Application of SVM-RFE on EEG signals for detecting the most relevant scalp regions linked to affective valence processing

In this work, event related potentials (ERPs) induced by visual stimuli categorized with different value of affective valence are studied. EEG signals are recorded during visualization of selected pictures belonging to International Affective Picture System (IAPS). A Morlet wavelet filter is used to transform the EEG input space to a topography-time–frequency feature space. Support vector machine-recursive feature elimination (SVM-RFE) is applied for detecting scalp spectral dynamics of interest (SSDOIs) in this feature space, allowing to identify the most relevant time intervals, frequency bands and EEG channels. This feature selection method has proven to outperform the classical t-test in the discrimination of brain cortex regions involved in affective valence processing. Furthermore, the presented combination of feature extraction and selection techniques can be applied as an alternative in other different clinical applications.     

Comparison of four test methods to measure damping properties of materials by using piezoelectric transducers

This article presents the experimental results of damping loss factor and Young’s modulus obtained for stiff and flexible materials through the use of four different methodologies: the Central Impedance Method, the Modified Oberst Method, the Seismic Response Method, and the simply supported beam method. The first three methods are based on the ASTM standard but using different experimental setting and different Frequency Response Functions. The fourth method corresponds to a non-resonant technique used in the characterization of materials at very low frequencies. In this work, the results of damping loss factor and Young’s modulus obtained through these four methods are compared, the variability of results is studied and the sensitivity of each technique when facing controlled temperature variations is verified.     

Lipid Damage Inhibition in Hake by Active Packaging Film with Natural Antioxidants

The capacity of the natural antioxidant to retard oxidation of polyunsaturated fatty acids in hake (Merluccius merluccius) muscle was investigated. Hake fillets were packaged in low‐density polyethylene with the natural antioxidant (sample C1 = 7 mg/dm² film and sample C2 = 24 mg/dm² film) or without the antioxidant (control sample) and frozen for 12 months at ?20°C. The results confirm the efficacy of an active packaging with a natural antioxidant derived from barley husks to slow the progress of lipid hydrolysis and increase oxidative stability in hake muscle. Determination of peroxide value, conjugated dienes, free fatty acids, thiobarbituric acid reactive substances (TBARS) and anisidine value (AV) proved suitable for studying lipid hydrolysis and primary and secondary lipid oxidation over time. After 6 months of frozen storage, the TBARS levels were lower in hake packed with low‐density polyethylene with the natural antioxidant (C1 and C2) than in the control sample; at month 12, the TBARS values of C1 and C2 were lower (16 and 21%, respectively) than the control samples. AVs observed in samples C1 and C2 at month 9 were lower than those observed in the control sample at month 12. Copyright © 2011 John Wiley & Sons, Ltd.     

Monitoring of ochratoxin A exposure of the Portuguese population through a nationwide urine survey — Winter 2007

Ochratoxin A (OTA) is a mycotoxin produced by a variety of fungi, such as Penicillium verrucosum and Aspergillium spp., which has been found to have a wide number of potentially deadly toxic effects, and can enter the human organism through a variety of means. It then finds its way into the bloodstream and, after a lengthy process, is eventually excreted through the urine. It can thus be detected in its original form not only in blood samples but also in this biological medium. As such, and in an attempt to evaluate the exposure of the Portuguese population to this mycotoxin, morning urine samples were collected during the Winter of 2007, from each of five geographically distinct Portuguese locations — Bragança, Porto, Coimbra, Alentejo, and Algarve — and subjected to extraction by immunoaffinity columns and to OTA quantification through liquid chromatography coupled with fluorescence detection. Prevalent incidence was higher than 95% with Coimbra being the exception (incidence of 73.3%). In nearly all locations, the OTA content of most samples was found to be above the limit of quantification (LOQ) of 0.008 ng/ml. Indeed, excluding Coimbra, with an OTA content level of 0.014 ng/ml, all regions featured content values over 0.021 ng/ml.     

Assessment of the presence and dynamics of fungi in drinking water sources using cultural and molecular methods

A comparison of different isolation techniques and culture media for detection of filamentous fungi and yeasts in the aquatic environment revealed that the use of membrane filtration with the media dichloran rose bengal chloramphenicol (DRBC) optimized fungi detection in terms of abundance and variety in three untreated water sources with very different characteristics (surface water, spring water, and groundwater). The diversity of the fungi population captured by direct DNA extraction of fungi collected by membrane filtration was compared with the isolates obtained after selective growth using different culture media through amplification of the internal transcribed spacer gene and denaturing gradient gel electrophoresis (DGGE). The Czapek-Dox agar, Sabouraud dextrose agar, and DRBC media showed closer similarities to those obtained by the uncultured biomass for the different water sources. Based on these data and the best enumeration results, DRBC is recommended for the assessment of fungi in water sources using culture-based methods. DGGE was also used to monitor temporal variations in the fungal population structure and showed that each water matrix possessed a distinct population profile as well as that changes in the fungal community can be expected in the different matrices throughout the year.     

The Association between Gut Microbiota and Osteoarthritis: Does the Disease Begin in the Gut?

Some say that all diseases begin in the gut. Interestingly, this concept is actually quite old, since it is attributed to the Ancient Greek physician Hippocrates, who proposed the hypothesis nearly 2500 years ago. The continuous breakthroughs in modern medicine have transformed our classic understanding of the gastrointestinal tract (GIT) and human health. Although the gut microbiota (GMB) has proven to be a core component of human health under standard metabolic conditions, there is now also a strong link connecting the composition and function of the GMB to the development of numerous diseases, especially the ones of musculoskeletal nature. The symbiotic microbes that reside in the gastrointestinal tract are very sensitive to biochemical stimuli and may respond in many different ways depending on the nature of these biological signals. Certain variables such as nutrition and physical modulation can either enhance or disrupt the equilibrium between the various species of gut microbes. In fact, fat-rich diets can cause dysbiosis, which decreases the number of protective bacteria and compromises the integrity of the epithelial barrier in the GIT. Overgrowth of pathogenic microbes then release higher quantities of toxic metabolites into the circulatory system, especially the pro-inflammatory cytokines detected in osteoarthritis (OA), thereby promoting inflammation and the initiation of many disease processes throughout the body. Although many studies link OA with GMB perturbations, further research is still needed.     

COVID-19 and Lung Mast Cells: The Kallikrein–Kinin Activation Pathway

Mast cells (MCs) have relevant participation in inflammatory and vascular hyperpermeability events, responsible for the action of the kallikrein–kinin system (KKS), that affect patients inflicted by the severe form of COVID-19. Given a higher number of activated MCs present in COVID-19 patients and their association with vascular hyperpermeability events, we investigated the factors that lead to the activation and degranulation of these cells and their harmful effects on the alveolar septum environment provided by the action of its mediators. Therefore, the pyroptotic processes throughout caspase-1 (CASP-1) and alarmin interleukin-33 (IL-33) secretion were investigated, along with the immunoexpression of angiotensin-converting enzyme 2 (ACE2), bradykinin receptor B1 (B1R) and bradykinin receptor B2 (B2R) on post-mortem lung samples from 24 patients affected by COVID-19. The results were compared to 10 patients affected by H1N1pdm09 and 11 control patients. As a result of the inflammatory processes induced by SARS-CoV-2, the activation by immunoglobulin E (IgE) and degranulation of tryptase, as well as Toluidine Blue metachromatic (TB)-stained MCs of the interstitial and perivascular regions of the same groups were also counted. An increased immunoexpression of the tissue biomarkers CASP-1, IL-33, ACE2, B1R and B2R was observed in the alveolar septum of the COVID-19 patients, associated with a higher density of IgE⁺ MCs, tryptase⁺ MCs and TB-stained MCs, in addition to the presence of intra-alveolar edema. These findings suggest the direct correlation of MCs with vascular hyperpermeability, edema and diffuse alveolar damage (DAD) events that affect patients with a severe form of this disease. The role of KKS activation in events involving the exacerbated increase in vascular permeability and its direct link with the conditions that precede intra-alveolar edema, and the consequent DAD, is evidenced. Therapy with drugs that inhibit the activation/degranulation of MCs can prevent the worsening of the prognosis and provide a better outcome for the patient.     

The effect of cocoa fermentation and weak organic acids on growth and ochratoxin A production by Aspergillus species

The acidic characteristics of cocoa beans have influence on flavor development in chocolate. Cocoa cotyledons are not naturally acidic, the acidity comes from organic acids produced by the fermentative microorganisms which grow during the processing of cocoa. Different concentrations of these metabolites can be produced according to the fermentation practices adopted in the farms, which could affect the growth and ochratoxin A production by fungi. This work presents two independent experiments carried out to investigate the effect of some fermentation practices on ochratoxin A production by Aspergillus carbonarius in cocoa, and the effect of weak organic acids such as acetic, lactic and citric at different pH values on growth and ochratoxin A production by A. carbonarius and Aspergillus niger in culture media. A statistical difference (ρ<0.05) in the ochratoxin A level in the cured cocoa beans was observed in some fermentation practices adopted. The laboratorial studies demonstrate the influence of organic acids on fungal growth and ochratoxin A production, with differences according to the media pH and the organic acid present. Acetic acid was the most inhibitory acid against A. carbonarius and A. niger. From the point of view of food safety, considering the amount of ochratoxin A produced, fermentation practices should be conducted towards the enhancement of acetic acid, although lactic and citric acids also have an important role in lowering the pH to improve the toxicity of acetic acid.     

Accurate and reliable image classification by using conformal predictors in the TJ-II Thomson scattering

The charge-coupled device camera of the TJ-II Thomson scattering (TS) can capture five different classes of images. Typically, different data processing is performed depending on the kind of image that is acquired. The procedure can be automated to recognize the type of image. To this end, machine learning methods (MLM) are applied. However, usually, MLM classify without confidence estimates. An image classifier based on conformal predictors has been developed for the TJ-II TS. It provides a couple of indicators (confidence and credibility) for each classification that measures the accuracy and reliability of the prediction. Results achieve success rates of about 97%. The implemented classifier is valid for any kind of images.