Rayleigh mixture model for plaque characterization in intravascular ultrasound

Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology.     

Topic Tomographies (TopTom): a visual approach to distill information from media streams

In this paper we present Top Tom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user‐generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low‐dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. Top Tom implements a batch processing pipeline able to run both in near‐real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast‐like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States.     

Response to treatment of chronic daily headache with analgesic abuse

The incidence of right aneurysms of the innominate or subclavian arteries is not very high. The majority of these aneurysms is placed in the distal segment of subclavian arteries. These aneurysms are involved in the complex of the thoracic outlet compressive neurovascular syndrome, especially in occurrence of the cervical rib. All aneurysms in this region can rupture and embolize. This is the main purpose of surgical management of this clinical entity. The aim of this study is to refer an interesting case history of a relatively young patient with a right aneurysm of the middle portion of left subclavian artery. The patient had no known vascular risks and the aneurysm was asymptomatic, the only sign was the visible and palpable pulsating mass over the left clavicle. The aneurysms of the middle and central portion of the left subclavian artery are usually explored through the left high posterolateral thoracotomy. The authors refer their experience with the use of a modified technique of exposure--supraclavicular (or transclavicular) incision with the subperiostal resection of the medial portion of the clavicle. This approach affords excellent exposure and a safe surgical procedure. This approach has been described in 1988 by H. Machleder. The advantage of this approach is a diminished risk of surgery in comparison with the transthoracic approach. The authors suppose, however, that it can be useful in traumatic or occlusive lesions, as well.     

Molecular Genetics of GLUT1DS Italian Pediatric Cohort: 10 Novel Disease-Related Variants and Structural Analysis

GLUT1 deficiency syndrome (GLUT1DS1; OMIM #606777) is a rare genetic metabolic disease, characterized by infantile-onset epileptic encephalopathy, global developmental delay, progressive microcephaly, and movement disorders (e.g., spasticity and dystonia). It is caused by heterozygous mutations in the SLC2A1 gene, which encodes the GLUT1 protein, a glucose transporter across the blood-brain barrier (BBB). Most commonly, these variants arise de novo resulting in sporadic cases, although several familial cases with AD inheritance pattern have been described. Twenty-seven Italian pediatric patients, clinically suspect of GLUT1DS from both sporadic and familial cases, have been enrolled. We detected by trios sequencing analysis 25 different variants causing GLUT1DS. Of these, 40% of the identified variants (10 out of 25) had never been reported before, including missense, frameshift, and splice site variants. Their structural mapping on the X-ray structure of GLUT1 strongly suggested the potential pathogenic effects of these novel disease-related mutations, broadening the genotypic spectrum heterogeneity found in the SLC2A1 gene. Moreover, 24% is located in a vulnerable region of the GLUT1 protein that involves transmembrane 4 and 5 helices encoded by exon 4, confirming a mutational hotspot in the SLC2A1 gene. Lastly, we investigated possible correlations between mutation type and clinical and biochemical data observed in our GLUT1DS cohort, revealing that splice site and frameshift variants are related to a more severe phenotype and low CSF parameters.     

Batch and Fed‐Batch Degradation of Enrofloxacin by the Fenton Process

Enrofloxacin is a synthetic second‐generation fluoroquinolone used as an antimicrobial agent exclusively in veterinary medicine. To simulate the treatment of wastewater contaminated by enrofloxacin, four‐day long fed‐batch runs were carried out according to the Fenton process with an enrofloxacin solution as model, to which hydrogen peroxide and ferrous ion were added twice a day. The residual enrofloxacin concentration was practically coincident to that detected at the end of the batch tests. Hydrogen peroxide was almost completely consumed after each feeding period, while the total organic carbon (TOC) concentration decreased gradually within three days, corresponding to a reduction > 58 %. From the third day on, the TOC falling rate was quite low. A yellow sludge settled due to the precipitation of both Fe(OH)₃ and a complex formed by ferric ion with adsorbed enrofloxacin and/or its oxidation products.     

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg–Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN’s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.     

Communication via Mobile Vesicles in Brane Calculi

P systems and Brane calculi are two (families of) computational models inspired by the structure and the functioning of living cells. Although they have different goals there is a recent growing of interests in results that bridge the two research areas.Here we consider an important kind of communication based on the natural budding of mobile membranes (e.g., Golgi apparatus) that is already defined for P systems and we show how to construct an analogous communication in the basic Phago/Exo/Pino Brane calculus.     

Fingerprint Clustering with Bounded Number of Missing Values

The problem of clustering fingerprint vectors with missing values is an interesting problem in Computational Biology that has been proposed in Figueroa et al. (J. Comput. Biol. 11(5):887–901, 2004). In this paper we show some improvements in closing the gaps between the known lower bounds and upper bounds on the approximability of variants of the biological problem. Moreover, we have studied two additional variants of the original problem proposed in Figueroa et al. (Proc. 11th Computing: The Australasian Theory Symposium (CATS), CRPIT, vol. 41, pp. 57–60, 2005). We prove that all such problems are APX-hard even when each fingerprint contains only two unknown positions and we present a greedy algorithm that has constant approximation factors for these variants. Despite the hardness of these restricted versions of the problem, we show that the general clustering problem on an unbounded number of missing values such that they occur for every fixed position of an input vector in at most one fingerprint is polynomial time solvable.