University of Coimbra
  • Coimbra, Coimbra, Portugal
Recent publications
Background: The complex system of stressors related to the coronavirus disease 2019 (COVID-19) pandemic has affected the global population, provoking a broad range of psychological reactions. Although numerous studies have investigated the mental health impact of COVID-19, qualitative research and cross-country comparisons are still rare. Objective: This qualitative study aimed to explore self-perceived challenges and opportunities related to COVID-19 across six European countries. The overall objective was to provide a differentiated picture of individual subjective experiences in the early stages of the pandemic. Method: The present study included 7309 participants from Austria, Croatia, Georgia, Greece, Poland, and Portugal. We performed qualitative content analysis according to Mayring analyse open-ended questions regarding stressful events, positive and negative aspects of the pandemic, and recommendations to cope with the pandemic situation. MAXQDA software was used for data management and analysis. Results: Participants' accounts were moderately consistent across the countries. The most prominent themes regarding stressful and negative pandemic aspects included: Restrictions and changes in daily life, Emotional distress, and Work and finances. Answers about positive pandemic consequences were mainly centred around the themes Reflection and growth, Opportunity for meaningful/enjoyable activities, and Benefits on interpersonal level. Key themes identified from participants' recommendations to cope with the pandemic included Beneficial behavioural adjustment, Beneficial cognitive-emotional strategies, and Social support. Conclusions: Participants experienced various challenges, but also shared several positive pandemic consequences and recommendations to cope with the pandemic. These first-hand data could inform mental health practices to promote well-being during COVID-19 and similar global challenges in the participating countries and possibly beyond. Highlights: We examined COVID-19-related experiences in 7309 adults from six European countries.Besides challenges, participants identified many positive pandemic consequences.Participants' recommendations to cope with COVID-19 included behavioural and cognitive-emotional strategies.
The urgent need to minimize the use of natural resources, while reducing the environmental impacts of human activity is a challenge that implies a radical change in industrial processes. Such is the case of the construction sector, and more particularly, of the highly valuable and omnipresent material of structural concrete. The developments made on the theme of the performance of structural concretes containing waste-based alkali-activated binders have, according to the reviewed literature, upgraded these family of materials from a mere possibility to a viable alternative to ordinary Portland cement binders. In fact, as this chapter shows, as long as proper curing conditions and material proportions are implemented, granulated blast furnace slag or fly ash-based concretes may be used to produce structurally sound beams, columns, walls, tunnel panels, or even, railway sleepers. Furthermore, the high ductility, high temperature resistance, lower CO2 emissions involved in their fabrication, and the enhanced ability to incorporate waste proves the suitability of these materials for, at the very least, niche structural applications.
Background Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design. Methods A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72 , 41 GRN , and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be). Results The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72 , GRN , and MAPT ). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period. Discussion We created gene-specific cognitive composite scores for C9orf72 , GRN , and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration.
Background The concomitant role of the Central Executive, the Saliency and the Social Cognition networks in autism spectrum disorder (ASD) in demanding ecological tasks remains unanswered. We addressed this question using a novel task-based fMRI virtual-reality task mimicking a challenging daily-life chore that may present some difficulties to individuals with ASD: the EcoSupermarketX. Methods Participants included 29 adolescents: 15 with ASD and 15 with typical neurodevelopment (TD). They performed the EcoSupermarketX (a shopping simulation with three goal-oriented sub-tasks including “no cue”, “non-social” or “social” cues), during neuroimaging and eye-tracking. Results ASD differed from TD only in total time and distance to complete the “social cue” sub-task with matched eye-tracking measures. Neuroimaging revealed simultaneous hyperactivation across social, executive, and saliency circuits in ASD. In contrast, ASD showed reduced activation in the parahippocampal gyrus, involved in scene recognition. Conclusions When performing a virtual shopping task matching the performance of controls, ASD adolescents hyperactivate three core networks: executive, saliency and social cognition. Parahippocampal hypoactivation is consistent with effortless eidetic scene processing, in line with the notion of peaks and valleys of neural recruitment in individuals with ASD. These hyperactivation/hypoactivation patterns in daily life tasks provide a circuit-level signature of neural diversity in ASD, a possible intervention target.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
Muons are particles with a spin of ½ that can be implanted into a wide range of condensed matter materials to act as a local probe of the surrounding atomic environment. Measurement of the muon’s precession and relaxation provides an insight into how it interacts with its local environment. From this, unique information is obtained about the static and dynamic properties of the material of interest. This has enabled muon spin spectroscopy, more commonly known as muon spin rotation/relaxation/resonance (μSR), to develop into a powerful tool to investigate material properties such as fundamental magnetism, superconductivity and functional materials. Alongside this, μSR may be used to study, for example, energy storage materials, ionic diffusion in potential batteries, the dynamics of soft matter, free radical chemistry, reaction kinetics, semiconductors, advanced manufacturing and cultural artefacts. This Primer is intended as an introductory article and introduces the μSR technique, the typical results obtained and some recent advances across various fields. Data reproducibility and limitations are also discussed, before highlighting promising future developments. Muon spin spectroscopy examines how muons interact with their local environment through measurement of the muon’s precession and relaxation. This provides unique information about the static and dynamic properties of a material. This Primer gives an introductory overview to muon spin spectroscopy, describing how muons are produced and used experimentally in various applications.
The combination between online social networks (OSN) and decision processes provides a favorable social data analysis paradigm for efficient decision support and business-processes integration. This paper presents a framework for handling OSN’s contents, providing a simpler and effective approach for information retrieval and processing. The objective is to address a decision-making problem, by using that framework to extract, process, structure and analyze the OSN’s data. The decision process is not only guided by OSN data, but also by social network analysis methodology and is entirely based on the communications among social media users. Our framework combines two different, though complementary, perspectives: the analysis of the interactions among users and the semantic analysis of their discourses. In addition, it aims to bridge technology and manual-based approaches, thus enhancing the possibilities for making a better use of an OSN, using free-available software. The case study, herein, aims to estimate customers’ requests, solely based on their Facebook posts, showing that the unstructured data of the web’s discourse can be used to support this kind of decision processes.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Understanding the physical basis of corneal transparency has been a subject of interest amongst physicists, basic scientists and ophthalmologists. Impairment of corneal clarity is a significant cause of visual morbidity worldwide. Thus, it is essential to understand the mechanisms behind corneal transparency and how the alterations due to corneal pathologies affect vision. We use Maxwell’s equations to model light propagation in ocular tissues and a nodal discontinuous Galerkin method combined with an explicit Runge-Kutta method to simulate light propagation in normal and pathological corneas. Our simulation results illustrate that an increase in the diameter of some fibres causes an increase in backscattering. Thus, these may represent some of the physical changes in the cornea that might result in loss of transparency and visual morbidity.
Background Match analysis has evolved exponentially over the past decades in team sports resulting in a significant number of published systematic reviews and meta-analyses. An umbrella review of the available literature is needed to provide an integrated overview of current knowledge and contribute to more robust theoretical explanations of team performance. Methods The Web of Science (all databases), PubMed, Cochrane Library (Cochrane Database of Systematic Reviews), Scopus, and SPORTDiscus databases were searched for relevant publications prior to 19 February 2021. Appraisal of the methodological quality of included articles was undertaken using the tool for Assessing the Methodological Quality of Systematic Reviews (AMSTAR-2). Twenty-four studies were reviewed that met the following criteria: (1) contained relevant data from match analyses in team ball sports; (2) were defined as systematic reviews or/and meta-analyses; and (3) were written in the English language. Results The overall methodological quality of the 24 included reviews, obtained through the AMSTAR-2, revealed very low confidence ratings (Critically Low, n = 12) for the results of most systematic reviews of match analyses in team ball sports. Additionally, the results showed that research is focused mainly on four levels of analysis: (1) dyadic (microlevel); (2) individual (molecular level; predominant); (3) group (mesolevel), and (4) team dynamics (macrolevel). These levels of analysis included tactical, technical, physical, and psychosocial variables. Team performance was contextualized at two levels, with reference to: (1) match context (e.g. match status, match location, match period, quality of opposition) and (2) sociodemographic and environmental constraints (sex, age groups, competitive level, altitude, temperature, pitch surface). Conclusions The evolution of methods for match analysis in team ball sports indicates that: (1) an individual-level performance analysis was predominant; (2) the focus on intermediate levels of analysis, observing performance in dyadic and group interactions, has received less attention from researchers; (3) neglected areas of research include psychosocial aspects of team sports and women’s performance; and (4) analyses of match contexts need greater depth. Registration : The protocol was registered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols with the number 202080067 and the DOI number https://doi.org/10.37766/inplasy2020.8.0067 .
Background Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive diagnostic test with a high diagnostic yield. Optimal specimen acquisition is of a key importance; however, rapid on-site cytology examination (ROSE) during EBUS-TBNA has limited access. In an attempt to provide immediate feedback to the operator, the intervention pulmonology team started to classify macroscopically every lymph node sample in terms of abundance. The main objective of this study was to clarify whether this on-site macroscopic evaluation of EBUS sample was related to histology results and therefore any helpful for clinical practice. Results From a total of 288 lymph node stations sampled, adequate/diagnostic histological results were present in 11.1% of “insufficient” samples, 40.9% “sufficient” samples, 76.4% “good” samples and 88.1% of “excellent” samples. This was statistically significant with p -value under 0.0001. Also, there was a statistical agreement between samples that were macroscopically “insufficient” or “sufficient” with “inadequate” and “dubious” histological results and also between macroscopically “good” and “excellent” samples and histological results that were adequate/diagnostic. And that statistical agreement was of moderate magnitude according to the “Landis and Koch” classification (k = 0.386). Conclusions The positive relationship between the on-site macroscopic evaluation of the EBUS sample as “excellent” and the “adequate/diagnostic” histological result is of high clinical importance since it represents a fast, cheap and easy method that provides immediate feedback to the operator influencing his conduct; by obtaining additional passes to achieve an “excellent” will ensure a higher percentage of samples with a diagnosis, accelerating the patients treatment.
Background Sustainable production and consumption are two important issues, which mutually interact. Whereas individuals have little direct influence on the former, they can play a key role on the latter. This paper describes the subject matter of sustainable consumption and outlines its key features. It also describes some international initiatives in this field. Results By means of an international survey, the study explores the emphasis given to sustainable consumption during the second wave of the COVID-19 pandemic, and the degree of preparedness in individuals to engage in the purchase of green and sustainably manufactured products. The main results indicate that the pandemic offered an opportunity to promote sustainable consumption; nevertheless, the pandemic alone cannot be regarded as a ‘game changer’ in this topic. Conclusions Apart from an online survey with responses from 31 countries, which makes it one of the most representative studies on the topic, a logit model was used to analyse the main variables that affect the probability of pro-environmental consumption behaviour because of the COVID-19 pandemic. The paper lists some of the technological and social innovations that may be needed, so as to guide more sustainable consumption patterns in a post-pandemic world.
Background The implementation of the Sustainable Development Goals (SDGs) requires much planning and the provision of resources, especially regarding the necessary investments, technologies and infrastructures needed. Yet, it is presently unclear how available these elements are, what gaps exist, what changes have taken place in terms of their availability since the adoption of the SDGs and what their requirements will be in the future. The knowledge gap has become even more concerning because of the impact of the COVID-19 pandemic. Using a bibliometric analysis, an assessment of the global progress of SDG implementation and requirements, identifying challenges through the development of a matrix, and a set of 11 case studies to triangulate the holistic analysis, an assessment of the global progress of the SDGs implementation and the impact of the COVID-19 pandemic on this process was carried out. Results The findings suggest that the scope and width of resources limitation are currently undermining the implementation of the SDGs. Apart from the fact that the pace of progress has been insufficient, the potential of the SDGs in pursuing sustainability and improving life quality is not fully realised. This trend suggests that a substantial acceleration of the efforts is needed, especially for the five SDGs whose progress since 2015 has not been optimal, namely SDG2, SDG11, SDG13, SDG15, and SDG16, while SDG3, SDG7, SDG9, SDG14, and SDG17 show signs of progress. The case studies showed that different industries have dissimilar effects on achieving the SDGs, with the food sector correlating with 15 SDGs, as opposed to the energy sector correlating with 6 SDGs. Accordingly, the priority level assessment in terms of achieving the SDGs, points to the need to further advance the above-mentioned five SDGs, i.e., 2, 11, 13, 15 and 16. Conclusions This study fills in a knowledge gap in respect of the current need for and availability of investments, new technologies, and infrastructures to allow countries to pursue the SDGs. It is suggested that this availability is rather limited in specific contexts. In respect of the needs to be addressed, these include resource-related constraints, limited technologies and infrastructures, affecting SDG2, SDG11, SDG13, SDG15, and SDG16, whose progress needs to be enhanced. Since the global progress in the process of implementation of the SDGs depends directly and indirectly on addressing the resource gaps, it is suggested that this topic be further investigated, so that the present imbalances in the three dimensions of sustainable development: the economic, social and environmental, be adequately addressed.
We present a comprehensive theoretical study of conventional superconductivity in cubic antiperovskites materials with composition XYZ 3 where X and Z are metals, and Y is H, B, C, N, O, and P. Our starting point are electron–phonon calculations for 397 materials performed with density-functional perturbation theory. While 43% of the materials are dynamically unstable, we discovered 16 compounds close to thermodynamic stability and with T c higher than 5 K. Using these results to train interpretable machine-learning models, leads us to predict a further 57 (thermodynamically unstable) materials with superconducting transition temperatures above 5 K, reaching a maximum of 17.8 K for PtHBe 3 . Furthermore, the models give us an understanding of the mechanism of superconductivity in antiperovskites. The combination of traditional approaches with interpretable machine learning turns out to be a very efficient methodology to study and systematize whole classes of materials and is easily extendable to other families of compounds or physical properties.
This work presents an innovative ultra-sensitive biosensor having the Spike protein on carbon-based screen-printed electrodes (SPEs), for monitoring in point-of-care antibodies against SARS-CoV-2, a very important tool for epidemiological monitoring of COVID-19 infection and establishing vaccination schemes. In an innovative and simple approach, a highly conductive support is combined with the direct adsorption of Spike protein to enable an extensive antibody capture. The high conductivity was ensured by using carboxylated carbon nanotubes on the carbon electrode, by means of a simple and quick approach, which also increased the surface area. These were then modified with EDC/NHS chemistry to produce an amine layer and undergo Spike protein adsorption, to generate a stable layer capable of capturing the antibodies against SARS-CoV-2 in serum with great sensitivity. Electrochemical impedance spectroscopy was used to evaluate the analytical performance of this biosensor in serum. It displayed a linear response between 1.0 pg/mL and 10 ng/mL, with a detection limit of ∼0.7 pg/mL. The analysis of human positive sera containing antibody in a wide range of concentrations yielded accurate data, correlating well with the reference method. It also offered the unique ability of discriminating antibody concentrations in sera below 2.3 μg/mL, the lowest value detected by the commercial method. In addition, a proof-of-concept study was performed by labelling anti-IgG antibodies with quantum dots to explore a new electrochemical readout based on the signal generated upon binding to the anti-S protein antibodies recognised on the surface of the biosensor. Overall, the alternative serologic assay presented is a promising tool for assessing protective immunity to SARS-CoV-2 and a potential guide for revaccination.
Plant-based diets are often promoted as healthier and more sustainable and thus as a mechanism to achieve the targets proposed to mitigate climate change and noncommunicable diseases. However, plant-based diets can be perceived as more expensive than the common omnivorous diets, when considering the expensive novel meat substitutes and also the higher costs of fruits and vegetables, whose consumption is perceived to increase. Therefore, the present study assesses the question: Do plant-based consumers spend more on food compared to omnivorous consumers? Based on primary data ( n = 1040) collected through an online survey, representative of the Portuguese population, through logistic regressions, it was possible to conclude that plant-based consumers, particularly vegan, are associated with lower food expenditures compared to omnivorous consumers. In fact, plant-based consumers are shown to spend less than all other consumers assessed. Food policies aligning healthiness and sustainability with affordability can deliver a major boost for the promotion of plant-based diets and help achieve the mitigation targets proposed.
Background Achondroplasia is the most common form of skeletal dysplasia, with serious comorbidities and complications that may occur from early infancy to adulthood, requiring lifelong management from a multidisciplinary team expert in the condition The European Achondroplasia Forum guiding principles of management highlight the importance of accurate diagnosis and timely referral to a centre specialised in the management of achondroplasia to fully support individuals with achondroplasia and their families, and to appropriately plan management. The European Achondroplasia Forum undertook an exploratory audit of its Steering Committee to ascertain the current situation in Europe and to understand the potential barriers to timely diagnosis and referral. Results Diagnosis of achondroplasia was primarily confirmed prenatally (66.6%), at Day 0 (12.8%) or within one month after birth (12.8%). For suspected and confirmed cases of achondroplasia, a greater proportion were identified earlier in the prenatal period (87.1%) with fewer diagnoses at Day 0 (5.1%) or within the first month of life (2.6%). Referral to a specialist centre took place after birth (86.6%), predominantly within the first month, although there was a wide variety in the timepoint of referral between countries and in the time lapsed between suspicion or confirmed diagnosis of achondroplasia and referral to a specialist centre. Conclusions The European Achondroplasia Forum guiding principles of management recommend diagnosis of achondroplasia as early as possible. If concerns are raised at routine ultrasound, second line investigation should be implemented so that the diagnosis can be reached as soon as possible for ongoing management. Clinical and radiological examination supported by molecular testing is the most effective way to confirm diagnosis of achondroplasia after birth. Referral to a centre specialised in achondroplasia care should be made as soon as possible on suspicion or confirmation of diagnosis. In countries or regions where there are no official skeletal dysplasia reference or specialist centres, priority should be given to their creation or recognition, together with incentives to improve the structure of the existing multidisciplinary team managing achondroplasia. The length of delay between diagnosis of achondroplasia and referral to a specialist centre warrants further research.
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10,697 members
Bruno F. O. Nascimento
  • Department of Chemistry
Sandra Correia
  • Centre for Functional Ecology - Science for People & the Planet
Cláudio M. Nunes
  • Department of Chemistry
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Rua Larga , 3004-504, Coimbra, Coimbra, Portugal
Head of institution
Amílcar Falcão
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http://www.uc.pt/
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