Neopterin levels are independently associated with cardiac remodeling in patients with chronic heart failure

Neopterin, a marker of inflammation and monocyte activation, is found increased in patients with heart failure (HF). This study investigates whether neopterin levels correlate with left ventricular (LV) remodeling and brain natriuretic peptide (BNP), a marker of cardiac stress, in chronic HF (CHF) patients with different severity of disease. The relationship between elevated neopterin levels and LV enlargement in CHF patients suggests a crucial role of monocyte activation in the development of cardiac dysfunction in CHF patients. Assessment of neopterin levels is a potential biomarker to evaluate the progression of LV remodeling in CHF patients

A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers

The manufacturing of nanomaterials by the electrospinning process requires accurate and meticulous inspection of related scanning electron microscope ( SEM ) images of the electrospun nanofiber, to ensure that no structural defects are produced. The presence of anomalies prevents practical application of the electrospun nanofibrous material in nanotechnology. Hence, the automatic monitoring and quality control of nanomaterials is a relevant challenge in the context of Industry 4.0. In this paper, a novel automatic classification system for homogenous ( anomaly-free ) and non-homogenous ( with defects ) nanofibers is proposed. The inspection procedure aims at avoiding direct processing of the redundant full SEM image. Specifically, the image to be analyzed is first partitioned into sub-images ( nanopatches ) that are then used as input to a hybrid unsupervised and supervised machine learning system. In the first step, an autoencoder ( AE ) is trained with unsupervised learning to generate a code representing the input image with a vector of relevant features. Next, a multilayer perceptron ( MLP ) , trained with supervised learning, uses the extracted features to classify non-homogenous nanofiber ( NH-NF ) and homogenous nanofiber ( H-NF ) patches. The resulting novel AE-MLP system is shown to outperform other standard machine learning models and other recent state-of-the-art techniques, reporting accuracy rate up to 92.5% . In addition, the proposed approach leads to model complexity reduction with respect to other deep learning strategies such as convolutional neural networks ( CNN ) . The encouraging performance achieved in this benchmark study can stimulate the application of the proposed scheme in other challenging industrial manufacturing tasks

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways.publishedVersio

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

DYNAMIC MODEL DESIGN FOR AN ON BOARD MULTI-PURPOSE PRECISE ORBIT DETERMINATION SCHEME

This work provides a possible design methodology devoted to future development of a generalized on board Earth orbit navigation system. A multipurpose dynamic model architecture is exploited in order to perform trade-off and sensitivity analysis for orbit propagation force model and structural parameters identification against a target mission scenario. The dynamic model configuration is considered also within a sequential estimation process where external trajectory observations are available. The study introduces the possibility to preliminary assess the achievable performance of the navigation system by using the Cramer Rao Lower Bound in its parametric definition for dynamic estimators. The recursive approximation around the nominal mission path is considered by updating the Fisher Information Matrix. The developed design logic is finally applied on a representative orbit determination problem belonging to high orbit navigation scenarios

Asynchronous Traffic on the Sidelink of 5G V2X

International audienceThe Cellular Vehicle-to-Everything (C-V2X) technology has been specified to support V2X communications in Long Term Evolution (LTE) and beyond cellular networks. Whereas Release 14 specifications mainly target the sidelink support of periodic cooperative awareness messages (CAMs) exchanged among vehicles, 3GPP is currently discussing C-V2X enhancements to enable new features in 5G Releases 16 and 17, among which the support of asynchronous messages like Decentralized Environmental Messages (DENMs). Such type of messages can be generated upon an accident or other hazardous events on the road, but also to allow a vehicle to join/leave a platoon. They need to be promptly and reliably disseminated to guarantee safe driving. In this paper, we analyse the DENM delivery performance over the sidelink, when considering the C-V2X autonomous resource allocation scheme, also known as Mode 4 in Release 14 and as Mode 2 in the next Releases. The suitability to DENMs of the resource selection algorithm specified for CAMs in Release 14 is first investigated, before analyzing some suggested parameter adjustments for Release 16, and elaborating on their most suitable tuning under different simulation settings

DENM Repetitions to Enhance Reliability of the Autonomous Mode in NR V2X Sidelink

International audienceThe first set of specifications for the Cellular-Vehicle-to-Everything (C-V2X) technology has been issued by the Third Generation Partnership Project (3GPP) in Release 14 to enable the exchange of periodic cooperative awareness messages supporting basic safety applications. Enhancements towards 5G New Radio (NR) V2X are under study in Release 16 in order to support advanced vehicular use cases with stricter latency and reliability demands, and different traffic patterns (e.g., aperiodic messages, unicast delivery). In this paper, we focus on the support of aperiodic traffic like Decentralized Environmental Messages (DENMs), which are sent out asynchronously to vehicles alerting them to road hazard events such as anomalous traffic conditions, road-works or signal violation, emergency braking. DENMs can be repeatedly transmitted in a relevant area to increase message reliability during the event lifetime. Simulations have been conducted to analyze scenarios where periodic and event-triggered messages share the same radio resource pool(s) in the autonomous sidelink mode of NR V2X. The main parameters of the autonomous resource allocation mechanism affecting the DENM delivery have been investigated as well as the benefits of DENM repetitions, while also considering their impact over periodically transmitted messages, under different simulation settings

Improving the DENM Reliability over 5G-V2X Sidelink through Repetitions and Diversity Combining

International audienceThe fifth-generation vehicle-to-everything (5G-V2X) communication technology is under development by the Third Generation Partnership Project (3GPP) mainly to support direct communications among vehicles over the sidelink interface. Both periodic cooperative awareness messages (CAMs) and sporadic alert messages, such as Decentralized Environmental Messages (DENMs), are transmitted in broadcast over the sidelink to support basic safety applications and more advanced cooperative driving use cases. The two classes of messages may suffer from poor reliability either when considered individually or when competing among each other for the limited radio resources, which are accessed without a centralized coordination. In this paper, we analyze the DENM performance over the 5G-V2X sidelink under the autonomous resource allocation scheme, also known as Mode 4 in 3GPP Release 14 and as Mode 2 in the next Releases. Message repetitions and time-frequency diversity have been exploited to improve the DENM performance by also using Maximum Ratio Combining (MRC) at the receiver. Achieved simulation results show improvements in terms of DENM reliability, with a negligible impact on periodic messages

A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability

In complex real-life motor skills such as unconstrained throwing, performance depends on how accurate is on average the outcome of noisy, high-dimensional, and redundant actions. What characteristics of the action distribution relate to performance and how different individuals select specific action distributions are key questions in motor control. Previous computational approaches have highlighted that variability along the directions of first order derivatives of the action-to-outcome mapping affects performance the most, that different mean actions may be associated to regions of the actions space with different sensitivity to noise, and that action covariation in addition to noise magnitude matters. However, a method to relate individual high-dimensional action distribution and performance is still missing. Here we introduce a decomposition of performance into a small set of indicators that compactly and directly characterize the key performance-related features of the distribution of high-dimensional redundant actions. Central to the method is the observation that, if performance is quantified as a mean score, the Hessian (second order derivatives) of the action-to-score function determines how the noise of the action distribution affects performance. We can then approximate the mean score as the sum of the score of the mean action and a tolerance-variability index which depends on both Hessian and action covariance. Such index can be expressed as the product of three terms capturing noise magnitude, noise sensitivity, and alignment of the most variable and most noise sensitive directions. We apply this method to the analysis of unconstrained throwing actions by non-expert participants and show that, consistently across four different throwing targets, each participant shows a specific selection of mean action score and tolerance-variability index as well as specific selection of noise magnitude and alignment indicators. Thus, participants with different strategies may display the same performance because they can trade off suboptimal mean action for better tolerance-variability and higher action variability for better alignment with more tolerant directions in action space.Published versionEuropean Union’s Horizon 2020 research and innovation programme under grant agreement No 644727 to AdA (https://cogimon.eu/cognitiveinteraction-motion-cogimon); Italian Ministry of Health (IRCCS Fondazione Santa Lucia - Ricerca Corrente) to FL (http://www.salute.gov.it/portale/ temi/p2_5.jsp?lingua=italiano&area=Ricerca% 20sanitaria&menu=corrente) Italian Space Agency (grants I/006/06/0 and 2019-11-U.0) to FL (https:// www.asi.it/) Italian University Ministry (PRIN grants 2015HFWRYY to AdA and FL; 2017CBF8NJ_005 to FL; https://prin.miur.it/index. php?pag=2015) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript