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Apresentação do número 35 da REVELL.

Spain has grown economically due to the recent boosts in the industrial sector, the agricultural sector, construction and services. Those who carry out agricultural tasks are mainly undocumented immigrants living in marginal neighborhoods. Objectives: to know the perception of undocumented Moroccan migrants living in marginal neighborhoods regarding access to the Public Health System. Methods: A qualitative method with a phenomenological approach was used to get closer to the experience of the participants in the study. In this work, 24 semi-structured interviews were conducted following a guide with a set of open questions to facilitate an in-depth discussion of the topics of interest. The participants were given an informed consent form, which guaranteed anonymity and confidentiality regarding the information obtained. For this, codes were used to identify them. The data were stored, managed, classified, and organized with the ATLAS-ti 9 software. Results: access and use of health services by the immigrants in the study was difficult due to communication problems related to language and culture, the discriminatory attitude and lack of cultural competence of health personnel, and the location of the neighborhoods (which were marginal far from urban centers), as well as the lack of transportation to health centers. Conclusions: it is an ethical imperative of the Health System to offer greater attention to the population in situations of extreme vulnerability, implement intercultural mediators and train health professionals in cultural competence.

The present research evaluated the potential use of the macroalga Sargassum sp., which was modified with filamentous fungus Cunninghamella echinulata for the biosorption of methylene blue (MB) dye. The modified fungal biomass (FERsarg) was obtained through solid-state fermentation of enzyme (alginate lyase). The FERsarg showed a pHPZC of 7.9, a low mass loss, material micro/mesoporous, and the presence of hydroxyl, carboxylic, phenolic, and carbonyl functional groups. The influence of biomass dosage, solution pH, contact time, initial concentration, and temperature were evaluated for MB biosorption, and the best results were obtained at 2 g L-1 and pH 6. The kinetic study revealed a better fit for the pseudo-second-order model, while the Sips model best described the equilibrium experimental data. The equilibrium was reached within 180 min and showed qmax yielding of 115.49 mg g-1 at 323 K. The thermodynamic understanding of the present research revealed that the biosorbent exhibited spontaneous, exothermic, and physical nature for MB removal. The adsorptive mechanism shows that the process was controlled by electrostatic attraction. Also the feasibility of using residual fermented biomass as a potential adsorbent was applied and discussed, contributing to the concept of minimum waste generation, and supporting the concept of circular bioeconomy. HIGHLIGHTS The Sargassum sp. biomass demonstrated improved adsorption of methylene blue (MB) dye.; Kinetic studies favored pseudo-second-order modeling, while the Sips model accurately represented equilibrium data.; Utilizing fermented biomass as an effective adsorbent promotes a circular bioeconomy, aligning with sustainability goals and minimizing waste in the research process.;

The independence and autonomy of both elderly and disabled people have been a growing concern in today’s society. Therefore, wheelchairs have proven to be fundamental for the movement of these people with physical disabilities in the lower limbs, paralysis, or other type of restrictive diseases. Various adapted sensors can be employed in order to facilitate the wheelchair’s driving experience. This work develops the proof concept of a brain–computer interface (BCI), whose ultimate final goal will be to control an intelligent wheelchair. An event-related (de)synchronization neuro-mechanism will be used, since it corresponds to a synchronization, or desynchronization, in the mu and beta brain rhythms, during the execution, preparation, or imagination of motor actions. Two datasets were used for algorithm development: one from the IV competition of BCIs (A), acquired through twenty-two Ag/AgCl electrodes and encompassing motor imagery of the right and left hands, and feet; and the other (B) was obtained in the laboratory using an Emotiv EPOC headset, also with the same motor imaginary. Regarding feature extraction, several approaches were tested: namely, two versions of the signal’s power spectral density, followed by a filter bank version; the use of respective frequency coefficients; and, finally, two versions of the known method filter bank common spatial pattern (FBCSP). Concerning the results from the second version of FBCSP, dataset A presented an F1-score of 0.797 and a rather low false positive rate of 0.150. Moreover, the correspondent average kappa score reached the value of 0.693, which is in the same order of magnitude as 0.57, obtained by the competition. Regarding dataset B, the average value of the F1-score was 0.651, followed by a kappa score of 0.447, and a false positive rate of 0.471. However, it should be noted that some subjects from this dataset presented F1-scores of 0.747 and 0.911, suggesting that the movement imagery (MI) aptness of different users may influence their performance. In conclusion, it is possible to obtain promising results, using an architecture for a real-time application.

Salmonellosis, an infectious disease caused by the Salmonella species, encompasses a broad spectrum of clinical manifestations, ranging from mild self-limiting gastroenteritis to severe systemic infections. It affects millions of people annually, causing immense morbidity and economic losses worldwide. This study aims to evaluate the occurrence of Salmonella in water and raw foods, focusing on meat, fish, shellfish, and vegetables consumed in the city of Nampula, north of Mozambique. A total of 81 samples of meat, fish and shellfish, vegetables, and water were collected from nine of the ten municipal markets in Nampula City. Salmonella detections were performed according to ISO 6579-1. A chi-square test was performed in the Python programming language to detect associations between positive samples and market localization. The results showed a high frequency of Salmonella. From the total sample, 38.5% were Salmonella positive. Fresh vegetables were the most contaminated samples, followed by fish, shellfish, raw meat, and water. The outcomes of this study did not find an association between the sample collection location and the test results for Salmonella. In this study, serovars of Salmonella were not identified which hinders the association of Salmonella occurrence with diseases. Consequently, we propose that the next study should focus on detecting the serotypes of Salmonella strains.

In various fields, such as economics, finance, bioinformatics, geology, and medicine, namely, in the cases of electroencephalogram, electrocardiogram, and biotechnology, cluster analysis of time series is necessary. The first step in cluster applications is to establish a similarity/dissimilarity coefficient between time series. This article introduces an extension of the affinity coefficient for the autoregressive expansions of the invertible autoregressive moving average models to measure their similarity between them. An application of the affinity coefficient between time series was developed and implemented in R. Cluster analysis is performed with the corresponding distance for the estimated simulated autoregressive moving average of order one. The primary findings indicate that processes with similar forecast functions are grouped (in the same cluster) as expected concerning the affinity coefficient. It was also possible to conclude that this affinity coefficient is very sensitive to the behavior changes of the forecast functions: processes with small different forecast functions appear to be well separated in different clusters. Moreover, if the two processes have at least an infinite number of π- weights with a symmetric signal, the affinity value is also symmetric.

While extensive research has documented the cognitive changes associated with Parkinson’s disease (PD), a relatively small portion of the empirical literature investigated the language abilities of individuals with PD. Recently, artificial intelligence applied to linguistic data has shown promising results in predicting the clinical diagnosis of neurodegenerative disorders, but a deeper investigation of the current literature available on PD is lacking. This systematic review investigates the nature of language disorders in PD by assessing the contribution of machine learning (ML) to the classification of patients with PD. A total of 10 studies published between 2016 and 2023 were included in this review. Tasks used to elicit language were mainly structured or unstructured narrative discourse. Transcriptions were mostly analyzed using Natural Language Processing (NLP) techniques. The classification accuracy (%) ranged from 43 to 94, sensitivity (%) ranged from 8 to 95, specificity (%) ranged from 3 to 100, AUC (%) ranged from 32 to 97. The most frequent optimal linguistic measures were lexico-semantic (40%), followed by NLP-extracted features (26%) and morphological consistency features (20%). Artificial intelligence applied to linguistic markers provides valuable insights into PD. However, analyzing measures derived from narrative discourse can be time-consuming, and utilizing ML requires specialized expertise. Moving forward, it is important to focus on facilitating the integration of both narrative discourse analysis and artificial intelligence into clinical practice.

Background : Calprotectin (CP) is a calcium- and zinc-binding protein that plays a key role in innate immunity and in the recruitment of inflammatory cells. CP can be detected both in serum and in fecal samples. Serum CP (sCP) is more specific for autoimmune diseases, while fecal CP (fCP) has been well investigated for gastrointestinal diseases. Few studies have shown the clinical effectiveness of sCP as an acute-phase biomarker for gastrointestinal diseases. Aim : The aim of this narrative review is to discuss the role of sCP as a useful alternative biomarker of the acute-phase activity of gastrointestinal diseases and as a possible tool for screening and monitoring these diseases. Material and Methods : We searched original articles, abstracts, reviews, case reports, and clinical trials on PubMed ® , Up-to-Date ® , and Medscape ® in the last ten years. Conclusion : We found that sCP could represent a useful biomarker in the evaluation of the inflammatory stage in patients with immune-mediated gastrointestinal diseases, but more studies are needed to promote its routine use in clinical practice as a diagnostic and prognostic biomarker as a replacement for fCP.