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BACKGROUND Increases in cardiac troponin (cTn) in coronavirus disease 2019 (COVID-19) have been associated with worse prognosis. Nonetheless, data about the significance of cTn in elderly subjects with COVID-19 are lacking. METHODS From a registry of consecutive patients with COVID-19 admitted to a hub hospital in Italy from 25/02/2020 to 03/07/2020, we selected those ≥ 60 year-old and with cTnI measured within three days from the molecular diagnosis of SARS-CoV-2 infection. When available, a second cTnI value within 48 h was also extracted. The relationship between increased cTnI and all-cause in-hospital mortality was evaluated by a Cox regression model and restricted cubic spline functions with three knots. RESULTS Of 343 included patients (median age: 75.0 (68.0−83.0) years, 34.7% men), 88 (25.7%) had cTnI above the upper-reference limit (0.046 µg/L). Patients with increased cTnI had more comorbidities, greater impaired respiratory exchange and higher inflammatory markers on admission than those with normal cTnI. Furthermore, they died more (73.9%vs. 37.3%, P < 0.001) over 15 (6−25) days of hospitalization. The association of elevated cTnI with mortality was confirmed by the adjusted Cox regression model (HR = 1.61, 95%CI: 1.06−2.52, P = 0.039) and was linear until 0.3 µg/L, with a subsequent plateau. Of 191 (55.7%) patients with a second cTnI measurement, 49 (25.7%) had an increasing trend, which was not associated with mortality (univariate HR = 1.39, 95%CI: 0.87−2.22, P = 0.265). CONCLUSIONS In elderly COVID-19 patients, an initial increase in cTn is common and predicts a higher risk of death. Serial cTn testing may not confer additional prognostic information.

The SARS-CoV-2 infection causes severe respiratory involvement (COVID-19) in 5–20% of patients through initial immune derangement, followed by intense cytokine production and vascular leakage. Evidence of immune involvement point to the participation of T, B, and NK cells in the lack of control of virus replication leading to COVID-19. NK cells contribute to early phases of virus control and to the regulation of adaptive responses. The precise mechanism of NK cell dysregulation is poorly understood, with little information on tissue margination or turnover. We investigated these aspects by multiparameter flow cytometry in a cohort of 28 patients hospitalized with early COVID-19. Relevant decreases in CD56brightCD16+/- NK subsets were detected, with a shift of circulating NK cells toward more mature CD56dimCD16+KIR+NKG2A+ and “memory” KIR+CD57+CD85j+ cells with increased inhibitory NKG2A and KIR molecules. Impaired cytotoxicity and IFN-γ production were associated with conserved expression of natural cytotoxicity receptors and perforin. Moreover, intense NK cell activation with increased HLA-DR and CD69 expression was associated with the circulation of CD69+CD103+ CXCR6+ tissue-resident NK cells and of CD34+DNAM-1brightCXCR4+ inflammatory precursors to mature functional NK cells. Severe disease trajectories were directly associated with the proportion of CD34+DNAM-1brightCXCR4+ precursors and inversely associated with the proportion of NKG2D+ and of CD103+ NK cells. Intense NK cell activation and trafficking to and from tissues occurs early in COVID-19, and is associated with subsequent disease progression, providing an insight into the mechanism of clinical deterioration. Strategies to positively manipulate tissue-resident NK cell responses may provide advantages to future therapeutic and vaccine approaches., Author summary This is a detailed study of activating and inhibitory receptors in NK cells of COVID-19 patients when first admitted to the hospital for respiratory insufficiency. NK cells are known to be the first line of defense against invading viruses, and regulate downstream B and T cell responses, including antibody production. We observed intense NK cell activation with decreased functional activity, as well as intense circulation of putative tissue resident CD69+CD103+CXCR6+ NK cells, with a related surge in inflammatory CD34+ precursors from the bone marrow. The findings suggest that there is unprecedented trafficking of NK cells from peripheral tissues, their increased death with recruitment of emergency precursors from the bone marrow, and a relationship with the subsequent course of the disease of the patients. This in turn suggests possible areas of treatment and prevention.

Introduction. Following the observation that 1 or 2 pandemic peak due to the circulation of AH1N1v had occurred in most countries and in most World Health Organization (WHO) Regions, WHO declared on August 10th, 2010 that the world was moving into the post-pandemic period, whose surveillance presents considerable interest both from epidemiological and clinical point of view. We described the epidemiological picture emerged from syndromic and virological surveillance during the post-pandemic season in Liguria, Italy. Materials and methods. An Emergency Department Syndrome surveillance system, based on data collected at ?San Martino? and IRCCS ?G. Gaslini? Liguria Regional Reference University Hospitals for adults and children is active since July 2007. Monitored syndromes include ?Influenza-Like Illness? (ILI) and ?Low Respiratory Tract Infections? (LRTI). The Ligurian Regional Reference laboratory for Influenza virological surveillance and diagnosis offers rapid detection of influenza viruses by real-time and block RT-PCR, viral culture and genetic characterization by entire sequence analysis of haemagglutinin- and neuraminidase-coding regions in accordance with the international standards established by the global laboratory network. Results and discussion. The integration of syndromic surveillance system and laboratory surveillance for rapid detection and characterization of the disease responsible agent represented a specific and sensitive tool for influenza surveillance. The post-pandemic season was characterized by early onset and by the heaviest impacts for ILI and LRTI among the recent epidemic seasons. In contrast to the picture observed during the pandemic season, the 2010/11 winter was characterized by the intensive circulation of pandemic AH1N1v coupled with sustained activity due to influenza B and Respiratory Syncytial Virus (RSV). Antigenic and molecular characterization of influenza strains confirmed the good matching between circulating and 2010/11 vaccine viruses., Journal of Preventive Medicine and Hygiene, Vol 52, No 3 (2011)

Background. A prevalence study aimed to update the epide- miological scenario of Hospital-Acquired Infections (HAI) was performed at the San Martino University Hospital of Genoa, the Regional Reference Adult-care Center in Liguria, Italy, with more than 1300 beds. Materials and methods. The investigation was performed in all the wards, except the Psychiatric Units, between 19th March and 6th April, 2007, using a one-day monitoring system for each ward. International standardized criteria and definitions for the surveillance of HAI were used for the collection of data, which were recorded in specific software for subsequent consolidation, analysis and quality control. Results. The hospital infection control staff actively monitored 912 inpatients: a total of 84 HAI among 72 patients were diag- nosed, with an overall prevalence of infections and affected cases of 9.2% (95% CI: 7.3-11.1) and 7.9% (95% CI: 6.1-9.7), respectively. Urinary Tract Infections (UTI) (30.9%), Respira- tory Tract Infections (RTI) (28.6%) and Blood Stream Infections (BSI) (21.4%) were found to be the most frequent infections. As expected, both specific prevalence and localization of HAI var- ied considerably between wards, with the highest values recorded in Intensive Care Units (ICU) and in Functional Rehabilitation wards. RTI (26.3%) and BSI (13.2%) were found primarily rep- resented in ICU, while the highest values of UTI (13.3%) were registered in Functional Rehabilitation Units. Enterococcus spp. (16.8%), Candida spp. (14%), Pseudomonas spp. (12.2), Staphylococcus aureus (10.7%), Escherichia coli (10.3%) and Coagulase-negative staphylococci (CNS) (9.3%) were the most frequent pathogens isolated. The overall rate of administration of antibiotics was 55.3% and penicillin (26.7%), cephalosporins (22.8%) and fluoroquinolones (17.9%) were found to be the leading antibacterial administered. Conclusion. Results of the present study have been, and are currently, used for orientating surveillance and control hospital policies, planning activities according to a rational and evidence- based approach., Journal of Preventive Medicine and Hygiene, Vol 51, No 2 (2010)

This paper presents a new approach to build RF dynamic behavioral models, based on time-delay neural networks (TDNNs), suitable for FET devices, and capable to identify the working class and to characterize both short- and long-term device memory, through a time-domain training procedure, for a wide range of input power levels. The presented model has been effectively applied to GaN-based devices, working in class A, AB and B

This paper presents a new RF dynamic behavioral model based on a neural network (NN) approach suitable for FET devices in a wide range of working classes, and capable to identify the device response, through the training procedure, for a wide range of input power levels. The presented model has been effectively applied to GaN-based devices at 1 GHz, working in class A and B.

A new method for characterization of HEMT distortion parameters, which extracts the coefficents of Taylor series expansion of Ids(Vgs,Vds), including all crossterms, from low-frequency harmonic measurements, has been developed. The extracted parameters will be used either in a Volterra series model around a fixed bias point for third order characterization of small-signal Ids nonlinearity, and in a large-signal model of Ids characteristic, where its partial derivatives have been locally characterized up to the third order in the whole bias region, using a novel neural network representation. The two models have been verified by harmonic measurements on a AMS HEMT at 5 GHz.

A new procedure to learn a nonlinear model together with its derivative parameters using a composite neural network is presented.So far neural networks have never been used to extract large-signal device model accounting for distortion parameters.Applying this method to FET devices leads to nonlinear models for current- voltage functions which allow improved prediction of weak and mildly device nonlinearities in the whole bias region. The resulting models have demonstrated to be suitable for both small-signal and large-signal analyses,including intermodulation distortion prediction.

This paper revisits an optical receiver topology, for a wavelength division multiplexing (WDM) optical network at 2.5 Gbps bit rate, based on non-tunable wavelength demultiplexing and electronic switching.We demonstrate novel, monolithically integrated, four-channel optical receiver module composed of MESFET transimpedance amplifiers and switches that can be independently switched “on” or “off” electronically by a digital signal. The selector chips have also been reconfigured as a 16 channel selector array. Frequency and noise performance as well as switching speed and crosstalk between neighboring channels have been investigated.

In this work two distinct optical receiver conjurations are investigated for use in the downstream direction of ATM PON networks based on wavelength division multiplexing (WDM). The goal is to overcome the slow tuning speed of optical filters, achieving channel selection in the nanosecond time frame and allowing the implementation of an efficient ATM/WDM protocol.

Artificial neural networks (ANNs)are presented for the fast and accurate modeling of passive and active devices in MMICs.ANNs trained with S-parameter over a wide range of frequencies were used for rectangular spiral inductor modeling and HEMT device small-signal models.After training and testing the ANN S-parameter model can be implemented as a two-port network into commercial circuit simulators.This enable the ANN model to be used in the design,analysis,and optimization of microwave circuits.A combination of ANN models trained with S-parameter and dc drain current measurements was implemented into an HP microwave circuit simulator to provide a small- signal bias-dependent active model.The proposed technique is capable of providing easy,fast and accurate simulation models for MMIC components where models based on equivalent circuit parameters (ECPs)do not exist or are not accurate over the desired region of operation.

A front-end discriminator for application in readout electronics of gas chamber particle detectors, composed of a high-gain pulse amplifier integrated with a threshold comparator and an ECL logic buffer, has been designed. An 8-channels full custom chip has been fabricated in GaAs IC technology. The chip turns out very stable, featuring high voltage gain (>1000), gain-bandwidth product (1011) and sensitivity (~50uV), fast rise time (1.5ns), and only 25mW per channel of power consumption, while providing the ECL dynamic to the output pulses.

A front-end circuit composed of a high gain pulse amplifier cascaded by a threshold comparator has been designed for application in readout electronics of particle detectors. A prototype realized with a 8CH full custom chip in GaAs technology by GIGA foundry for application in gas chamber particle detector (RPC) is described. The chip exhibits a 0.2 mV minimum threshold, 150 MHz bandwidth and 50 mW per channel of power consumption.

A simple amplitude equalization technique has been applied to coaxial cables to allow binary data transmission up to 1 Gbit/s in a domestic or office environment, where data link lenght is less than 200 m., and cable installation appears economically advantageous as compared to fiber optic. A new monolithic integrated equalizer-amplifier has been designed to fit to different cable types and lenghts by mean of a voltage-controlled equalization.