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- Data from the Researcher Mental Health Observatory STAIRCASE SurveyPublication . Santos, Marlene; Rocha, Nuno; Santos, Marlene; Rocha, NunoThe data presented here derives from the Sustainable Working Conditions in Academia survey (STAIRCASE) on researcher mental health. The survey addresses the ongoing mental health crisis in academia by providing comprehensive, multilevel data on researcher well-being and its structural determinants. We employed a cross-sectional between-participant study design to collect data from 4,296 researchers between September 15, 2023, and August 26, 2024. The sample, which primarily includes researchers based in European countries, has a mean age of 38.1 years (SD = 10.7) and consists of 63.7% female participants. Participants provided data on key mental health outcomes – including depression, anxiety, stress, burnout, and well-being – alongside detailed assessments of working conditions, leadership behavior, and organizational characteristics. The dataset facilitates a holistic, multilevel investigation of academic mental health beyond individual risk factors by including the individual, leadership, institutional, and national context. By enabling analyses across hierarchical levels this dataset provides the necessary evidence to identify systemic drivers of mental (ill) health and inform the development of effective, system-wide strategies for meaningful change in academic work environments.
- Forecasting and clustering the burden of non communicable diseases in Europe to support public health policyPublication . Vinhal, Cláudia; Oliveira, Alexandra; Faria, Brígida Mónica; Pimenta, Rui; Nascimento, Ana Paula; Oliveira, Alexandra; Faria, Brigida Monica; Pimenta, Rui; Nascimento, Ana PaulaThis study aims to model Disability Adjusted Life Years (DALYs) for cardiovascular diseases and neurological disorders using ARIMA models, exploring regional disparities and evaluating model performance across countries. This is a quantitative, exploratory time series study using secondary data from the Global Burden of Disease (GBD) database, covering annual DALYs across 48 European countries, from 1990 until 2019. ARIMA models were applied using an automated algorithm. Model performance was assessed using MAE, RMSE, MSE, and MAPE. Time series were compared using Piccolo distances, and countries were clustered with hierarchical average linkage. Cluster quality was evaluated using Silhouette, Dunn, McClain, and C-index. Simpler ARIMA models often yielded better forecasts than more complex ones, particularly in smaller countries such as San Marino and Monaco. Cardiovascular disease time series were grouped into 2 clusters, while neurological disorders formed 15 clusters, reflecting diverse epidemiological and reporting patterns. The mean MAPE was 6.8% for cardiovascular diseases and 0.95% for neurological disorders, indicating greater predictive accuracy and stability for the latter. ARIMA modelling is effective for capturing temporal dynamics in DALY data, but should be tailored to avoid overfitting. Clustering countries based on time series similarities reveals insights into health system differences and regional disease patterns. These findings support the use of data-driven approaches to improve forecasting and inform global public health planning.
- European network on optimizing treatment with therapeutic antibodies in Chronic Inflammatory Diseases: Overview, progress and perspectivesPublication . Tachkov, Konstantin; Rumano, Merita; Bluett, James; Bogavac-Stanojević, Nataša; Dreesen, Erwin; Itik, Mehmet; Kararigas, Georgios; Kawalec, Paweł; Santos, Marlene; Skrede, Silje; Petrova, Guenka; Mulleman, Denis; Santos, MarleneTreatment of chronic inflammatory diseases has been revolutionized with the introduction of targeted therapies using therapeutic antibodies. However, a large proportion of patients do not respond to treatment, or they lose response over time. To overcome this challenge, researchers have started to investigate strategies for treatment optimization, based on the development of patient stratification tools and therapeutic drug monitoring (TDM). The aim of the COST Action European Network on Optimizing Treatment with Therapeutic Antibodies in chronic inflammatory diseases (ENOTTA) is to create an interdisciplinary, pan-European network to defragment and structure scientific research in this field. Through the network, ENOTTA will facilitate the implementation of tools for patient stratification, as well as individualized (TDM-guided) approaches. These strategies should be cost-effective and provide therapeutic antibody treatment optimization for the treatment of chronic inflammatory diseases. This article highlights the key achievements of the ENOTTA consortium to date.
- Toxicity of lanthanum and yttrium oxide nanoparticles and bulk forms on Folsomia candida: a study of single versus mixture exposuresPublication . Santos, Joana; Capitão, Ana; Barbosa, Manuel; Pires, Thomás; Pinto, Edgar; Silva, Ana L. Daniel da; Barreto, Angela; Maria, Vera L.; Pinto, EdgarThe intensive use of rare earth elements (REEs) raises concerns about their effects on soil organisms, particularly under mixture exposure scenarios. This study evaluated the toxicity of lanthanum oxide (La2O3) and yttrium oxide (Y2O3) nanoparticles (NPs) and bulk forms on Folsomia candida. Single (0–2500mg/kg) and dual mixture exposures were tested for effects on survival, reproduction, avoidance behavior, and biochemical markers. No effects on survival and avoidance behavior were observed. NPs were more toxic than bulk forms. La2O3 NPs reduced reproduction (≥ 1250mg/kg) and acetylcholinesterase (AChE) activity (2500mg/kg), whereas Y2O3 NPs exhibited greatest toxicity, reducing reproduction (≥ 313mg/kg) and increasing catalase (CAT) (156 and 625mg/kg) and glutathione reductase (GR) (625 and 2500mg/kg) activities. Mixture exposures revealed complex interactions (synergism, antagonism, or no interaction), with toxicity depending on concentration, endpoint, and material form. Besides, higher number of biochemical endpoints were affected by mixture exposures, but dissimilar responses were observed with different concentrations: 2500mg/kg Y2O3 NPs + 2500mg/kg La2O3 NPs decreased reproduction and increased GR, glutathione S-transferases (GST) and AChE activities; 2500mg/kg Y2O3 NPs + 625mg/ kg La2O3 NPs increased CAT, GR, GST and AChE activities; 625mg/kg Y2O3 NPs + 625mg/kg La2O3 NPs increased GR activity; 156mg/kg Y2O3 NPs + 2500mg/kg La2O3 NPs decreased AChE activity, increased GR activity and lipid peroxidation levels. This study highlights that REE exposures, particularly mixtures, can pose risks to soil organisms and emphasizes the need to include mixture interactions in risk assessments.
- Immersive technology applications in radiation protection for fluoroscopy - A systematic reviewPublication . Videira, Sara; Rodrigues, Matilde A.; Santos, Joana; da Silva, Manuela Vieira; Rodrigues, Matilde; Vieira da Silva, ManuelaImmersive technology is being increasingly incorporated into various professional and educational settings for occupational safety and health training. This review aims to assess the impact of immersive technology on the radiation protection (RP) of workers exposed to ionising radiation during fluoroscopy-guided procedures. Studies were collected from six databases on 3 April 2024: PubMed, Academic Search Complete, Scopus, Web of Science Core Collection, ScienceDirect, and Engineering Village. Additionally, studies were identified through snowball sampling techniques. Eligible studies assessed RP learning via immersive technology among healthcare workers or trainees exposed to ionising radiation from fluoroscopy in operating or interventional rooms. Additionally, only original research articles published in peer-reviewed journals and written in Portuguese, Spanish, English, and French were included. The review followed PRISMA and PICo, using narrative synthesis and bibliometric analysis. Quality was assessed using the Mixed Methods Appraisal Tool checklist. Ten studies involving 358 individuals (37 % trainees/students; 63 % workers) were analysed. All assessed the usefulness of RP education/training, and most (9/10) reported an improved understanding of scattered radiation. Technologies used included virtual reality (7/10), augmented reality (2/10), and mixed reality (1/10). Radiation scatter visualisation was present in the majority (9/10) of the studies, and 1/10 combined immersive technology with clinical training. These technologies enhance learning outcomes, support effective RP teaching, and optimise work practices. Integrating clinical training with RP education is essential. Implications for practice: This study supports healthcare professionals and educators in understanding how immersive technology (virtual, augmented, and mixed reality) is being applied and evaluated in training and real work contexts. Insights into methods, outcomes, and study populations inform practical use, while bibliometric data highlight key sources and authors for future reference and collaboration.
- Green zero-valent iron nanoparticles from Cistus ladanifer by-products for glyphosate remediation in water and soilPublication . Fernandes, Filipe; Paíga, Paula; Freitas, Maria; Pinho, Cláudia; Oliveira, Ana Isabel; Delerue-Matos, Cristina; Grosso, Clara; Pinho, Cláudia; Oliveira, Ana IsabelFood and agricultural sectors produce large quantities of waste that present high potential for valorization. Cistus ladanifer L., used in the perfume and essential oil industries, produces post-distillation residues rich in phenolic compounds (PCs). These residues can be exploited for the green synthesis of nano zero-valent iron (nZVI), widely studied for environmental remediation. The aim of this study was to develop green synthesized nZVI using Abbreviations: AAE, Ascorbic acid equivalents; ABTS•+, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid; AES, Analytical Eco-scale; AGREE, Analytical Greenness Calculator; AMPA, Aminomethylphosphonic acid; C-nZVI, Chemically synthesized nZVI; CLL, C. ladanifer leaves; CLS, C. ladanifer stems; DPPH•, 1,1- diphenyl-2-picrylhydrazyl; DLS, Dynamic light scattering; EDS, Energy-dispersive X-ray spectroscopy; EOs, Essential oils; FeCl3, Iron chloride; FMOC-Cl, 9-fluorenylmethyl chloroformate; FRAP, Ferric reducing antioxidant power assay; FTIR, Fourier-transform infrared spectroscopy; GAE, Gallic acid equivalents; GEMAM, Greenness evaluation metric for analytical methods; Glyph, Glyphosate; H2O, Water; HCl, Hydrochloric acid; HPLC, High-performance liquid chromatography; HPLC-FLD, High-performance liquid chromatography with fluorescence detection; LC-MS, Liquid chromatography-mass spectrometry; MeOH, Methanol; MES, Green Certificate Modified Eco-scale; MoGAPI, Modified Green Analytical Procedure Index; MRLs, Maximum residue levels; MTT, (3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide); NaBH4, Sodium borohydrate; nZVI, Nano zero-valent iron; NaOH, Sodium hydroxide; NNP, No nanoparticles; NPs, Nanoparticles; NS, No soil; PCs, Phenolic compounds; PDI, Polydispersity index; SEM, Scanning electron microscopy; SQUID, Superconducting quantum interference device; TG, Thermogravimetric analysis; TPC, Total phenolic content; XPS, X-ray photoelectron spectroscopy; XRD, X-ray diffraction; ZP, Zeta potential; Fe3O4, Magnetite; γ-Fe2O3, Maghemite; γ-FeO, Lepidocrocite.
- Impact of the addition of botanical ingredients on the physicochemical properties, polyphenolic content, and antioxidant activity of craft beersPublication . Pereira, Maria João; Santos, Diana; Pinho, Cláudia; Oliveira, Ana Isabel; Oliveira, Ana IsabelThe incorporation of botanical ingredients into craft beer has emerged as a promising strategy to enhance nutritional value and expand its sensory diversity. Thus, this review aims to discuss the impact of adding botanical extracts on the physicochemical properties, phenolic content, and antioxidant potential of craft beers. A narrative review was conducted using PubMed, Science Direct, Web of Science, and b-on databases, with the keywords ‘craft beer’, ‘physicochemical properties’, ‘polyphenolic content’, and ‘antioxidant activity’. The incorporation of botanical ingredients into beers modified the physicochemical parameters, total phenolic content (TPC), and antioxidant activity. These effects varied according to the type of matrix, concentration, timing of addition, beer style, and brewing conditions. Overall, an increase in beer TPC and antioxidant activity was observed. However, higher TPC can present technological challenges, as phenolic–protein interaction may lead to turbidity. Conversely, enhanced antioxidant potential contributes to oxidative stability and extends the shelf-life of beer. Future studies should validate the current results, explore new bioactive matrices, and evaluate variables that ensure the functional quality of beer. Practical applications under real production conditions should also be prioritized to guarantee effective functional benefits without compromising the stability and sensory acceptance of craft beer.
- Advanced botanical authentication of honey: Using an ultrasensitive electrochemical genosensor and RT-qPCR for the detection of Castanea sativaPublication . Morais, Stephanie; Pereira, Eduarda; Ferreira, Mariana; Santos, Marlene; Soares, Sónia; Texeira, Ana L.; Domingues, Valentina; Delerue-Matos, Cristina; Barroso, M. Fátima; Santos, MarleneFood fraud is a reoccurring issue for the food industry, with significant public health and economic implications. Honey, a natural ingredient prized for its sweetness and inherent nutritional profile and health benefits, is one of the most frequently adulterated foods found in the international market. This fraudulent act not only damages the reputation of the honey industry but also presents a hazard to the consumers’ health. So, in this study, a disposable electrochemical genosensor was developed to detect Castanea sativa (chestnut tree) DNA in commercial honey samples. For this, a 103 bp C. sativa specific DNA-target oligonucleotide and its complementary probe were selected and designed. The genosensor methodology implied a sandwich hybridization format, for which the complementary sequence was cut into a 22 bp thiolated DNAcapture probe and an 81 bp fluorescein isothiocyanate-labelled DNA-signaling probe. Using chronoamperometric measurements, the enzymatic amplification of the electrochemical signal was obtained in a 0.03 to 1.00 nM concentration range, with a LOD and LOQ of 3.01 and 10.04 pM, respectively. The developed genosensor was able to detect the presence of the chestnut DNA in real chestnut plants and commercial honey samples. These results were then validated real-time quantitative PCR (RT-qPCR). In fact, conventional PCR coupled with gel electrophorese was not able to detect the presence of heather in honey. Therefore, electrochemical genosensors are a promising and cost-effective analytical tool to authenticate the botanical origin of honey, guaranteeing its safety, quality and authenticity.
- “Can a chatbot be used in the full-text screening in a systematic review?”Publication . Martins, André Miguel; Juan, Luis Félix Valero; Oliveira, Adriana; Martins, João Paulo; Santos, Marlene; Santos, Marlene; Oliveira Martins, João PauloLarge language model–based artificial intelligence tools are increasingly explored to support systematic reviews, yet evidence regarding their reliability in full-text screening remains limited. This study evaluated the performance of two versions of ChatGPT (4.0 and 5.0) compared with human reviewers during article selection for a systematic review on influenza vaccine effectiveness. A total of 170 full-text articles were independently assessed for eligibility using predefined inclusion and exclusion criteria. Human reviewers served as the gold standard. ChatGPT 4.0 and 5.0 were prompted using standardized instructions mirroring the review protocol. Agreement with human decisions was evaluated using accuracy, sensitivity, specificity, precision, F1-score, and Cohen’s κ. Intra-model reproducibility was assessed for ChatGPT 5.0. Results: ChatGPT 4.0 achieved an accuracy of 0.71 (95% CI: 0.64–0.78) and a Cohen’s κ of 0.43, indicating moderate agreement with human reviewers. ChatGPT 5.0 demonstrated improved performance, with accuracy increasing 0.06 to 0.77 (95% CI: 0.70–0.83), sensitivity of 0.87, specificity of 0.70, and κ of 0.55, corresponding to moderate-to-substantial agreement. Intra-model reproducibility for ChatGPT 5.0 showed 80% agreement (κ = 0.60), indicating partial but imperfect consistency. ChatGPT 5.0 outperformed ChatGPT 4.0 in full-text screening accuracy and reproducibility, approaching but not matching human performance. These findings support the use of current LLMs as decision- support tools rather than autonomous reviewers in systematic reviews. Transparent reporting of model versions, prompts, and input quality is essential to ensure credible AI-assisted evidence synthesis.
- Health literacy of the higher education community in a European country: a cross-sectional surveyPublication . Ferreira, Pedro L.; Morais, Carminda; Pimenta, Rui; Ribeiro, Inês; Alves, Sandra M.; Pedro, Ana R.; Escoval, Ana; RALS; Alves, Sandra MariaHealth literacy is a dynamic and multidimensional concept. Examining health literacy among higher education students and teachers is crucial for promoting informed health decisions and encouraging healthier behaviors. Our study aimed to measure health literacy among higher education students and teachers, assess the impact of sociodemographic variables, and compare health literacy levels between these groups.