2* <20 ms. Forty-seven percentage of patients changed the chelation regimen based on MRI. The frequency of heart failure (HF) significantly decreased after baseline MRI from 3.5 to 0.8% (P < 0.0001). Forty-six patients died during the study, and HF accounted for 34.8% of deaths. CONCLUSION: Over 10 years, continuous monitoring of cardiac iron and a tailored chelation therapy allowed MIO reduction, with consequent improvement of cardiac function and reduction of cardiac complications and mortality from MIO-related HF. A national networking for rare diseases therefore proved effective in improving the care and reducing cardiac outcomes of TM patients.

Relationship between pancreatic iron overload, glucose metabolism and cardiac complications in sickle cell disease: An Italian multicentre study.

OBJECTIVES: Evidence about the cross-talk between iron, glucose metabolism, and cardiac disease is increasing. We aimed to explore the link of pancreatic iron by Magnetic Resonance Imaging (MRI) with glucose metabolism and cardiac complications (CC) in sickle cell disease (SCD) patients. METHODS: We considered 70 SCD patients consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia Network. Iron overload was quantified by R2* technique and biventricular function by cine images. Macroscopic myocardial fibrosis was evaluated by late gadolinium enhancement technique. Glucose metabolism was assessed by the oral glucose tolerance test. RESULTS: Patients with an altered glucose metabolism showed a significantly higher pancreas R2* than patients with normal glucose metabolism. Pancreatic siderosis emerged as a risk factor for the development of metabolic alterations (OddsRatio 8.25, 95%confidence intervals 1.51-45.1; p = .015). Global pancreas R2* values were directly correlated with mean serum ferritin levels and liver iron concentration. Global pancreas R2* was not significantly associated with global heart R2* and macroscopic myocardial fibrosis. Patients with history of CC showed a significantly higher global pancreas R2* than patients with no CC. CONCLUSIONS: Our findings support the evaluation of pancreatic R2* by MRI in SCD patients to prevent the development of metabolic and cardiac disorders.

Pinning control of networks: Dimensionality reduction through simultaneous block-diagonalization of matrices.

In this paper, we study the network pinning control problem in the presence of two different types of coupling: (i) node-to-node coupling among the network nodes and (ii) input-to-node coupling from the source node to the "pinned nodes." Previous work has mainly focused on the case that (i) and (ii) are of the same type. We decouple the stability analysis of the target synchronous solution into subproblems of the lowest dimension by using the techniques of simultaneous block diagonalization of matrices. Interestingly, we obtain two different types of blocks, driven and undriven. The overall dimension of the driven blocks is equal to the dimension of an appropriately defined controllable subspace, while all the remaining undriven blocks are scalar. Our main result is a decomposition of the stability problem into four independent sets of equations, which we call quotient controllable, quotient uncontrollable, redundant controllable, and redundant uncontrollable. Our analysis shows that the number and location of the pinned nodes affect the number and the dimension of each set of equations. We also observe that in a large variety of complex networks, the stability of the target synchronous solution is de facto only determined by a single quotient controllable block.

Matryoshka and disjoint cluster synchronization of networks.

The main motivation for this paper is to characterize network synchronizability for the case of cluster synchronization (CS), in an analogous fashion to Barahona and Pecora [Phys. Rev. Lett. 89, 054101 (2002)] for the case of complete synchronization. We find this problem to be substantially more complex than the original one. We distinguish between the two cases of networks with intertwined clusters and no intertwined clusters and between the two cases that the master stability function is negative either in a bounded range or in an unbounded range of its argument. Our proposed definition of cluster synchronizability is based on the synchronizability of each individual cluster within a network. We then attempt to generalize this definition to the entire network. For CS, the synchronous solution for each cluster may be stable, independent of the stability of the other clusters, which results in possibly different ranges in which each cluster synchronizes (isolated CS). For each pair of clusters, we distinguish between three different cases: Matryoshka cluster synchronization (when the range of the stability of the synchronous solution for one cluster is included in that of the other cluster), partially disjoint cluster synchronization (when the ranges of stability of the synchronous solutions partially overlap), and complete disjoint cluster synchronization (when the ranges of stability of the synchronous solutions do not overlap).

Cluster synchronization of networks via a canonical transformation for simultaneous block diagonalization of matrices.

We study cluster synchronization of networks and propose a canonical transformation for simultaneous block diagonalization of matrices that we use to analyze the stability of the cluster synchronous solution. Our approach has several advantages as it allows us to: (1) decouple the stability problem into subproblems of minimal dimensionality while preserving physically meaningful information, (2) study stability of both orbital and equitable partitions of the network nodes, and (3) obtain a parameterization of the problem in a small number of parameters. For the last point, we show how the canonical transformation decouples the problem into blocks that preserve key physical properties of the original system. We also apply our proposed algorithm to analyze several real networks of interest, and we find that it runs faster than alternative algorithms from the literature.

Reservoir computing with random and optimized time-shifts.

We investigate the effects of application of random time-shifts to the readouts of a reservoir computer in terms of both accuracy (training error) and performance (testing error). For different choices of the reservoir parameters and different "tasks," we observe a substantial improvement in both accuracy and performance. We then develop a simple but effective technique to optimize the choice of the time-shifts, which we successfully test in numerical experiments.

Phenotypical and functional abnormalities of circulating neutrophils in patients with ß-thalassemia.

ß-Thalassemia is an inherited single gene disorder related to reduced synthesis of the ß-globin chain of hemoglobin. Patients with ß-thalassemia present variable clinical severity ranging from asymptomatic trait to severe transfusion-dependent anemia and multiple organs complications. Moreover, multiple immune abnormalities are a major concern in ß-thalassemia patients. Aberrant neutrophil effector function plays a pivotal role in infection susceptibility in these patients. In severe and persistent inflammation, immature neutrophils are released from the bone marrow and are functionally different compared with mature ones. Despite some abnormalities reported for thalassemia patient's immune system, few data exist on the characterization of human neutrophils in ß-thalassemia. The aim of this study was to investigate the phenotype and function of circulating neutrophil subsets in patients with ß-thalassemia major and with ß-thalassemia intermedia divided in transfusion-dependent and non-transfusion-dependent. By the use of immunochemical and cytofluorimetric analyses, we observed that patients' CD16+ neutrophils exhibit abnormalities in their phenotype and functions and the abnormalities vary according to the clinical form of the disease and to the neutrophil subset (CD16bright and CD16dim). Abnormalities include altered surface expression of the innate immune receptor CD45, Toll-like receptor 4, and CD32, reduced ability to produce an oxidative burst, and elevated levels of membrane lipid peroxidation, especially in patients with a more severe form of the disease. Overall, our results indicating the occurrence of an immuno-senescent phenotype on circulating neutrophils from thalassemia patients suggest the usefulness of neutrophil feature assessment as a tool for better clinical management of ß-thalassemia.

Delays induced cluster synchronization in chaotic networks.

We study networks of coupled oscillators and analyze the role of coupling delays in determining the emergence of cluster synchronization. Given a network topology and a particular arrangement of the coupling delays over the network connections, different patterns of cluster synchronization may emerge. We focus on a simple ring network of six bidirectionally coupled identical oscillators, for which with two different values of the delays, a total of eight cluster synchronization patterns may emerge, depending on the assignment of the delays to the ring connections. We analyze stability of each of the patterns and find that for large enough coupling strength and specific values of the delays, they can all be stabilized. We construct an experimental ring of six bidirectionally coupled Colpitts oscillators, with delayed connections obtained by coupling the oscillators via RF cables of appropriate length. We find that experimental observations of cluster synchronization are in essential agreement with theoretical predictions. We also verify our theory in a fully connected network of fifty nodes for which connections are randomly assigned to be either undelayed or delayed with a given probability.

Cluster Synchronization in Multilayer Networks: A Fully Analog Experiment with LC Oscillators with Physically Dissimilar Coupling.

We investigate cluster synchronization in experiments with a multilayer network of electronic Colpitts oscillators, specifically a network with two interaction layers. We observe and analytically characterize the appearance of several cluster states as we change coupling in the layers. In this study, we innovatively combine bifurcation analysis and the computation of transverse Lyapunov exponents. We observe four kinds of synchronized states, from fully synchronous to a clustered quasiperiodic state-the first experimental observation of the latter state. Our work is the first to study fundamentally dissimilar kinds of coupling within an experimental multilayer network.

Stability analysis of reservoir computers dynamics via Lyapunov functions.

A Lyapunov design method is used to analyze the nonlinear stability of a generic reservoir computer for both the cases of continuous-time and discrete-time dynamics. Using this method, for a given nonlinear reservoir computer, a radial region of stability around a fixed point is analytically determined. We see that the training error of the reservoir computer is lower in the region where the analysis predicts global stability but is also affected by the particular choice of the individual dynamics for the reservoir systems. For the case that the dynamics is polynomial, it appears to be important for the polynomial to have nonzero coefficients corresponding to at least one odd power (e.g., linear term) and one even power (e.g., quadratic term).

Symmetry induced group consensus.

There has been substantial work studying consensus problems for which there is a single common final state, although there are many real-world complex networks for which the complete consensus may be undesirable. More recently, the concept of group consensus whereby subsets of nodes are chosen to reach a common final state distinct from others has been developed, but the methods tend to be independent of the underlying network topology. Here, an alternative type of group consensus is achieved for which nodes that are "symmetric" achieve a common final state. The dynamic behavior may be distinct between nodes that are not symmetric. We show how group consensus for heterogeneous linear agents can be achieved via a simple coupling protocol that exploits the topology of the network. We see that group consensus is possible on both stable and unstable trajectories. We observe and characterize the phenomenon of "isolated group consensus," where one or more clusters may achieve group consensus while the other clusters do not.

Symmetries in the time-averaged dynamics of networks: Reducing unnecessary complexity through minimal network models.

Complex networks are the subject of fundamental interest from the scientific community at large. Several metrics have been introduced to characterize the structure of these networks, such as the degree distribution, degree correlation, path length, clustering coefficient, centrality measures, etc. Another important feature is the presence of network symmetries. In particular, the effect of these symmetries has been studied in the context of network synchronization, where they have been used to predict the emergence and stability of cluster synchronous states. Here, we provide theoretical, numerical, and experimental evidence that network symmetries play a role in a substantially broader class of dynamical models on networks, including epidemics, game theory, communication, and coupled excitable systems; namely, we see that in all these models, nodes that are related by a symmetry relation show the same time-averaged dynamical properties. This discovery leads us to propose reduction techniques for exact, yet minimal, simulation of complex networks dynamics, which we show are effective in order to optimize the use of computational resources, such as computation time and memory.

Generating symmetric graphs.

Symmetry in graphs which describe the underlying topology of networked dynamical systems plays an essential role in the emergence of clusters of synchrony. Many real networked systems have a very large number of symmetries. Often one wants to test new results on large sets of random graphs that are representative of the real networks of interest. Unfortunately, existing graph generating algorithms will seldom produce graphs with any symmetry and much less ones with desired symmetry patterns. Here, we present an algorithm that is able to generate graphs with any desired symmetry pattern. The algorithm can be coupled with other graph generating algorithms to tune the final graph's properties of interest such as the degree distribution.

Targeted synchronization in an externally driven population of mechanical oscillators.

We experimentally investigate the synchronization of driven metronomes using a servo motor to impose external control. We show that a driven metronome will only synchronize in a narrow range near its own frequency; when we introduce coupling between metronomes, we can widen the range of frequencies over which a metronome will synchronize to the external input. Using these features, we design a signal to synchronize a population of dissimilar metronomes; separately we design a signal to selectively synchronize a subpopulation of metronomes within a heterogeneous population.

Optimal control of networks in the presence of attackers and defenders.

We consider the problem of a dynamical network whose dynamics is subject to external perturbations ("attacks") locally applied at a subset of the network nodes. We assume that the network has an ability to defend itself against attacks with appropriate countermeasures, which we model as actuators located at (another) subset of the network nodes. We derive the optimal defense strategy as an optimal control problem. We see that the network topology as well as the distribution of attackers and defenders over the network affect the optimal control solution and the minimum control energy. We study the optimal control defense strategy for several network topologies, including chain networks, star networks, ring networks, and scale free networks.