On the numerical computation of the Mittag-Leffler function

Recently simple limiting functions establishing upper and lower bounds on the Mittag-Leffler function were found. This paper follows those expressions to design an efficient algorithm for the approximate calculation of expressions usual in fractional-order control systems. The numerical experiments demonstrate the superior efficiency of the proposed method.

Predictive Biomarkers of Bacillus Calmette-Gu´erin Immunotherapy Response in Bladder Cancer: Where AreWe Now?

The most effective therapeutic option for managing nonmuscle invasive bladder cancer (NMIBC), over the last 30 years, consists of intravesical instillations with the attenuated strain Bacillus Calmette-Gu´erin (the BCG vaccine). This has been performed as an adjuvant therapeutic to transurethral resection of bladder tumour (TURBT) and mostly directed towards patients with highgrade tumours, T1 tumours, and in situ carcinomas. However, from 20% to 40% of the patients do not respond and frequently present tumour progression. Since BCG effectiveness is unpredictable, it is important to find consistent biomarkers that can aid either in the prediction of the outcome and/or side effects development. Accordingly, we conducted a systematic critical review to identify themost preeminent predictive molecular markers associated with BCG response. To the best of our knowledge, this is the first review exclusively focusing on predictive biomarkers for BCG treatment outcome. Using a specific query, 1324 abstracts were gathered, then inclusion/exclusion criteria were applied, and finally 87 manuscripts were included. Several molecules, including CD68 and genetic polymorphisms, have been identified as promising surrogate biomarkers. Combinatory analysis of the candidate predictive markers is a crucial step to create a predictive profile of treatment response.

Desenvolvimento e aplicação de um biossensor para monitorização de creatinina, um biomarcador associado a doenças emergentes

Este trabalho descreve o desenvolvimento de um material sensor para creatinina por impressão molecular em estrutura polimérica (MIP) e a sua aplicação no desenvolvimento de um dispositivo de natureza potenciométrica para a determinação da molécula alvo em fluidos biológicos. A creatinina é um dos biomarcadores mais utilizados no acompanhamento da doença renal, já que é um bom indicador da taxa de filtração glomerular (TFG). Os materiais biomiméticos desenhados para interação com a creatinina foram obtidos por polimerização radicalar, recorrendo a monómeros de ácido metacríclico ou de vinilpiridina e a um agente de reticulação apropriado. De modo a aferir o efeito da impressão da creatinina na resposta dos materiais MIP à sua presença, foram também preparados e avaliados materiais de controlo, obtidos sem impressão molecular (NIP). O controlo da constituição química destes materiais, incluindo a extração da molécula impressa, foi realizado por Espectroscopia de Raman e de Infravermelho com Transformada de Fourrier. A afinidade de ligação entre estes materiais e a creatinina foi também avaliada com base em estudos cinéticos. Todos os materiais descritos foram integrados em membranas selectivas de elétrodos seletivos de ião, preparadas sem ou com aditivo iónico lipófilo, de carga negativa ou positiva. A avaliação das características gerais de funcionamento destes elétrodos, em meios de composição e pH diferentes, indicaram que as membranas com materiais impressos e aditivo aniónico eram as únicas com utilidade analítica. Os melhores resultados foram obtidos em solução tampão Piperazine-N,N′-bis(2- ethanesulfonic acid), PIPES, de pH 2,8, condição que permitiu obter uma resposta quasi-Nernstiana, a partir de 1,6×10-5 mol L-1. Estes elétrodos demonstraram ainda uma boa selectividade ao apresentaram uma resposta preferencial para a creatinina quando na presença de ureia, carnitina, glucose, ácido ascórbico, albumina, cloreto de cálcio, cloreto de potássio, cloreto de sódio e sulfato de magnésio. Os elétrodos foram ainda aplicados com sucesso na análise de amostras sintéticas de urina, quando os materiais sensores eram baseados em ácido metacrilico, e soro, quando os materiais sensores utilizados eram baseados em vinilpiridina.

On the numerical computation of the Mittag-Leffler function

Recently simple limiting functions establishing upper and lower bounds on the Mittag-Leffler function were found. This paper follows those expressions to design an efficient algorithm for the approximate calculation of expressions usual in fractional-order control systems. The numerical experiments demonstrate the superior efficiency of the proposed method.

Analysis of Systems with Backlash and Impacts through the Describing Function

This paper analyses the dynamical properties of systems with backlash and impact phenomena based on the describing function method. The dynamics is illustrated using the Nyquist and Bode plots and the results are compared with those of standard models.

Aerobic Exercise Does Not Predict Brain Derived Neurotrophic Factor And Cortisol Alterations in Depressed Patients

The pathophysiology of depression is related to neurobiological changes that occur in the monoamine system, hypothalamic-pituitary-adrenal axis, neurogenesis system and the neuroimmune system. In recent years, there has been a growing interest in the research of the effects of exercise on brain function, with a special focus on its effects on brainderived neurotrophic factor (BDNF), cortisol and other biomarkers. Thus, the aim of this study is to present a review investigating the acute and chronic effects of aerobic exercise on BDNF and cortisol levels in individuals with depression. It was not possible to establish an interaction between aerobic exercise and concentration of BDNF and cortisol, which may actually be the result of the divergence of methods, such as type of exercises, duration of the sessions, and prescribed intensity and frequency of sessions.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.