Abstract
We developed and tested the performance of a new wavelet based algorithm for Augmentation Index (AIx) determination. The evaluation method relies on reference cardiac-like pulses that are synthesized using a weighted combination of exponentially shaped sub-pulses that represent the three main components of real pulses: the systolic stroke, its reflected replica and the carotid reservoir or windkessel effect. The pulses are parameterized so as to reproduce the main types of cardiac waveforms. The values of AIx yielded by the new algorithm are compared with the ones computed directly from the synthesized waveform and with the values produced by standard Probability Density Function (PDF) analysis.

Abstract
An arterial pressure waveform recorder and analyser based on a Microchip PIC microcontroller (mu C), dsPIC33FJ256GP710 is described in this article. Our purpose is to develop a dsPIC based signal monitoring and processing system for cardiovascular studies, specially dedicated to arterial pressure waveform (APW) capture. We developed a piezoelectric (PZ) probe designed to reproduce the APW from the pulsatile activity taken non-invasively at the vicinity of a superficial artery. The advantages in developing a microcontroller based system show up in decreasing the associate cost, as well as in increasing the functionality of the system. Based on a MathWorks Simulink platform, the system supports the development and transfer of program code from a personal computer to the microcontroller, and evaluation of its execution on rapid prototyping hardware. Results demonstrate that embedded system can be an alternative to be used in autonomous cardiovascular probes. Although additional studies are still required, this probe seems to be a valid, low cost and easy to use alternative to expensive and hard to manipulate devices in the market.

Abstract
Diabetic retinopathy (DR) is the leading cause of blindness in adults. In diabetes, there is activation of microglial cells and a concomitant release of inflammatory mediators. However, it remains unclear how diabetes triggers an inflammatory response in the retina. Activation of P2 purinergic receptors by adenosine triphosphate (ATP) may contribute to the inflammatory response in the retina, insofar as it has been shown to be associated with microglial activation and cytokine release. In this work, we evaluated how high glucose, used as a model of hyperglycemia, considered the main factor in the development of DR, affects the extracellular levels of ATP in retinal cell cultures. We found that basal extracellular ATP levels were not affected by high glucose or mannitol, but the extracellular elevation of ATP, after a depolarizing stimulus, was significantly higher in retinal cells cultured in high glucose compared with control or mannitol-treated cells. The increase in the extracellular ATP was prevented by application of botulinum neurotoxin A or by removal of extracellular calcium. In addition, degradation of exogenously added ATP was significantly lower in high-glucose-treated cells. It was also observed that, in retinal cells cultured under high-glucose conditions, the changes in the intracellular calcium concentrations were greater than those in control or mannitol-treated cells. In conclusion, in this work we have shown that high glucose alters the purinergic signaling system in the retina, by increasing the exocytotic release of ATP and decreasing its extracellular degradation. The resulting high levels of extracellular ATP may lead to inflammation involved in the pathogenesis of DR. (C) 2008 Wiley-Liss, Inc.

Abstract
Over the last years, great emphasis has been placed on the role of arterial stiffness in the development of cardiovascular diseases. This hemodynamic parameter, generally associated to age and blood pressure increase, can be assessed by the measurement of pulse wave velocity (PWV). Currently available devices that measure PWV are expensive and need to be operated by skilled medical staff, reducing the potential of ambulatory setting. This research project aims at developing and testing the sensoring and algorithmic basis of an alternative and non-invasive device for PWV assessment. The proposed device is based on a double-headed sensor probe and allows the assessment of PWV in one single location, providing important information on local arterial hemodynamics. Although studies to validate the clinical use of this system are still required, it has already demonstrated good performance on a dedicated test bench system, capable of reproducing a range of relevant cardiovascular system's properties. © 2011 IEEE.

Abstract
In a clinical context, physicians usually take into account information from more than one data modality when making decisions regarding cancer diagnosis and treatment planning. Artificial intelligence-based methods should mimic the clinical method and take into consideration different sources of data that allow a more comprehensive analysis of the patient and, as a consequence, a more accurate diagnosis. Lung cancer evaluation, in particular, can benefit from this approach since this pathology presents high mortality rates due to its late diagnosis. However, many related works make use of a single data source, namely imaging data. Therefore, this work aims to study the prediction of lung cancer when using more than one data modality. The National Lung Screening Trial dataset that contains data from different sources, specifically, computed tomography (CT) scans and clinical data, was used for the study, the development and comparison of single-modality and multimodality models, that may explore the predictive capability of these two types of data to their full potential. A ResNet18 network was trained to classify 3D CT nodule regions of interest (ROI), whereas a random forest algorithm was used to classify the clinical data, with the former achieving an area under the ROC curve (AUC) of 0.7897 and the latter 0.5241. Regarding the multimodality approaches, three strategies, based on intermediate and late fusion, were implemented to combine the information from the 3D CT nodule ROIs and the clinical data. From those, the best model-a fully connected layer that receives as input a combination of clinical data and deep imaging features, given by a ResNet18 inference model-presented an AUC of 0.8021. Lung cancer is a complex disease, characterized by a multitude of biological and physiological phenomena and influenced by multiple factors. It is thus imperative that the models are capable of responding to that need. The results obtained showed that the combination of different types may have the potential to produce more comprehensive analyses of the disease by the models.

Abstract
The great incidence of cardiovascular (CV) diseases in the world spurs the search for new solutions to enable an early detection of pathological processes and provides more precise diagnosis based in multi-parameters assessment. The pulse wave velocity (PWV) is considered one of the most important clinical parameters for evaluate the CV risk, vascular adaptation, and therapeutic efficacy. Several studies were dedicated to find the relationship between PWV measurement and pathological status in different diseases, and proved the relevance of this parameter. The commercial devices dedicate to PWV estimation make a regional assessment (measured between two vessels), however a local measurement is more precise evaluation of artery condition, taking into account the differences in the structure of arteries. Moreover, the current devices present some limitations due to the contact nature. Emerging trends in CV monitoring are moving away from more invasive technologies to non-invasive and non-contact solutions. The great challenge is to explore the new instrumental solutions that allow the PWV assessment with fewer approximations for an accurately evaluation and relatively inexpensive techniques in order to be used in the clinical routine. © The Author(s) 2015.