Double coherence resonance in neuron models driven by discrete correlated noise

We study the influence of correlations among discrete stochastic excitatory or inhibitory inputs on the response of the FitzHugh-Nagumo neuron model. For any level of correlation the emitted signal exhibits at some finite noise intensity a maximal degree of regularity, i.e., a coherence resonance. Furthermore, for either inhibitory or excitatory correlated stimuli a {\it Double Coherence Resonance} (DCR) is observable. DCR refers to a (absolute) maximum coherence in the output occurring for an optimal combination of noise variance and correlation. All these effects can be explained by taking advantage of the discrete nature of the correlated inputs.Comment: 4 pages, 3 figures in eps, to appear in Physical Review Letter

Free energy landscape of mechanically unfolded model proteins: extended Jarzinsky versus inherent structure reconstruction

The equilibrium free energy landscape of off-lattice model heteropolymers as a function of an internal coordinate, namely the end-to-end distance, is reconstructed from out-of-equilibrium steered molecular dynamics data. This task is accomplished via two independent methods: by employing an extended version of the Jarzynski equality (EJE) and the inherent structure (IS) formalism. A comparison of the free energies estimated with these two schemes with equilibrium results obtained via the umbrella sampling technique reveals a good quantitative agreement among all the approaches in a range of temperatures around the ``folding transition'' for the two examined sequences. In particular, for the sequence with good foldability properties, the mechanically induced structural transitions can be related to thermodynamical aspects of folding. Moreover, for the same sequence the knowledge of the landscape profile allows for a good estimation of the life times of the native configuration for temperatures ranging from the folding to the collapse temperature. For the random sequence, mechanical and thermal unfolding appear to follow different paths along the landscape.Comment: Latex manuscript, 20 pages, 23 figures, submitted to Physical Review

Discrete Breathers in a Realistic Coarse-Grained Model of Proteins

We report the results of molecular dynamics simulations of an off-lattice protein model featuring a physical force-field and amino-acid sequence. We show that localized modes of nonlinear origin (discrete breathers) emerge naturally as continuations of a subset of high-frequency normal modes residing at specific sites dictated by the native fold. In the case of the small $\beta$-barrel structure that we consider, localization occurs on the turns connecting the strands. At high energies, discrete breathers stabilize the structure by concentrating energy on few sites, while their collapse marks the onset of large-amplitude fluctuations of the protein. Furthermore, we show how breathers develop as energy-accumulating centres following perturbations even at distant locations, thus mediating efficient and irreversible energy transfers. Remarkably, due to the presence of angular potentials, the breather induces a local static distortion of the native fold. Altogether, the combination of this two nonlinear effects may provide a ready means for remotely controlling local conformational changes in proteins.Comment: Submitted to Physical Biolog

Dynamical response of the Hodgkin-Huxley model in the high-input regime

The response of the Hodgkin-Huxley neuronal model subjected to stochastic uncorrelated spike trains originating from a large number of inhibitory and excitatory post-synaptic potentials is analyzed in detail. The model is examined in its three fundamental dynamical regimes: silence, bistability and repetitive firing. Its response is characterized in terms of statistical indicators (interspike-interval distributions and their first moments) as well as of dynamical indicators (autocorrelation functions and conditional entropies). In the silent regime, the coexistence of two different coherence resonances is revealed: one occurs at quite low noise and is related to the stimulation of subthreshold oscillations around the rest state; the second one (at intermediate noise variance) is associated with the regularization of the sequence of spikes emitted by the neuron. Bistability in the low noise limit can be interpreted in terms of jumping processes across barriers activated by stochastic fluctuations. In the repetitive firing regime a maximization of incoherence is observed at finite noise variance. Finally, the mechanisms responsible for spike triggering in the various regimes are clearly identified.Comment: 14 pages, 24 figures in eps, submitted to Physical Review

Ultrasonography of salivary glands in primary Sjögren's syndrome: A comparison with contrast sialography and scintigraphy

Objective. To compare ultrasonography (US) of salivary glands with contrast sialography and scintigraphy, in order to evaluate the diagnostic value of this method in primary SS (pSS). Methods. The diagnostic value of parotid gland US was studied in 77 patients with pSS (male/female ratio 3/74; mean age 54 yrs) and in 79 with sicca symptoms but without SS. The two groups were matched for sex and age. Imaging findings of US were graded using an ultrasonographic score ranging from 0 to 16, which was obtained by the sum of the scores for each parotid and submandibular gland. The sialographic and scintigraphic patterns were classified in four different stages. The area under receiver operating characteristic curve (AUC-ROC) was employed to evaluate the screening methods performance. Results. Of the 77 patients with pSS, 66 had abnormal US findings. Mean US score in pSS patients was 9.0 (range from 3 to 16). Subjects without confirmed pSS had the mean US score 3.9 (range from 0 to 9) (P < 0.0001). Results of sialography showed that 59 pSS patients had abnormal findings at Stage 1 (n = 4), Stage 2 (n = 8), Stage 3 (n = 33) or Stage 4 (n = 14), and 58 patients had abnormal scintigraphic findings at Stage 1 (n = 11), Stage 2 (n = 18), Stage 3 (n = 25) or Stage 4 (n = 4). Through ROC curves US arose as the best performer (AUC = 0.863 +/- 0.030), followed by sialography (AUC = 0.804 +/- 0.035) and by salivary gland scintigraphy (AUC = 0.783 +/- 0.037). The difference between AUC-ROC curve of salivary gland US and scintigraphy was significant (P = 0.034). Setting the cut-off score 6 US resulted in the best ratio of sensitivity (75.3%) to specificity (83.5%), with a likelihood ratio of 4.58. If a threshold 8.0 was applied the test gained specificity, at the cost of a serious loss of sensitivity (sensitivity 54.5%, specificity 97.5%, likelihood ratio 21.5). Conclusions. Salivary gland US is a useful method in visualizing glandular structural changes in patients suspected of having pSS and it may represent a good option as a first-line imaging tool in the diagnostics of the disease

Extra-articular rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease that mainly affects the joints, though a consistent proportion of patients may also display extra articular manifestations (EAMs). From rheumatoid nodules to interstitial lung disease, from cardiovascular events to vasculitis, the spectrum of EAMs encompasses various conditions with different prognoses. EAMs may also occur as first RA manifestation, therefore the coordination with other health professionals, including general practitioners, is needed. The aim of this article is to provide an overview on EAMs in RA with particular focus on the recognised risk factors and the available recommendations for managing them, as well as comorbidities in RA patients

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

Relationship between the prevalence of subclinical tenosynovitis and treatment in patients with RA in clinical remission: STARTER study

Objective: This study is a sub-analysis from the patient cohort of the STARTER (Sonographic Tenosynovitis Assessment in RheumaToid arthritis patiEnts in Remission) study. The aim was to evaluate differences in ultrasound-detected joint and/or tendon involvement between patients receiving therapies based on a combination of conventional synthetic DMARDs (csDMARDs) and biologic DMARDs (bDMARDs) and those who were treated with either csDMARDs or bDMARDs in monotherapy. Material and methods: Four hundred and twenty-seven consecutive patients with a diagnosis of RA were recruited between October 2013 and June 2014. They were divided into three subgroups based on their therapy at baseline: patients with bDMARD in monotherapy, patients with csDMARD in monotherapy and patients in combination therapy (csDMARD + bDMARD). At baseline, 6 months and 12 months, a clinical examination (28 joint count) and an ultrasound evaluation were performed in each patient. A score of grey-scale (GS) and power Doppler (PD) synovitis and tenosynovitis was calculated based on the OMERACT scoring systems. Results: Two hundred and fifty-six patients completed the observation period: 48 patients from the bDMARD group (18.75%), 152 patients from the csDMARD group (59.38%) and 56 patients from csDMARD + bDMARD group (21.88%). The analysis showed that GS tenosynovitis and PD tenosynovitis are better controlled in combination therapy than they are ith csDMARD alone (P=0.025 and P=0.047, respectively); for PD synovitis, there was a better response in those who were treated with the combination therapy when compared with the patients receiving csDMARD (P=0.01) or bDMARD (P=0.02) alone. Conclusions: The analysis showed a lower prevalence of subclinical inflammatory manifestations detected with ultrasound imaging in those patients treated with the combination therapy than in those in monotherapy

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role