Giandomenico Nollo

Inhibition of Candida albicans adhesion on medical‐grade silicone by a Lactobacillus‐derived biosurfactant

The study aimed at investigating the ability of biosurfactant (BS) produced by a Lactobacillus brevis isolate (CV8LAC) to inhibit adhesion and biofilm formation of Candida albicans on medical‐grade silicone elastomeric disks (SEDs).

Critical Issues in Reprocessing Single-Use Medical Devices for Interventional Cardiology

1.1 Single-use vs. multiple use medical devices During the 1960s and the early 1970s, most medical devices made of glass, rubber, or metal were generally considered to be reusable. This concept did not change until the late 1970s, when medical devices started to enter the market labelled “single-use only” . During the same decades, clinical medicine has undergone substantial changes, with traditional open surgical procedures giving way to new minimally invasive techniques such as endovascular and laparoscopic intervention. Such procedures required new instruments allowing delicate and complex manipulations through small incisions, with the effector portion of the device located some distance from the operator’s hand, demanding stable and predictable performance. During this same period, patients and clinicians have become increasingly concerned about the risk of infectious disease transmission, particularly human immunodeficiency virus and hepatitis B and C viruses. One solution to both demands was found in single-use devices (SUDs), shaped from newly developed fabrication materials, firstly polymers, and intended to be discarded after use on a given patient. Consequently, the past three decades have seen an explosion in the production and use of single-use medical devices, stemming from a desire to improve product performance and minimize the potential for disease transmission, and enabled by advances in manufacturing techniques.

Quantifying Changes in EEG Complexity Induced by Photic Stimulation

OBJECTIVES This study aims to characterize EEG complexity, measured as the prediction error resulting from nonlinear prediction, in healthy humans during photic stimulation. METHODS EEGs were recorded from 15 subjects with eyes closed (EC) and eyes open (EO), during the baseline condition and during stroboscopic photic stimulation (PS) at 5, 10, and 15 Hz. The mean squared prediction error (MSPE) resulting from nearest neighbor local linear prediction was taken as complexity index. Complexity maps were generated interpolating the MSPE index over a schematic scalp representation. RESULTS Statistical analysis revealed that: i) EEG shows good predictability in all conditions and seems to be well explained by a linear stochastic process; ii) the complexity is lower with EC than with EO and increases significantly during PS, to a lesser extent during 10 Hz stimulation; iii) significant differences of EEG complexity are detectable between anterior-central and posterior scalp regions. CONCLUSIONS Changes in EEG complexity during PS can be successfully assessed using nonlinear prediction. The observed modifications in the patterns of complexity seem to reflect neurophysiological behaviors and suggest future applicability of the method in clinical settings.

Implantable Cardioverter-Defibrillator in Dilated Cardiomyopathy after the DANISH-Trial Lesson. A Poly-Parametric Risk Evaluation Is Needed to Improve the Selection of Patients

Citation: Disertori M, Masè M, Rigoni M, Nollo G, Arbustini E and Ravelli F (2017) Implantable Cardioverter-Defibrillator in Dilated Cardiomyopathy after the DANISH-Trial Lesson. A Poly-Parametric Risk Evaluation Is Needed to Improve the Selection of Patients. Front. Physiol. 8:873. doi: 10.3389/fphys.2017.00873 Implantable Cardioverter-Defibrillator in Dilated Cardiomyopathy after the DANISH-Trial Lesson. A Poly-Parametric Risk Evaluation Is Needed to Improve the Selection of Patients

Information-theoretic assessment of cardiovascular-brain networks during sleep

This study was aimed at detecting the structure of the physiological network underlying the regulation of the cardiovascular and brain systems during normal sleep. To this end, we measured from the polysomnographic recordings of 10 healthy subjects the normalized spectral power of heart rate variability in the high frequency band (HF) and the EEG power in the δ, θ, α, σ, and β bands. Then, the causal statistical dependencies within and between these six time series were assessed in terms of internal information (conditional self entropy, CSE) and information transfer (transfer entropy, TE) computed via a linear method exploiting multiple regression models and a nonlinear method combining nearest neighbour entropy estimation with dimensionality reduction. The statistical significance of CSE and TE was assessed using an F-test for the linear method, and an empirical randomization test for the nonlinear method. Both approaches consistently detected structured networks of physiological interactions, revealing (i) strong internal information in all systems; (ii) information transfer directed predominantly from heart to brain; (iii) bidirectional interactions between HF and β EEG power. Moreover, the nonlinear method evidenced higher information flowing out of the δ node. These results highlight the potential of the information-theoretic framework to assess linear and nonlinear dynamics manifested in the functional network that underlies the autonomic regulation of cardiovascular and brain functions during sleep.