Neurokinin-1 receptor, a new modulator of lymphangiogenesis in obese-asthma phenotype

Aims Obesity and asthma are widely prevalent and associated disorders. Recent studies of our group revealed that Substance P (SP) is involved in pathophysiology of obese-asthma phenotype in mice through its selective NK1 receptor (NK1-R). Lymphangiogenesis is impaired in asthma and obesity, and SP activates contractile and inflammatory pathways in lymphatics. Our aim was to study whether NK1-R expression was involved in lymphangiogenesis on visceral (VAT) and subcutaneous (SAT) adipose tissues and in the lungs, in obese-allergen sensitized mice. Main methods Diet-induced obese and ovalbumin (OVA)-sensitized Balb/c mice were treated with a selective NK1-R antagonist (CJ 12,255, Pfizer Inc., USA) or placebo. Lymphatic structures (LYVE-1 +) and NK1-R expression were analyzed by immunohistochemistry. A semi-quantitative score methodology was used for NK1-R expression. Key findings Obesity and allergen-sensitization together increased the number of LYVE-1 + lymphatics in VAT and decreased it in SAT and lungs. NK1-R was mainly expressed on adipocyte membranes of VAT, blood vessel areas of SAT, and in lung epithelium. Obesity and allergen-sensitization combined increased the expression of NK1-R in VAT, SAT and lungs. NK1-R antagonist treatment reversed the effects observed in lymphangiogenesis in those tissues. Significance The obese-asthma phenotype in mice is accompanied by increased expression of NK1-R on adipose tissues and lung epithelium, reflecting that SP released during inflammation may act directly on these tissues. Blocking NK1-R affects lymphangiogenesis, implying a role of SP, with opposite physiological consequences in VAT, and in SAT and lungs. Our results provide a clue for a novel SP role in the obese-asthma phenotype.

Fractional dynamics of genetic algorithms using hexagonal space tessellation

The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

Caracterização molecular da resistência a antimicrobianos em Escherichia coli produtoras de β-lactamases de espectro alargado isoladas em cães e estudo da partilha de clones bacterianos entre animais de companhia e coabitantes humanos

A pressão seletiva originada pelo uso excessivo de antimicrobianos na medicina humana e veterinária tem contribuído para a emergência de estirpes bacterianas multirresistentes, sendo os estudos mais escassos relativamente à sua presença nos animais de companhia. Porque os animais e os seus proprietários partilham o mesmo espaço habitacional, apresentando comportamentos de contacto próximo, existe uma hipótese elevada de transferência microbiana inter-espécie. Ante esta possibilidade é importante escrutinar o papel dos animais de companhia enquanto reservatórios de estirpes e de genes de resistência, bem como a sua envolvência na disseminação de estirpes bacterianas multirresistentes. Importa também, investigar o papel das superfícies e objetos domésticos partilhados por ambos, como potenciadores deste fenómeno. O objetivo deste trabalho foi, identificar o filogrupo e fazer a caracterização molecular dos genes que conferem resistência aos β-lactâmicos e às quinolonas, em quarenta isolados de Escherichia coli produtoras de β-lactamases de espectro alargado (ESBL), obtidas em zaragatoas fecais de cães consultados no Hospital Veterinário do ICBAS-UP. Complementarmente pretendeu-se inferir sobre a partilha de clones de Escherichia coli e Enterococcus spp. com elevadas resistências, em cinco agregados familiares (humanos e seus animais de companhia) assim como avaliar a potencial disseminação de estirpes multirresistentes no ambiente doméstico. Previamente foram recolhidas zaragatoas de fezes, pelo e mucosa oral dos animais e em alguns casos, dos seus proprietários, e ainda do ambiente doméstico. As zaragatoas foram processadas e as estirpes isoladas com base em meios seletivos. Foram realizados testes de suscetibilidade antimicrobiana de modo a estabelecer o fenótipo de resistência de cada isolado. O DNA foi extraído por varias metodologias e técnicas de PCR foram utilizadas para caracterização de filogrupos (Escherichia coli) e identificação da espécie (Enterococcus spp.). A avaliação da proximidade filogenética entre isolados foi efetuada por ERIC PCR e PFGE. No conjunto de quarenta isolados produtores de ESBL e/ou resistentes a quinolonas verificou-se que 47,5% pertenciam ao filogrupo A, havendo uma menor prevalência do filogrupo D (25,0%), B1 (17,5%), e B2 (10,0%).A frequência de resistência nestes isolados é factualmente elevada, sendo reveladora de uma elevada pressão seletiva. Com exceção de dois isolados, os fenótipos foram justificados pela presença de β-lactamases. A frequência da presença de genes foi: 47% blaTEM, 34% blaSHV, 24% blaOXA , 18% blaCTX-M-15, 8% blaCTX-M-2, 3% blaCTX-M-9. Nos isolados resistentes às quinolonas verificou-se maioritariamente a presença de mutações nos genes cromossomais gyrA e parC, e em alguns casos a presença de um determinante de resistência mediado por plasmídeo – qnrS. Nos cinco “agregados familiares” (humanos e animais) estudados foi observada uma partilha frequente de clones de E. coli e Enterococcus faecalis com múltiplas resistências, isolados em fezes e mucosa oral de cães e gatos e fezes e mãos dos respetivos proprietários, evidenciando-se assim uma possível transferência direta entre coabitantes (agregados A, C, D, E). Ficou também comprovado com percentagens de similaridade genotípica superiores a 94% que essa disseminação também ocorre para o ambiente doméstico, envolvendo objetos dos animais e de uso comum (agregados A, E). Os resultados obtidos reforçam a necessidade de um uso prudente dos antimicrobianos, pois elevados padrões de resistências terão um impacto não só na qualidade de vida dos animais mas também na saúde humana. Adicionalmente importa sensibilizar os proprietários para a necessidade de uma maior vigilância relativamente às formas de interação com os animais, bem como para a adoção de medidas higiénicas cautelares após essa mesma interação.

Neurokinin-1 receptor, a new modulator of lymphangiogenesis in obese-asthma phenotype

Aims: Obesity and asthma are widely prevalent and associated disorders. Recent studies of our group revealed that Substance P (SP) is involved in pathophysiology of obese-asthma phenotype in mice through its selective NK1 receptor (NK1-R). Lymphangiogenesis is impaired in asthma and obesity, and SP activates contractile and inflammatory pathways in lymphatics. Our aim was to study whether NK1-R expression was involved in lymphangiogenesis on visceral (VAT) and subcutaneous (SAT) adipose tissues and in the lungs, in obeseallergen sensitized mice. Main methods: Diet-induced obese and ovalbumin (OVA)-sensitized Balb/c mice were treated with a selective NK1-R antagonist (CJ 12,255, Pfizer Inc., USA) or placebo. Lymphatic structures (LYVE-1+) and NK1-R expression were analyzed by immunohistochemistry. A semi-quantitative score methodology was used for NK1-R expression. Key findings: Obesity and allergen-sensitization together increased the number of LYVE-1+ lymphatics in VAT and decreased it in SAT and lungs. NK1-R was mainly expressed on adipocyte membranes of VAT, blood vessel areas of SAT, and in lung epithelium. Obesity and allergen-sensitization combined increased the expression of NK1-R in VAT, SAT and lungs. NK1-R antagonist treatment reversed the effects observed in lymphangiogenesis in those tissues. Significance: The obese-asthma phenotype in mice is accompanied by increased expression of NK1-R on adipose tissues and lung epithelium, reflecting that SP released during inflammation may act directly on these tissues. Blocking NK1-R affects lymphangiogenesis, implying a role of SP, with opposite physiological consequences in VAT, and in SAT and lungs. Our results provide a clue for a novel SP role in the obese-asthma phenotype.

A preliminary idea for an 8-competitive, log2 DMAX + log2 log2 1/U asymptotic-space, interface generation algorithm for two-level hierarchical scheduling of constrained-deadline sporadic tasks on a uniprocessor

Consider a single processor and a software system. The software system comprises components and interfaces where each component has an associated interface and each component comprises a set of constrained-deadline sporadic tasks. A scheduling algorithm (called global scheduler) determines at each instant which component is active. The active component uses another scheduling algorithm (called local scheduler) to determine which task is selected for execution on the processor. The interface of a component makes certain information about a component visible to other components; the interfaces of all components are used for schedulability analysis. We address the problem of generating an interface for a component based on the tasks inside the component. We desire to (i) incur only a small loss in schedulability analysis due to the interface and (ii) ensure that the amount of space (counted in bits) of the interface is small; this is because such an interface hides as much details of the component as possible. We present an algorithm for generating such an interface.

A complex protocol layer as a linux user-space process

With the current complexity of communication protocols, implementing its layers totally in the kernel of the operating system is too cumbersome, and it does not allow use of the capabilities only available in user space processes. However, building protocols as user space processes must not impair the responsiveness of the communication. Therefore, in this paper we present a layer of a communication protocol, which, due to its complexity, was implemented in a user space process. Lower layers of the protocol are, for responsiveness issues, implemented in the kernel. This protocol was developed to support large-scale power-line communication (PLC) with timing requirements.

Space-time monitoring of prescribed burnt soils performance – an effective tool for forest management

Among the most important measures to prevent wild forest fires is the use of prescribed and controlled burning actions in order to reduce the availability of fuel mass. However, the impact of these activities on soil physical and chemical properties varies according to the type of both soil and vegetation and is not fully understood. Therefore, soil monitoring campaigns are often used to measure these impacts. In this paper we have successfully used three statistical data treatments - the Kolmogorov-Smirnov test followed by the ANOVA and the Kruskall-Wallis tests – to investigate the variability among the soil pH, soil moisture, soil organic matter and soil iron variables for different monitoring times and sampling procedures.

SMYD3 contributes to a more aggressive phenotype of prostate cancer and targets Cyclin D2 through H4K20me3

Prostate cancer (PCa) is one of the most incident cancers worldwide but clinical and pathological parameters have limited ability to discriminate between clinically significant and indolent PCa. Altered expression of histone methyltransferases and histone methylation patterns are involved in prostate carcinogenesis. SMYD3 transcript levels have prognostic value and discriminate among PCa with different clinical aggressiveness, so we decided to investigate its putative oncogenic role on PCa.We silenced SMYD3 and assess its impact through in vitro (cell viability, cell cycle, apoptosis, migration, invasion assays) and in vivo (tumor formation, angiogenesis). We evaluated SET domain's impact in PCa cells' phenotype. Histone marks deposition on SMYD3 putative target genes was assessed by ChIP analysis.Knockdown of SMYD3 attenuated malignant phenotype of LNCaP and PC3 cell lines. Deletions affecting the SET domain showed phenotypic impact similar to SMYD3 silencing, suggesting that tumorigenic effect is mediated through its histone methyltransferase activity. Moreover, CCND2 was identified as a putative target gene for SMYD3 transcriptional regulation, through trimethylation of H4K20.Our results support a proto-oncogenic role for SMYD3 in prostate carcinogenesis, mainly due to its methyltransferase enzymatic activity. Thus, SMYD3 overexpression is a potential biomarker for clinically aggressive disease and an attractive therapeutic target in PCa.

Efficient Legendre spectral tau algorithm for solving two-sided space-time Caputo fractional advection-dispersion equation

In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.

State Space Analysis of Forest Fires

This paper studies forest fires from the perspective of dynamical systems. Burnt area, precipitation and atmospheric temperatures are interpreted as state variables of a complex system and the correlations between them are investigated by means of different mathematical tools. First, we use mutual information to reveal potential relationships in the data. Second, we adopt the state space portrait to characterize the system’s behavior. Third, we compare the annual state space curves and we apply clustering and visualization tools to unveil long-range patterns. We use forest fire data for Portugal, covering the years 1980–2003. The territory is divided into two regions (North and South), characterized by different climates and vegetation. The adopted methodology represents a new viewpoint in the context of forest fires, shedding light on a complex phenomenon that needs to be better understood in order to mitigate its devastating consequences, at both economical and environmental levels.

Fractional State Space Analysis of Economy Systems

This paper examines modern economic growth according to the multidimensional scaling (MDS) method and state space portrait (SSP) analysis. Electing GDP per capita as the main indicator for economic growth and prosperity, the long-run perspective from 1870 to 2010 identifies the main similarities among 34 world partners’ modern economic growth and exemplifies the historical waving mechanics of the largest world economy, the USA. MDS reveals two main clusters among the European countries and their old offshore territories, and SSP identifies the Great Depression as a mild challenge to the American global performance, when compared to the Second World War and the 2008 crisis.

An Exact Schedulability Test for Global FP Using State Space Pruning

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

Fractional State Space Analysis of Temperature Time Series

Atmospheric temperatures characterize Earth as a slow dynamics spatiotemporal system, revealing long-memory and complex behavior. Temperature time series of 54 worldwide geographic locations are considered as representative of the Earth weather dynamics. These data are then interpreted as the time evolution of a set of state space variables describing a complex system. The data are analyzed by means of multidimensional scaling (MDS), and the fractional state space portrait (fSSP). A centennial perspective covering the period from 1910 to 2012 allows MDS to identify similarities among different Earth’s locations. The multivariate mutual information is proposed to determine the “optimal” order of the time derivative for the fSSP representation. The fSSP emerges as a valuable alternative for visualizing system dynamics.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.