The tricuspid valve in hypoplastic left heart syndrome: Echocardiography provides insight into anatomy and function

Tricuspid regurgitation (TR) is commonly seen in surgically palliated patients with hypoplastic left heart syndrome, and when significant, is associated with an increase in both morbidity and mortality. Tricuspid valve dysfunction appears to be the result of a combination of inherent structural malformations and the unique physiological circumstances resulting from right ventricular pressure and volume overload. Valve dysfunction evolves rapidly, and manifests early on in the surgical pathway. Whilst traditional echocardiographic imaging can identify anatomical defects and dysfunction resulting in varying degrees of regurgitation even at early stages, more sophisticated investigations such as 3D echocardiography, strain imaging and transesophageal 3DE might prove useful to better demonstrate the complex interactions between abnormal anatomy of the valve complex, ventricular function, mechanical synchrony, and TR. Recognition of specific mechanisms of TR can enhance patient-specific care by directing precise surgical interventions and by informing the best timing for intervention on the valve

Analisi della funzione tiroidea in 50 pazienti con COVID-19: uno studio retrospettivo

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Cognitive visual tracking and camera control

Cognitive visual tracking is the process of observing and understanding the behaviour of a moving person. This paper presents an efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario. Such a high-level feedback control loop, which is the main novelty of our work, will serve to reduce uncertainties in the observed scene and to maximize the amount of information extracted from it. It is implemented with a distributed camera system using SQL tables as virtual communication channels, and Situation Graph Trees for knowledge representation, inference and high-level camera control. A set of experiments in a surveillance scenario show the effectiveness of our approach and its potential for real applications of cognitive vision

Short-term complexity of cardiac autonomic control during sleep: REM as a potential risk factor for cardiovascular system in aging.

peer reviewedINTRODUCTION: Sleep is a complex phenomenon characterized by important modifications throughout life and by changes of autonomic cardiovascular control. Aging is associated with a reduction of the overall heart rate variability (HRV) and a decrease of complexity of autonomic cardiac regulation. The aim of our study was to evaluate the HRV complexity using two entropy-derived measures, Shannon Entropy (SE) and Corrected Conditional Entropy (CCE), during sleep in young and older subjects. METHODS: A polysomnographic study was performed in 12 healthy young (21.1+/-0.8 years) and 12 healthy older subjects (64.9+/-1.9 years). After the sleep scoring, heart period time series were divided into wake (W), Stage 1-2 (S1-2), Stage 3-4 (S3-4) and REM. Two complexity indexes were assessed: SE(3) measuring the complexity of a distribution of 3-beat patterns (SE(3) is higher when all the patterns are identically distributed and it is lower when some patterns are more likely) and CCE(min) measuring the minimum amount of information that cannot be derived from the knowledge of previous values. RESULTS: Across the different sleep stages, young subjects had similar RR interval, total variance, SE(3) and CCE(min). In the older group, SE(3) and CCE(min) were reduced during REM sleep compared to S1-2, S3-4 and W. Compared to young subjects, during W and sleep the older subjects showed a lower RR interval and reduced total variance as well as a significant reduction of SE(3) and CCE(min). This decrease of entropy measures was more evident during REM sleep. CONCLUSION: Our study indicates that aging is characterized by a reduction of entropy indices of cardiovascular variability during wake/sleep cycle, more evident during REM sleep. We conclude that during aging REM sleep is associated with a simplification of cardiac control mechanisms that could lead to an impaired ability of the cardiovascular system to react to cardiovascular adverse events

Lactobacillus gasseri SF1183 Affects Intestinal Epithelial Cell Survival and Growth

It is now commonly accepted that the intestinal microbiota plays a crucial role in the gut physiology and homeostasis, and that both qualitative and quantitative alterations in the compositions of the gut flora exert profound effects on the host’s intestinal cells. In spite of this, the details of the interaction between commensal bacteria and intestinal cells are still largely unknown and only in few cases the molecular mechanisms have been elucidated. Here we analyze the effects of molecules produced and secreted by Lactobacillus gasseri SF1183 on human intestinal HCT116 cells. L. gasseri is a well known species of lactic acid bacteria, commonly associated to the human intestine and SF1183 is a human strain previously isolated from an ileal biopsy of an healthy volunteer. SF1183 produces and secretes, in a growth phase-dependent way, molecule(s) able to drastically interfere with HCT116 cell proliferation. Although several attempts to purify and identify the bioactive molecule(s) have been so far unsuccessful, a partial characterization has indicated that it is smaller than 3 kDa, thermostable and of proteinaceous nature. L. gasseri molecule(s) stimulate a G1-phase arrest of the cell cycle by up-regulation of p21WAF1 rendering cells protected from intrinsic and extrinsic apoptosis. A L. gasseri-mediated reduction of apoptosis and of cell proliferation could be relevant in protecting epithelial barrier integrity and helping in reconstituting tissutal homeostasis

Battery models for battery powered applications: A comparative study

Battery models have gained great importance in recent years, thanks to the increasingly massive penetration of electric vehicles in the transport market. Accurate battery models are needed to evaluate battery performances and design an efficient battery management system. Different modeling approaches are available in literature, each one with its own advantages and disadvantages. In general, more complex models give accurate results, at the cost of higher computational efforts and time-consuming and costly laboratory testing for parametrization. For these reasons, for early stage evaluation and design of battery management systems, models with simple parameter identification procedures are the most appropriate and feasible solutions. In this article, three different battery modeling approaches are considered, and their parameters' identification are described. Two of the chosen models require no laboratory tests for parametrization, and most of the information are derived from the manufacturer's datasheet, while the last battery model requires some laboratory assessments. The models are then validated at steady state, comparing the simulation results with the datasheet discharge curves, and in transient operation, comparing the simulation results with experimental results. The three modeling and parametrization approaches are systematically applied to the LG 18650HG2 lithium-ion cell, and results are presented, compared and discussed

A bank of unscented Kalman filters for multimodal human perception with mobile service robots

A new generation of mobile service robots could be ready soon to operate in human environments if they can robustly estimate position and identity of surrounding people. Researchers in this field face a number of challenging problems, among which sensor uncertainties and real-time constraints. In this paper, we propose a novel and efficient solution for simultaneous tracking and recognition of people within the observation range of a mobile robot. Multisensor techniques for legs and face detection are fused in a robust probabilistic framework to height, clothes and face recognition algorithms. The system is based on an efficient bank of Unscented Kalman Filters that keeps a multi-hypothesis estimate of the person being tracked, including the case where the latter is unknown to the robot. Several experiments with real mobile robots are presented to validate the proposed approach. They show that our solutions can improve the robot's perception and recognition of humans, providing a useful contribution for the future application of service robotics