Abstract
Abstract Background Heart Rate Variability (HRV) is an increasing area of interest in patients with epilepsy. The effects of epilepsy on the autonomic control of the heart are not completely understood and that autonomic dysfunction has been implicated in some cases of Sudden Unexpected Death in Epilepsy (SUDEP). Objective To study the influence of generalized tonic-clonic seizures (GTCS) on HRV of patients with focal refractory epilepsy. Method We prospectively evaluated (January 2015 to July 2018) 121 patients admitted to our institution's Epilepsy Monitoring Unit. All patients performed a 48-hour Holter recording. Patients who had GTCS during the recording were included and we selected the first GTCS as the index seizure. HRV (AVNN, SDNN, RMSSD, pNN50, and LF/HF) was evaluated by analyzing 5-min-ECG epochs during inter-ictal and post-ictal periods: baseline, pre-ictal (5 min before the GTCS seizure), post-ictal (5 min after the seizure), and late post-ictal (>5 hours after the seizure). We compared HRV data from these patients with normative values for a healthy population (controlling age and gender). The study was approved by our Institution Ethics Committee and all patients gave informed consent. Results Twenty three patients were included (mean age: 38.61±11.58; 70% Female). Thirty percent presented cardiovascular risk factors without known cardiac disease. We found significant differences between the analyzed periods for all but one (LF/HF) HRV metrics (using Friedman test, p<0.05, two-tailed). Specifically during the post-ictal period, we found a significant reduction for AVNN, SDNN, RMSSD and pNN50 (Wilcoxon test, p<0.05; two-tailed). LF/HF was increased during this period, but changes were not statistically significant. There was also a tendency for a reduction of AVNN, SDNN, RMSSD and pNN50 and an increase of LF/HF in our patients during all the analyzed periods when compared to normative healthy population values. Conclusion Our work shows reduced HRV after a GTCS in patients with focal resistant epilepsy, both in inter-ictal and post-ictal periods, when compared to normative healthy population values. These results might reflect long term structural changes in autonomic centers. The HRV changes were significant particularly during the post-ictal period, and should prompt further investigation, giving this period is critical for SUDEP.

Abstract
Background/objective: Playing a wind instrument implies rhythmic jaw movements where the embouchure applies forces with different directions and intensities towards the orofacial structures. These features are relevant when comparing the differences between a clarinettist and a saxophone player embouchure, independently to the fact that both belong to the single-reed instrument group, making therefore necessary to update the actual classification. Methods: Lateral cephalograms were taken to single-reed, double-reed and brass instrumentalists with the purpose of analyzing the relationship of the mouthpiece and the orofacial structures. Results: The comparison of the different wind instruments showed substantial differences. Therefore the authors purpose a new classification of wind instruments: Class 1 single-reed mouthpiece, division 1– clarinet, division 2 –saxophone; Class 2 double-reed instruments, division 1– oboe, division 2– bassoon; Class 3 cup-shaped mouthpiece, division 1– trumpet and French horn, division 2- trombone and tuba; Class 4 aperture mouthpieces, division 1– flute, division 2 – transversal flute and piccolo. Conclusions: Elements such as dental arches, teeth and lips, assume vital importance at a new nomenclature and classification of woodwind instruments that were in the past mainly classified by the type of mouthpiece and not taking into consideration its relationship with their neighboring structures. © 2019 Craniofacial Research Foundation

Abstract
Skin temperature regulation is dependent on the autonomic nervous system function, which may be impaired in patients with neuropathy. Literature reporting thermographic assessment of patients with established diagnosis of Diabetic Foot (DF) is scarce, but this information is completely absent in patients suffering from Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP). The aim of this study is to compare skin temperature distribution in patients with DF and TTR-FAP. Thermograms of the dorsal and plantar surfaces of twelve neuropathic patients, six with DF and six with TTR-FAP, were assessed and compared. Skin temperature was significantly higher in the diabetic foot group, in both regions of interest. Thermal symmetry values were high, but similar in both groups. The bias between the right and left foot was smaller, with smaller limits of agreement in TTR-FAP patients, suggesting a lower agreement between the temperature of the right and left feet in DF patients.

Abstract
This paper proposes a new methodology to automatically segment and measure the volume of pulmonary nodules in lung computed tomography (CT) scans. Estimating the malignancy likelihood of a pulmonary nodule based on lesion characteristics motivated the development of an unsupervised pulmonary nodule segmentation and volume measurement as a preliminary stage for pulmonary nodule characterization. The idea is to optimally cluster a set of feature vectors composed by intensity and shape-related features in a given feature data space extracted from a pre-detected nodule. For that purpose, a metaheuristic search based on evolutionary computation is used for clustering the corresponding feature vectors. The proposed method is simple, unsupervised and is able to segment different types of nodules in terms of location and texture without the need for any manual annotation. We validate the proposed segmentation and volume measurement on the Lung Image Database Consortium and Image Database Resource Initiative - LIDC-IDRI dataset. The first dataset is a group of 705 solid and sub-solid (assessed as part-solid and non-solid) nodules located in different regions of the lungs, and the second, more challenging, is a group of 59 sub-solid nodules. The average Dice scores of 82.35% and 71.05% for the two datasets show the good performance of the segmentation proposal. Comparisons with previous state-of-the-art techniques also show acceptable and comparable segmentation results. The volumes of the segmented nodules are measured via ellipsoid approximation. The correlation and statistical significance between the measured volumes of the segmented nodules and the ground-truth are obtained by Pearson correlation coefficient value, obtaining an R-value >= 92.16% with a significance level of 5%.

Abstract
In view of the growing importance of nanotechnologies, the detection of nanoparticles type in several contexts has been considered a relevant topic. Several organisms, including the National Institutes of Health, have been highlighting the urge of developing nanoparticles exposure risk assessment assays, since very little is known about their physiological responses. Although the identi fi cation/characterization of synthetically produced nanoparticles is considered a priority, there are many examples of \ naturally" generated nanostructures that provide useful information about food components or human physiology. In fact, several nanoscale extracellular vesicles are present in physiological fluids with high potential as cancer biomarkers. However, scientists have struggled to fi nd a simple and rapid method to accurately detect/identify nanoparticles, since their majority have diameters between 100-150 nm -far below the di ff raction limit. Currently, there is a lack of instruments for nanoparticles detection and the few instrumentation that is commonly used is costly, bulky, complex and time consuming. Thus, considering our recent studies on particles identi fi cation through back-scattering, we examined if the time/frequency-domain features of the back-scattered signal provided from a 100 nm polystyrene nanoparticles suspension are able to detect their presence only by dipping a polymeric lensed optical fi ber in the solution. This novel technique allowed the detection of synthetic nanoparticles in distilled water versus \ blank solutions" (only distilled water) through Multivariate Statistics and Arti fi cial Intelligence (AI)-based techniques. While the state-of-the-art methods do not o ff er a ff ordable and simple approaches for nanoparticles detection, our technique can contribute for the development of a device with innovative characteristics.

Abstract