Paediatric HIV infection in the 'omics era: defining transcriptional signatures of viral control and vaccine responses

Modern technologies and their increased accessibility have shifted 'benchtop' medical research to the larger dimension of 'omics. The huge amount of data derived from gene expression and sequencing experiments has propelled physicians, basic scientists and bioinformaticians towards a common goal to transform 'big data' into predictive constructs that are readily available and will offer clinical utility. Although most of the studies available in the literature have been performed on healthy subjects and in peripheral blood mononuclear cells (PBMC), which are a heterogenous and extremely variable pool of cells, scientists are now trying to address mechanistic questions in purified cell subsets in pathological conditions. In the field of HIV, few attempts have been made to comprehensively evaluate gene-expression profiles of infected patients with different disease status. With the view of discovering a path towards remission or viral eradication, perinatally HIV-infected children represent a unique model. In fact the well-defined time of infection and the resulting opportunity to start early treatment, thereby generating a smaller size of viral reservoir and a more intact immune system, allow for investigation of therapeutic strategies to defeat the virus. In this scenario, 'transcriptomic' or gene expression technologies and supporting bioinformatics applications need to be strategically integrated to provide novel information about immune correlates of virus control following treatment interruption. Here we review modern techniques for gene expression analysis and discuss the best transcriptomic strategies applicable to the field of functional cure in paediatric HIV infection

Low- to high-velocity frictional properties of the clay-rich gouges from the slipping zone of the 1963 Vaiont slide, northern Italy

The final slip of about 450 m at about 30 m/s of the 1963 Vaiont landslide (Italy) was preceded by >3 year long creeping phase which was localized in centimeter-thick clay-rich layers (60–70% smectites, 20–30% calcite and quartz). Here we investigate the frictional properties of the clay-rich layers under similar deformation conditions as during the landslide: 1–5 MPa normal stress, 2 × 10^(−7) to 1.31 m/s slip rate and displacements up to 34 m. Experiments were performed at room humidity and wet conditions with biaxial, torsion and rotary shear apparatus. The clay-rich gouge was velocity-independent to velocity-weakening in both room humidity and wet conditions. In room humidity experiments, the coefficient of friction decreased from 0.47 at v 0.70 m/s: full lubrication results from the formation of a continuous water film in the gouge. The Vaiont landslide occurred under wet to saturated conditions. The unstable behavior of the landslide is explained by the velocity-weakening behavior of the Vaiont clay-rich gouges. The formation of a continuous film of liquid water in the slipping zone reduced the coefficient of friction to almost zero, even without invoking the activation of thermal pressurization. This explains the extraordinary high velocity achieved by the slide during the final collapse

QRS Complex Separation from Convolutive Mixtures of Biolectrical Signals Acquired by Wearable Systems

Independent component analysis (ICA) has been widely used to remove artefacts from multichannel biomedical signal acquisitions under the hypothesis that there is statistical independence among the original sources. However, the basic ICA model does not take into account the influence on the mixing process of the different paths from the signal sources to the sensors In this study we propose a convolutive mixtures model in order to overcome the limitations of the basic ICA approach. The independent components are estimated in the frequency domain, where the convolutive model can be solved through an instantaneous mixing model. The signals are reconstructed back to the observation space resolving the ICA model ambiguities. Simulations are carried out to optimize of the proposed method for convolutive mixtures of electrocardiographic (ECG) and motion artefacts signals. The algorithm is tested on real ECG signals acquired by wearable systems in order to preserve the QRS complex when the signals are degraded by real life conditions of acquisition

A Wireless Flexible Sensorized Insole for Gait Analysis

This paper introduces the design and development of a novel pressure-sensitive foot insole for real-time monitoring of plantar pressure distribution during walking. The device consists of a flexible insole with 64 pressure-sensitive elements and an integrated electronic board for high-frequency data acquisition, pre-filtering, and wireless transmission to a remote data computing/storing unit. The pressure-sensitive technology is based on an optoelectronic technology developed at Scuola Superiore Sant'Anna. The insole is a low-cost and low-power battery-powered device. The design and development of the device is presented along with its experimental characterization and validation with healthy subjects performing a task of walking at different speeds, and benchmarked against an instrumented force platform

A flexible sensor technology for the distributed measurement of interaction pressure

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted

A Multimodal Perception Framework for Users Emotional State Assessment in Social Robotics

In this work, we present an unobtrusive and non-invasive perception framework based on the synergy between two main acquisition systems: the Touch-Me Pad, consisting of two electronic patches for physiological signal extraction and processing; and the Scene Analyzer, a visual-auditory perception system specifically designed for the detection of social and emotional cues. It will be explained how the information extracted by this specific kind of framework is particularly suitable for social robotics applications and how the system has been conceived in order to be used in human-robot interaction scenarios

Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions

Monitoring physical activities during post-stroke rehabilitation in daily life may help physicians to optimize and tailor the training program for patients. The European research project INTERACTION (FP7-ICT-2011-7-287351) evaluated motor capabilities in stroke patients during the recovery treatment period. We developed wearable sensing platform based on the sensor fusion among inertial, knitted piezoresistive sensors and textile EMG electrodes. The device was conceived in modular form and consists of a separate shirt, trousers, glove, and shoe. Thanks to the novel fusion approach it has been possible to develop a model for the shoulder taking into account the scapulo-thoracic joint of the scapular girdle, considerably improving the estimation of the hand position in reaching activities. In order to minimize the sensor set used to monitor gait, a single inertial sensor fused with a textile goniometer proved to reconstruct the orientation of all the body segments of the leg. Finally, the sensing glove, endowed with three textile goniometers and three force sensors showed good capabilities in the reconstruction of grasping activities and evaluating the interaction of the hand with the environment, according to the project specifications. This paper reports on the design and the technical evaluation of the performance of the sensing platform, tested on healthy subjects

A soft robot structure with limbless resonant, stick and slip locomotion

We present a smart robot structure that exploits anisotropic friction to achieve stick-slip locomotion. The robot is made out of three components: a plastic beam, a planar dielectric elastomer actuator and four bristle pads with asymmetric rigid metallic bristles. We show that when the robot is electronically activated at increasing frequency, its structure exploits the resonance condition to reach the maximum locomotion speed. The fundamental frequency of the structure is estimated both analytically and numerically, allowing the range of frequencies in which the top locomotion speed was observed during the experiments to be identified. The locomotion speed of the robot as a function of the actuation frequency is estimated with a frequency response analysis performed on a discretised model of the structure, revealing good agreement with the experimental evidence