Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems

Cool Core Clusters from Cosmological Simulations

We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non-cool-core systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and in observations. Furthermore, we also find that simulated cool-core clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic cool-core structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.Comment: 6 pages, 4 figures, accepted in ApJL, v2 contains some modifications on the text (results unchanged

Beta-blocker treatment guided by head-up tilt test in neurally mediated syncope

This study was an open-label, uncontrolled, dose-escalation trial of beta-blockers in patients with a history of syncope without warning or syncope resulting in trauma (malignant vasovagal syncope) who had positive head-up tilt test (HUT) responses, with or without isoproterenol infusion. Thirty patients (mean age, 37 +/- 21 years) with recurrent syncopal and near-syncopal episodes of unexplained origin in the previous year (6 +/- 14 syncopal episodes and 17 +/- 3 near-syncopes) underwent HUT for diagnostic purposes and for guiding prophylactic treatment. After patients were given a 10-minute rest in a recumbent position, rye performed an WT at 70 degrees for 25 minutes; if indicated, isoproterenol testing was performed at incremental dosages (dye steps at 10-minute intervals at 80 degrees), AU patients experienced syncope during HUT, 15 (50%) at baseline HUT and 15 (50%) during isoproterenol infusion (1 to 3 mu g/min; mean, 1.6 mu g/min). Sixteen syncopes were of vasodepressor type, 10 were mixed, and 4 were of cardioinhibitory type. After baseline HUT, betablocking drugs were prescribed to all patients as follows: 1 patient was given propranolol (160 mg daily), and 29 patients were given metoprolol (246 +/- 49 mg daily), with a dose titration period of 14 days. HUT was repeated after 3 weeks, and 24 patients (80%) had negative results (no syncope or anomalous responses). After further dosage adjustment of beta-blockers in nonresponders, a negative HUT was obtained in 28 patients (93%). Overall mean metoprolol daily dose was 262 +/- 60 mg (29 patients), and propranolol was administered at 160 mg daily in 1 patient. Thirteen patients (43%) reported side effects, none of which required drug withdrawal. At an average follow-up of 16 +/- 4 months, none of the patients experienced syncope, a statistically significant reduction. Moreover, a statistically significant reduction in the number of near-syncopal episodes was observed in comparison to the previous year. None of the patients discontinued treatment because of long-term side effects. Beta-blockers were well tolerated and achieved a high rate of efficacy, even in cardioinhibitory syncopes. In conclusion, in selected patients with malignant vasovagal syncope, treatment with metoprolol or propranolol at relatively high doses is feasible and, if guided by HUT results, is associated with a favorable outcome in terms of freedom from syncopal recurrences. Appropriate titration to achieve the full beta-blocking effect appears to be advisable

Is Social Training Delivered with a Head-Mounted Display Suitable for Patients with Hereditary Ataxia?

Social cognition is fundamental in everyday life to understand “others’ behavior”, which is a key feature of social abilities. Previous studies demonstrated the efficacy of a rehabilitative intervention in semi-immersive virtual reality (VR) controlled by whole-body motion to improve the ability of patients with cerebellar disorders to predict others’ intentions (VR-SPIRIT). Patients with severe ataxia that have difficulties at multiple levels of social processing could benefit from this intervention in terms of improving their social prediction skills, but they may have difficulties in controlling VR with whole-body movements. Therefore, we implemented VR-SPIRIT on a wearable, affordable, and easy-to-use technology, such as the Oculus Quest, a head-mounted display. The aim of this work was to evaluate the usability and tolerability of this VR application. We recruited 10 patients (37.7 ± 14.8 years old, seven males) with different types of hereditary ataxia who performed a single VR-SPIRIT session using the Oculus Quest viewer. After the session, patients answered a series of questionnaires to investigate the overall usability of the system and its potential effects in terms of cyber sickness. The preliminary results demonstrated system usability and tolerability. Indeed, only three patients did not complete the session due to different problems (dizziness, nausea, and boredom). In future studies, more patients will be enrolled to assess the effectiveness of the application, paving the way for the implementation of social training that can also be delivered at home

Cosmological hydrodynamical simulations of galaxy clusters: X-ray scaling relations and their evolution

We analyse cosmological hydrodynamical simulations of galaxy clusters to study the X-ray scaling relations between total masses and observable quantities such as X-ray luminosity, gas mass, X-ray temperature, and $Y_{X}$. Three sets of simulations are performed with an improved version of the smoothed particle hydrodynamics GADGET-3 code. These consider the following: non-radiative gas, star formation and stellar feedback, and the addition of feedback by active galactic nuclei (AGN). We select clusters with $M_{500} > 10^{14} M_{\odot} E(z)^{-1}$, mimicking the typical selection of Sunyaev-Zeldovich samples. This permits to have a mass range large enough to enable robust fitting of the relations even at $z \sim 2$. The results of the analysis show a general agreement with observations. The values of the slope of the mass-gas mass and mass-temperature relations at $z=2$ are 10 per cent lower with respect to $z=0$ due to the applied mass selection, in the former case, and to the effect of early merger in the latter. We investigate the impact of the slope variation on the study of the evolution of the normalization. We conclude that cosmological studies through scaling relations should be limited to the redshift range $z=0-1$, where we find that the slope, the scatter, and the covariance matrix of the relations are stable. The scaling between mass and $Y_X$ is confirmed to be the most robust relation, being almost independent of the gas physics. At higher redshifts, the scaling relations are sensitive to the inclusion of AGNs which influences low-mass systems. The detailed study of these objects will be crucial to evaluate the AGN effect on the ICM.Comment: 24 pages, 11 figures, 5 tables, replaced to match accepted versio

Effect of practical layered dielectric loads on SAR patterns from dual concentric conductor microstrip antennas

Radiation patterns of 2 and 4cm square Dual Concentric Conductor (DCC) microstrip antennas were studied theoretically with Finite Difference Time Domain (FDTD) analysis and compared with experimental measurements of power deposition (SAR) in layered lossy dielectric loads. Single and array configurations were investigated with 915 MHz excitation applied across either one, two or four sides, or four corners of the square apertures. FDTD simulations were carried out for realistic models of a muscle tissue load coupled to the DCC antennas with a 5 mm thick bolus of either distilled water or low loss Silicone Oil. This study characterizes the effect on SAR of adding three additional thin dielectric layers which are necessary for clinical use of the applicator. These layers consist of a 0.1 mm thick dielectric coating on the array surface to provide electrical isolation of DCC apertures, and 0.15 mm thick plastic layers above and below the bolus to contain the liquid. Experimental measurements of SAR in a plane 1 cm deep in muscle phantom agree well with theoretical FDTD simulations in the multi-layered tissue models. These studies reveal significant changes in SAR for applicator configurations involving low dielectric constant (Er) layers on either side of a high Er water bolus layer. Prominent changes include a broadening and centring of the SAR under each aperture as well as increased SAR penetration in muscle. No significant differences are noted between the simple and complete load configurations for the low Er Silicone Oil bolus. Both theoretical and measured data demonstrate relatively uniform SAR distributions with50% of maximum SAR extending to the perimeter of single and multi-aperture array configurations of DCC applicators when using a thin 5 mm water or Silicone Oil bolus

VHCF response of heat-treated SLM Ti6Al4V Gaussian specimens with large loaded volume

Abstract Among the materials used for the production of components through Additive Manufacturing (AM) processes, the Selective-Laser-Melting (SLM) Ti6Al4V alloy is widely employed in aerospace applications for its high specific strength and in biomedical applications for its good biocompatibility. Actual structural applications are generally limited to static loading conditions where the large defects originating during the SLM process do not play a significant role for the static failure. On the contrary, the same defects strongly affect the fatigue response of the parts since they act as crack initiation sites that rapidly lead to fatigue failure. In the literature, a lot of research has been carried out to investigate the quasi-static and the High-Cycle Fatigue properties of the SLM Ti6Al4V alloy but there are still few studies on its Very-High-Cycle Fatigue (VHCF) response. In the paper, the VHCF response of Ti6Al4V specimens, which are vertically orientated during the SLM building and then subjected to a conventional heat treatment (2 hours heating in vacuum at 850°C), is experimentally assessed. Ultrasonic VHCF tests are carried out on Gaussian specimens with a large risk-volume (2300 mm3). Fracture surfaces are investigated for revealing the defect originating the fatigue failure. The Stress Intensity Factor Threshold associated to the experimental failures is finally estimated

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of pathology-driven anatomical remodeling is a crucial step for the diagnosis and treatment of many conditions. Deep learning approaches have recently achieved wide success in the analysis of medical images, but they lack interpretability in the feature extraction and decision processes. In this work, we propose a new interpretable deep learning model for shape analysis. In particular, we exploit deep generative networks to model a population of anatomical segmentations through a hierarchy of conditional latent variables. At the highest level of this hierarchy, a two-dimensional latent space is simultaneously optimised to discriminate distinct clinical conditions, enabling the direct visualisation of the classification space. Moreover, the anatomical variability encoded by this discriminative latent space can be visualised in the segmentation space thanks to the generative properties of the model, making the classification task transparent. This approach yielded high accuracy in the categorisation of healthy and remodelled left ventricles when tested on unseen segmentations from our own multi-centre dataset as well as in an external validation set, and on hippocampi from healthy controls and patients with Alzheimer's disease when tested on ADNI data. More importantly, it enabled the visualisation in three-dimensions of both global and regional anatomical features which better discriminate between the conditions under exam. The proposed approach scales effectively to large populations, facilitating high-throughput analysis of normal anatomy and pathology in large-scale studies of volumetric imaging

Homologous Recombination Deficiency in Ovarian Cancer: from the Biological Rationale to Current Diagnostic Approaches

The inability to efficiently repair DNA double-strand breaks using the homologous recombination repair pathway is defined as homologous recombination deficiency (HRD). This molecular phenotype represents a positive predictive biomarker for the clinical use of poly (adenosine diphosphate [ADP]-ribose) polymerase inhibitors and platinum-based chemotherapy in ovarian cancers. However, HRD is a complex genomic signature, and different methods of analysis have been developed to introduce HRD testing in the clinical setting. This review describes the technical aspects and challenges related to HRD testing in ovarian cancer and outlines the potential pitfalls and challenges that can be encountered in HRD diagnostics

Longevity of implantable cardioverter-defibrillators: implications for clinical practice and health care systems

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