Wound Healing

A cicatrização de feridas constitui um processo complexo e coordenado, envolvendo a interacção entre células e vários sistemas mensageiros. Este processo pode dividir-se em 3 fases: inflamatória, proliferativa e de remodelação. O mecanismo exacto das feridas crónicas permanece ainda por esclarecer. Os avanços recentes da biologia molecular permitiram identificar moléculas que evidenciaram novos mecanismos fisiopatológicos das feridas crónicas, assim como possíveis alvos terapêuticos. Este artigo tem como objectivo uma revisão dos mecanismos envolvidos na cicatrização, pilar fundamental para a compreensão e abordagem de doentes com feridas crónicas, prática corrente em Dermatologia

The importance of Vancomycin and Aminoglycoside pharmacokinetics monitoring

info:eu-repo/semantics/publishedVersio

Using Patient-Reported Outcome Measures to Evaluate Care for Patients With Inflammatory Chronic Rheumatic Disease

Objectives: Few countries integrate patient-reported outcome measures (PROMs) in routine performance assessment and those that do focus on elective surgery. This study addresses the challenges of using PROMs to evaluate care in chronic conditions. We set out a modeling strategy to assess the extent to which changes over time in self-reported health status by patients with inflammatory chronic rheumatic disease are related to their biological drug therapy and rheumatology center primarily responsible for their care. Methods: Using data from the Portuguese Register of Rheumatic Diseases, we assess health status using the Health Assessment Questionnaire-Disability Index for rheumatic patients receiving biological drugs between 2000 and 2017. We specify a fixed-effects model using the least squares dummy variables estimator. Results: Patients receiving infliximab or rituximab report lower health status than those on etanercept (the most common therapy) and patients in 4 of the 26 rheumatology centers report higher health status than those at other centers. Conclusions: PROMs can be used for those with chronic conditions to provide the patient's perspective about the impact on their health status of the choice of drug therapy and care provider. Care for chronic patients might be improved if healthcare organizations monitor PROMs and engage in performance assessment initiatives on a routine basis.info:eu-repo/semantics/publishedVersio

Prickly Connections: Sociodemographic Factors Shaping Attitudes, Perception and Biological Knowledge about the European Hedgehog

The modern lifestyle of humans is leading to a limited exposure to nature. While several wild species are adapting and thriving in anthropic environments, natural history knowledge is declining, and positive attitudes and behaviours towards nature are facing challenges. Because anticipating attitudes and engendering broad-based support for nature-related measures requires a good grasp of social contexts, we set out to evaluate the sociodemographic factors driving the perception, attitudes towards, and natural history knowledge of a keystone species—the European hedgehog. In 2022, we conducted a questionnaire answered by 324 Portuguese adults. We found generally positive feelings and attitudes towards this species. A higher degree of academic qualifications and previous personal experience with the species seem to play a role in (i) people’s perception about human impacts on hedgehogs and (ii) positive attitudes, especially during encounters where the animals were in difficulty. Despite this, the extent of natural history knowledge was low overall, and the study population was self-aware of this. Our insights underline the need to tailor educational programmes if we are to encourage people to re-establish meaningful connections with nature, to foster social support for biodiversity stewardship, and to implement the One Health approach in a way that resonates with distinct social groups.We thank Clarisse Rodrigues from Centro de Recuperação e Interpretação do Ouriço (CRIDO) and all the staff at Centro de Recuperação de Animais Selvagens da Universidade de Trás-os-Montes e Alto Douro (CRAS-HVUTAD). We extend our gratitude to Associação Social e Cultural de Louredo, Associação de Solidariedade Social de Nespereira, Associação de Apoio à 3.ª Idade S. Miguel de Beire and Centro Social e Paroquial de Sousela for their willingness to help us with the elderly participants. Micaela Rodrigues participated in this study in the context of her final internship in veterinary nursing licentiate degree. We acknowledge the Portuguese Foundation for Science and Technology (FCT) for the financial support to CISAS (UIDB/05937/2020 and UIDP/05937/2020). Three anonymous reviewers are thanked for their helpful insights

Needle Tip Force Estimation using an OCT Fiber and a Fused convGRU-CNN Architecture

Needle insertion is common during minimally invasive interventions such as biopsy or brachytherapy. During soft tissue needle insertion, forces acting at the needle tip cause tissue deformation and needle deflection. Accurate needle tip force measurement provides information on needle-tissue interaction and helps detecting and compensating potential misplacement. For this purpose we introduce an image-based needle tip force estimation method using an optical fiber imaging the deformation of an epoxy layer below the needle tip over time. For calibration and force estimation, we introduce a novel deep learning-based fused convolutional GRU-CNN model which effectively exploits the spatio-temporal data structure. The needle is easy to manufacture and our model achieves a mean absolute error of 1.76 +- 1.5 mN with a cross-correlation coefficient of 0.9996, clearly outperforming other methods. We test needles with different materials to demonstrate that the approach can be adapted for different sensitivities and force ranges. Furthermore, we validate our approach in an ex-vivo prostate needle insertion scenario.Comment: Accepted for Publication at MICCAI 201

Semi-parametric seasonal unit root tests

We extend the M class of unit root tests introduced by Stock (1999, Cointegration, Causality and Forecasting. A Festschrift in Honour of Clive W.J. Granger. Oxford University Press), Perron and Ng (1996, Review of Economic Studies 63, 435–463) and Ng and Perron (2001, Econometrica 69, 1519–1554) to the seasonal case, thereby developing semi-parametric alternatives to the regression-based augmented seasonal unit root tests of Hylleberg, Engle, Granger, and Yoo (1990, Journal of Econometrics 44, 215–238). The success of this class of unit root tests to deliver good finite sample size control even in the most problematic (near-cancellation) case where the shocks contain a strong negative moving average component is shown to carry over to the seasonal case as is the superior size/power trade-off offered by these tests relative to other available tests

Using patient-reported outcome measures to evaluate care for patients with inflammatory chronic rheumatic disease

Objectives: Few countries integrate Patient-Reported Outcome Measures (PROMs) in routine performance assessment, and those that do focus on elective surgery. This study addresses the challenges of using PROMs to evaluate care in chronic conditions. We set out a modelling strategy to assess the extent to which changes over time in self-reported health status by patients with inflammatory chronic rheumatic disease are related to their biological drug therapy and Rheumatology centre primarily responsible for their care. Methods: Using data from the Portuguese Register of Rheumatic Diseases, we assess the health status using the Health Assessment Questionnaire-Disability Index (HAQ-DI) for rheumatic patients receiving biological drugs between 2000 and 2017. We employ a fixed effects model using the Least Squares Dummy Variables estimator. Results: Patients receiving infliximab or rituximab report lower health status than those on etanercept (the most common therapy) and patients in 4 of the 26 Rheumatology centres report higher health status than those at other centres. Conclusions: PROMs can be used for those with chronic conditions to provide the patient’s perspective about the impact on their health status of the choice of drug therapy and care provider. Care for chronic patients might be improved if healthcare organisations monitor PROMs and engage in performance assessment initiatives on a routine basis

Diagnostic Challenge in a Sickle Cell Disease Patient with COVID-19

Acute chest syndrome is a life-threatening complication in sickle cell disease. Infections are frequently implied, and like other viruses, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be a trigger. In addition, due to their inflammatory status, they may present a higher risk for severe coronavirus disease 2019 (COVID-19). Pneumonia and acute chest syndrome share clinical, laboratory, and radiological features and may overlap, which makes their differential diagnosis especially challenging. We describe a case of an adolescent with homozygous sickle cell disease that developed acute chest syndrome in the context of COVID-19. With it, we intend to bring awareness to the potential role of imaging in the differential diagnosis and in establishing the best approach for the patient. Chest computed tomography findings were suggestive of an alternative diagnosis to COVID-19 pneumonia and red cell transfusion, fluid management, analgesics, and antibiotics were administered with favorable outcome.info:eu-repo/semantics/publishedVersio

Testing for Episodic Predictability in Stock Returns

Standard tests based on predictive regressions estimated over the full available sample data have tended to find little evidence of predictability in stock returns. Recent approaches based on the analysis of subsamples of the data have been considered, suggesting that predictability where it occurs might exist only within so-called 'pockets of predictability' rather than across the entire sample. However, these methods are prone to the criticism that the sub-sample dates are endogenously determined such that the use of standard critical values appropriate for full sample tests will result in incorrectly sized tests leading to spurious findings of stock returns predictability. To avoid the problem of endogenously-determined sample splits, we propose new tests derived from sequences of predictability statistics systematically calculated over sub-samples of the data. Specifically, we will base tests on the maximum of such statistics from sequences of forward and backward recursive, rolling, and double-recursive predictive sub-sample regressions. We develop our approach using the over-identified instrumental variable-based predictability test statistics of Breitung and Demetrescu (2015). This approach is based on partial-sum asymptotics and so, unlike many other popular approaches including, for example, those based on Bonferroni corrections, can be readily adapted to implementation over sequences of subsamples. We show that the limiting distributions of our proposed tests are robust to both the degree of persistence and endogeneity of the regressors in the predictive regression, but not to any heteroskedasticity present even if the sub-sample statistics are based on heteroskedasticity-robust standard errors. We therefore develop fixed regressor wild bootstrap implementations of the tests which we demonstrate to be first-order asymptotically valid. Finite sample behaviour against a variety of temporarily predictable processes is considered. An empirical application to US stock returns illustrates the usefulness of the new predictability testing methods we propose

Testing for Episodic Predictability in Stock Returns

Standard tests based on predictive regressions estimated over the full available sample data have tended to find little evidence of predictability in stock returns. Recent approaches based on the analysis of subsamples of the data suggest in fact that predictability where it occurs might exist only within so-called \pockets of predictability" rather than across the entire sample. However, these methods are prone to the criticism that the subsample dates are endogenously determined such that the use of standard critical values appropriate for full sample tests will result in incorrectly sized tests leading to spurious findings of stock returns predictability. To avoid the problem of endogenously-determined sample splits, we propose new tests derived from sequences of predictability statistics systematically calculated over subsamples of the data. Specifically, we will base tests on the maximum of such statistics from sequences of forward and backward recursive, rolling, and double-recursive predictive subsample regressions. We develop our approach using the over-identified instrumental variable-based predictability test statistics of Breitung and Demetrescu (2015). This approach is based on partial-sum asymptotics and so, unlike many other popular approaches including, for example, those based on Bonferroni corrections, can be readily adapted to implementation over sequences of subsamples. We show that the limiting null distributions of our proposed test statistics depend in general on whether the putative predictor is strongly or weakly persistent and on any heteroskedasticity present (indeed on any timevariation present in the unconditional variance matrix of the innovations), the latter even if the subsample statistics are based on heteroskedasticity-robust standard errors. As a consequence, we develop fixed regressor wild bootstrap implementations of the tests which we demonstrate to be first-order asymptotically valid. Finite sample behaviour against a variety of temporarily predictable processes is considered. An empirical application to US stock returns illustrates the usefulness of the new predictability testing methods we propose