Percorrer por autor "Rodrigues, P. M."
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- Assessment of the post-acute covid-19 syndrome cardiovascular effect through ECG analysisPublication . Ribeiro, P.; Souza, C. C. C. D.; Camerino, C. M. C.; Pordeus, D.; Leite, C. F.; Marques, J. A. L.; Madeiro, J. P.; Rodrigues, P. M.Introduction: SARS-CoV-2, a virus responsible for the emergence of the life-threatening disease known as COVID-19, exhibits a diverse range of clinical manifestations. The spectrum of symptoms varies widely, encompassing mild to severe presentations, while a considerable portion of the population remains asymptomatic. COVID-19, primarily a respiratory virus, has been linked to cardiovascular complications in some patients. Notably, cardiac issues can also arise after recovery, contributing to post-acute COVID-19 syndrome, a significant concern for patient health. The present study intends to evaluate the post-acute COVID-19 syndrome cardiovascular effect through ECG by comparing patients affected with cardiac diseases without COVID-19 diagnosis report (class 1) and patients with cardiac pathologies who present post-acute COVID-19 syndrome (class 2). Methods: From 2 body positions, a total of 10 non-linear features, extracted every 1 second under a multi-band analysis performed by Discrete Wavelet Transform (DWT), have been compressed by 6 statistical metrics to serve as inputs for an individual feature analysis by the means of Mann-Whitney U-test and XROC classification. Results and Discussion: 480 Mann-Whitney U-test statistical analyses and XROC discrimination approaches have been done. The percentage of statistical analysis with significant differences (p<0.05) was 30.42% (146 out of 480). The best overall results were obtained by approximating the feature Energy, with the data compressor Kurtosis in the body position Down. Those results were 83.33% of Accuracy, 83.33% of Sensitivity, 83.33% of Specificity and 87.50% of AUC. Conclusions: The results show that the applied methodology can be a way to show changes in cardiac behaviour provoked by post-acute COVID-19 syndrome.
- gBIOT - Nutraceutical biopolymeric-biocatalytic microbot against gut inflammatory disordersPublication . Sousa, A. S.; Pintado, M. M.; Matos, R. D.; Sousa, C. C.; Machado, M. F.; Coelho, M.; Rodrigues, P. M.; Magalhães, A. M.; Coscueta, E. R.gBiOT is a novel project that proposes micro-robotic technology for nutraceuticals and therapeutic foods for gastrointestinal tract disorders. Gastrointestinal disorders have high prevalence and morbidity, leading to neoplasia and cancer. Recent advances in nanotechnology have opened up new opportunities in the food sector, allowing for the development of health-food products containing nanosized ingredients that can benefit the entire food chain. However, colon-targeted drug delivery systems have gained the most attention as potential carriers for the local treatment of colonic disorders. While current delivery systems have some benefits, they must be improved to be more than passive delivery systems. Advanced steps would include developing biocompatible devices that can actively identify inflamed regions in the gastrointestinal tract, counteract proinflammatory metabolites, and release drugs to alleviate abnormality. Such devices could propel themselves in the gastrointestinal tract environment, making them active in various tasks. gBiOT aims to address these unmet needs by developing a modular microbot prototype that executes intelligent functions under gastrointestinal disorders. The project is developing functionalized microbots that will test to assess the microbiota interaction and preclinical tests. This would lead to the development of practical solutions for the prophylaxis and control of gastrointestinal diseases with minimal impact on patient quality of life and via sustainable methodologies.
- Speech non-linear multiband-time-series analysis for detecting Alzheimer’s diseasePublication . Silva, M. G.; Ribeiro, P.; Bispo, B. C.; Rodrigues, P. M.Introduction: Alzheimer’s Disease (AD) is a prevalent neurodegenerative disorder, anticipated to triple in cases by 2050. It constitutes 50-75% of dementia cases and currently lacks a cure. Early diagnosis is crucial, allowing for treatments that may delay its progression. Traditional diagnostic methods, though effective, are invasive and expensive. Speech signal analysis has emerged as a promising non-invasive, cost-effective alternative for early AD diagnosis. Methods: This study investigates the application of non-linear analysis under a Discrete Wavelet Transform (DWT) of speech signals for detecting AD stages. The dataset comprises 360 audio recordings from the DementiaBank Spanish Ivanova Corpus, categorized into AD, Mild Cognitive Impairment (MCI), and healthy control groups. The 360 speech signals were cleaned by removing artifacts through a filter and moments of silence utilizing Voice Activity Detection (VAD). A 50% overlap rectangular sliding window process of a 5-second duration was used, and within each window, the signal was decomposed by DWT into six bands. From each band, 10 non-linear parameters analyze the complex dynamics of our speech signals. Each feature time series is compressed over time per band, utilizing six compression metrics, and the resulting data are divided into groups based on gender and AD stage. Classical machine learning classification was implemented, and an iterative application of various normalization, feature selection, and optimization techniques was employed. The final step tested 20 classifiers to determine the most effective model for discrimination between groups. Results and Discussion: Our findings show a 100% accuracy between men with AD and women with AD, healthy men and women with AD, and men with AD and healthy women. Furthermore, nearly all of our 15 group comparisons have an accuracy of higher than 90.9%. Conclusion: In conclusion, our techniques culminated in a model that achieved good model performance and could differentiate between men and women, and between the three studied stages of AD.
- A systematic review of natural products for skin applications: targeting inflammation, wound healing, and photo-agingPublication . Fernandes, A.; Rodrigues, P. M.; Pintado, M.; Tavaria, F. K.Background: Every day the skin is constantly exposed to several harmful factors that induce oxidative stress. When the cells are incapable to maintain the balance between antioxidant defenses and reactive oxygen species, the skin no longer can keep its integrity and homeostasis. Chronic inflammation, premature skin aging, tissue damage, and immunosuppression are possible consequences induced by sustained exposure to environmental and endogenous reactive oxygen species. Skin immune and non-immune cells together with the microbiome are essential to efficiently trigger skin immune responses to stress. For this reason, an ever-increasing demand for novel molecules capable of modulating immune functions in the skin has risen the level of their development, particularly in the field of natural product-derived molecules. Purpose: In this review, we explore different classes of molecules that showed evidence in modulate skin immune responses, as well as their target receptors and signaling pathways. Moreover, we describe the role of polyphenols, polysaccharides, fatty acids, peptides, and probiotics as possible treatments for skin conditions, including wound healing, infection, inflammation, allergies, and premature skin aging. Methods: Literature was searched, analyzed, and collected using databases, including PubMed, Science Direct, and Google Scholar. The search terms used included “Skin”, “wound healing”, “natural products”, “skin microbiome”, “immunomodulation”, “anti-inflammatory”, “antioxidant”, “infection”, “UV radiation”, “polyphenols”, “polysaccharides”, “fatty acids”, “plant oils”, “peptides”, “antimicrobial peptides”, “probiotics”, “atopic dermatitis”, “psoriasis”, “auto-immunity”, “dry skin”, “aging”, etc., and several combinations of these keywords. Results: Natural products offer different solutions as possible treatments for several skin conditions. Significant antioxidant and anti-inflammatory activities were reported, followed by the ability to modulate immune functions in the skin. Several membrane-bound immune receptors in the skin recognize diverse types of natural-derived molecules, promoting different immune responses that can improve skin conditions. Conclusion: Despite the increasing progress in drug discovery, several limiting factors need future clarification. Understanding the safety, biological activities, and precise mechanisms of action is a priority as well as the characterization of the active compounds responsible for that. This review provides directions for future studies in the development of new molecules with important pharmaceutical and cosmeceutical value.
- β-glucans derived from mushroom Coriolus versicolor for applications on skin wound healingPublication . Fernandes, A. S.; Rodrigues, P. M.; Pintado, M.; Tavaria, F. K.The beneficial effects of natural compounds in cosmeceutical and biopharmaceutic fields have been extensively studied over the years, and gained popularity because of their distinct advantages, including fewer side effects, better tolerance, and relatively low expenses. Currently, with the growing demand for the use of nature-derived molecules, the research aiming for new biomolecules has increased. Beta-glucans have proved their pluripotent bioactivity (antioxidant, anti-inflammatory, antimicrobial, anti-cancer, regenerative effects, immunomodulation, healing properties) in skin cells. These properties are dependent on several aspects, such as the source, molecular weight, solubility, degree of branching, charge of polymers, and structure in aqueous media. The versatility of these molecules makes them a challenge for the studies of structure–activity relationships, once each different compound (with a unique structure) will show different biological activity. Regarding the high levels of environmental and endogenous stresses that the skin is exposed leading to premature aging and chronic inflammation, this ongoing work aims to explore the ability of b-glucans extracted from C. versicolor to act as antioxidant and anti-inflammatory molecules in the skin and to eventually promote wound healing and tissue cicatrization. Therefore, assays exploring cytotoxic, antioxidant, and anti-inflammatory activities of different b-glucans in keratinocytes (HaCaT) and human fibroblast (HFF) cell lines were performed. The effects of b-glucans on angiogenesis were assessed by the migration (wound healing activity) and the tube formation assay (differentiation and vascular formation) using cell models of human umbilical vein endothelial cells (HUVEC) and mouse macrophage cells (RAW 264.7). Lastly, two well-known ECM components, hyaluronic acid, and collagen were evaluated to understand the effects of b-glucans in the production of these components in a human fibroblast cell line (HFF).