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- Advancing the understanding of pupil size variation in occupational safety and health: A systematic review and evaluation of open-source methodologiesPublication . Ferreira, Filipa; Ferreira, Simão; Mateus, Catarina; Rocha, Nuno; Coelho, Luís; Rodrigues, MatildePupil size can be used as an important biomarker for occupational risks. In recent years, there has been an increase in the development of open-source tools dedicated to obtaining and measuring pupil diameter. However, it remains undetermined determined whether these tools are suitable for use in occupational settings. This study explores the significance of pupil size variation as a biomarker for occupational risks and evaluates existing open-source methods for potential use in both research and occupational settings, with the goal of to prevent occupational accidents and improve the health and performance of workers. To this end, a two-phase systematic literature review was conducted in the Web of Science™, ScienceDirect®, and Scopus® databases. For the relevance of monitoring pupil size variation in occupational settings, 15 articles were included. The articles were divided into three groups: mental workload, occupational stress, and mental fatigue. In most cases, pupil dilation increased with workload enhancement and with higher levels of stress. Regarding fatigue, it was noted that an increase in this condition corresponded with a decrease in pupil size. With respect to the open-source methodologies, 16 articles were identified, which were categorized into two groups: algorithms and software. Convolutional neural networks (CNN)1 have exhibited superior performance among the various algorithmic approaches studied. Building on this insight, and considering the evaluations of software options, MEYE emerges as the premier open-source system for deployment in occupational settings due to its compatibility with a standard computer webcam. This feature positions MEYE as a particularly practical tool for workers in stable environments, like those of developers and administrators.
- Affinity coefficient for clustering autoregressive moving average modelsPublication . Nascimento, Ana Paula; Oliveira, Alexandra; Faria, Brígida Mónica; Pimenta, Rui; Vieira, Mónica; Prudêncio, Cristina; Nicolau, Helena BacelarIn 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.
- An integration of intelligent approaches and economic criteria for predictive analytics of occupational accidentsPublication . Gholamizadeh, Kamran; Zarei, Esmaeil; Yazdi, Mohammad; Rodrigues, Matilde A.; Shirmohammadi-Khorram, Nasrin; Mohammadfam, IrajOccupational accidents are a significant concern, resulting in human suffering, economic crises, and social issues. Despite ongoing efforts to comprehend their causes and predict their occurrences, the use of machine learning models in this domain remains limited. This study aims to address this gap by investigating intelligent approaches that incorporate economic criteria to predict occupational accidents. Four machine learning algorithms, Random Forest (RF), Support Vector Machine (SVM), Multivariate Adaptive Regression Spline (MARS), and M5 Tree Model (M5), were employed to predict occupational accidents, considering three economic criteria: basic income (BI), inflation index (II), and price index (PI). The study focuses on identifying the most suitable model for predicting the frequency of occupational accidents (FOA) and determining the economic criteria with the greatest influence. The results reveal that the RF model accurately predicts accidents across all income levels. Additionally, among the economic criteria, II had the most significant impact on accidents. The findings suggest that a reduction in FOA is unlikely in the coming years due to the increasing growth of II and PI, coupled with a slight annual increase in BI. Implementing appropriate countermeasures to enhance workers’ economic welfare, particularly for low-income employees, is crucial for reducing occupational accidents. This research underscores the potential of machine learning models in predicting and preventing occupational accidents while highlighting the critical role of economic factors. It contributes valuable insights for scholars, practitioners, and policymakers to develop effective strategies and interventions to improve workplace safety and workers’ economic well-being
- Application of CytoPath®easy vials in Cervical Cancer screening: Self‑sampling approachPublication . Fernandes, Sílvia P. M.; Vilarinho, Ana Sofia; Frutuoso, Amaro; Teixeira, Cidália; Silva, Regina Augusta A. P."CytoPath®Easy kit (DiaPath S.p.A.) offers a major advantage compared to other commercially available kits available for the screening of cervical cancer, as it does not require additional equipment for sample processing. Using this methodology, collected epithelial cells are immersed in a preservative liquid before setting as a thin layer on a slide via gravity sedimentation. Aims: To evaluate the suitability of the CytoPath®Easy kit for the processing of cervicalsamples, detection of pre‑neoplastic lesions, and nucleic preservation and extraction for HR‑HPV diagnosis. A total of 242 self‑sampled cervicalspecimens were utilized, with 192 collected in CytoPath®Easy vials and 50 collected and processed using the ThinPrepTM for comparative analysis. The samples underwent processing, Papanicolaou staining, and microscopic evaluation for morphological parameters. The extracted nucleic acids were assessed for purity and integrity, and the detection of high‑risk human papillomavirus (HR‑HPV) was carried out using the Alinitym HR HPV system kit (Abbott Laboratórios Lda). Both methods demonstrated effective performance, enabling the morphological assessment of the cervical epithelium. Statistical analysis indicated that ThinPrepTM yielded significantly better results in terms of cellularity. Conversely, CytoPath®Easy exhibited superior performance in terms of the quantity of extracted DNA and its degree of purification. Concerning the time consumed during processing, both methods were comparable, with the CytoPath®Easy methodology standing out for its cost‑effectiveness, as it does not necessitate additional instruments and consumables. The novel CytoPath®Easy methodology proves effective in preserving both nucleic acids and cell morphology characteristics, two crucial features for cervical cancer screening."
- Betulinic acid for glioblastoma treatment: Reality, challenges and perspectivesPublication . Fernandes, Sílvia; Vieira, Mariana; Prudêncio, Cristina; Ferraz, RicardoBetulinic acid is a naturally occurring compound that can be obtained through methanolic or ethanolic extraction from plant sources, as well as through chemical synthesis or microbial biotransformation. Betulinic acid has been investigated for its potential therapeutic properties, and exhibits anti-inflammatory, antiviral, antimalarial, and antioxidant activities. Notably, its ability to cross the blood–brain barrier addresses a significant challenge in treating neurological pathologies. This review aims to compile information about the impact of betulinic acid as an antitumor agent, particularly in the context of glioblastoma. Importantly, betulinic acid demonstrates selective antitumor activity against glioblastoma cells by inhibiting proliferation and inducing apoptosis, consistent with observations in other cancer types. Compelling evidence published highlights the acid’s therapeutic action in suppressing the Akt/NFκB-p65 signaling cascade and enhancing the cytotoxic effects of the chemotherapeutic agent temozolomide. Interesting findings with betulinic acid also suggest a focus on researching the reduction of glioblastoma’s invasiveness and aggressiveness profile. This involves modulation of extracellular matrix components, remodeling of the cytoskeleton, and secretion of proteolytic proteins. Drawing from a comprehensive review, we conclude that betulinic acid formulations as nanoparticles and/or ionic liquids are promising drug delivery approaches with the potential for translation into clinical applications for the treatment and management of glioblastoma.
- Bioactive peptides from milk proteins with antioxidant, anti-inflammatory, and antihypertensive activitiesPublication . Borges, Thaís; Coelho, Pedro; Prudêncio, Cristina; Gomes, Ana; Gomes, Paula; Ferraz, Ricardo; Coelho, Pedro; Prudêncio, Cristina; Ferraz, RicardoPeptides from protein ingredients exhibit key biological activities, including antimicrobial, antihypertensive, antioxidant, anti-inflammatory, analgesic, and immunomodulatory effects. Aligning with the One Health approach, there is growing investment in promoting pet health and well-being. As a result, sustainable functional ingredients are increasingly essential for pet food development. In this work, peptides derived from lactoferrins of different mammalian species were synthesized and their antioxidant, anti-inflammatory, and antihypertensive activities were investigated. This study examined the antioxidant, anti-inflammatory, antihypertensive activities, and cytotoxicity of bioactive peptides derived from lactoferrins of various mammalian species through spectroscopical methods. The peptides were produced via chemical synthesis (bottom-up approach). Peptides derived from bovine lactoferrin showed the most promising antioxidant and anti-inflammatory activities, whereas those derived from human lactoferrin showed the highest antihypertensive effects and the lowest cytotoxicity. In short, milk-derived peptides with antioxidant, anti-inflammatory, and antihypertensive activity were identified. This motivates further studies to better characterize these peptides, including their properties and pharmacokinetics in vivo, to assess their true potential as nutraceutical agents.
- Challenges of learning human digital twin: case study of mental wellbeing: Using sensor data and machine learning to create HDTPublication . Vildjiounaite, Elena; Kallio, Johanna; Kantorovitch, Julia; Kinnula, Atte; Ferreira, Simão; Rodrigues, Matilde; Rocha, NunoHuman Digital Twin (HDT) is a powerful tool to create a virtual replica of a human, to be used for example for designing interactions with physical systems, preventing cognitive overload, managing human capital, and maintaining a healthy and motivated workforce. Building human twins is a challenging task due to the need to reliably represent each corresponding human being, and the fact that human beings notably differ from each other. Therefore, relying solely on expert knowledge is insufficient, and human twins must learn the specifics of each individual in order to accurately represent them. This paper focuses on AI methods for modelling the mental wellbeing of knowledge workers because the mounting cognitive demands of both white-collar and blue-collar work lead to employees’ stress, and stress leads to diminished creativity and motivation, increased sick leaves, and in severe cases, accidents, burnouts, and disabilities. This paper describes the main building blocks of AI-based detectors of mental stress and highlights the main challenges and future directions of research., which are expected to be relevant also for HDT learning in other domains because the high degree of individuality is ubiquitous in all human activities.
- A cross-national investigation of psychosis-like experiences in five European countries included in the E-CLECTIC study: Psychometric challenges in studying their measurementPublication . Siddi, Sara; Ochoa, Susana; Larøi, Frank; Lincoln, Tania M.; Schlier, Bjorn; Zaytseva, Yuliya; Laloyaux, Julien; Kozáková, Eva; Cella, Matteo; Ntouros, Evangelos; Bozikas, Vasileios; Rocha, Nuno; Gawęda, Łukasz; Rocha, Susana Aguiar; Preti, AntonioPsychotic-like experiences (PLEs) are subtle, subclinical perturbations of perceptions and thoughts and are common in the general population. Their characterisation and unidimensionality are still debated. This study was conducted by the Electronic–halluCinations-Like Experiences Cross-culTural International Consortium (E-CLECTIC) and aimed at measuring the Community Assessment of Psychic Experiences (CAPE) factorial structure across five European countries (Belgium; Czech Republic, Germany; Greece, and Spain) and testing the adequacy of the unidimensional polytomous Rasch model of the tool via Partial Credit Model (PCM) of the CAPE to detect people with a high risk for developing psychosis. The sample included 1461 participants from the general population. The factorial analysis confirmed the best fit for the bifactor implementation of the three-factor model, including the positive, negative and depressive dimensions and a general factor. Moreover, the unidimensional polytomous Rasch analysis confirmed that CAPE responses reflected one underlying psychosis proneness. The study proved that the CAPE measures a single latent dimension of psychosis-proneness. The CAPE might help locate and estimate psychosis risk and can be used as a screening tool in primary care settings/education settings.
- A custom-built single-channel in-ear electroencephalography sensor for sleep phase detection: an interdependent solution for at-home sleep studiesPublication . Borges, Daniel Filipe; Soares, Joana Isabel; Silva, Heloísa; Felgueiras, João; Batista, Carla; Ferreira, Simão; Rocha, Nuno; Leal, AlbertoSleep is vital for health. It has regenerative and protective functions. Its disruption reduces the quality of life and increases susceptibility to disease. During sleep, there is a cyclicity of distinct phases that are studied for clinical purposes using polysomnography (PSG), a costly and technically demanding method that compromises the quality of natural sleep. The search for simpler devices for recording biological signals at home addresses some of these issues. We have reworked a single-channel in-ear electroencephalography (EEG) sensor grounded to a commercially available memory foam earplug with conductive tape. A total of 14 healthy volunteers underwent a full night of simultaneous PSG, in-ear EEG and actigraphy recordings. We analysed the performance of the methods in terms of sleep metrics and staging. In another group of 14 patients evaluated for sleep-related pathologies, PSG and in-ear EEG were recorded simultaneously, the latter in two different configurations (with and without a contralateral reference on the scalp). In both groups, the in-ear EEG sensor showed a strong correlation, agreement and reliability with the ‘gold standard’ of PSG and thus supported accurate sleep classification, which is not feasible with actigraphy. Single-channel in-ear EEG offers compelling prospects for simplifying sleep parameterisation in both healthy individuals and clinical patients and paves the way for reliable assessments in a broader range of clinical situations, namely by integrating Level 3 polysomnography devices. In addition, addressing the recognised overestimation of the apnea-hypopnea index, due to the lack of an EEG signal, and the sparse information on sleep metrics could prove fundamental for optimised clinical decision making.
- Dissociating cognitive and affective empathy across psychopathy dimensions: the role of interoception and alexithymiaPublication . Campos, Carlos; Rocha, Nuno Barbosa; Barbosa, FernandoThis study examined the associations between psychopathy dimensions (triarchic phenotypes and classical factors), empathy domains (cognitive and affective), and interoception (interoceptive attention and accuracy) while accounting for the putative role of alexithymia. A community sample (n = 515) completed an online survey encompassing: Triarchic Psychopathy Measure (boldness, meanness, disinhibition); Levenson Self-Report Psychopathy Scale (primary and secondary psychopathy); Body Perception Questionnaire (interoceptive attention); Interoceptive Accuracy Scale; Toronto Alexithymia Scale. Hierarchical linear regression models were implemented for hypothesis-driven analyses examining the associations between psychopathy, empathy, and interoception while controlling for sex, age, and alexithymia. Exploratory path models were employed to investigate alexithymia and/or cognitive empathy as mediators between interoception and psychopathy. Our results largely confirmed the postulated empathy profiles across psychopathy dimensions, as meanness and primary psychopathy displayed a broad empathy impairment, while disinhibition and secondary psychopathy were only associated with diminished cognitive empathy. Importantly, boldness displayed a unique pattern (enhanced cognitive empathy and reduced affective empathy), further reinforcing its importance within the constellation of psychopathy traits. Contrary to our hypotheses, self-perceived interoceptive attention and accuracy were not associated with either psychopathy dimension after controlling for alexithymia. However, interoceptive accuracy and alexithymia were associated with cognitive empathy, while alexithymia was also positively related to all psychopathy dimensions (as expected), despite the unexpected strong and negative association with boldness. Exploratory analyses suggested significant indirect effects (mediation) between interoceptive accuracy and psychopathy via alexithymia and/or cognitive empathy. These mediating effects must be interpreted with caution and future studies should be designed to formally test this model.