A Color Vision-Based Lane Tracking System for Autonomous Driving on Unmarked Roads

This work describes a color Vision-based System intended to perform stable autonomous driving on unmarked roads. Accordingly, this implies the development of an accurate road surface detection system that ensures vehicle stability. Although this topic has already been documented in the technical literature by different research groups, the vast majority of the already existing Intelligent Transportation Systems are devoted to assisted driving of vehicles on marked extra urban roads and highways. The complete system was tested on the BABIECA prototype vehicle, which was autonomously driven for hundred of kilometers accomplishing different navigation missions on a private circuit that emulates an urban quarter. During the tests, the navigation system demonstrated its robustness with regard to shadows, road texture, and weather and changing illumination conditions.     

Packet Video Broadcasting with General-Purpose Operating Systems in an Ethernet

Video transmission with general-purpose PCs poses a number of requirements that radically differ from those of high-end dedicated video servers. We analyze the scenario of an Ethernet local area network in which a number of PCs are transmitting video streams, while other TCP/IP applications are also running concurrently. Our findings show that since the operating system clock resolution cannot cope with the transmission timing requirements the following holds: if the video transmission is performed with exact timing accuracy to maintain a constant rate then CPU load grows to 100%, thus blocking the PC for other user applications; on the other hand, if transmission is performed in a bursty manner, i.e. with sleep system calls, then CPU load decreases dramatically but the increased burstiness of the video stream has a negative impact on network performance (for example, capture effect in the Ethernet). Furthermore, the impact of video transmission over the rest of TCP/IP applications running on the same network depends heavily on the packet size. We provide an integrated analysis of operating system and network parameters to achieve video broadcasting while preserving timing requirements and minimizing the impact on other applications.     

Development and Characterization of a Factor V-Deficient CRISPR Cell Model for the Correction of Mutations

Factor V deficiency, an ultra-rare congenital coagulopathy, is characterized by bleeding episodes that may be more or less intense as a function of the levels of coagulation factor activity present in plasma. Fresh-frozen plasma, often used to treat patients with factor V deficiency, is a scarcely effective palliative therapy with no specificity to the disease. CRISPR/Cas9-mediated gene editing, following precise deletion by non-homologous end-joining, has proven to be highly effective for modeling on a HepG2 cell line a mutation similar to the one detected in the factor V-deficient patient analyzed in this study, thus simulating the pathological phenotype. Additional CRISPR/Cas9-driven non-homologous end-joining precision deletion steps allowed correction of 41% of the factor V gene mutated cells, giving rise to a newly developed functional protein. Taking into account the plasma concentrations corresponding to the different levels of severity of factor V deficiency, it may be argued that the correction achieved in this study could, in ideal conditions, be sufficient to turn a severe phenotype into a mild or asymptomatic one.     

Technical Validation and Clinical Implications of Ultrasensitive PCR Approaches for EGFR-Thr790Met Mutation Detection in Pretreatment FFPE Samples and in Liquid Biopsies from Non-Small Cell Lung Cancer Patients

In pretreatment tumor samples of EGFR-mutated non-small cell lung cancer (NSCLC) patients, EGFR-Thr790Met mutation has been detected in a variable prevalence by different ultrasensitive assays with controversial prognostic value. Furthermore, its detection in liquid biopsy (LB) samples remains challenging, being hampered by the shortage of circulating tumor DNA (ctDNA). Here, we describe the technical validation and clinical implications of a real-time PCR with peptide nucleic acid (PNA-Clamp) and digital droplet PCR (ddPCR) for EGFR-Thr790Met detection in diagnosis FFPE samples and in LB. Limit of blank (LOB) and limit of detection (LOD) were established by analyzing negative and low variant allele frequency (VAF) FFPE and LB specimens. In a cohort of 78 FFPE samples, both techniques showed an overall agreement (OA) of 94.20%. EGFR-Thr790Met was detected in 26.47% of cases and was associated with better progression-free survival (PFS) (16.83 ± 7.76 vs. 11.47 ± 1.83 months; p = 0.047). In LB, ddPCR was implemented in routine diagnostics under UNE-EN ISO 15189:2013 accreditation, increasing the detection rate of 32.43% by conventional methods up to 45.95%. During follow-up, ddPCR detected EGFR-Thr790Met up to 7 months before radiological progression. Extensively validated ultrasensitive assays might decipher the utility of pretreatment EGFR-Thr790Met and improve its detection rate in LB studies, even anticipating radiological progression.     

Special issue on distributed computing and artificial intelligence

4:1! Google’s artificial intelligence (AI) program, AlphaGo, has won Go Master Lee Sedol in a best-of-five competition held in Korean March 9?15, 2016. Seen by many as a landmark moment for AI, the outcome did not come as a surprise, considering the excellent combination of 1920 CPUs with sophisticated AI algorithms, including neural networks and Monte Carlo tree search (Gibney, 2016; Silver et al., 2016). Indeed, research on distributed computing and artificial intelligence (DCAI) has matured during the last decade and many effective applications are now deployed, performing an increasingly important role in modern computer science, including the two most hyped technologies: Internet of Things and Big Data. Indeed, it is fair to say that the application of artificial intelligence in distributed environments is becoming an essential element of high added value and economic potential.     

BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

Wireless Personal Communications - The integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Smart objects will be the building...     

Critical Review on Fatty Acid-Based Food and Nutraceuticals as Supporting Therapy in Cancer

Fatty acids have an important place in both biological and nutritional contexts and, from a clinical point of view, they have known consequences for diseases’ onset and development, including cancer. The use of fatty acid-based food and nutraceuticals to support cancer therapy is a multidisciplinary subject, involving molecular and clinical research. Knowledge regarding polyunsaturated fatty acids essentiality/oxidizability and the role of lipogenesis-desaturase pathways for cell growth, as well as oxidative reactivity in cancer cells, are discussed, since they can drive the choice of fatty acids using their multiple roles to support antitumoral drug activity. The central role of membrane fatty acid composition is highlighted for the application of membrane lipid therapy. As fatty acids are also known as biomarkers of cancer onset and progression, the personalization of the fatty acid-based therapy is also possible, taking into account other important factors such as formulation, bioavailability and the distribution of the supplementation. A holistic approach emerges combining nutra- and pharma-strategies in an appropriate manner, to develop further knowledge and applications in cancer therapy.     

Effective Natural Killer Cell Degranulation Is an Essential Key in COVID-19 Evolution

NK degranulation plays an important role in the cytotoxic activity of innate immunity in the clearance of intracellular infections and is an important factor in the outcome of the disease. This work has studied NK degranulation and innate immunological profiles and functionalities in COVID-19 patients and its association with the severity of the disease. A prospective observational study with 99 COVID-19 patients was conducted. Patients were grouped according to hospital requirements and severity. Innate immune cell subpopulations and functionalities were analyzed. The profile and functionality of innate immune cells differ between healthy controls and severe patients; CD56dim NK cells increased and MAIT cells and NK degranulation rates decreased in the COVID-19 subjects. Higher degranulation rates were observed in the non-severe patients and in the healthy controls compared to the severe patients. Benign forms of the disease had a higher granzymeA/granzymeB ratio than complex forms. In a multivariate analysis, the degranulation capacity resulted in a protective factor against severe forms of the disease (OR: 0.86), whereas the permanent expression of NKG2D in NKT cells was an independent risk factor (OR: 3.81; AUC: 0.84). In conclusion, a prompt and efficient degranulation functionality in the early stages of infection could be used as a tool to identify patients who will have a better evolution.     

Profile of TREM2-Derived circRNA and mRNA Variants in the Entorhinal Cortex of Alzheimer’s Disease Patients

Genetic variants in TREM2, a microglia-related gene, are well-known risk factors for Alzheimer’s disease (AD). Here, we report that TREM2 originates from circular RNAs (circRNAs), a novel class of non-coding RNAs characterized by a covalent and stable closed-loop structure. First, divergent primers were designed to amplify circRNAs by RT-PCR, which were further assessed by Sanger sequencing. Then, additional primer sets were used to confirm back-splicing junctions. In addition, HMC3 cells were used to assess the microglial expression of circTREM2s. Three candidate circTREM2s were identified in control and AD human entorhinal samples. One of the circRNAs, circTREM2_1, was consistently amplified by all divergent primer sets in control and AD entorhinal cortex samples as well as in HMC3 cells. In AD cases, a moderate negative correlation (r = −0.434) was found between the global average area of Aβ deposits in the entorhinal cortex and circTREM2_1 expression level. In addition, by bioinformatics tools, a total of 16 miRNAs were predicted to join with circTREM2s. Finally, TREM2 mRNA corresponding to four isoforms was profiled by RT-qPCR. TREM2 mRNA levels were found elevated in entorhinal samples of AD patients with low or intermediate ABC scores compared to controls. To sum up, a novel circRNA derived from the TREM2 gene, circTREM2_1, has been identified in the human entorhinal cortex and TREM2 mRNA expression has been detected to increase in AD compared to controls. Unraveling the molecular genetics of the TREM2 gene may help to better know the innate immune response in AD.     

An adaptive tracking algorithm for direction finding and array shape estimation in a nonstationary environment

This paper presents an adaptive tracking algorithm for the subspace-based direction of arrival estimation of multiple sources in a nonstationary, environment. The nonstationarities are due to moving sources or to timevarying distortions of the sensor array shape. The proposed algorithm relies on the properties of a linear operator, referred to as the Propagator, which only exploits the linear independency of the source steering vectors. The Propagator allows not only the calibration of the array shape, but also the determination of the source and the noise subspaces without any eigendecomposition of the cross-spectral matrix of the received signals. A gradientbased adaptive algorithm is here proposed for the on-line estimation of the Propagator. A theoretical analysis of the behaviour of this algorithm in a nonstationary environment is given. Simulations are carried out in the case of moving sources and in the case of a time-varying array shape. They exhibit the good performances of the proposed algorithm.