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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."
- Assessing carbohydrate counting accuracy: Current limitations and future directionsPublication . Amorim, Débora; Miranda, Francisco; Santos, Andreia; Graça, Luís; Rodrigues, João; Rocha, Mara; Pereira, Maria Aurora; Sousa, Clementina; Felgueiras, Paula; Abreu, Carlos; Costa-Rodrigues, JoaoDiabetes mellitus is a prevalent chronic autoimmune disease with a high impact on global health, affecting millions of adults and resulting in significant morbidity and mortality. Achieving optimal blood glucose levels is crucial for diabetes management to prevent acute and long-term complications. Carbohydrate counting (CC) is widely used by patients with type 1 diabetes to adjust prandial insulin bolus doses based on estimated carbohydrate content, contributing to better glycemic control and improved quality of life. However, accurately estimating the carbohydrate content of meals remains challenging for patients, leading to errors in bolus insulin dosing. This review explores the current limitations and challenges in CC accuracy and emphasizes the importance of personalized educational programs to enhance patients’ abilities in carbohydrate estimation. Existing tools for assessing patient learning outcomes in CC are discussed, highlighting the need for individualized approaches tailored to each patient’s needs. A comprehensive review of the relevant literature was conducted to identify educational programs and assessment tools dedicated to training diabetes patients on carbohydrate counting. The research aims to provide insights into the benefits and limitations of existing tools and identifies future research directions to advance personalized CC training approaches. By adopting a personalized approach to CC education and assessment, healthcare professionals can empower patients to achieve better glycemic control and improve diabetes management. Moreover, this review identifies potential avenues for future research, paving the way for advancements in personalized CC training and assessment approaches and further enhancing diabetes management strategies.
- Assessing resilience potentials in management of occupational safety and health in hospitals: Development and validation of a toolPublication . Afonso-Fernandes, J.; Barbosa, J.; Arezes, P.; Pardo-Ferreira, C.; Rubio-Romero, J.C.; Rodrigues, Matilde Alexandra; Rodrigues, MatildeA resilient Occupational Safety and Health (OSH) management system is crucial for effectively addressing potential future public emergencies, ensuring the continuous protection of workers' safety and health. Therefore, it is essential for organizations, particularly hospitals, to assess their resilient performance and employ tools that are appropriate and tailored to their specific context. This study aims to enhance the understanding of resilience potentials in OSH management within hospital settings. To this end, an assessment tool was developed based on the Resilience Assessment Grid (RAG). A Delphi study involving subject matter experts was conducted to refine the tailored RAG tool. Following this, a pilot test was administered to 404 healthcare professionals across three public hospitals, with subsequent psychometric analysis. Exploratory Factor Analysis (EFA) identified a four-dimensional structure. Goodness-of-fit indices demonstrated acceptable values, confirming the adequacy of the measurement model. Reliability testing indicated that the 29 item assessment tool is both valid and reliable. The tailored RAG tool was successfully validated, enabling the identification of strengths and weaknesses in OSH management.
- Assessing resilience potentials in management of occupational safety and health in hospitals: Development and validation of a toolPublication . Fernandes, Joana Afonso; Barbosa, Judite Lopes; Arezes, Pedro; Ferreira, María del Carmen Pardo; Rubio-Romero, Juan Carlos; Rodrigues, Matilde A.; Rodrigues, Matilde; Afonso Fernandes, JoanaA resilient Occupational Safety and Health (OSH) management system is crucial for effectively addressing potential future public emergencies, ensuring the continuous protection of workers’ safety and health. Therefore, it is essential for organizations, particularly hospitals, to assess their resilient performance and employ tools that are appropriate and tailored to their specific context. This study aims to enhance the understanding of resilience potentials in OSH management within hospital settings. To this end, an assessment tool was developed based on the Resilience Assessment Grid (RAG). A Delphi study involving subject matter experts was conducted to refine the tailored RAG tool. Following this, a pilot test was administered to 404 healthcare professionals across three public hospitals, with subsequent psychometric analysis. Exploratory Factor Analysis (EFA) identified a four- dimensional structure. Goodness-of-fit indices demonstrated acceptable values, confirming the adequacy of the measurement model. Reliability testing indicated that the 29 item assessment tool is both valid and reliable. The tailored RAG tool was successfully validated, enabling the identification of strengths and weaknesses in OSH management.
- Assessing the impact of binge drinking and a prebiotic intervention on the gut–brain axis in young adults: protocol for a randomised controlled trialPublication . Martins, Diogo Prata; Nobre, Clarisse; Antunes, Natália Almeida; Azevedo, Pedro; Sousa, Sónia S.; Crego, Alberto; Cryan, John; Sampaio, Adriana; Carbia, Carina; Caneda, Eduardo LópezAdolescence and youth are periods of significant maturational changes, which seem to involve greater susceptibility to disruptive events in the brain, such as binge drinking (BD). This pattern—characterised by repeated episodes of alcohol intoxication—is of particular concern, as it has been associated with significant alterations in the developing brain. Recent evidence indicates that alcohol may also induce changes in gut microbiota composition and that such disturbances can lead to impairments in both brain function and behaviour. Moreover, there is evidence suggesting that microbiota-targeted interventions (psychobiotics) may help mitigate alcohol-induced damage in individuals with chronic alcohol use, positively influencing cognitive and brain functioning. However, the triadic relationship between BD, gut microbiota and brain structure/function, as well as the therapeutic potential of gut microbiota-targeted interventions in young binge drinkers, remains largely unexplored. This double-blind, parallel, randomised controlled study aims to evaluate whether a BD pattern disrupts gut microbiota diversity in young college students (primary outcome). Additionally, it seeks to determine whether alcohol-induced alterations in the microbial composition and function are associated with immunological, cognitive, neurostructural and neurofunctional impairments (secondary outcomes). A total of 82 college students (36 non/low drinkers and 46 binge drinkers (BDs)), matched for age and sex, will be recruited from the University of Minho (Portugal). During the pre-intervention phase, all participants will undergo a comprehensive assessment protocol, including gut microbiota profiling, measurement of inflammatory markers, neuropsychological testing and structural and functional MRI. BDs will then be randomly assigned to a 6-week intervention with either a prebiotic (inulin) or a placebo (maltodextrin). Post-intervention assessment will mirror the baseline protocol, and craving and alcohol use will be monitored for 3 months. The present protocol was approved by the Ethics Committee for Social and Human Sciences of the University of Minho (CEICSH 078/2022), ensuring compliance with national and international ethical guidelines, including the Declaration of Helsinki. Participation is voluntary and preceded by informed consent, with confidentiality and data processing safeguarded in accordance with the General Data Protection Regulation. All procedures are safe and non-invasive, and the prebiotics used are recognised as food ingredients in Europe, hold Generally Recognized as Safe status in the USA and are classified as dietary fibres by the Food and Drug Administration. Findings will be disseminated in national and international scientific forums, with preference for publication in open-access, peer-reviewed journals.
- Assessing work-related musculoskeletal disorders and psychosocial risks in bus drivers: Insights from a municipal company case study in PortugalPublication . Silva, Tânia T.; Mendes, Tatiana R.; Lapa, Inês; Carvalho, Paulo; Rodrigues, Matilde A.; Rodrigues, Matilde; Carvalho, PauloThe public transport sector plays a crucial role in society, oering essential services and providing employment to a significant number of drivers. Despite the importance of this sector, it is essential to recognize that drivers are exposed to various occupational risks inherent to their daily work, which can have serious implications for their health. This study aims to characterize and analyse Work-Related Musculoskeletal Disorders (WMSD) and psychosocial risks in a public transport company. In the initial phase of the study, a questionnaire was administered to assess musculoskeletal symptoms and psychosocial risks. In the second phase, an inertial motion capture system was used to evaluate the risk of developing WMSD. The results revealed a significant and concerning prevalence of burnout, with over 60% of workers reporting high or severe levels across all dimensions (i.e., personal, work-related, and client-related burnout). Depression, anxiety, and stress were within typical ranges, though a relevant percentage of participants exhibited severe and extremely severe levels of depression (7.2%), anxiety (12.2%), and stress (8%). Musculoskeletal discomfort was highly prevalent, particularly in the lower back (68.3%) and neck regions (57.2%), regarding pain over the last 12 months. Additionally, the risk of developing WMSDs was high across the various microtasks, which were analyzed across dierent bus lines and routes, with Rapid Upper Limb Assessment (RULA) scores ranging from 4 (Medium Risk) to 7 (Very High Risk). Based on the results, varying bus types and routes is recommended. Programs should enhance wellbeing, and studies should assess interventions on health, stress, and occupational risks focused on enhancing worker wellbeing should be implemented, and future studies should assess the impact of interventions targeting health, stress, and occupational risks.
- Betulinic acid and obesity-related disordersPublication . Azevedo, Lara; Ferraz, Ricardo; Vieira, Mónica; Prudêncio, Cristina; Fernandes, Sílvia; Ferraz, Ricardo; Almeida Vieira, Mónica Andreia; Prudêncio, Cristina; Fernandes, SílviaThe obesity epidemic is not just a health issue, it is increasingly driving a shift in the prevalence of chronic diseases, affecting 890 million adults and straining healthcare systems worldwide. Conditions such as type 2 diabetes mellitus, cardiovascular diseases, non-alcoholic fatty liver disease, and various cancer types are closely tied to this growing crisis. Betulinic acid has anti-inflammatory, antioxidant and anti-cancer properties and modulates key metabolic pathways such as NF-κB and AMPK signaling. This compound improves insulin sensitivity, reduces hepatic steatosis, mitigates the progression of atherosclerosis and fibrosis, and suppresses inflammatory responses, which are important in treating those obesity-related disorders. Additionally, betulinic acid use in cancer treatment has been explored due to its potential in angiogenesis and metastasis inhibition and promotion of apoptosis. This review spotlights the therapeutic potential of the natural compound betulinic acid in processes such as insulin sensitivity, glucose and lipid metabolism, adiposity, inflammation, oxidative stress, intestinal microbiota, and other mechanisms underlying different obesity-related disorders. Overall, besides strong therapeutic potential of betulinic acid, described limitations such as poor aqueous solubility, limited bioavailability, production and extraction have resulted in scarce clinical data making it premature to draw definitive conclusions regarding its application in clinical practice.