A linear approach for sparse coding by a two-layer neural network

Many approaches to transform classification problems from non-linear to linear by feature transformation have been recently presented in the literature. These notably include sparse coding methods and deep neural networks. However, many of these approaches require the repeated application of a learning process upon the presentation of unseen data input vectors, or else involve the use of large numbers of parameters and hyper-parameters, which must be chosen through cross-validation, thus increasing running time dramatically. In this paper, we propose and experimentally investigate a new approach for the purpose of overcoming limitations of both kinds. The proposed approach makes use of a linear auto-associative network (called SCNN) with just one hidden layer. The combination of this architecture with a specific error function to be minimized enables one to learn a linear encoder computing a sparse code which turns out to be as similar as possible to the sparse coding that one obtains by re-training the neural network. Importantly, the linearity of SCNN and the choice of the error function allow one to achieve reduced running time in the learning phase. The proposed architecture is evaluated on the basis of two standard machine learning tasks. Its performances are compared with those of recently proposed non-linear auto-associative neural networks. The overall results suggest that linear encoders can be profitably used to obtain sparse data representations in the context of machine learning problems, provided that an appropriate error function is used during the learning phase

Multiscale Analysis of Information Dynamics for Linear Multivariate Processes

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using state-space (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors

Neural Networks with Non-Uniform Embedding and Explicit Validation Phase to Assess Granger Causality

A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments performed will show that the method presented in this work can detect the correct dynamical information flows occurring in a system of time series. Additionally we adopt a non-uniform embedding framework according to which only the past states that actually help the prediction are entered into the model, improving the prediction and avoiding the risk of overfitting. This method also leads to a further improvement with respect to traditional Granger causality approaches when redundant variables (i.e. variables sharing the same information about the future of the system) are involved. Neural networks are also able to recognize dynamics in data sets completely different from the ones used during the training phase

MuTE: a new matlab toolbox for estimating the multivariate transfer entropy in physiological variability series

We present a new time series analysis toolbox, developed in Matlab, for the estimation of the Transfer entropy (TE) between time series taken from a multivariate dataset. The main feature of the toolbox is its fully multivariate implementation, that is made possible by the design of an approach for the non-uniform embedding (NUE) of the observed time series. The toolbox is equipped with parametric (linear) and non-parametric (based on binning or nearest neighbors) entropy estimators. All these estimators, implemented using the NUE approach in comparison with the classical approach based on uniform embedding, are tested on RR interval, systolic pressure and respiration variability series measured from healthy subjects during head-up tilt. The results support the necessity of resorting to NUE for obtaining reliable estimates of the multivariate TE in short-term cardiovascular and cardiorespiratory variability

Serum low density lipoprotein subclasses in asthma

Background: The levels of serum low-density lipoproteins (LDL) have been implicated in the inflammatory cascade in a murine model of asthma. Recent findings suggest that LDL may modulate the inflammatory state of the asthmatic airways in humans. Objective: We explored whether LDL subclasses are associated with the occurrence and severity of asthma. Methods: 24 asthmatics (M/F: 11/13) and 24 healthy individuals, with normal BMI and absence of metabolic syndrome, matched for age and gender. Serum concentrations of LDL subclasses were distributed as seven bands (LDL-1 and -2 defined as large, least pro-inflammatory LDL, and LDL-3 to 7 defined as small, most pro-inflammatory LDL), using the LipoPrintª System (Quantimetrix Corporation, Redondo Beach, CA, USA). Results: LDL-1 was similar in the two groups (56 ± 16% vs. 53 ± 11, p = NS), while LDL-2 was significantly lower in asthmatics as compared to controls (35 ± 8% vs. 43 ± 10%, p = 0.0074). LDL-3 levels were two-fold higher in the asthmatics, but the difference did not reach the statistical significance (8± 7.3% vs. 4±3%, p=NS). Smaller subclasses LDL-4 to LDL-7 were undetectable in controls. In asthmatics, LDL-1 was positively associated with VC% predicted (r=+0.572, pZ0.0035) and FEV1% predicted (r=+0.492, p=+.0146). LDL-3 was inversely correlated with both VC% predicted (r =-0.535, p =0.0071) and FEV1% predicted (r =-0.465, p = 0.0222). Conclusions: The findings of this pilot study suggest a role of LDL in asthma, and advocate for larger studies to confirm the association between asthma and dyslipidemia

Preliminary results of citraves™ effects on low density lipoprotein cholesterol and waist circumference in healthy subjects after 12 weeks: A pilot open-label study

Appropriate monitoring and control of modifiable risk factors, such as the level of lowdensity lipoprotein cholesterol (LDL-C) and other types of dyslipidemia, have an important role in the prevention of cardiovascular diseases (CVD). Recently, various nutraceuticals with lipid-lowering effects have gained attention. In addition to the plant-derived bioactive compounds, recent studies suggested that plant cells are able to release small lipoproteic structures named extracellular vesicles (EVs). The interaction between EVs and mammalian cells could lead to beneficial effects through anti-inflammatory and antioxidant activities. The present study aimed to assess the safety of the new patented plant-based product citraVes™, containing extracellular vesicles (EVs) from Citrus limon (L.) Osbeck juice, and to investigate its ability to modulate different CV risk factors in healthy subjects. A cohort of 20 healthy volunteers was recruited in a prospective open-label study. All participants received the supplement in a spray-dried formulation at a stable dose of 1000 mg/day for 3 months. Anthropometric and hematobiochemical parameters were analyzed at the baseline and after the follow-up period of 1 and 3 months. We observed that the supplement has an effect on two key factors of cardiometabolic risk in healthy subjects. A significant change in waist circumference was found in women after 4 (85.4 [79.9, 91.0] cm, p < 0.005) and 12 (85.0 [80.0, 90.0] cm, p < 0.0005) weeks, when compared to the baseline value (87.6 [81.7, 93.6] cm). No difference was found in men (baseline: 100.3 [95.4, 105.2] cm; 4 weeks: 102.0 [95.7, 108.3] cm; 12 weeks: 100.0 [95.3, 104.7] cm). The level of LDL-C was significantly lower at 12 weeks versus 4 weeks (p = 0.0064). Our study evaluated, for the first time, the effects of a natural product containing plant-derived EVs on modifiable risk factors in healthy volunteers. The results support the use of EV extracts to manage cardiometabolic risk factors successfully

TREOIRLEABHAR CLILSTORE DO CHLEACHTÓIRÍ

[EN] The Clilstore Practitioner Guidebook comprises an introductory guide to using clilstore.eu in Content and Language Integrated Learning (CLIL) contexts and provides technical guidance for CLIL practitioners at all educational levels. The book is divided into 6 chapters. Chapter 1 includes an introduction to CLIL and tries to give answers to common concerns put forward by teachers when they first decide to implement CLIL in their classes. Chapter 2 comprises a detailed description of Clilstore and its two complementary tools, Multidict and Wordlink, focusing on how the system can be used to create lessons that provide learners with content knowledge, as well as supporting language acquisition. It also draws on how to use the integrated Portfolio utility and the personalized Vocabulary lists that include a test yourself function. Chapter 3 focuses on various assessment models for CLIL. Chapter 4 provides an overview of the Help videos that have been created by the partnership to guide teachers in creating open access materials and explain the functionality of all the options the system provides. Chapter 5 includes a number of Clilstore units created by the project members to exemplify the wealth of possibilities the tool offers and how to link unit content to the 5 Cs in CLIL. Chapter 6 includes a comprehensive list of solutions to help teachers quickly overcome any hurdle encountered when starting to create CLIL teaching materials with Clilstore. Lastly, the Guidebook includes a wealth of useful resources for teachers to enhance their lessons and closes with the list of references and suggestions for further reading.[ES] La Guía para practicantes de Clilstore consiste en un manual introductorio para usar clilstore.eu en contextos de Aprendizaje Integrado de Contenidos y Lenguas Extranjeras (AICLE) y proporciona orientación técnica para los practicantes de AICLE en todos los niveles educativos. El libro está dividido en seis capítulos. El Capítulo 1 incluye una introducción a AICLE y trata de dar respuestas a las preocupaciones comunes que plantean los profesores cuando deciden implementar AICLE en sus clases por primera vez. El Capítulo 2 comprende una descripción detallada de Clilstore y sus dos herramientas complementarias, Multidict y Wordlink, centrándose en cómo se puede usar el sistema para crear lecciones que brinden a los alumnos conocimiento del contenido, además de apoyar la adquisición del idioma. También se basa en cómo utilizar la utilidad Portafolio integrada y las listas de vocabulario personalizadas que incluyen una función de autoexamen. El capítulo 3 se centra en varios modelos de evaluación de AICLE. El Capítulo 4 proporciona una descripción general de los videos de ayuda que ha creado la asociación para guiar a los profesores en la creación de materiales de acceso abierto y explicar la funcionalidad de todas las opciones que ofrece el sistema. El Capítulo 5 incluye una serie de unidades Clilstore creadas por los miembros del proyecto para ejemplificar la gran cantidad de posibilidades que ofrece la herramienta y cómo vincular el contenido de la unidad con las 5 C en AICLE. El Capítulo 6 incluye una lista completa de soluciones para ayudar a los profesores a superar rápidamente cualquier obstáculo que encuentren al comenzar a crear materiales didácticos AICLE con Clilstore. Por último, la Guía incluye una gran cantidad de recursos útiles para que los profesores mejoren sus lecciones y se cierra con la lista de referencias y sugerencias para lecturas adicionales.Andersen, K.; Attard-Montalto, S.; Azzariti, A.; Ó Dónaill, C.; Ó Donnaíle, C.; Hansen, M.; Licata, G.... (2021). Clilstore Practitioner Guidebook. Ana Gimeno Sanz. http://hdl.handle.net/10251/181708

Effects of the dose of erythropoiesis stimulating agents on cardiovascular events, quality of life, and health-related costs in hemodialysis patients: the clinical evaluation of the dose of erythropoietins (C.E. DOSE) trial protocol

<p>Abstract</p> <p>Background</p> <p>Anemia is a risk factor for death, adverse cardiovascular outcomes and poor quality of life in patients with chronic kidney disease (CKD). Erythropoietin Stimulating Agents (ESA) are commonly used to increase hemoglobin levels in this population. In observational studies, higher hemoglobin levels (around 11-13 g/dL) are associated with improved survival and quality of life compared to hemoglobin levels around 9-10 g/dL. A systematic review of randomized trials found that targeting higher hemoglobin levels with ESA causes an increased risk of adverse vascular outcomes. It is possible, but has never been formally tested in a randomized trial, that ESA dose rather than targeted hemoglobin concentration itself mediates the increased risk of adverse vascular outcomes. The Clinical Evaluation of the DOSe of Erythropoietins (C.E. DOSE) trial will assess the benefits and harms of a high versus a low fixed ESA dose for the management of anemia in patients with end stage kidney disease.</p> <p>Methods/Design</p> <p>This is a randomized, prospective open label blinded end-point (PROBE) trial due to enrol 2204 hemodialysis patients in Italy. Patients will be randomized 1:1 to 4000 IU/week versus 18000 IU/week of intravenous epoietin alfa or beta, or any other ESA in equivalent doses. The dose will be adjusted only if hemoglobin levels fall outside the 9.5-12.5 g/dL range. The primary outcome will be a composite of all-cause mortality, non fatal stroke, non fatal myocardial infarction and hospitalization for cardiovascular causes. Quality of life and costs will also be assessed.</p> <p>Discussion</p> <p>The C.E.DOSE study will help inform the optimal therapeutic strategy for the management of anemia of hemodialysis patients, improving clinical outcomes, quality of life and costs, by ascertaining the potential benefits and harms of different fixed ESA doses.</p> <p>Trial registration</p> <p>Clinicaltrials.gov NCT00827021</p

The Role of LDH Serum Levels in Predicting Global Outcome in HCC Patients Undergoing TACE: Implications for Clinical Management

In many tumor types serum lactate dehydrogenase (LDH) levels is an indirect marker of tumor hypoxia, neo-angiogenesis and worse prognosis. However data about hepatocellular carcinoma (HCC) are lacking in the clinical setting of patients undergoing transarterial-chemoembolization (TACE) in whom hypoxia and neo-angiogenesis may represent a molecular key to treatment failure. Aim of our analysis was to evaluate the role of LDH pre-treatment levels in determining clinical outcome for patients with HCC receiving TACE. One hundred and fourteen patients were available for our analysis. For all patients LDH values were collected within one month before the procedure. We divided our patients into two groups, according to LDH serum concentration registered before TACE (first: LDH≤450 U/l 84 patients; second: LDH>450 U/l 30 patients). Patients were classified according to the variation in LDH serum levels pre- and post-treatment (increased: 62 patients vs. decreased 52 patients). No statistically significant differences were found between the groups for all clinical characteristics analyzed (gender, median age, performance status ECOG, staging systems). In patients with LDH values below 450 U/l median time to progression (TTP) was 16.3 months, whereas it was of 10.1 months in patients above the cut-off (p = 0.0085). Accordingly median overall survival (OS) was 22.4 months and 11.7 months (p = 0.0049). In patients with decreased LDH values after treatment median TTP was 12.4 months, and median OS was 22.1 months, whereas TTP was 9.1 months and OS was 9.5 in patients with increased LDH levels (TTP: p = 0.0087; OS: p<0.0001). In our experience, LDH seemed able to predict clinical outcome for HCC patients undergoing TACE. Given the correlation between LDH levels and tumor angiogenesis we can speculate that patients with high LDH pretreatment levels may be optimal candidates for clinical trial exploring a multimodality treatment approach with TACE and anti-VEGF inhibitors in order to improve TTP and OS