Gradients of O-information highlight synergy and redundancy in physiological applications

The study of high order dependencies in complex systems has recently led to the introduction of statistical synergy, a novel quantity corresponding to a form of emergence in which patterns at large scales are not traceable from lower scales. As a consequence, several works in the last years dealt with the synergy and its counterpart, the redundancy. In particular, the O-information is a signed metric that measures the balance between redundant and synergistic statistical dependencies. In spite of its growing use, this metric does not provide insight about the role played by low-order scales in the formation of high order effects. To fill this gap, the framework for the computation of the O-information has been recently expanded introducing the so-called gradients of this metric, which measure the irreducible contribution of a variable (or a group of variables) to the high order informational circuits of a system. Here, we review the theory behind the O-information and its gradients and present the potential of these concepts in the field of network physiology, showing two new applications relevant to brain functional connectivity probed via functional resonance imaging and physiological interactions among the variability of heart rate, arterial pressure, respiration and cerebral blood flow

Synergistic information transfer in the global system of financial markets

Uncovering dynamic information flow between stock market indices has been the topic of several studies which exploited the notion of transfer entropy or Granger causality, its linear version. The output of the transfer entropy approach is a directed weighted graph measuring the information about the future state of each target provided by the knowledge of the state of each driving stock market index. In order to go beyond the pairwise description of the information flow, thus looking at higher order informational circuits, here we apply the partial information decomposition to triplets consisting of a pair of driving markets (belonging to America or Europe) and a target market in Asia. Our analysis, on daily data recorded during the years 2000 to 2019, allows the identification of the synergistic information that a pair of drivers carry about the target. By studying the influence of the closing returns of drivers on the subsequent overnight changes of target indexes, we find that (i) Korea, Tokyo, Hong Kong, and Singapore are, in order, the most influenced Asian markets; (ii) US indices SP500 and Russell are the strongest drivers with respect to the bivariate Granger causality; and (iii) concerning higher order effects, pairs of European and American stock market indices play a major role as the most synergetic three-variables circuits. Our results show that the Synergy, a proxy of higher order predictive information flow rooted in information theory, provides details that are complementary to those obtained from bivariate and global Granger causality, and can thus be used to get a better characterization of the global financial system

Numerical simulations of compressible Rayleigh-Taylor turbulence in stratified fluids

We present results from numerical simulations of Rayleigh-Taylor turbulence, performed using a recently proposed lattice Boltzmann method able to describe consistently a thermal compressible flow subject to an external forcing. The method allowed us to study the system both in the nearly-Boussinesq and strongly compressible regimes. Moreover, we show that when the stratification is important, the presence of the adiabatic gradient causes the arrest of the mixing process.Comment: 15 pages, 11 figures. Proceedings of II Conference on Turbulent Mixing and Beyond (TMB-2009

Quantifying high-order interdependencies on individual patterns via the local O-information: Theory and applications to music analysis

High-order, beyond-pairwise interdependencies are at the core of biological, economic, and social complex systems, and their adequate analysis is paramount to understand, engineer, and control such systems. This paper presents a framework to measure high-order interdependence that disentangles their effect on each individual pattern exhibited by a multivariate system. The approach is centered on the local O-information, a new measure that assesses the balance between synergistic and redundant interdependencies at each pattern. To illustrate the potential of this framework, we present a detailed analysis of music scores from J. S. Bach, which reveals how high-order interdependence is deeply connected with highly nontrivial aspects of the musical discourse. Our results place the local O-information as a promising tool of wide applicability, which opens other perspectives for analyzing high-order relationships in the patterns exhibited by complex systems

Bovine papillomavirus 1 gets out of the flock: Detection in an ovine wart in Sicily

A proliferative cauliflower lesion was excised from the udder of a sheep. Histological investigation confirmed the macroscopic classification of the lesion as a papilloma, without any fibroblastic proliferation. PCR revealed the presence of bovine papillomavirus (BPV), which was further confirmed by the identification of a Deltapapillomavirus 4 by Next Generation Sequencing analysis. This was subsequently classified as bovine papillomavirus type 1. Negative staining electron microscopy (EM) analyses produced negative test results for papillomavirus particles. RNA in situ hybridization (ISH) confirmed the presence of BPV-1. The results further confirm the ability of BPVs belonging to the Deltapapillomavirus genus to infect distantly related species and to cause lesions that are different from sarcoids

Massive proliferative cutaneous lesions associated with Poxviridae and Papillomaviridaeviral species in ruminants

n/

Fast and real-time electrical transistor assay for quantifying SARS-CoV-2 neutralizing antibodies

Due to the SARS-CoV-2 pandemic renewed attention has been directed towards viral neutralization assays and neutralizing antibodies quantification, for vaccine pre-clinical trials and determining vaccine efficacy over time. The gold standard to assess antibody titer is the plaque reduction neutralization test, an end-point assay which evaluates the highest serum antibody dilution that neutralizes viral replication, by inspecting the cytopathic effect induced on cell cultures. Here, we use planar, PEDOT:PSS-based organic electrochemical transistors for real-time, remote-controlled, reliable and fast electrical monitoring of the cytopathic effect induced by SARS29 CoV-2 on Vero E6 cell lines, allowing the quantification of serum neutralizing titer. Our low-cost and scalable device has the potential to speed-up large-scale viral neutralization screening without the need for cancerous staining or highly specialized operators. Finally, the technology could be easily transferred to assess neutralizing antibody response towards different viruses in their permissive cell substrates

Association between proton pump inhibitor therapy and clostridium difficile infection: a contemporary systematic review and meta-analysis.

Abstract Introduction Emerging epidemiological evidence suggests that proton pump inhibitor (PPI) acid-suppression therapy is associated with an increased risk of Clostridium difficile infection (CDI). Methods Ovid MEDLINE, EMBASE, ISI Web of Science, and Scopus were searched from 1990 to January 2012 for analytical studies that reported an adjusted effect estimate of the association between PPI use and CDI. We performed random-effect meta-analyses. We used the GRADE framework to interpret the findings. Results We identified 47 eligible citations (37 case-control and 14 cohort studies) with corresponding 51 effect estimates. The pooled OR was 1.65, 95% CI (1.47, 1.85), I2 = 89.9%, with evidence of publication bias suggested by a contour funnel plot. A novel regression based method was used to adjust for publication bias and resulted in an adjusted pooled OR of 1.51 (95% CI, 1.26–1.83). In a speculative analysis that assumes that this association is based on causality, and based on published baseline CDI incidence, the risk of CDI would be very low in the general population taking PPIs with an estimated NNH of 3925 at 1 year. Conclusions In this rigorously conducted systemic review and meta-analysis, we found very low quality evidence (GRADE class) for an association between PPI use and CDI that does not support a cause-effect relationship