Average synaptic activity and neural networks topology: a global inverse problem

The dynamics of neural networks is often characterized by collective behavior and quasi-synchronous events, where a large fraction of neurons fire in short time intervals, separated by uncorrelated firing activity. These global temporal signals are crucial for brain functioning. They strongly depend on the topology of the network and on the fluctuations of the connectivity. We propose a heterogeneous mean--field approach to neural dynamics on random networks, that explicitly preserves the disorder in the topology at growing network sizes, and leads to a set of self-consistent equations. Within this approach, we provide an effective description of microscopic and large scale temporal signals in a leaky integrate-and-fire model with short term plasticity, where quasi-synchronous events arise. Our equations provide a clear analytical picture of the dynamics, evidencing the contributions of both periodic (locked) and aperiodic (unlocked) neurons to the measurable average signal. In particular, we formulate and solve a global inverse problem of reconstructing the in-degree distribution from the knowledge of the average activity field. Our method is very general and applies to a large class of dynamical models on dense random networks

Heterogeneous Mean Field for neural networks with short term plasticity

We report about the main dynamical features of a model of leaky-integrate-and fire excitatory neurons with short term plasticity defined on random massive networks. We investigate the dynamics by a Heterogeneous Mean-Field formulation of the model, that is able to reproduce dynamical phases characterized by the presence of quasi-synchronous events. This formulation allows one to solve also the inverse problem of reconstructing the in-degree distribution for different network topologies from the knowledge of the global activity field. We study the robustness of this inversion procedure, by providing numerical evidence that the in-degree distribution can be recovered also in the presence of noise and disorder in the external currents. Finally, we discuss the validity of the heterogeneous mean-field approach for sparse networks, with a sufficiently large average in-degree

Influenza B-cells protective epitope characterization: a passkey for the rational design of new broad-range anti-influenza vaccines

The emergence of new influenza strains causing pandemics represents a serious threat to human health. From 1918, four influenza pandemics occurred, caused by H1N1, H2N2 and H3N2 subtypes. Moreover, in 1997 a novel influenza avian strain belonging to the H5N1 subtype infected humans. Nowadays, even if its transmission is still circumscribed to avian species, the capability of the virus to infect humans directly from avian reservoirs can result in fatalities. Moreover, the risk that this or novel avian strains could adapt to inter-human transmission, the development of resistance to anti-viral drugs and the lack of an effective prevention are all incumbent problems for the world population. In this scenario, the identification of broadly neutralizing monoclonal antibodies (mAbs) directed against conserved regions shared among influenza isolates has raised hopes for the development of monoclonal antibody-based immunotherapy and “universal” anti-influenza vaccines

Potential impact of a microarray-based nucleic acid assay for rapid detection of gram-negative bacteria and resistance markers in positive blood cultures

We evaluated the Verigene Gram-negative blood culture (BC-GN) test, a microarray that detects Gram-negative bacteria and several resistance genes. A total of 102 positive blood cultures were tested, and the BC-GN test correctly identified 97.9% of the isolates within its panel. Resistance genes (CTX-M, KPC, VIM, and OXA genes) were detected in 29.8% of the isolates, with positive predictive values of 95.8% (95% confidence interval [CI], 87.7% to 98.9%) in Enterobacteriaceae and 100% (95% CI, 75.9% to 100%) in Pseudomonas aeruginosa and negative predictive values of 100% (95% CI, 93.9% to 100%) and 78.6% (95% CI, 51.0% to 93.6%), respectively

Combined prophylactic and therapeutic use maximizes hydroxychloroquine anti-SARS-CoV-2 effects in vitro

While the SARS-CoV-2 pandemic is heavily hitting the world, it is of extreme importance that significant in vitro observations guide the quick set up of clinical trials. In this study, we evidence that the anti-SARS-CoV2 activity of a clinically achievable hydroxychloroquine concentration is maximized only when administered before and after the infection of Vero E6 and Caco-2 cells. This suggests that only a combined prophylactic and therapeutic use of hydroxychloroquine may be effective in limiting viral replication in patients