Mutual information rate and bounds for it

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two data sets (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators

Production and transfer of energy and information in Hamiltonian systems

We present novel results that relate energy and information transfer with sensitivity to initial conditions in chaotic multi-dimensional Hamiltonian systems. We show the relation among Kolmogorov-Sinai entropy, Lyapunov exponents, and upper bounds for the Mutual Information Rate calculated in the Hamiltonian phase space and on bi-dimensional subspaces. Our main result is that the net amount of transfer from kinetic to potential energy per unit of time is a power-law of the upper bound for the Mutual Information Rate between kinetic and potential energies, and also a power-law of the Kolmogorov-Sinai entropy. Therefore, transfer of energy is related with both transfer and production of information. However, the power-law nature of this relation means that a small increment of energy transferred leads to a relatively much larger increase of the information exchanged. Then, we propose an ?experimental? implementation of a 1-dimensional communication channel based on a Hamiltonian system, and calculate the actual rate with which information is exchanged between the first and last particle of the channel. Finally, a relation between our results and important quantities of thermodynamics is presented

COVID-19 related acute genital ulcer: a case report

Acute vulvar ulcer (Lipschütz's ulcer) is a rare lesion with local hyperimmunoreactivity triggered by infection, which is characterized by acute, painful, and necrotic ulcerations. This condition is usually found in non-sexually active adolescents, and it resolves spontaneously. We report a case of a 35-year-old woman who was diagnosed with COVID-19 who did not have severe symptoms, but had high levels of D-dimer for 9 days. The COVID-19 diagnosis was followed by the appearance of an acute, necrotic, extremely painful vulvar ulcer, although symptoms caused by COVID-19 had improved. We emphasize the importance of the differential diagnosis to exclude diseases such as Behçet's syndrome, Sexually Transmitted Infections, as well as the presence of viruses that generally trigger Lipschütz's ulcer, such as Epstein-Barr virus and cytomegalovirus. No treatment is usually necessary, however, in the present report due to the pain experienced by the patient, we successfully used oral prednisone.info:eu-repo/semantics/publishedVersio

Maintaining extensivity in evolutionary multiplex networks

In this paper, we explore the role of network topology on maintaining the extensive property of entropy. We study analytically and numerically how the topology contributes to maintaining extensivity of entropy in multiplex networks, i.e. networks of subnetworks (layers), by means of the sum of the positive Lyapunov exponents, HKS, a quantity related to entropy. We show that extensivity relies not only on the interplay between the coupling strengths of the dynamics associated to the intra (short-range) and inter (long-range) interactions, but also on the sum of the intra-degrees of the nodes of the layers. For the analytically treated networks of size N, among several other results, we show that if the sum of the intra-degrees (and the sum of inter-degrees) scales as N?+1, ? > 0, extensivity can be maintained if the intra-coupling (and the inter-coupling) strength scales as N??, when evolution is driven by the maximisation of HKS. We then verify our analytical results by performing numerical simulations in multiplex networks formed by electrically and chemically coupled neurons

Do brain networks evolve by maximizing their information flow capacity?

We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization

Fifty years of impact on liver pathology:a history of the Gnomes

Professional societies play a major role in medicine and science. The societies tend to be large with well-developed administrative structures. An additional model, however, is based on small groups of experts who meet regularly in an egalitarian model in order to discuss disease-specific scientific and medical problems. In order to illustrate the effectiveness of this model, the history and practices are examined of a long-standing successful example, the International Liver Pathology Group, better known as the Gnomes. The history shows that groups such as the Gnomes offer a number of important benefits not available in larger societies and nurturing such groups advances science and medicine in meaningful ways. The success of the Gnomes’ approach provides a road map for future small scientific groups

Global priority multidrug-resistant pathogens do not resist photodynamic therapy.

Microbial drug-resistance demands immediate implementation of novel therapeutic strategies. Antimicrobial photodynamic therapy (aPDT) combines the administration of a photosensitizer (PS) compound with low-irradiance light to induce photochemical reactions that yield reactive oxygen species (ROS). Since ROS react with nearly all biomolecules, aPDT offers a powerful multitarget method to avoid selection of drug-resistant strains. In this study, we assayed photodynamic inactivation under a standardized method, combining methylene blue (MB) as PS and red light, against global priority pathogens. The species tested include Acinetobacter baumannii, Klebsiella aerogenes, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterococcus faecium, Enterococcus faecalis, Staphylococcus aureus, Candida albicans and Cryptococcus neoformans. Our strain collection presents resistance to all tested antimicrobials (>50). All drug-resistant strains were compared to their drug-sensitive counterparts. Regardless of resistance phenotype, MB-aPDT presented species-specific dose-response kinetics. More than 5log10 reduction was observed within less than 75 s of illumination for A. baumannii, E. coli, E. faecium, E. faecalis and S. aureus and within less than 7 min for K. aerogenes, K. pneumoniae, P. aeruginosa, C. albicans and C. neoformans. No signs of correlations in between drug-resistance profiles and aPDT sensitivity were observed. Therefore, MB-aPDT can provide effective therapeutic protocols for a very broad spectrum of pathogens. Hence, we believe that this study represents a very important step to bring aPDT closer to implementation into mainstream medical practices

Mesenchymal stem cells secretome-induced axonal outgrowth is mediated by BDNF

Mesenchymal stem cells (MSCs) have been used for cell-based therapies in regenerative medicine, with increasing importance in central and peripheral nervous system repair. However, MSCs grafting present disadvantages, such as, a high number of cells required for transplantation and low survival rate when transplanted into the central nervous system (CNS). In line with this, MSCs secretome which present on its composition a wide range of molecules (neurotrophins, cytokines) and microvesicles, can be a solution to surpass these problems. However, the effect of MSCs secretome in axonal elongation is poorly understood. In this study, we demonstrate that application of MSCs secretome to both rat cortical and hippocampal neurons induces an increase in axonal length. In addition, we show that this growth effect is axonal intrinsic with no contribution from the cell body. To further understand which are the molecules required for secretome-induced axonal outgrowth effect, we depleted brain-derived neurotrophic factor (BDNF) from the secretome. Our results show that in the absence of BDNF, secretome-induced axonal elongation effect is lost and that axons present a reduced axonal growth rate. Altogether, our results demonstrate that MSCs secretome is able to promote axonal outgrowth in CNS neurons and this effect is mediated by BDNF.European Regional Development Fund (ERDF), through the Centro 2020 Regional Operational Programme under project CENTRO-01–0145-FEDER-000008:BrainHealth 2020, and through the COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation and Portuguese national funds via FCT – Fundação para a Ciência e a Tecnologia, I.P., under projects PTDC/SAU-NEU/104100/2008, EXPL/NEU-NMC/0541/2012 and UID/NEU/04539/2013. This work was also funded by Marie Curie Actions - International reintegration grant #249288, 7th Framework programme, EU. Partially funded by Prémios Santa Casa Neurociências - Prize Melo e Castro for Spinal Cord Injury Research; Portuguese Foundation for Science and Technology (IF Development Grant to A.J.S.); NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme; by FEDER funds, through the Competitiveness Factors Operational Programme (COMPETE), and by national funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038. The authors would also like to acknowledge Prof. J.E. Davies from the Institute of Biomaterials and Biomedical Engineering at the University of Toronto, Canada, for kindly providing some of the HUCPVCs lots used in the present workinfo:eu-repo/semantics/publishedVersio

Inference of financial networks using the normalised mutual information rate

In this paper we study data from financial markets using an information theory tool that we call the normalised Mutual Information Rate and show how to use it to infer the underlying network structure of interrelations in foreign currency exchange rates and stock indices of 14 countries world-wide and the European Union. We first present the mathematical method and discuss about its computational aspects, and then apply it to artificial data from chaotic dynamics and to correlated random variates. Next, we apply the method to infer the network structure of the financial data. Particularly, we study and reveal the interrelations among the various foreign currency exchange rates and stock indices in two separate networks for which we also perform an analysis to identify their structural properties. Our results show that both are small-world networks sharing similar properties but also having distinct differences in terms of assortativity. Finally, the consistent relationships depicted among the 15 economies are further supported by a discussion from the economics view point

Fetal microchimerism in kidney biopsies of lupus nephritis patients may be associated with a beneficial effect

Abstract\ud \ud Introduction\ud Microchimeric male fetal cells (MFCs) have been associated with systemic lupus erythematosus, and published studies have further correlated MFC with lupus nephritis (LN). In the present study, we evaluated the frequency of MFC in the renal tissue of patients with LN.\ud \ud \ud Methods\ud Twenty-seven renal biopsies were evaluated: Fourteen were from women with clinical and laboratory findings of LN, and thirteen were from controls. Genomic DNA was extracted from kidney biopsies, and the male fetal DNA was quantified using real-time quantitative polymerase chain reactions for the detection of specific Y chromosome sequences.\ud \ud \ud Results\ud MFCs were detected in 9 (64%) of 14 of patients with LN, whereas no MFCs were found in the control group (P = 0.0006). No differences in pregnancy history were found between patients with LN and the control group. Significantly higher amounts of MFCs were found in patients with LN with serum creatinine ≤1.5 mg/dl. Furthermore, women with MFCs had significantly better renal function at the time of biopsy (P = 0.03). In contrast, patients with LN without MFCs presented with more severe forms of glomerulonephritis (World Health Organization class IV = 60% and class V = 40%).\ud \ud \ud Conclusions\ud Our data indicate a high prevalence of MFCs in renal biopsy specimens from women with LN, suggesting a role for MFCs in the etiology of LN. The present report also provides some evidence that MFCs could have a beneficial effect in this disease