Effect of Resveratrol on Markers of Oxidative Stress and Sirtuin 1 in Elderly Adults with Type 2 Diabetes.

Type 2 diabetes (T2D) affects a large part of the adult population and impairs its quality of life. Because of this, natural compounds with antioxidant, anti-inflammatory and hypoglycemic properties have been used as adjuvants. Among these compounds, resveratrol (RV) stands out, a polyphenol that has been studied in several clinical trials, the results of which are controversial.

Arterial Fistulas in Urinary Diverted Patients: A Report of 5 Cases.

Objective: Arterio-urinary fistulae are a rare but potentially lethal complication that may arise after pelvic surgery, such as radical cystectomy. Historically, open surgery was the gold standard treatment, but currently endovascular treatment has gained prominence.

Methods: We report our centre experience in endovascular treatment of cystectomy-related arterial fistulae and review the reported literature on the topic.

Emotion Classification from EEG with a Low-Cost BCI Versus a High-End Equipment.

The assessment of physiological signals such as the electroencephalography (EEG) has become a key point in the research area of emotion detection. This study compares the performance of two EEG devices, a low-cost brain-computer interface (BCI) (Emotiv EPOC+) and a high-end EEG (BrainVision), for the detection of four emotional conditions over 20 participants. For that purpose, signals were acquired with both devices under the same experimental procedure, and a comparison was made under three different scenarios, according to the number of channels selected and the sampling frequency of the signals analyzed.

Evaluation of Brain Functional Connectivity from Electroencephalographic Signals Under Different Emotional States.

The identification of the emotional states corresponding to the four quadrants of the valence/arousal space has been widely analyzed in the scientific literature by means of multiple techniques. Nevertheless, most of these methods were based on the assessment of each brain region separately, without considering the possible interactions among different areas. In order to study these interconnections, this study computes for the first time the functional connectivity metric called cross-sample entropy for the analysis of the brain synchronization in four groups of emotions from electroencephalographic signals.

Detection of Negative Stress through Spectral Features of Electroencephalographic Recordings and a Convolutional Neural Network.

In recent years, electroencephalographic (EEG) signals have been intensively used in the area of emotion recognition, partcularly in distress identification due to its negative impact on physical and mental health. Traditionally, brain activity has been studied from a frequency perspective by computing the power spectral density of the EEG recordings and extracting features from different frequency sub-bands. However, these features are often individually extracted from single EEG channels, such that each brain region is separately evaluated, even when it has been corroborated that mental processes are based on the coordination of different brain areas working simultaneously.

Hypoglycemic Effect of Resveratrol: A Systematic Review and Meta-Analysis.

Resveratrol (RV) is a polyphenolic compound with antioxidant, anti-inflammatory, and hypoglycemic properties. Several in vitro and animal model studies have demonstrated the beneficial effects of RV; however, the results in humans are not conclusive. After a search of different databases, 32 studies were selected for this systematic review and 30 were included in the meta-analysis.

The Effect of 600 mg Alpha-lipoic Acid Supplementation on Oxidative Stress, Inflammation, and RAGE in Older Adults with Type 2 Diabetes Mellitus.

Alpha-lipoic acid (ALA) has been used as a dietary supplement at different doses in patients with diabetes mellitus type 2 (T2DM) due to its antioxidant, anti-inflammatory, and hypoglycemic effects. However, the reports on the effects of ALA are controversial. For this reason, the purpose of the present study was to determine the effect of 600 mg/day of ALA on the markers of oxidative stress (OxS) and inflammation and RAGE in older adults with T2DM.

Multi-Lag Analysis of Symbolic Entropies on EEG Recordings for Distress Recognition.

Distress is a critical problem in developed societies given its long-term negative effects on physical and mental health. The interest in studying this emotion has notably increased during last years, being electroencephalography (EEG) signals preferred over other physiological variables in this research field. In addition, the non-stationary nature of brain dynamics has impulsed the use of non-linear metrics, such as symbolic entropies in brain signal analysis.

The influence of an educational internet-based intervention in the beliefs and attitudes of primary care professionals on non-specific chronic low back pain: study protocol of a mixed methods approach.

Background: Personal convictions in referral to pain cause misbeliefs in health professionals, which can influence patients who suffer from non-specific chronic low back pain. Likewise, health professionals' beliefs affect their advice and attitudes towards patients' treatment, becoming a possible cause of greater disability. The development of educational interventions based on the best scientific evidence in neurophysiology of pain could be a way to provide information and advice to primary care health professionals to change their cognition towards chronic non-specific low back pain.

Multiscale Entropy Analysis for Recognition of Visually Elicited Negative Stress From EEG Recordings.

Automatic identification of negative stress is an unresolved challenge that has received great attention in the last few years. Many studies have analyzed electroencephalographic (EEG) recordings to gain new insights about how the brain reacts to both short- and long-term stressful stimuli. Although most of them have only considered linear methods, the heterogeneity and complexity of the brain has recently motivated an increasing use of nonlinear metrics.