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- The ‘extra’ sparkle in higher education Institutions: Exploring staff perceptions towards corporate volunteeringPublication . Silva, Carina; Mendes, Telma; Ferreira, Marisa R.; Faria, TatianaThe analysis of barriers to volunteering and the intraorganizational conditions that can promote or hinder employee engagement in volunteer programs are important for researchers and practitioners. Despite the relevance of these topics, they remain unexplored in the context of Higher Education Institutions (HEIs), especially from the staff perspective. This represents an important theoretical gap, as HEIs are institutions that act in the public interest and represent the ideal context for spreading the culture of corporate volunteering due to their potential to connect theory to practice. Therefore, this study aims to explore how intraorganizational support moderates the relationship between both motivations and barriers to volunteering with the personal/impersonal outcomes of participating in these activities. The research is based on a sample of 155 public HEI employees obtained from the Northern Euro-region of Portugal/Galicia. The results of the partial least squares structural equation modeling (PLS-SEM) suggest that motivations to volunteer were positively associated with personal/impersonal outcomes stemming from these activities, while barriers to volunteering were negatively related. When testing the moderating effects, we found that HEI intraorganizational support weakened (strengthened) the positive (negative) relationship between motivations (barriers) to volunteer and the personal/impersonal outcomes stemming from volunteer activities. Overall, this empirical evidence allows us to understand both motivations and barriers to volunteering, as well as how intraorganizational conditions discourage participation in volunteering.
- Changes in co-contraction magnitude during functional tasks following anterior cruciate ligament reconstruction: A systematic reviewPublication . Paredes, Ricardo; Crasto, Carlos; Mesquita Montes, António; Arias-Buría, José L.Anterior cruciate ligament reconstruction (ACLR) is a common orthopedic surgery procedure whose incidence has increased over the past few decades. Nevertheless, it is believed that neuromuscular control remains altered from the early stages after ACLR to later years. Therefore, the aim of this study was to systematically evaluate the magnitude of co-contraction during functional tasks in subjects with unilateral ACLR. A systematic review design was followed. The search strategy was conducted in PubMed, Scopus, EBSCO, PEDro, Cochrane Library, and Web of Science databases from inception to March 2024. The inclusion criteria involved studies using electromyography (EMG) data to calculate muscle pair activation via the co-contraction index (CCI) in ACLR individuals during functional tasks. The Preferred Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and study quality was evaluated using National Institutes of Health (NIH) Study Quality Assessment Tools. The search strategy found a total of 792 studies, of which 15 were included in this systematic review after reviewing the eligibility criteria. The magnitude of co-contraction was assessed in a total of 433 ACLR individuals and 206 controls during functional tasks such as hop, drop-land, step-up/step-down, and gait. Overall, approximately 79.6% of individuals who had undergone ACLR exhibited increased levels of co-contraction magnitude in the ACLR limb, while 8.5% showed low co-contraction levels. The findings of the review suggest that, during functional tasks, most individuals who have undergone ACLR exhibit changes of co-contraction magnitude in the involved limb.
- Editorial for “3D breast cancer segmentation in DCE‐MRI using deep learning with weak annotation”Publication . Nogueira, Luísa; Adubeiro, Nuno; Nunes, Rita G.Magnetic resonance imaging (MRI) shows higher diagnostic performance in the detection of breast tumors, compared with other imaging modalities. Breast MRI protocols include dynamic contrast-enhanced (DCE) images with high spatial and temporal resolution and are central indiagnosis, staging, and follow-up of breast cancer. DCE features provide physiological and anatomical lesion characteristics. To extract these data, manual lesion segmentation is currently performed, which is a critical time-consuming step,introducing bias and variability and impacting the reproducibility of the extracted features. To overcome these limitations, artificial intelligence algorithms have been explored, especially deep learning (DL) methods, for automatic lesion segmentation. This has been an active area of research, pivotal in the analysis of quantitative medical images. Most lesion segmentation methods have been based on semiautomatic or supervised learning approaches, presenting an important limitation: slice-by-slice 2D segmentations are typically performed, leading to suboptimal 3D masks upon concatenation. Recently, DL methods based on vision transformers have gained popularity in breast lesion segmentation, improving results over traditional machine learning. Although fully convolutional neural networks (CNNs) show powerful learning capabilities, their performance in learning long-range dependencies is limited, presenting decreased capacity in the segmentation of structures including different shapes and scales. UNETR is an architecture that replaces the CNN-based encoder with a transformer, which can capture low-level details in 3D segmentation. UNETR directly connects the encoder to the decoder via skip connections and can directly use volumetric data. Compared with CNN or transformer-based segmentation methods, UNETR can better capture dependencies at diverse spatial scales, both local and long-range enabling improved segmentation. In this retrospective study, Kim et al developed a model based on weak annotations, for detection and 3D segmentation of breast cancer in a sample of 736 women, using different input combinations in a three-time point (3TP) approach, from DCE-MRI images, acquired in two 3 T scanners from different manufacturers. The sample was divided into training (N = 544)and test sets (N = 192). To reduce the workload required toobta in ground truth segmentations, tumors were first segmented using weak annotations by two radiologists in consensus drawing bounding rectangles encompassing the lesion on two projection images. The rectangles were used to generate a 3D bounding box applied to the image obtained by subtracting the pre-contrast from the post-contrast image. An automatic thres holding method was used for automatic lesion segmentation; the mask was then refined to better define the lesion boundaries and exclude noisyor confounding regions (false positives). For training the segmen-tation network, images acquired at three different temporal acquisition points (pre-contrast, early, and delayed post-contrast) were used to construct three inputs: input 1 (pre-contrast, early phase),input 2 (pre-contrast, early, and delayed phase), and input 3 (pre-contrast and delayed phase). A different UNETR model wastrained for each input, and segmentation performances were compared, qualitatively and quantitatively, based on MRI features and immunohistochemical (IHC) classification. The best DL model presented a reliable performance for automated 3D segmentation of breast cancer with a median dicesimilarity coefficient (DSC) of 0.75 for the whole breast and 0.89 for the index lesion. The performance of the UNETR model was in accordance with the DSC values reported by other researchers employing alternative segmentation algorithms. Regarding the qualitative analysis of the segmentation results, the segmentation was successfully done in 83% of the cases derived from inputs 1 and 2, and from these, 95% were considered as acceptable detection. The authors also evaluated the performance of the segmentation according to base line characteristics and found significant differences for the whole breast and main lesion. For main lesion, significant differences were observed according to lesion size and IHC type. Regarding visual analysis, significant differences were found between lesion type (mass vs. non-mass enhancement) and background parenchymal enhancement (BPE) level. In their study, there were nine cases of failed segmentation, which corresponded totumors with small volumes, from which five cases were not segmented and four cases corresponded to abundant BPE,meaning false-positive results.© 2023 International Society for Magnetic Resonance in Medicine. 2263 Further developments of 3D UNETR architecture could be done to improve small lesion detection, to distinguish between mass and non-mass lesions, especially the boundaries of non-masses, and to distinguish between BPE and tumors. Attending to the implementation of DL algorithms in the clinical practice, this type of algorithm is expected to improve the detection of small lesions and the prediction of response to treatment, there by reducing the number of performed biopsies and, potentially, enabling the use of an abbreviated MRI pro-tocol, which would reduce MRI exam durations, improving patient comfort, and reducing costs.
- Editorial for “Detecting adverse pathology of prostate cancer with a deep learning approach based on a 3D swin-transformer model and biparametric MRI: A multicenter retrospective study"Publication . Adubeiro, Nuno; Nogueira, LuísaProstate cancer (PCa) is the second most prevalent cancer among men worldwide. Timely and accurate diagnosis is important to avoid overtreatment of men with indolent, clinically insignificant PCa and to offer radical curative treatment with life-threatening, clinically significant PCa. Radical prostatectomy (RP) has become the standard care for eligible patients because of its cancer control and improved survival. Although most patients remained disease-free after RP, 20%–30% of patients develop recurrence of the disease at follow-up.3 Therefore, the assessment of reliable prognostic predictors of recurrence after RP is clinically important for guiding clinical decision-making and patient counseling. To date, several factors are considered adverse pathology (AP) features such as preoperative prostate-specific antigen (PSA) levels, Gleason score, tumor stage, surgical margin status, lymph node invasion, extracapsular extension (ECE), and seminal vesicle invasion (SVI). All of them have been identified as prognostic factors for recurrence after RP.
- Environmentally friendly and cost-effective approaches to reduce toxin content in toxic cyanobacterial biomassesPublication . Loss, Letícia; Azevedo, Joana; Azevedo, Tomé; Freitas, Marisa; Vasconcelos, Vítor; Campos, AlexandreCyanobacterial outgrowths are naturally occurring processes in eutrophic aquatic ecosystems. Furthermore, as a result of climate change and anthropogenic pollution, cyanobacteria harmful algal blooms (CyanoHABs) are expanding worldwide. CyanoHABs are considered a threat to human health and environment due to the production of potent toxic substances, but at the same time, valuable products can be obtained from these microorganisms. The main objective of this study was to test straightforward and cost-effective methods to reduce the toxin content of cyanobacterial biomass for the exploitation of this important biological resource. To carry out this study, lyophilized or hydrated biomass from microcystin-LR (MC-LR) producing Microcystis aeruginosa and cylindrospermopsin (CYN) producing Chrysosporum ovalisporum strains were subjected to the following treatments: (1) thermal (50 °C); (2) ultraviolet (UV) radiation; (3) ozone; and (4) sunlight, for periods varying between 2 and 12 h. MC-LR and CYN concentrations were quantified by LC-MS and compared between experimental groups. The results show a significant reduction in the amount of MC-LR in M. aeruginosa biomass (lyophilized and hydrated) exposed to sunlight. Since no other treatment reduced MC-LR in M. aeruginosa biomass, this molecule was demonstrated to be very stable. Regarding CYN, the concentration of this toxin in C. ovalisporum biomass was significantly reduced with the exposure to UV radiation, to approximately 51% of the initial concentration after 2 h of exposure; 86% reduction after 5 h of exposure; and 77% reduction after 12 h of exposure. Overall, this study demonstrates that the toxicity of cyanobacterial biomass can be reduced by employing environmentally friendly and cost-effective treatments with sunlight and UV radiation.
- Applications of brain wave classification for controlling an intelligent wheelchairPublication . Avelar, Maria Carolina; Almeida, Patricia; Faria, Brígida Mónica; Reis, Luís PauloThe 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.
- Contributions for the validation of the European Portuguese version of the vascular quality of life-6 questionnaire for Peripheral Artery diseasePublication . Oliveira, Rafaela; Pedras, Susana; Pimenta, Rui; Silva, IvonePeripheral arterial disease (PAD) is an occlusive atherosclerotic disease of the arteries of the extremities of the body that affects more than 230 million people worldwide. The most common symptom is intermittent claudication, described as leg pain which occurs mainly while walking. The symptoms impair the ambulation and functional capacity of patients, leading to loss of mobility, disease deterioration, increased risk of other cardiovascu-lar diseases, and lower quality of life (QoL). Therefore, the aim of this study was to perform a cross-cultural adaptation and validation of the VascuQol-6 questionnaire for the Portuguese population to obtain a quick, sensitive, and easy-to-use way to assess the QoL of Portuguese patients diagnosed with PAD. The Vascular Quality of Life-6 Questionnaire (VascuQoL-6) was adapted and translated into European Portuguese using standard validation methodology, including 115 patients with a mean age of 64.67 (7.23) years, with PAD with IC stable for more than three months; and ABI < 0.9 at rest. VascuQoL-6, SF-36, International Physical Activity Questionnaire (IPAQ), and the PAD Knowledge Questionnaire (PADKQ) were used. Reliability, con-struct validity analysis through convergent and discriminant validity, known-group validity, and responsiveness analysis were tested. The Cronbach’s alpha was 0.64 and the average inter-item correlation was 0.27, indicating acceptable internal consistency. VascuQoL-6 was positively associated with SF-36 Physical Component Summary and Mental Component Summary scores (r = 0.64, p < 0.01 and r = 0.42, p < 0.01, re-spectively). In turn, there was no significant correlation between VascuQoL-6 scores and the PADKQ or IPAQ. A statistically significant difference between groups according to IC severity [F(2.47) = 8.35, p < 0.001] was found. A paired samples t-test showed differences between VascuQol-6 scores before a walking program (M = 15.65, SD = 3.09), and after a walking program (M = 17.41, SD = 2.71), t(67) = 3.94, p ≤ 0.001. The VascuQoL-6 is a six-item instrument to assess the QoL associated with PAD with good psychometric properties, convergent and dis-criminant validity with SF-36, PADKQ and IPAQ. The instrument proved to have known group validity and responsiveness.
- Sleep quality of heavy vhicles’ professional drivers: an analysis based on self-perceived feedbackPublication . Faria, Brígida Mónica; Lopes, Tatiana; Oliveira, Alexandra; Pimenta, Rui; Gonçalves, Joaquim; Carvalho, Victor; Faria, Brigida Monica; Pimenta, Rui; Oliveira, AlexandraSleep is a crucial biological need for all individuals, being reparative on a physical and mental level. Driving heavy vehicles is a task that requires constant attention and vigilance, and sleep deprivation leads to behavioral and physiological changes that can develop sleep disorders which can put lives at risk The main objectives of this study are to describe and evaluate sleep quality, excessive daytime sleepiness, circadian preference, and risk of suffering from obstructive sleep apnea in a population of Portuguese professional drivers. To fulfill the objectives, 43 Portuguese professional drivers, between 23 and 63 years old, answered validated questionnaires: Epworth Sleepiness Scale, Morningness–Eveningness, Stop-Bang Questionnaire, and Pittsburgh Sleep Quality Index. Results indicated that older drivers tend to experience higher daytime sleepiness (11 ± 3.4; p = 0.002) and obstructive sleep apnea risk (4.5 ± 1.5; p = 0.03). Regarding sleep quality, the majority of drivers were classified with poor sleep quality (74.4%). It was possible to infer statistical differences between groups based on body mass index (p = 0.037), the type of route (p = 0.01), and physical activity (p = 0.005). Drivers have an indifferent circadian preference and small-course drivers have a worse sleep health perception. Therefore, it is essential to implement prevention programs, promoting the basic rules for better sleep quality as well as identifying sleep disorders to minimize possible road accidents.
- Da eticidade discursiva: pelos “véus” da liberdade? da fhrónesis à ruach dos silêncios?Publication . Rodrigues, Ricardo Alexandre CardosoOs desafios da vida em sociedade corroboram pactos, acordos, convenções de diversas ordens, apresentando, pois, como substrato comum, a comunicação, em concreto, os códigos da linguagem, pacificadores de intenções, apesar dos incontornáveis diferenciais de desempenho, apreensão e compreensão, entre universos múltiplos. Os espaços, físicos, intangíveis e temporais, são templos, são oportunidades, são momentos, que decidimos, convencionamos, ocupar com silêncios, palavras, ações, omissões, etc., forjados que são pelas/nas boas egrégoras das liberdades. De um modo geral, as liberdades são poderes, faculdades, potências, ético-juridicamente considerados, expansíveis, atribuídos aos indivíduos, e que se realizam até, em paralelo, concorrencialmente, e através das liberdades dos demais, em espaços plenos de possibilidades. Posições jurídicas, reforçadas pelas expressões de créditos sociais, em particular, de índole garantística e responsabilizante.
- Validity of central pain processing biomarkers for predicting the occurrence of oncological chronic pain: a study protocolPublication . Carrillo‑de‑la‑Peña, M. T.; Fernandes, C.; Castro, Catarina; Medeiros, R.Despite recent improvements in cancer detection and survival rates, managing cancer-related pain remains a significant challenge. Compared to neuropathic and inflammatory pain conditions, cancer pain mechanisms are poorly understood, despite pain being one of the most feared symptoms by cancer patients and significantly impairing their quality of life, daily activities, and social interactions. The objective of this work was to select a panel of biomarkers of central pain processing and modulation and assess their ability to predict chronic pain in patients with cancer using predictive artificial intelligence (AI) algorithms. We will perform a prospective longitudinal cohort, multicentric study involving 450 patients with a recent cancer diagnosis. These patients will undergo an in-person assessment at three different time points: pretreatment, 6 months, and 12 months after the first visit. All patients will be assessed through demographic and clinical questionnaires and self-report measures, quantitative sensory testing (QST), and electroencephalography (EEG) evaluations. We will select the variables that best predict the future occurrence of pain using a comprehensive approach that includes clinical, psychosocial, and neurophysiological variables. This study aimed to provide evidence regarding the links between poor pain modulation mechanisms at precancer treatment in patients who will later develop chronic pain and to clarify the role of treatment modality (modulated by age, sex and type of cancer) on pain. As a final output, we expect to develop a predictive tool based on AI that can contribute to the anticipation of the future occurrence of pain and help in therapeutic decision making.