Assessment of poststress left ventricular ejection fraction by gated SPECT: comparison with equilibrium radionuclide angiocardiography

PURPOSE: We compared left ventricular (LV) ejection fraction obtained by gated SPECT with that obtained by equilibrium radionuclide angiocardiography in a large cohort of patients. METHODS: Within 1 week, 514 subjects with suspected or known coronary artery disease underwent same-day stress-rest (99m)Tc-sestamibi gated SPECT and radionuclide angiocardiography. For both studies, data were acquired 30 min after completion of exercise and after 3 h rest. RESULTS: In the overall study population, a good correlation between ejection fraction measured by gated SPECT and by radionuclide angiocardiography was observed at rest (r=0.82, p<0.0001) and after stress (r=0.83, p<0.0001). In Bland-Altman analysis, the mean differences in ejection fraction (radionuclide angiocardiography minus gated SPECT) were -0.6% at rest and 1.7% after stress. In subjects with normal perfusion (n=362), a good correlation between ejection fraction measured by gated SPECT and by radionuclide angiocardiography was observed at rest (r=0.72, p<0.0001) and after stress (r=0.70, p<0.0001) and the mean differences in ejection fraction were -0.9% at rest and 1.4% after stress. Also in patients with abnormal perfusion (n=152), a good correlation between the two techniques was observed both at rest (r=0.89, p<0.0001) and after stress (r=0.90, p<0.0001) and the mean differences in ejection fraction were 0.1% at rest and 2.5% after stress. CONCLUSION: In a large study population, a good agreement was observed in the evaluation of LV ejection fraction between gated SPECT and radionuclide angiocardiography. However, in patients with perfusion abnormalities, a slight underestimation in poststress LV ejection fraction was observed using gated SPECT as compared to equilibrium radionuclide angiocardiography

Improving P300 Speller performance by means of optimization and machine learning

Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous system (PNS). These interfaces record a user’s brain activity and translate it into control commands for external devices, thus providing the PNS with additional artificial outputs. In this framework, the BCIs based on the P300 Event-Related Potentials (ERP), which represent the electrical responses recorded from the brain after specific events or stimuli, have proven to be particularly successful and robust. The presence or the absence of a P300 evoked potential within the EEG features is determined through a classification algorithm. Linear classifiers such as stepwise linear discriminant analysis and support vector machine (SVM) are the most used discriminant algorithms for ERPs’ classification. Due to the low signal-to-noise ratio of the EEG signals, multiple stimulation sequences (a.k.a. iterations) are carried out and then averaged before the signals being classified. However, while augmenting the number of iterations improves the Signal-to-Noise Ratio, it also slows down the process. In the early studies, the number of iterations was fixed (no stopping environment), but recently several early stopping strategies have been proposed in the literature to dynamically interrupt the stimulation sequence when a certain criterion is met in order to enhance the communication rate. In this work, we explore how to improve the classification performances in P300 based BCIs by combining optimization and machine learning. First, we propose a new decision function that aims at improving classification performances in terms of accuracy and Information Transfer Rate both in a no stopping and early stopping environment. Then, we propose a new SVM training problem that aims to facilitate the target-detection process. Our approach proves to be effective on several publicly available datasets

Targeted Protein Degradation for Infectious Diseases: from Basic Biology to Drug Discovery

Targeted protein degradation (TPD) is emerging as one of the most innovative strategies to tackle infectious diseases. Particularly, proteolysis-targeting chimera (PROTAC)-mediated protein degradation may offer several benefits over classical anti-infective small-molecule drugs. Because of their peculiar and catalytic mechanism of action, anti-infective PROTACs might be advantageous in terms of efficacy, toxicity, and selectivity. Importantly, PROTACs may also overcome the emergence of antimicrobial resistance. Furthermore, anti-infective PROTACs might have the potential to (i) modulate "undruggable"targets, (ii) "recycle"inhibitors from classical drug discovery approaches, and (iii) open new scenarios for combination therapies. Here, we try to address these points by discussing selected case studies of antiviral PROTACs and the first-in-class antibacterial PROTACs. Finally, we discuss how the field of PROTAC-mediated TPD might be exploited in parasitic diseases. Since no antiparasitic PROTAC has been reported yet, we also describe the parasite proteasome system. While in its infancy and with many challenges ahead, we hope that PROTAC-mediated protein degradation for infectious diseases may lead to the development of next-generation anti-infective drugs

Noninvasive Ultrasound Monitoring of Embryonic and Fetal Development in Chinchilla lanigera to Predict Gestational Age: Preliminary Evaluation of This Species as a Novel Animal Model of Human Pregnancy

Ultrasound is a noninvasive routine method that allows real-time monitoring of fetal development in utero to determine gestational age and to detect congenital anomalies and multiple pregnancies. To date, the developmental biology of Chinchilla lanigera has not yet been characterized. This species has been found to undergo placentation, long gestation, and fetal dimensions similar to those in humans. The aim of this study was to assess the use of high-frequency ultrasound (HFUS) and clinical ultrasound (US) to predict gestational age in chinchillas and evaluate the possibility of this species as a new animal model for the study of human pregnancy. In this study, 35 pregnant females and a total of 74 embryos and fetuses were monitored. Ultrasound examination was feasible in almost all chinchilla subjects. It was possible to monitor the chinchilla embryo with HFUS from embryonic day (E) 15 to 60 and with US from E15 to E115 due to fetus dimensions. The placenta could be visualized and measured with HFUS from E15, but not with US until E30. From E30, the heartbeat became detectable and it was possible to measure fetal biometrics. In the late stages of pregnancy, stomach, eyes, and lenses became visible. Our study demonstrated the importance of employing both techniques while monitoring embryonic and fetal development to obtain an overall and detailed view of all structures and to recognize any malformation at an early stage. Pregnancy in chinchillas can be confirmed as early as the 15th day postmating, and sonographic changes and gestational age are well correlated. The quantitative measurements of fetal and placental growth performed in this study could be useful in setting up a database for comparison with human fetal ultrasounds. We speculate that, in the future, the chinchilla could be used as an animal model for the study of US in human pregnancy

GIADA performance during Rosetta mission scientific operations at comet 67P

The Grain Impact Analyser and Dust Accumulator (GIADA) instrument onboard Rosetta studied the dust environment of comet 67P/Churyumov–Gerasimenko from 3.7 au inbound, through perihelion, to 3.8 au outbound, measuring the dust flow and the dynamic properties of individual particles. GIADA is composed of three subsystems: 1) Grain Detection System (GDS); 2) Impact Sensor (IS); and 3) Micro-Balances System (MBS). Monitoring the subsystems’ performance during operations is an important element for the correct calibration of scientific measurements. In this paper, we analyse the GIADA inflight calibration data obtained by internal calibration devices for the three subsystems during the period from 1 August 2014 to 31 October 2015. The calibration data testify a nominal behaviour of the instrument during these fifteen months of mission; the only exception is a minor loss of sensitivity for one of the two GDS receivers, attributed to dust contamination

Status of the Cylindical-GEM project for the KLOE-2 Inner Tracker

The status of the R&D on the Cylindrical-GEM (CGEM) detector foreseen as Inner Tracker for KLOE-2, the upgrade of the KLOE experiment at the DAFNE phi-factory, will be presented. The R&D includes several activities: i) the construction and complete characterization of the full-size CGEM prototype, equipped with 650 microns pitch 1-D longitudinal strips; ii) the study of the 2-D readout with XV patterned strips and operation in magnetic field (up to 1.5T), performed with small planar prototypes in a dedicated test at the H4-SPS beam facility; iii) the characterization of the single-mask GEM technology for the realization of large-area GEM foils.Comment: 4 pages, 10 figures, Presented at Vienna Conference on Instrumentation (Feb 15-20, 2010, Vienna, Austria). Submitted to the Proceeding

An 18F-labeled poly(ADP-ribose) polymerase positron emission tomography imaging agent

Poly(ADP-ribose) polymerase (PARP) is involved in repair of DNA breaks and is over-expressed in a wide variety of tumors, making PARP an attractive biomarker for positron emission tomography (PET) and single photon emission computed tomography imaging. Consequently, over the past decade, there has been a drive to develop nuclear imaging agents targeting PARP. Here, we report the discovery of a PET tracer that is based on the potent PARP inhibitor olaparib (1). Our lead PET tracer candidate, [18F]20, was synthesized and evaluated as a potential PARP PET radiotracer in mice bearing subcutaneous glioblastoma xenografts using ex vivo biodistribution and PET−magnetic resonance imaging techniques. Results showed that [18F]20 could be produced in a good radioactivity yield and exhibited specific PARP binding allowing visualization of tumors overexpressing PARP. [18F]20 is therefore a potential candidate radiotracer for in vivo PARP PET imaging

Validation of statistical clustering on TES dataset using synthetic Martian spectra

In this work we present some results concerning the analysis of Thermal Emission Spectrometer (TES) data, looking at the methane Q-branch spectral signature at 1304 cm-1. Such analysis has been enabled by producing some synthetic spectral datasets, simulating the atmospheric and surface variability observed on Mars, excluding the high latitude regions. The use of synthetic spectra is aimed to provide a better comprehension of the influence that the atmospheric state vector and its composition have on the spectral behavior. This effort is important, because the TES data are characterized by a low resolution (10 cm-1) and a significant random and systematic noise which could, in principle, give results whose quality needs to be improved. We apply statistical clustering of the synthetic spectra to evaluate the effectiveness of detecting methane, and estimating its abundance