CP properties of symmetry-constrained two-Higgs-doublet models

The two-Higgs-doublet model can be constrained by imposing Higgs-family symmetries and/or generalized CP symmetries. It is known that there are only six independent classes of such symmetry-constrained models. We study the CP properties of all cases in the bilinear formalism. An exact symmetry implies CP conservation. We show that soft breaking of the symmetry can lead to spontaneous CP violation (CPV) in three of the classes.Comment: 14 pages, 2 tables, revised version adapted to the journal publicatio

A Unique Relationship Determining Strength of Silty/Clayey Soils - Portland Cement Mixes

This technical note advances the understanding of the key parameters controlling unconfined compressive strength (qu) of artificially cemented silty/clayey soils by considering distinct moisture contents, distinct specimen porosities (η), different Portland cement contents and any curing time periods. The qu values of the specimens moulded for each curing period were normalized (i.e. divided) by the qu attained by a specimen with a specific porosity/cement ratio. A unique relationship was found, establishing the relationship between strength for artificially cemented silty/clayey soils considering all porosities, Portland cement amounts, moisture contents and curing periods studied. From a practical viewpoint, this means that, at limit, carrying out only one unconfined compression test with a silty/clayey soil specimen, moulded with a specific Portland cement amount, a specific porosity and moisture content and cured for a given time period, allows the determination of a general relationship equation that controls the strength for an entire range of porosities and cement contents, reducing considerably the amount of moulded specimens and reducing projects development cost and time

An artificial CO-releasing metalloprotein built by histidine-selective metallation.

We report the design and synthesis of an aquacarbonyl Ru(II) dication cis-[Ru(CO)2(H2O)4](2+) reagent for histidine (His)-selective metallation of interleukin (IL)-8 at site 33. The artificial, non-toxic interleukin (IL)-8-Ru(II)(CO)2 metalloprotein retained IL-8-dependent neutrophil chemotactic activity and was shown to spontaneously release CO in live cells.We thank the European Commission (Marie Curie CIG to G.J.L.B., Marie Curie IEF to O.B.), FCT Portugal (FCT Investigator to G.J.L.B.) and the EPSRC for generous funding.This is the final published version. It first appeared at http://pubs.rsc.org/en/Content/ArticleLanding/2015/CC/c4cc10204e#!divAbstract

Endothelial dysfunction is associated with cerebrovascular events in pre-dialysis ckd patients: A prospective study

Background: Patients with chronic kidney disease (CKD) have markedly increased rates of end stage renal disease, major adverse cardiovascular/cerebrovascular events (MACCEs), and mortality. Endothelial dysfunction (ED) is an early marker of atherosclerosis that is emerging as an increasingly important non-traditional cardiovascular risk factor in CKD. There is a lack of clinical studies examining the association between ED and both cardiovascular and renal endpoints in patients with CKD. Aims: We examined the association between reactive hyperemia index (RHI), a validated measure of endothelial function measured by peripheral arterial tonometry (PAT), with traditional cardiovascular risk factors in pre-dialysis CKD patients and prospectively evaluated the role of RHI as predictor of renal and cardiovascular outcomes in this population. Methods: One hundred and twenty pre-dialysis patients with CKD stages 1 to 5 (CKD group) and 18 healthy kidney donor candidates (control group) were recruited and had a successful RHI measurement by PAT. General demographic and clinical information including traditional cardiovascular risk factors were registered from all participants. Thereafter, patients were prospectively followed-up for a median time of 47 (IQR 19–66) months to determine associations of RHI with renal outcomes, MACCEs, hospitalizations or mortality. Results: In the CKD patient population, the mean age was 57.7 ± 15.5 years, the mean eGFR was 54.9 ± 36.7 mL/min/1.73 m2 (CKD-EPI) and 57 were males (47.5%). At baseline, in univariate analysis, RHI in the CKD group correlated positively with eGFR (r = 0.332, p < 0.0001) and correlated negatively with age (r = -0.469, p < 0.0001), Charlson index (r = -0.399, p < 0.0001), systolic blood pressure (r = -0.256, p = 0.005), and proteinuria (r = 0.211, p = 0.027). Reactive hyperemia index in the control group did not significantly differ from RHI observed in patients with CKD stages 1 to 5 (2.09 ± 0.40 vs. 2.01 ± 0.06, p = 0.493). In adjusted analysis, only age (ß = -0.014, p = 0.003) remained independently associated with RHI at baseline. During follow-up, 8 patients suffered a MACCEs, 33 patients experienced renal function deterioration, 17 patients were hospitalized for medical reasons and 6 patients died. RHI at baseline was not significantly associated with CKD progression (1.94 vs. 2.02, p = 0.584), hospitalizations (1.90 vs. 2.04, p = 0.334), and all-cause mortality (1.65 vs. 2.01, p = 0.208) or MACCEs (1.77 vs. 2.01, p = 0.356), but was significantly associated with cerebrovascular events (1.27 vs. 2.02, p = 0.004) and with a composite cardiovascular outcome (MACCEs, hospital admissions and death; 1.73 vs. 2.07, p = 0.035). Conclusion: Our results suggest that RHI may be a predictor for the development of cerebrovascular events in pre-dialysis CKD patients who may benefit from more aggressive preventive measures.This research was funded by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT—Fundação para a Ciência e a Tecnologia/ Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274), a grant from Portuguese Society of Nephrology

Circulating renalase as predictor of renal and cardiovascular outcomes in pre-dialysis ckd patients: A 5-year prospective cohort study

Chronic kidney disease (CKD) is an independent risk factor for adverse cardiovascular and cerebrovascular events (MACCEs), and mortality since the earlier stages. Therefore, it is critical to identify the link between CKD and cardiovascular risk (CVR) through early and reliable biomarkers. Acknowledging that CKD and CKD progression are associated with increased sympathetic tone, which is implicated in CVR, and that renalase metabolizes catecholamines, we aimed to evaluate the relationship between renalase serum levels (RNLS) and cardiovascular and renal outcomes. The study included 40 pre-dialysis CKD patients (19F:21M) with median age of 61 (IQ 45–66) years. At baseline, we measured RNLS as well as routine biomarkers of renal and cardiovascular risk. A prospective analysis was performed to determine whether RNLS are associated with CKD progression, MACCEs, hospitalizations and all-cause mortality. At baseline, the median level of RNLS and median estimated glomerular filtration rate (eGFR) were 63.5 (IQ 48.4–82.7) µg/mL and 47 (IQ 13–119) mL/min/1.73 m2, respectively. In univariate analysis, RNLS were strongly associated with eGFR, age and Charlson Index. Over the course of a mean follow-up of 65 (47 to 70) months, 3 (7.5%) deaths, 2 (5%) fatal MACCEs, 17 (42.5%) hospital admissions occurred, and 16 (40%) patients experienced CKD progression. In univariate analysis, RNLS were associated with CKD progression (p = 0.001), hospitalizations (p = 0.001) and all-cause mortality (p = 0.022) but not with MACCEs (p = 0.094). In adjusted analysis, RNLS predicted CKD progression and hospitalizations regardless of age, Charlson comorbidity index, cardiovascular disease, hypertension, diabetes and dyslipidemia. Our results suggest that RNLS, closely related with renal function, might have a potential role as predictor of renal outcomes, hospitalizations, and mortality in pre-dialysis CKD patients.This work was financed by FEDER-Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020-Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT-Fundação para a Ciência e a Tecnolo-gia/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project “Institute for Research and Innovation in Health Sciences” (POCI-01-0145-FEDER-007274), and a grant from Portuguese Society of Nephrology

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND: Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL). METHODS: We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients. RESULTS: Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei. CONCLUSION: The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls

Optimizing the use of systemic corticosteroids in severe asthma (ROSA II project): a national Delphi consensus study

Although the prevalence of severe asthma is not high (5–10% of patients), it is responsible for a large part of the overall disease burden and costs (50–60% of total costs), especially if the condition remains uncontrolled (which occurs in around 40% of cases). Currently, for patients without disease control or presenting frequent exacerbations despite optimal therapy, add-on treatments, traditionally long-acting anticholinergics, oral corticosteroids (OCS), or biologic agents (monoclonal antibodies) are recommended. Nonetheless, the long-term use of oral/systemic corticosteroids (CS) is significantly associated with adverse effects, acute and chronic complications that may decrease health-related quality of life and worsen prognosis, thus requiring additional monitoring and management. Conversely, target therapies (i.e., omalizumab, mepolizumab, reslizumab, benralizumab, and more recently, dupilumab) have been developed grounded on the different phenotypes and endotypes of severe asthma, and are gradually reducing the reliance on OCS (i.e., greater specificity for achieving disease control by reducing the risk of exacerbations and requirements for rescue medication and OCS, with limited adverse events).This work was supported by AstraZeneca.info:eu-repo/semantics/publishedVersio

Characterization of the striatal extracellular matrix in a mouse model of Parkinson’s disease

Parkinson’s disease’s etiology is unknown, although evidence suggests the involvement of oxidative modifications of intracellular components in disease pathobiology. Despite the known involvement of the extracellular matrix in physiology and disease, the influence of oxidative stress on the matrix has been neglected. The chemical modifications that might accumulate in matrix components due to their long half-live and the low amount of extracellular antioxidants could also contribute to the disease and explain ineffective cellular therapies. The enriched striatal extracellular matrix from a mouse model of Parkinson’s disease was characterized by Raman spectroscopy. We found a matrix fingerprint of increased oxalate content and oxidative modifications. To uncover the effects of these changes on brain cells, we morphologically characterized the primary microglia used to repopulate this matrix and further quantified the effects on cellular mechanical stress by an intracellular fluorescence resonance energy transfer (FRET)-mechanosensor using the U-2 OS cell line. Our data suggest changes in microglia survival and morphology, and a decrease in cytoskeletal tension in response to the modified matrix from both hemispheres of 6-hydroxydopamine (6-OHDA)-lesioned animals. Collectively, these data suggest that the extracellular matrix is modified, and underscore the need for its thorough investigation, which may reveal new ways to improve therapies or may even reveal new therapies.This research was funded by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE 2020 Operational Program for Competitiveness and Internationalization (POCI), Portugal 2020, and Portuguese funds through FCT (ID/BIM/04293/2020), UnIC (UID/IC/00051/2019), iBiMED (UID/BIM/04501/2020 and POCI-01-0145-FEDER-007628), and LAQV/REQUIMTE (UIDB/50006/2020) research units as well as RV’s Fellowship Grant (IF/00286/2015). Ana Freitas acknowledges FCT for her PhD scholarship (SFRH/BD/111423/2015), Miguel Aroso is hired through the Scientific Employment Stimulus from FCT (CEECIND/03415/2017), and M.L. has an FCT RJEC Id 3762 contract.The authors thank Eduardo D Martín Montiel for his support, fruitful discussions, suggestions, and technical and scientific help. The authors also thank Sofia Lamas and all the i3S Animal facility personnel for their support with the animals throughout the study. Raman spectroscopy, together with wide field and confocal microscopy, were performed at the i3S Scientific Platform Bioimaging, member of the PPBI (Plataforma Portuguesa de Bioimagem, POCI-01-0145-FEDER-022122)

REALMS Study: Real-World Effectiveness and Safety of Fingolimod in Patients with Relapsing-Remitting Multiple Sclerosis in Portugal

Background: Fingolimod, an oral sphingosine 1-phosphate receptor modulator, is approved by EMA for relapsing-remitting multiple sclerosis (RRMS). Objectives: To assess the effectiveness and safety of fingolimod in patients with RRMS in real-world clinical practice in Portugal. Methods: Retrospective, multicentre, non-interventional study, reporting 3 years follow-up of data collected from October 2015 to July 2016. Sociodemographic data and previous treatments at baseline and data regarding disease evolution, including number of relapses, annualised relapse rates (ARR) and Expanded Disability Status Scale (EDSS), were collected. Results: Two-hundred and seventy-five participants were enrolled in the REALMS study. Results showed that the main reason to switch to fingolimod was failure of previous treatment (56.7%) and only 3.6% were naïve patients. In the total population, there was a significant decrease in ARR of 64.6% in the first year of treatment, 79.7% in the second year and 82.3% in the third year, compared with baseline. More than 67.0% of patients had no relapses during the 3 years after switching to fingolimod. EDSS remained stable throughout the study. Conclusions: Therapy with fingolimod showed a sustained effectiveness and safety over the 3 years, particularly on patients switched from first-line drugs (BRACE). No new safety issues were reported.info:eu-repo/semantics/publishedVersio

Object classification for robotic platforms

Computer vision has been revolutionised in recent years by increased research in convolutional neural networks (CNNs); however, many challenges remain to be addressed in order to ensure fast and accurate image processing when applying these techniques to robotics. These challenges consist of handling extreme changes in scale, illumination, noise, and viewing angles of a moving object. The project main contribution is to provide insight on how to properly train a convolutional neural network (CNN), a specific type of DNN, for object tracking in the context of industrial robotics. The proposed solution aims to use a combination of documented approaches to replicate a pick-and-place task with an industrial robot using computer vision feeding a YOLOv3 CNN. Experimental tests, designed to investigate the requirements of training the CNN in this context, were performed using a variety of objects that differed in shape and size in a controlled environment. The general focus was to detect the objects based on their shape; as a result, a suitable and secure grasp could be selected by the robot. The findings in this article reflect the challenges of training the CNN through brute force. It also highlights the different methods of annotating images and the ensuing results obtained after training the neural network