ESS - TBIO - Comunicações em eventos científicos
Permanent URI for this collection
Browse
Recent Submissions
- From controlled to chaotic: Disparities in laboratory vs real-world stress detectionPublication . Ferreira, Simão; Rodrigues, Fátima; Kallio, Johanna; Coelho, Filipe; Kyllonen, Vesa; Rocha, Nuno; Rodrigues, Matilde A.; Vildjiounaite, Elena; Ferreira, Simão; Rodrigues, MatildeThis paper explores the discrepancies between laboratory and real-world stress detection, emphasizing the pronounced differences in data loss, data preprocessing, feature design, and classifier selection. Laboratory studies offer a controlled environment that optimizes data quality, whereas real-world settings introduce chaotic and unpredictable elements, coupled with a diverse range of human behaviours, resulting in substantial data loss and compromised data quality. We discuss the development of stress detectors for two distinct types of data: physiological and behavioural. We also address the specific challenges associated with designing effective stress detection systems for each data type and compare the features and classifiers used in both laboratory and real-world contexts. Additionally, this paper proposes future research directions aimed at crafting stress detectors that are robust and effective in real-life scenarios.
- Utilizing spent yeast for tannin adsorption in chestnut shell treatment solutionsPublication . Vieira, Elsa F.; Amaral, Tomás; Ferraz, Ricardo; Delerue-Matos, Cristina; Ferraz, RicardoThis study evaluated the use of brewer’s spent yeast (BSY) as an adsorbent for tannins from a chestnut shell extract (CS tannin extract). This extract was derived from an alkaline treatment (5% NaOH (v/v)) to recover cellulosic material from chestnut shells and needed valorization. Various BSY treatments, including lyophilization, immobilization in calcium alginate beads, and alkaline and acid treatments, were tested to identify which had the best tannin adsorption capacity. The results highlight BSY’s potential as a system to valorize tannins from this treatment solution.
- Comparing time series forecasting models for health indicators: A clustering analysis approachPublication . Vinhal, Cláudia; Oliveira, Alexandra; Faria, Brígida; Nascimento, Ana Paula; Pimenta, Rui; Oliveira, Alexandra; Faria, Brigida Monica; Pimenta, RuiTime series are the sequence of observations ordered by equal time intervals, crucial for understanding causality, trends, and forecasts. Its analysis can be applied to several areas, such as engineering, finance, and health (1,2). One problem with the time series study is clustering, mainly understanding when two parametric time series are considered similar (3). The sum of mortality and morbidity, referred to as “Burden of Disease”, is measured by a metric called “Disability Adjusted Life Years” (DALYs) (4). These indicators are direct measures of health care needs, reflecting the global burden of disease in the population, and are crucial for public health study and surveillance (5). DALYs can be represented by Autoregressive Integrated Moving Averages (ARIMA) models, and in this context understanding clusters is crucial. The primary goal is to compare different distance measures between ARIMA processes when used in clustering techniques. The study begins by exploring the temporal characteristics of DALYs, highlighting underlying patterns and trends. Then, ARIMA models are applied to represent and describe the time series. It’s on this representation of the time series that the Piccolo, the Maharaj, and the LPC distance measures are applied to use clustering techniques and identify clusters. Additionally, 8 distinct cluster validation metrics are used. Specific to 48 European countries, the results show that the choice of distance measure can greatly influence clustering outcomes and the number of clusters formed. While certain methods revealed geographic patterns, other factors, such as cultural or economic similarities, also influence cluster formation. These insights contribute to advancing the field of public health surveillance and intervention, ultimately aiming to alleviate the global burden of disease. This study offers insights into applying ARIMA processes in clustering techniques for analysing temporal health data. By comparing different distance measures, this research improves our understanding of underlying patterns and trends in health indicators over time.
- The role of interoceptive processing in prenatal depression and anxietyPublication . Praça, Maiara Silva; Braga, Patrícia Vilela; Marshall, Amanda; Lamela, Diogo; Jongenelen, Inês; Rocha, Nuno Barbosa; Costa, Raquel; Schütz-Bosbach, Simone; Pinto, Tiago Miguel; Feldman, Ruth; Campos, Carlos; Rocha, NunoPregnancy is a complex biological phenomenon that can modify several interoception domains (ability to perceive and subjectively experience inner bodily states). These changes in interoceptive processing may also play a role in the emergence of prenatal psychopathology, namely anxiety and depression. To examine the association between interoceptive processing and psychopathology (depression and anxiety) in first-time pregnant women (3rd trimester). 17 first-time expectant mothers (mean age = 32.71 years) completed data collection at 28-32 gestational age. Interoception was evaluated using self-report measures (Interoceptive Accuracy and Attention Scales), a performance-based interoceptive accuracy task (Heartbeat Tapping Task; participants are required to tap a key whenever they feel a heartbeat), and neural markers of infant-specific interoceptive processing (heartbeat-evoked potentials - HEP - during the Infant Face Repetition-Suppression Task). A cluster mass permutation test was employed to identify the electrodes and time-windows where HEP amplitude was effectively modulated (right frontal-central; 308 - 600 ms). The Edinburgh Postnatal Depression Scale was used to evaluate depressive symptoms, while the State Anxiety Inventory (STAI-S) measured current anxiety levels. Significant positive correlations were found between interoceptive attention and anxiety (r =.645; p = .017), as well as between interoceptive attention and depression (r = .749; p = .003). Interoceptive accuracy was neither correlated with anxiety nor depression. A large (albeit non-significant) negative correlation (r = -.301, p = .368) was found between depressive scores and HEP emotional modulation in the infant condition, suggesting that infant-specific emotional modulation of HEP may be reduced in prenatal depression. These preliminary findings suggest that interoceptive processing is associated with prenatal psychopathology across several levels. Self-perceived beliefs about interoceptive attention were positively associated with both anxiety and depression. Furthermore, infant-specific neural markers of interoceptive processing may also play an important role in prenatal depressive symptomatology.
- Neurophysiological markers of cardiac interoceptive processing in first-time expectant mothersPublication . Braga, Patrícia Vilela; Marshall, Amanda; Lamela, Diogo; Jongenelen, Inês; Rocha, Nuno Barbosa; Costa, Raquel; Pasion, Rita; Schütz-Bosbach, Simone; Pinto, Tiago Miguel; Feldman, Ruth; Campos, Carlos; Campos, Carlos; Rocha, NunoPregnancy is a complex biological phenomenon where two distinct pathways may produce changes in interoception (ability to perceive and subjectively experience inner bodily states). First, pregnancy modifies the parental caregiving brain network, which includes key regions for interoceptive processing, particularly the insula. Second, pregnancy also changes the strength, frequency, and/or nature of interoceptive signals across different modalities (e.g., cardiac, respiratory, gastric). This study investigates pregnancy-related changes in neural markers of cortical interoceptive processing, specifically heartbeat-evoked potentials (HEP), by comparing first-time expectant mothers with non-pregnant, age-matched females. Data were collected from first-time expectant mothers (n = 13; Mage = 32.15 years) and matched controls (n = 8; mean age = 30.88 years) at 28–32 weeks of gestation. EEG recordings, time-locked to R-peaks (ECG), were obtained while participants completed the Infant Face Repetition Suppression Task. This paradigm was designed to induce an emotion (sad vs. neutral) and age-specific (infant vs. adult) modulation of HEP amplitude. A cluster mass permutation test was employed to identify the electrodes and time-windows where HEP amplitude was effectively modulated (right frontal-central; 308 - 600 ms). Repetition-suppression effects on HEP amplitude were observed for adult stimuli (p = .049, d = 0.499), while no modulation was observed in the infant condition (p = .471, d = 0.174). Pregnant participants displayed significantly lower HEP amplitude in adult trials in comparison to non-pregnant controls (p = .046, g = 0.997). Despite significant differences only emerging in the adult trials, pregnant women displayed lower HEP amplitude across all conditions. These findings suggest that pregnancy modifies cardiac interoceptive processing, leading to an overall decrease in HEP amplitude. Contrary to our hypothesis, expectant mothers did not exhibit infant- or emotion-specific changes in neural markers of cardiac interoception.
- Does attention to cardiac sensations modulate heartbeat-evoked potentials even after controlling for cognitive demands?Publication . Braga, Patrícia Vilela; Vieira, Beatriz; Carina, Fernandes; Barbosa, Fernando; Santos, Fernando Ferreira; Pereira, Mariana R.; Rocha, Nuno Barbosa; Mazer, Prune; Pasion, Rita; Schütz-Bosbach, Simone; Paiva, Tiago Oliveira; Campos, Carlos; Campos, Carlos; Rocha, Nuno; Mazer, PruneHeartbeat-evoked potentials (HEP) have been shown to be modulated by attentional focus (cardiac vs. exteroceptive attention), suggesting that HEP are a neural correlate of interoceptive prediction errors. However, this effect has not been consistently replicated, and differences in cognitive effort when contrasting interoceptive vs. exteroceptive attention may be a confounding factor. We devised a modified Heartbeat Attention Task to examine whether cardiac attention can modulate HEP amplitude even when cognitive demands are matched across interoceptive and exteroceptive conditions. In exteroceptive blocks, subjects were required to count subtle bursts of volume increase embedded within a continuous white noise. The bursts’ volume was individually tailored for each participant (near absolute threshold) and were presented in a rhythmic pattern replicating a typical heart rate. In interoceptive blocks, participants were asked to count their heartbeats, whilst the white noise was still presented, ensuring that the neural effects were driven by the attention shift rather than sensory changes. The task was first completed by 50 participants (25F; 28.44y) during a 9-electrode EEG recording: frontal, central and parietal sites. No significant differences were found regarding counted heartbeats (M=122.00) vs white noise bursts (M=118.86) as well as on perceived attentional efforts (heart M=65.00 vs bursts M=67.00), indicating similar task demands across conditions. No significant differences between conditions were found on HEP amplitude across all electrodes (p > .137 for all), suggesting no attentional modulation of HEP amplitude after accounting for cognitive demands. Due to the reduced number of electrodes, a follow-up sample of 26 participants (13F; 21.73y) completed the task using a new EEG geodesic 64-channel sensor net. This dataset is currently under processing and will allow for a more comprehensive data-driven analytic approach (cluster-based permutation test) to ensure whether the attentional modulation of HEP amplitude is indeed absent when accounting for cognitive demands.
- Enhancing autism therapy through smart tangible-based digital storytelling: Co-design of activities and feasibility studyPublication . Guneysu, Arzu; Kuoppamäki, Sanna; Reis, Helena; Sylla, CristinaStorytelling is an effective evidence-based practice as an accepted intervention by therapists for the therapy of children with autism spectrum disorder (ASD). Digital storytelling, particularly using smart tangibles, offers a structured, interactive and engaging environment for children with ASD allowing for repetition, offering feedback with visual supports, and giving the child more authority over the learning experience. This study presents a co-designed approach to digital storytelling activities with smart tangibles for autism therapy, aimed at enhancing multiple social and behavioral skills. Through co-design sessions with therapists, activity flows and scenarios were developed to target specific skill improvements. These include free play exploration, positive stimulus introduction, fostering cooperation to address disturbances, and incorporating magical objects to facilitate peer turn-taking. Additionally, real-life connections were emphasized to promote emotional regulation and multicultural understanding while further activities are designed to overcome routine issues, build tolerance to change, and enhance cognitive structuring. Feasibility was demonstrated through integration into therapy sessions of five children, where therapists independently utilized the system, fostering immersive and interactive storytelling experiences. Overall, the co-designed activities offer insights into enhancing therapy interventions for children with ASD beyond specific contexts, contributing to the broader design of autism therapy activities.
- In vivo activity of peptide-ionic liquid conjugates against diabetic woundsPublication . Gomes, A.; Ferraz, Ricardo; Ferreira, M.; Maciel, J.; Plácido, A.; Leal, E.; Gameiro, P.; Gonçalves, Teresa; Carvalho, E.; Gomes, P.Due to widespread multidrug-resistant (MDR) microbes, efficient treatments for infected wounds are being exhausted, which means that there is an alarming lack of effective antibiotics to treat diabetic foot ulcers (DFU). The increasing life expectancy of the population and the growing incidence of unhealthy lifestyles is leading to a concerning rise in the number of people affected with diabetes and related complications, being DFU amongst the most troublesome. In 2014, already about 11% of the Portuguese population had diabetes and this number is continuously growing every year. [1] Like other chronic wounds, DFU are difficult to heal, but their association with other diabetes complications, such as peripheral neuropathy and ischemia, underpin an exceedingly low healing rate and high propensity for persistent infections. In connection with the above, we have recently advanced peptide-ionic liquid conjugates (PILC) as potential active pharmaceutical ingredients for topical formulations to tackle DFU. PILC combine a short cosmeceutical peptide with collagenboosting action, with an ioni q b , k “ k” -catalyzed azide-alkyne cycloaddition reaction. This revealed one conjugate with an outstanding performance in vitro, namely, potent collagen-inducing effect, alongside microbicidal (bactericidal and fungicidal) action.[2] This conjugate was now tested for its wound healing ability in a mouse model of streptozotocin (STZ)-induced type 1 diabetes. The promising results obtained thus far in this animal model, alongside biophysical investigations on the potential antimicrobial mechanism of action of PILC, will be presented in this communication.
- Life cycle assessment using machine learningPublication . Gomes, Sofia Carolina Moura; Faria, Brígida Mónica; Oliveira, Alexandra Alves; Pinto, EdgarLife Cycle Assessment (LCA) is a scientific methodology that allows for assessing the impacto f a producto or servisse on the environment, throughout its life ccycle. It includes defining objectives and contexto, inventory, impact assessment, and interpretation phases. Artificial Itelligence (AI) refers to computer systems capable of performing tasks that typically require human intelligence. Machine Learning (ML) is na área of AI that envolves the development of algorithms capable of learning from data and making predictions or decisions based on data. LCA and ML have been combined o overcome LCA’s complexity at various stages and for different purposes, namely, to develop surrogate LCA tools. This study focuses on the application of ML in the Life Cycle Inventory (LCI) phase to find pollutant emissions generated into the environment to complete the LCI phase of the LCA. The presente work seeks to answer the following question: “Can Machine Learning techniques be applied to predict outcome variables of the LCI phase of LCA?”. These variables include all the inouts and outputs throughout the life cycle of a producto. The database used in this work comprises 865 observations containing agricultural input variables (e.g. chemical fertilizer, pesticides, huma labor, diesel fuel) and production output (yield and environmental emissions). The data was collected from literature and refers to kiwi, watermelon, citrus, tea, and hazelnut crops in Guilan province in northern Iran. Na expert in the field validated the estimation of pollutant emissions, calculated using Agri-footprint 4.0 and the updated version Agri-footprint 6. Additional key methodologies, standards and reports were also cponsulted for this research. Th Decision Tress and Neural Network models developed were able to estimate the pollutant emissions generated into the environment throughout the production process. The results of the Absolute Normalized Error for the Decision Tree, Neural Network1 and Neural Network2 were 1124.79, 0.07 and 0.14 respectively. The Friedman test, with p-value˂ 0.001, less than α=0.05, reveals statistically significant diferences in the Absolute Normalized Error values in at least one of the models. The Wilcoxon tes (p-value˂0.001)indicates significant diferences between all the models.
- Surface-active ionic liquids derived from antimalarial drugs and natural lipids that display multi-stage antiplasmodial activityPublication . Ferraz, Ricardo; Silva, Ana Teresa; Oliveira, Isabel S.; Duarte, Denise; Moita, Diana; Nogueira, Fátima; Prudêncio, Miguel; Gomes, Paula; Marques, Eduardo F.The use of Ionic Liquids (ILs) in Medicinal and Pharmaceutical Chemistry has been greatly evolving since they were first used as alternative solvents for the chemical synthesis of active pharmaceutical ingredients (APIs). ILs are now used with other purposes in this area, such as adjuvants in drug formulation and delivery, or even as bioactive compounds per se. New ionic structures with biologically relevant properties can be easily obtained through straightforward reactions, as nearly all APIs are ionizable and can be paired with counter-ions that could be either inert or offer additional beneficial biological effects. This efficient, cost-effective strategy for the rescuing and repurposing of drugs is particularly appealing for finding new options to combat "diseases of poverty" like malaria. We implemented this approach to “recycle” classical antimalarial aminoquinolines, namely, chloroquine (CQ) and primaquine (PQ), by pairing them with natural acidic lipids through acid-base reactions. Our goal was to create novel ILs capable of targeting multiple stages of the Plasmodium parasite’s life cycle. Additionally, we were interested in that such ILs could act as surface-active ionic liquids (SAILs), able to self-assemble into nanostructures displaying adequate bioavailability. For this purpose, we paired the antimalarial drugs with either fatty acids or bile acids, due to their biocompatibility and amphiphilic nature. The antiplasmodial activity and self-aggregation properties of the new SAILs were determined. PQ fatty acid salts preserved the liver-stage antiplasmodial activity of the original drug, while exhibiting significantly enhanced activity against blood-stage parasites. In the case of bile salts, those derived from PQ retained the efficacy of the parent drug, whereas the CQ-derived salts proved to be novel triple-stage antiplasmodial agents. The SAILs obtained from bile acids showed a remarkable ability to self-aggregate, with a notably lower critical micelle concentration compared to their respective sodium salts. Overall, these findings open a new strategy for drug repurposing, extending beyond antimalarials and other anti-infective therapies.
- «
- 1 (current)
- 2
- 3
- »