The role of non-coding RNA in the development of pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a progressive disease of the small pulmonary arteries, characterised by pulmonary vascular remodelling due to excessive proliferation and resistance to apoptosis of pulmonary artery endothelial cells (PAECs) and pulmonary artery smooth muscle cells (PASMCs). The increased pulmonary vascular resistance and elevated pulmonary artery pressures result in right heart failure and premature death. Germline mutations of the bone morphogenetic protein receptor-2 (bmpr2) gene, a receptor of the transforming growth factor beta (TGF-β) superfamily, account for approximately 75%-80% of the cases of heritable form of PAH (HPAH) and 20% of sporadic cases or idiopathic PAH (IPAH). IPAH patients without known bmpr2 mutations show reduced expression of BMPR2. However only ~ 20% of bmpr2-mutation carriers will develop the disease, due to an incomplete penetrance, thus the need for a ‘second hit’ including other genetic and/or environmental factors is accepted. Diagnosis of PAH occurs most frequently when patients have reached an advanced stage of disease. Although modern PAH therapies can markedly improve a patient’s symptoms and slow the rate of clinical deterioration, the mortality rate from PAH remains unacceptably high. Therefore, the development of novel therapeutic approaches is required for the treatment of this multifaceted disease. Noncoding RNAs (ncRNAs) include microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). MiRNAs are ~ 22 nucleotide long and act as negative regulators of gene ex-pression via degradation or translational inhibition of their target mRNAs. Previous studies showed extensive evidence for the role of miRNAs in the development of PAH. LncRNAs are transcribed RNA molecules greater than 200 nucleotides in length. Similar to classical mRNA, lncRNAs are translated by RNA polymerase II and are generally alternatively spliced and polyadenylated. LncRNAs are highly versatile and function to regulate gene expression by diverse mechanisms. Unlike miRNAs, which exhibit well-defined actions in negatively regulating gene expression via the 3’-UTR of mRNAs, lncRNAs play more diverse and unpredictable regulatory roles. Although a number of lncRNAs have been intensively investigated in the cancer field, studies of the role of lncRNAs in vascular diseases such as PAH are still at a very early stage. The aim of this study was to investigate the involvement of specific ncRNAs in the development of PAH using experimental animal models and cell culture. The first ncRNA we focused on was miR-143, which is up-regulated in the lung and right ventricle tissues of various animal models of PH, as well as in the lungs and PASMCs of PAH patients. We show that genetic ablation of miR-143 is protective against the development of chronic hypoxia induced PH in mice, assessed via measurement of right ventricular systolic pressure (RVSP), right ventricular hypertrophy (RVH) and pulmonary vascular remodelling. We further report that knockdown of miR-143-3p in WT mice via anti-miR-143-3p administration prior to exposure of mice to chronic hypoxia significantly decreases certain indices of PH (RVSP) although no significant changes in RVH and pulmo-nary vascular remodelling were observed. However, a reversal study using antimiR-143-3p treatment to modulate miR-143-3p demonstrated a protective effect on RVSP, RVH, and muscularisation of pulmonary arteries in the mouse chronic hypoxia induced PH model. In vitro experiments showed that miR-143-3p overexpression promotes PASMC migration and inhibits PASMC apoptosis, while knockdown miR-143-3p elicits the opposite effect, with no effects observed on cellular proliferation. Interestingly, miR-143-3p-enriched exosomes derived from PASMCs mediated cell-to-cell communication between PASMCs and PAECs, contributing to the pro-migratory and pro-angiogenic phenotype of PAECs that underlies the pathogenesis of PAH. Previous work has shown that miR-145-5p expression is upregulated in the chronic hypoxia induced mouse model of PH, as well as in PAH patients. Genetic ablation and pharmacological inhibition (subcutaneous injection) of miR-145-5p exert a protective against the de-velopment of PAH. In order to explore the potential for alternative, more lung targeted delivery strategies, miR-145-5p expression was inhibited in WT mice using intranasal-delivered antimiR-145-5p both prior to and post exposure to chronic hypoxia. The decreased expression of miR-145-5p in lung showed no beneficial effect on the development of PH compared with control antimiRNA treated mice exposed to chronic hypoxia. Thus, miR-143-3p modulated both cellular and exosome-mediated responses in pulmonary vascular cells, while the inhibition of miR-143-3p prevented the development of experimental pulmonary hypertension. We focused on two lncRNAs in this project: Myocardin-induced Smooth Muscle Long noncoding RNA, Inducer of Differentiation (MYOSLID) and non-annotated Myolnc16, which were identified from RNA sequencing studies in human coronary artery smooth muscle cells (HCASMCs) that overexpress myocardin. MYOSLID was significantly in-creased in PASMCs from patients with IPAH compared to healthy controls and increased in circulating endothelial progenitor cells (EPCs) from bmpr2 mutant PAH patients. Exposure of PASMCs to hypoxia in vitro led to a significant upregulation in MYOSLID expres-sion. MYOSLID expression was also induced by treatment of PASMC with BMP4, TGF-β and PDGF, which are known to be triggers of PAH in vitro. Small interfering RNA (siR-NA)-mediated knockdown MYOSLID inhibited migration and induced cell apoptosis without affecting cell proliferation and upregulated several genes in the BMP pathway in-cluding bmpr1α, bmpr2, id1, and id3. Modulation of MYOSLID also affected expression of BMPR2 at the protein level. In addition, MYOSLID knockdown affected the BMP-Smad and BMP-non-Smad signalling pathways in PASMCs assessed by phosphorylation of Smad1/5/9 and ERK1/2, respectively. In PAECs, MYOSLID expression was also induced by hypoxia exposure, VEGF and FGF2 treatment. In addition, MYOSLID knockdown sig-nificantly decreased the proliferation of PAECs. Thus, MYOSLID may be a novel modulator in pulmonary vascular cell functions, likely through the BMP-Smad and –non-Smad pathways. Treatment of PASMCs with inflammatory cytokines (IL-1 and TNF-α) significantly in-duced the expression of Myolnc16 at a very early time point. Knockdown of Myolnc16 in vitro decreased the expression of il-6, and upregulated the expression of il-1 and il-8 in PASMCs. Moreover, the expression levels of chemokines (cxcl1, cxcl6 and cxcl8) were sig-nificantly decreased with Myolnc16 knockdown. In addition, Myolnc16 knockdown decreased the MAP kinase signalling pathway assessed by phosphorylation of ERK1/2 and p38 MAPK and inhibited cell migration and proliferation in PASMCs. Thus, Myolnc16 may a novel modulator of PASMCs functions through anti-inflammatory signalling pathways. In summary, in this thesis we have demonstrated how miR-143-3p plays a protective role in the development of PH both in vivo animal models and patients, as well as in vitro cell cul-ture. Moreover, we have showed the role of two novel lncRNAs in pulmonary vascular cells. These ncRNAs represent potential novel therapeutic targets for the treatment of PAH with further work addressing to investigate the target genes, and the pathways modulated by these ncRNAs during the development of PAH.

Numeric model to estimate pesticide deposition and losses from aerial spraying.

Pesticides applications have been described by many researches as a very inefficient process. In some cases, there are reports that only 0.02% of the applied products are used for the effective control of the problem. The main factor that influences pesticides applications is the droplet size formed on spraying nozzles. Many parameters affects the dynamic of the droplets, like wind, temperature, relative humidity, and others. Small droplets are biologically more active, but they are affected by evaporation and drift. On the other hand, the great droplets do not promote a good distribution of the product on the target. In this sense, associated with the risk of non target areas contamination and with the high costs involved in applications, the knowledge of the droplet size is of fundamental importance in the application technology. When sophisticated technology for droplets analysis is unavailable, is common the use of artificial targets like water-sensitive paper to sample droplets. On field sampling, water-sensitive papers are placed on the trials where product will be applied. When droplets impinging on it, the yellow surface of this paper will be stained dark blue, making easy their recognition. Collected droplets on this papers have different kinds of sizes. In this sense, the determination of the droplet size distribution gives a mass distribution of the material and so, the efficience of the application of the product. The stains produced by droplets shows a spread factor proportional to their respectives initial sizes. One of methodologies to analyse the droplets is a counting and measure of the droplets made in microscope. The Porton N-G12 graticule, that shows equaly spaces class intervals on geometric progression of square 2, are coulpled to the lens of the microscope. The droplet size parameters frequently used are the Volumetric Median Diameter (VMD) and the Numeric Median Diameter. On VMD value, a representative droplets sample is divided in two equal parts of volume, in such away one part contains droplets of sizes smaller than VMD and the other part contains droplets of sizes greater that VMD. The same process is done to obtaining the NMD, which divide the sample in two equal parts in relation to the droplets size. The ratio between VMD and NMD allows the droplets uniformity evaluation. After that, the graphics of accumulated probability of the volume and size droplets are plotted on log scale paper (accumulated probability versus median diameter of each size class). The graphics provides the NMD on the x-axes point corresponding to the value of 50% founded on the y-axes. All this process is very slow and subjected to operator error. So, in order to decrease the difficulty envolved with droplets measuring it was developed a numeric model, implemented on easy and accessfull computational language, which allows approximate VMD and NMD values, with good precision. The inputs to this model are the frequences of the droplets sizes colected on the water-sensitive paper, observed on the Porton N-G12 graticule fitted on microscope. With these data, the accumulated distribution of the droplet medium volumes and sizes are evaluated. The graphics obtained by plotting this distributions allow to obtain the VMD and NMD using linear interpolation, seen that on the middle of the distributions the shape of the curves are linear. These values are essential to evaluate the uniformity of droplets and to estimate the volume deposited on the observed paper by the density (droplets/cm2). This methodology to estimate the droplets volume was developed by 11.0.94.224 Project of the CNPMA/EMBRAPA. Observed data of herbicides aerial spraying samples, realized by Project on Pelotas/RS county, were used to compare values obtained manual graphic method and with those obtained by model has shown, with great precision, the values of VMD and NMD on each sampled collector, allowing to estimate a quantities of deposited product and, by consequence, the quantities losses by drifty. The graphics of variability of VMD and NMD showed that the quantity of droplets that reachs the collectors had a short dispersion, while the deposited volume shows a great interval of variation, probably because the strong action of air turbulence on the droplets distribution, enfasizing the necessity of a deeper study to verify this influences on drift.

An architecture for network acceleration as a service in the cloud continuum

The pervasive availability of connected devices in any industrial and societal sector is pushing for an evolution of the well-established cloud computing model. The emerging paradigm of the cloud continuum embraces this decentralization trend and envisions virtualized computing resources physically located between traditional datacenters and data sources. By totally or partially executing closer to the network edge, applications can have quicker reactions to events, thus enabling advanced forms of automation and intelligence. However, these applications also induce new data-intensive workloads with low-latency constraints that require the adoption of specialized resources, such as high-performance communication options (e.g., RDMA, DPDK, XDP, etc.). Unfortunately, cloud providers still struggle to integrate these options into their infrastructures. That risks undermining the principle of generality that underlies the cloud computing scale economy by forcing developers to tailor their code to low-level APIs, non-standard programming models, and static execution environments. This thesis proposes a novel system architecture to empower cloud platforms across the whole cloud continuum with Network Acceleration as a Service (NAaaS). To provide commodity yet efficient access to acceleration, this architecture defines a layer of agnostic high-performance I/O APIs, exposed to applications and clearly separated from the heterogeneous protocols, interfaces, and hardware devices that implement it. A novel system component embodies this decoupling by offering a set of agnostic OS features to applications: memory management for zero-copy transfers, asynchronous I/O processing, and efficient packet scheduling. This thesis also explores the design space of the possible implementations of this architecture by proposing two reference middleware systems and by adopting them to support interactive use cases in the cloud continuum: a serverless platform and an Industry 4.0 scenario. A detailed discussion and a thorough performance evaluation demonstrate that the proposed architecture is suitable to enable the easy-to-use, flexible integration of modern network acceleration into next-generation cloud platforms.

Developing a radiomic based machine learning model to identify patients with resected non-small-cell lung cancer at high risk of relapse

Background There is a wide variation of recurrence risk of Non-small-cell lung cancer (NSCLC) within the same Tumor Node Metastasis (TNM) stage, suggesting that other parameters are involved in determining this probability. Radiomics allows extraction of quantitative information from images that can be used for clinical purposes. The primary objective of this study is to develop a radiomic prognostic model that predicts a 3 year disease free-survival (DFS) of resected Early Stage (ES) NSCLC patients. Material and Methods 56 pre-surgery non contrast Computed Tomography (CT) scans were retrieved from the PACS of our institution and anonymized. Then they were automatically segmented with an open access deep learning pipeline and reviewed by an experienced radiologist to obtain 3D masks of the NSCLC. Images and masks underwent to resampling normalization and discretization. From the masks hundreds Radiomic Features (RF) were extracted using Py-Radiomics. Hence, RF were reduced to select the most representative features. The remaining RF were used in combination with Clinical parameters to build a DFS prediction model using Leave-one-out cross-validation (LOOCV) with Random Forest. Results and Conclusion A poor agreement between the radiologist and the automatic segmentation algorithm (DICE score of 0.37) was found. Therefore, another experienced radiologist manually segmented the lesions and only stable and reproducible RF were kept. 50 RF demonstrated a high correlation with the DFS but only one was confirmed when clinicopathological covariates were added: Busyness a Neighbouring Gray Tone Difference Matrix (HR 9.610). 16 clinical variables (which comprised TNM) were used to build the LOOCV model demonstrating a higher Area Under the Curve (AUC) when RF were included in the analysis (0.67 vs 0.60) but the difference was not statistically significant (p=0,5147).

Circumplex Model to analyze the impact of emotions on decision-making processes in innovation management

Group work allows participants to pool their thoughts and examine difficulties from several angles. In these settings, it is possible to attempt things that an individual could not achieve, combining a variety of abilities and knowledge to tackle more complicated and large-scale challenges. That’s why nowadays collaborative work is becoming more and more widespread to solve complex innovation dilemmas. Since innovation isn’t a tangible thing, most innovation teams used to take decisions based on performance KPIs such as forecasted engagement, projected profitability, investments required, cultural impacts etc. Have you ever wondered the reason why sometimes innovation group processes come out with decisions which are not the optimal meeting point of all the KPIs? Has this decision been influenced by other factors? Some researchers account part of this phenomenon to the emotions in group-based interaction between participants. I will develop a literature review that is split into three parts: first, I will consider some emotions theories from an individual perspective; secondly, a wider view of collective interactions theories will be provided; lastly, I will supply some recent collective interaction empirical studies. After the theoretical and empirical gaps have been tackled, the study will additionally move forward with a methodological point of view, about the Circumplex Model, which is the model I used to evaluate emotions in my research. This model has been applied to SUGAR project, which is the biggest design thinking academy worldwide.

Domain adaptation per classificazione di point cloud mediante pseudo-annotazioni

La classificazione di dati geometrici 3D come point cloud è un tema emergente nell'ambito della visione artificiale in quanto trova applicazione in molteplici contesti di guida autonoma, robotica e realtà aumentata. Sebbene nel mercato siano presenti una grande quantità di sensori in grado di ottenere scansioni reali, la loro annotazione costituisce un collo di bottiglia per la generazione di dataset. Per sopperire al problema si ricorre spesso alla domain adaptation sfruttando dati sintetici annotati. Questo elaborato si pone come obiettivo l'analisi e l'implementazione di metodi di domain adaptation per classificazione di point cloud mediante pseudo-labels. In particolare, sono stati condotti esperimenti all'interno del framework RefRec valutando la possibilità di sostituire nuove architetture di deep learning al modello preesistente. Tra queste, Transformer con mascheramento dell'input ha raggiunto risultati superiori allo stato dell'arte nell'adattamento da dati sintetici a reali (ModelNet->ScanNet) esaminato in questa tesi.

Tree regularized neural networks for key point analysis

This thesis contributes to the ArgMining 2021 shared task on Key Point Analysis. Key Point Analysis entails extracting and calculating the prevalence of a concise list of the most prominent talking points, from an input corpus. These talking points are usually referred to as key points. Key point analysis is divided into two subtasks: Key Point Matching, which involves assigning a matching score to each key point/argument pair, and Key Point Generation, which consists of the generation of key points. The task of Key Point Matching was approached using different models: a pretrained Sentence Transformers model and a tree-constrained Graph Neural Network were tested. The best model was the fine-tuned Sentence Transformers, which achieved a mean Average Precision score of 0.75, ranking 12 compared to other participating teams. The model was then used for the subtask of Key Point Generation using the extractive method in the selection of key point candidates and the model developed for the previous subtask to evaluate them.

Chemical Immobilization Of Crosslinked Polymeric Ionic Liquids On Nitinol Wires Produces Highly Robust Sorbent Coatings For Solid-phase Microextraction.

Super elastic nitinol (NiTi) wires were exploited as highly robust supports for three distinct crosslinked polymeric ionic liquid (PIL)-based coatings in solid-phase microextraction (SPME). The oxidation of NiTi wires in a boiling (30%w/w) H2O2 solution and subsequent derivatization in vinyltrimethoxysilane (VTMS) allowed for vinyl moieties to be appended to the surface of the support. UV-initiated on-fiber copolymerization of the vinyl-substituted NiTi support with monocationic ionic liquid (IL) monomers and dicationic IL crosslinkers produced a crosslinked PIL-based network that was covalently attached to the NiTi wire. This alteration alleviated receding of the coating from the support, which was observed for an analogous crosslinked PIL applied on unmodified NiTi wires. A series of demanding extraction conditions, including extreme pH, pre-exposure to pure organic solvents, and high temperatures, were applied to investigate the versatility and robustness of the fibers. Acceptable precision of the model analytes was obtained for all fibers under these conditions. Method validation by examining the relative recovery of a homologous group of phthalate esters (PAEs) was performed in drip-brewed coffee (maintained at 60 °C) by direct immersion SPME. Acceptable recoveries were obtained for most PAEs in the part-per-billion level, even in this exceedingly harsh and complex matrix.

Oxidative Stress And Susceptibility To Mitochondrial Permeability Transition Precedes The Onset Of Diabetes In Autoimmune Non-obese Diabetic Mice.

Beta cell destruction in type 1 diabetes (TID) is associated with cellular oxidative stress and mitochondrial pathway of cell death. The aim of this study was to determine whether oxidative stress and mitochondrial dysfunction are present in T1D model (non-obese diabetic mouse, NOD) and if they are related to the stages of disease development. NOD mice were studied at three stages: non-diabetic, pre-diabetic, and diabetic and compared with age-matched Balb/c mice. Mitochondria respiration rates measured at phosphorylating and resting states in liver and soleus biopsies and in isolated liver mitochondria were similar in NOD and Balb/c mice at the three disease stages. However, NOD liver mitochondria were more susceptible to calcium-induced mitochondrial permeability transition as determined by cyclosporine-A-sensitive swelling and by decreased calcium retention capacity in all three stages of diabetes development. Mitochondria H2O2 production rate was higher in non-diabetic, but unaltered in pre-diabetic and diabetic NOD mice. The global cell reactive oxygen species (ROS), but not specific mitochondria ROS production, was significantly increased in NOD lymphomononuclear and stem cells in all disease stages. In addition, marked elevated rates of 2',7'-dichlorodihydrofluorescein (H2DCF) oxidation were observed in pancreatic islets from non-diabetic NOD mice. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) and lipidomic approach, we identified oxidized lipid markers in NOD liver mitochondria for each disease stage, most of them being derivatives of diacylglycerols and phospholipids. These results suggest that the cellular oxidative stress precedes the establishment of diabetes and may be the cause of mitochondrial dysfunction that is involved in beta cell death.

Development And Characterization Of A Cationic Lipid Nanocarrier As Non-viral Vector For Gene Therapy.

The aim of the present work was to produce a cationic solid lipid nanoparticle (SLN) as non-viral vector for protein delivery. Cationic SLN were produced by double emulsion method, composed of softisan(®) 100, cetyltrimethylammonium bromide (CTAB), Tween(®) 80, Span(®) 80, glycerol and lipoid(®) S75 loading insulin as model protein. The formulation was characterized in terms of mean hydrodynamic diameter (z-ave), polydispersity index (PI), zeta potential (ZP), stability during storage time, stability after lyophilization, effect of toxicity and transfection ability in HeLa cells, in vitro release profile and morphology. SLN were stable for 30days and showed minimal changes in their physicochemical properties after lyophilization. The particles exhibited a relatively slow release, spherical morphology and were able to transfect HeLa cells, but toxicity remained an obstacle. Results suggest that SLN are nevertheless promising for delivery of proteins or nucleic acids for gene therapy.

Otimização do descascamento químico de raízes do yacon (Polymnia sonchifolia Poepp.)

A full factorial design 2³ was used to evaluate the effect of process variables in chemical peeling of yacon roots, cultivated in Curitiba, State of Paraná. Eleven treatments, with three central points, were done in which they had been evaluated at three different levels of sodium hydroxide solution, % (g/100 mL) [6, 10, 14], temperature of the same solution, °C [70, 80, 90], and residence time in the sodium hydroxide solution, minutes [2, 4, 6]. All the studied variables had affected significantly (p<0.05) the yield of yacon roots subjected to chemical peeling. The variable that most affected the yield was the time of permanence in the sodium hydroxide solution. The mathematical model obtained for the yield (%) was good with R² aj = 0.8497, and non significant lack of fit (p=0.9312).Therefore, the model can be used for predictive purposes. In the central point a satisfactory yield (84% to 87%) with a high percentage of removed peel was obtained (96% to 98%) indicating that the treatment with 10% of sodium hydroxide solution, temperature of 80º C per 4 minutes can be used in the chemical peeling of yacon roots.

PREDIÇÃO DA ATIVIDADE DE ÁGUA E RELAÇÃO ENTRE A ATIVIDADE DE ÁGUA E A DEPRESSÃO DO PONTO DE CONGELAMENTO DE SUCOS DE FRUTAS

This work proposes to determine the water activity and the freezing point depression of tangerine, pineapple and lemon juices at various concentrations (10-55oBrix) and to achieve a correlation between these properties. The freezing point depression was determined with a LAKTRON cryoscope and common laboratory materials. The water activity was determined with a DECAGON CX-2 hygrometer in the temperature range of 15 to 30oC. With the results, the adjustment to CHEN (1987) water activity prediction equation to non-electrolyte mixtures was verified, through the calculation of the variation coefficient (CV). Being CV smaller than 3% for the proposed model, it can be said that the experimental data have adjusted well to the prediction equation. The water activity and the freezing point depression was correlated for tangerine, pineapple and lemon juices and r2 values were higher than 99%. Therefore, it is possible to obtain the water activity by knowing the freezing point depression of studied juices.

Incapacidades fisicas em hanseniase e atividade fisica : coisa do passado ou problema do futuro

Universidade Estadual de Campinas . Faculdade de Educação Física

Utilização da discriminação grafica de Fisher para indicação dos dermatoglifos como referencial de potencialidade de atletas de basquetebol

Universidade Estadual de Campinas. Faculdade de Educação Física

Modelo para análise do ataque no futebol = : A model to analyze soccer offensive phase

Universidade Estadual de Campinas . Faculdade de Educação Física