Pregnancy and maternal uncorrected tetralogy of Fallot: A case report and review of the literature

Abstract Tetralogy of Fallot (TOF) is the most common congenital heart defect associated with systemic cyanosis. During pregnancy and delivery, dramatic alterations in cardiovascular physiology occurred. Pregnancy in women with unrepaired TOF may have a worsening in right to left shunt with an increase of the cyanosis and may imply an elevated risk of maternal and fetal morbidity and even mortality. We report and discuss a case of a 26 years old woman with uncorrected TOF. A multidisciplinary team was involved in the management of the case with the aim to minimize maternal and fetal complications. One of the main endpoint was to maintain an adequate oxygen saturation and good haemoglobin levels. A caesarean section was performed at 30 weeks and 5 days of gestation without any maternal or fetal complications. During the puerperium, the woman had an embolic occlusion of the right middle cerebral artery with any sequelae

SGLT2-inhibitors effects on the coronary fibrous cap thickness and MACEs in diabetic patients with inducible myocardial ischemia and multi vessels non-obstructive coronary artery stenosis

Background: Sodium-glucose transporter 2 inhibitors (SGLT2-I) could modulate atherosclerotic plaque progression, via down-regulation of inflammatory burden, and lead to reduction of major adverse cardiovascular events (MACEs) in type 2 diabetes mellitus (T2DM) patients with ischemic heart disease (IHD). T2DM patients with multivessel non-obstructive coronary stenosis (Mv-NOCS) have over-inflammation and over-lipids' plaque accumulation. This could reduce fibrous cap thickness (FCT), favoring plaque rupture and MACEs. Despite this, there is not conclusive data about the effects of SGLT2-I on atherosclerotic plaque phenotype and MACEs in Mv-NOCS patients with T2DM. Thus, in the current study, we evaluated SGLT2-I effects on Mv-NOCS patients with T2DM in terms of FCT increase, reduction of systemic and coronary plaque inflammation, and MACEs at 1 year of follow-up. Methods: In a multi-center study, we evaluated 369 T2DM patients with Mv-NOCS divided in 258 (69.9%) patients that did not receive the SGLT2-I therapy (Non-SGLT2-I users), and 111 (30.1%) patients that were treated with SGLT2-I therapy (SGLT2-I users) after percutaneous coronary intervention (PCI) and optical coherence tomography (OCT) evaluation. As the primary study endpoint, we evaluated the effects of SGLT2-I on FCT changes at 1 year of follow-up. As secondary endpoints, we evaluated at baseline and at 12 months follow-up the inflammatory systemic and plaque burden and rate of MACEs, and predictors of MACE through multivariable analysis. Results: At 6 and 12 months of follow-up, SGLT2-I users vs. Non-SGLT2-I users showed lower body mass index (BMI), glycemia, glycated hemoglobin, B-type natriuretic peptide, and inflammatory cells/molecules values (p < 0.05). SGLT2-I users vs. Non-SGLT2-I users, as evaluated by OCT, evidenced the highest values of minimum FCT, and lowest values of lipid arc degree and macrophage grade (p < 0.05). At the follow-up end, SGLT2-I users vs. Non-SGLT2-I users had a lower rate of MACEs [n 12 (10.8%) vs. n 57 (22.1%); p < 0.05]. Finally, Hb1Ac values (1.930, [CI 95%: 1.149-2.176]), macrophage grade (1.188, [CI 95%: 1.073-1.315]), and SGLT2-I therapy (0.342, [CI 95%: 0.180-0.651]) were independent predictors of MACEs at 1 year of follow-up. Conclusions: SGLT2-I therapy may reduce about 65% the risk to have MACEs at 1 year of follow-up, via ameliorative effects on glucose homeostasis, and by the reduction of systemic inflammatory burden, and local effects on the atherosclerotic plaque inflammation, lipids' deposit, and FCT in Mv-NOCS patients with T2DM

Inspeção de estruturas de betão armado com base em veículos aéreos não tripulados e processamento supervisionado de imagem

A presente dissertação tem como objetivos o desenvolvimento de ferramentas e procedimentos para a deteção de anomalias em estruturas de betão armado de forma semi automatizada recorrendo a técnicas de Deep Learning. Das várias anomalias que podem ser encontradas em estruturas de betão armado, destacam-se neste documento as fissuras e as armaduras expostas, para as quais foi desenvolvido um método alternativo de inspeção, baseado no processamento avançado de imagens, de modo a determinar se seria viável e vantajosa a substituição deste método pelo método de inspeção visual tradicional. As ferramentas desenvolvidas assentam em técnicas de Inteligência Artificial, em particilar as redes neuronais convolucionais (RNC), mais concretamente na utilização do transfer learning recorrendo à RNC Alexnet. Foram conduzidas experiências em diversas construções de modo a aferir a eficiência do método, recorrendo a veículos aéreos não tripulados (VANT), e em condições de acesso condicionado. Os resultados obtidos mostram ser bastante promissores, sendo previsível que do aprimoramento do método, possa resultar na adoção desta tecnologia como auxiliar nas inspeções visuais num futuro próximo.This dissertation aim is to develop tools and procedures for the detection of anomalies in reinforced concrete structures in a semi-automated way using Deep-Learning techniques. Of the various anomalies that can be found in reinforced concrete structures, this document highlights the exposed rebars and cracks, for which an alternative inspection method was developed, based in advanced image processing, in order to determine whether it would be feasible and advantageous to replace this method with the traditional visual inspection method. The tools developed are based on artificial intelligence techniques, in particular, convolutional neural networks (CNN), more specifically in the use of transfer-learning using the CNN Alexnet. Experiments were conducted in several constructions in order to assess the efficiency of the method, using unmanned aerial vehicles (UAV), under conditions of conditioned access. The results show to be quite promising, and it is foreseeable that its improvement may result in the adoption of this technology for aid in visual inspections in the near future

Enhancing treatment of osteoarthritis knee pain by boosting expectancy: A functional neuroimaging study

Objectives: Expectation can significantly modulate pain and treatment effects. This study aims to investigate if boosting patients' expectancy can enhance the treatment of knee osteoarthritis (KOA), and its underlying brain mechanism. Methods: Seventy-four KOA patients were recruited and randomized to three groups: boosted acupuncture (with a manipulation to enhance expectation), standard acupuncture, or treatment as usual (TAU). Each patient underwent six treatments before being debriefed, and four additional treatments after being debriefed. The fMRI scans were applied during the first and sixth treatment sessions. Results: We found significantly decreased knee pain in the boosted acupuncture group compared to the standard acupuncture or TAU groups after both six and ten treatments. Resting state functional connectivity (rsFC) analyses using the nucleus accumbens (NAc) as the seed showed rsFC increases between the NAc and the medial prefrontal cortex (MPFC)/rostral anterior cingulate cortex (rACC) and dorsolateral prefrontal cortex in the boosted group as compared to the standard acupuncture group after multiple treatments. Expectancy scores after the first treatment were significantly associated with increased NAc-rACC/MPFC rsFC and decreased knee pain following treatment. Conclusions: Our study provides a novel method and mechanism for boosting the treatment of pain in patients with KOA. Our findings may shed light on enhancing outcomes of pharmacological and integrative medicines in clinical settings

MIQuant – Semi-Automation of Infarct Size Assessment in Models of Cardiac Ischemic Injury

BACKGROUND: The cardiac regenerative potential of newly developed therapies is traditionally evaluated in rodent models of surgically induced myocardial ischemia. A generally accepted key parameter for determining the success of the applied therapy is the infarct size. Although regarded as a gold standard method for infarct size estimation in heart ischemia, histological planimetry is time-consuming and highly variable amongst studies. The purpose of this work is to contribute towards the standardization and simplification of infarct size assessment by providing free access to a novel semi-automated software tool. The acronym MIQuant was attributed to this application. METHODOLOGY/PRINCIPAL FINDINGS: Mice were subject to permanent coronary artery ligation and the size of chronic infarcts was estimated by area and midline-length methods using manual planimetry and with MIQuant. Repeatability and reproducibility of MIQuant scores were verified. The validation showed high correlation (r(midline length) = 0.981; r(area) = 0.970 ) and agreement (Bland-Altman analysis), free from bias for midline length and negligible bias of 1.21% to 3.72% for area quantification. Further analysis demonstrated that MIQuant reduced by 4.5-fold the time spent on the analysis and, importantly, MIQuant effectiveness is independent of user proficiency. The results indicate that MIQuant can be regarded as a better alternative to manual measurement. CONCLUSIONS: We conclude that MIQuant is a reliable and an easy-to-use software for infarct size quantification. The widespread use of MIQuant will contribute towards the standardization of infarct size assessment across studies and, therefore, to the systematization of the evaluation of cardiac regenerative potential of emerging therapies