902 resultados para Role Models


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Glioblastoma is the most malignant brain tumor in adults. The standard care of treatment is tumor resection, radiotherapy, and chemotherapy. Despite these invasive therapeutic approaches, glioblastoma prognosis remains unchanged. Therefore, a better understanding of the molecular mechanisms driving tumor transformation is needed to uncover novel therapeutic strategies. Several studies have shown the significance of lipid signaling and phospholipases (PLCs) in the regulation of different mechanisms in the central nervous system as well as in glioblastoma pathogenesis. This work suggests a potential role of PLCβ1 in the maintenance of a less aggressive phenotype of the tumor. Indeed, it was demonstrated that PLCβ1 gene was relatively less expressed in glioblastoma patients compared to their healthy/low-grade counterparts. Moreover, PLCβ1 silencing, in both immortalized and primary cell lines, led to increased cell migration, invasion, proliferation, cell survival and induced the upregulation of mesenchymal markers and metalloproteinases. Moreover, PLCγ1, another abundant PLC isoform in the brain, has been identified as a key element for the aggressiveness of glioblastoma. Data collected on patients’ biopsies and engineered cell models, suggested a strong correlation between PLCγ1 expression level and the acquisition of a more aggressive tumor phenotype. Finally, this trend was further probed using patient-derived glioblastoma stem cells (GSCs), which are a specific tumor population that drives aggressiveness, resistance, and recurrence in glioblastoma. GSCs analysis on the transcriptomic profiles confirmed that PLCγ1 downregulation modulated positively the activation of pathways that negatively regulate cell motility and migration and led to a decreased expression of genes involved in cancer development and progression. Taken together, these data highlight the importance of further investigating phospholipases as potential prognostic biomarkers and targets in the development of new therapeutic strategies for glioblastoma.

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Cardiomyopathies are a heterogeneous group of myocardial disorders defined by structural and functional alterations of the heart. These cardiac diseases can have both non-genetic and genetic origin. Nevertheless, a different etiology can trigger the same phenotype, as in the case of anthracycline-induced cardiotoxicity and desmin-related cardiomyopathy (DRM). Therefore, the aim of this study was to investigate the cellular mechanisms driving the development of these cardiotoxic conditions in in vitro models. Doxorubicin (DOX) is a commonly used antineoplastic drug for the treatment of a wide range of tumors. Besides, its clinical use is restricted because of dose-dependent cardiotoxicity. Our findings provided evidence that phospholipase C Beta 2 (PLCβ2) may have a critical role in DOX-induced cardiotoxicity in undifferentiated and differentiated H9c2 cell line. Interestingly, the results obtained revealed that cardiomyocytes are less sensitive to DOX, following the evaluation of cellular mechanisms such as: oxidative stress, apoptosis and cell proliferation. Nonetheless, the treatment induced a significant upregulation of PLCβ2 associated to morphological changes in both models, demonstrating the implication in a hypertrophic response. On the other hand, a hereditary DRM was associated to a missense mutation of aB crystallin (CRYAB), a chaperone protein involved in the regulation of the intermediate filament network. Since research has only been conducted on transgenic (TG) mice and neonatal rat cardiomyocytes, this study aimed at investigating cellular mechanisms triggered by CRYABR120G mutation in a hiPSC-derived DRM model. Our model confirmed the impairment of the cytoskeletal organization resulting in the formation of desmin and CRYAB aggregates and myofibril misalignment. Moreover, the missense mutation confirmed a hypertrophic cardiomyopathy phenotype, a feature of DRM patients, on cardiac engineered tissues. Lastly, these data obtained suggest that further research on PLCβ2 and CRYAB are needed to comprehend the molecular mechanisms behind the development of these 2 cardiac diseases.

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During the pathogenesis of hemolytic uremic syndrome (HUS), a severe sequela of Shiga toxin (Stx)-producing Escherichia coli (STEC) gastrointestinal infections, before the toxin acts on the target endothelial cells of the kidney and brain, several Stx forms are transported in the bloodstream: free Stx; Stx bound to circulating cells through Gb3Cer and TLR4 receptors; and Stx associated to blood cell-derived microvesicles. The latter form is mainly responsible for the development of life-threatening HUS in 15% of STEC-infected patients. Stx consist of five B subunits non-covalently bound to a single A subunit (uncleaved Stx) which can be cleaved in two fragments (A1 and A2) held by a disulfide bond (cleaved Stx). After reduction, the enzymatically active A1 fragment responsible for toxicity is released. Cleaved and uncleaved Stx are biologically active but functionally different, thus their presence in patients’ blood could affect the onset of HUS. Currently, there are no effective therapies for the treatment of STEC-infected patients and the gold standard strategies available for the diagnosis are very expensive and time-consuming. In this thesis, by exploiting the resolving power of SERS technology (Amplified Raman Spectroscopy on Surfaces), a plasmonic biosensor was developed as effective diagnostic tool for early detection of Stx in patients’ sera. An acellular protein synthesis system for detecting cleaved Stx2a in human serum based on its greater translation inhibition after treatment with reducing agents was developed and used to identify cleaved Stx in STEC-infected patients’ sera. Pathogenic microvesicles from Stx2a-challenged blood from healthy donors were isolated and characterized. The antibiotic NAB815, acting as inhibitor of toxin binding to TLR4 expressed by circulating cells, was found to be effective in impairing the formation of blood cell-derived microvesicles containing Stx2a, also having a protective effect in cellular models. This approach could be proposed as an innovative treatment for HUS prevention.

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Neuroinflammation is a crucial pathogenic mechanism that commonly underlies most neurodegenerative diseases. Microglia, the immune cells of the brain, play a critical role that changes depending on the stage of neuropathology: at early phases of brain diseases microglia display the neuroprotective phenotype which is switched to the classically activated pro-inflammatory subtype at later stages, contributing to neurodegeneration. The microglial phenotypic shift is characterized by a change in the release of bioactive molecules both soluble and through extracellular vesicles. Our in vitro studies aim to understand whether different types of activation could determine change in vesicles content, in particular miRNAs, and whether this could influence the activation state of control microglial cells. Microglial polarization has been induced in two different in vitro models: N9, microglial murine cell line, have been treated by using LPS towards a proinflammatory/neurotoxic phenotype or ATP towards antinflammatory/neuroprotective status; HMC3, human microglial cell line, have been activated using IFN-+ATP. We demonstrated that conditioned media/exosomes obtained from donor microglia were able to promote a pro-inflammatory phenotype in control cells, leading us to prove the existence of a neuroinflammation spreading process mediated by extracellular vesicles of microglia with a crucial role of miRNAs. Increased expression of miRNA-34a observed in N9 model underlines a possible contribution in the diffusion of proinflammatory activation of microglia. Thus, we tried to downregulate miR-34a expression using cleaving sequences of anti-mir-34a DNAzyme delivered by DNA nanostructures aimed to confirm the involvement of miR-34a in microglia polarization towards the neurotoxic phenotype. In conclusion, this thesis work reveal a new inflammation spreading mechanism that involves release of vesicles containing specific cargos by donor polarized microglia, particularly miRNAs, able to influence the phenotypic shift in unpolarized microglia: this process deserves to be deeply investigated as potential therapeutic target to counteract neurodegenerative diseases.

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The integration of digital technology in school is a complex phenomenon that affects both teaching and peer relationships. Accordingly, the main aim of this dissertation was to investigate the implementation of distance education among Italian teachers during the COVID-19 pandemic and analyze peer relationships concerning cyberbullying and bullying. While the theoretical section provided an overview of the phenomena, four empirical studies were presented. The first one tested a moderated moderation model among 178 secondary teachers on the interactions among perceived usefulness, perceived ease of use of technology and online teaching self-efficacy. Findings showed that each variable significantly predicted the intention to use technology. In addition, a moderation effect of online teaching self-efficacy on perceived usefulness was found. The second study analyzed the differences in factors promoting the integration of digital technology among 357 teachers of different levels and subjects and their positive and negative experiences with distance education. Results revealed several differences in the function of the grade and subjects taught. Moreover, four main themes emerged from the content analysis. The third study investigated the dyadic perception of bullying and cyberbullying among 50 students using the eye-tracker. Findings showed that, despite differences among different kinds of bullying and cyberbullying, the victim and bully were the most observed roles. Finally, the last study tested two multiple mediation models among 563 students on the association between bullying, cyberbullying, and well-being, considering three different variables related to the school context (peer network, teacher support and school connectedness). The results highlighted the importance of peer networks and school connectedness in mediating the association between victimization, cybervictimzation and well-being. Taken together, the findings provided a rich overview of digital technology integration in schools, highlighting positive and negative aspects and its implications for future research and school policies.

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The main topic of this thesis is confounding in linear regression models. It arises when a relationship between an observed process, the covariate, and an outcome process, the response, is influenced by an unmeasured process, the confounder, associated with both. Consequently, the estimators for the regression coefficients of the measured covariates might be severely biased, less efficient and characterized by misleading interpretations. Confounding is an issue when the primary target of the work is the estimation of the regression parameters. The central point of the dissertation is the evaluation of the sampling properties of parameter estimators. This work aims to extend the spatial confounding framework to general structured settings and to understand the behaviour of confounding as a function of the data generating process structure parameters in several scenarios focusing on the joint covariate-confounder structure. In line with the spatial statistics literature, our purpose is to quantify the sampling properties of the regression coefficient estimators and, in turn, to identify the most prominent quantities depending on the generative mechanism impacting confounding. Once the sampling properties of the estimator conditionally on the covariate process are derived as ratios of dependent quadratic forms in Gaussian random variables, we provide an analytic expression of the marginal sampling properties of the estimator using Carlson’s R function. Additionally, we propose a representative quantity for the magnitude of confounding as a proxy of the bias, its first-order Laplace approximation. To conclude, we work under several frameworks considering spatial and temporal data with specific assumptions regarding the covariance and cross-covariance functions used to generate the processes involved. This study allows us to claim that the variability of the confounder-covariate interaction and of the covariate plays the most relevant role in determining the principal marker of the magnitude of confounding.

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In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.

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Bioelectronic interfaces have significantly advanced in recent years, offering potential treatments for vision impairments, spinal cord injuries, and neurodegenerative diseases. However, the classical neurocentric vision drives the technological development toward neurons. Emerging evidence highlights the critical role of glial cells in the nervous system. Among them, astrocytes significantly influence neuronal networks throughout life and are implicated in several neuropathological states. Although they are incapable to fire action potentials, astrocytes communicate through diverse calcium (Ca2+) signalling pathways, crucial for cognitive functions and brain blood flow regulation. Current bioelectronic devices are primarily designed to interface neurons and are unsuitable for studying astrocytes. Graphene, with its unique electrical, mechanical and biocompatibility properties, has emerged as a promising neural interface material. However, its use as electrode interface to modulate astrocyte functionality remains unexplored. The aim of this PhD work was to exploit Graphene-oxide (GO) and reduced GO (rGO)-coated electrodes to control Ca2+ signalling in astrocytes by electrical stimulation. We discovered that distinct Ca2+dynamics in astrocytes can be evoked, in vitro and in brain slices, depending on the conductive/insulating properties of rGO/GO electrodes. Stimulation by rGO electrodes induces intracellular Ca2+ response with sharp peaks of oscillations (“P-type”), exclusively due to Ca2+ release from intracellular stores. Conversely, astrocytes stimulated by GO electrodes show slower and sustained Ca2+ response (“S-type”), largely mediated by external Ca2+ influx through specific ion channels. Astrocytes respond faster than neurons and activate distinct G-Protein Coupled Receptor intracellular signalling pathways. We propose a resistive/insulating model, hypothesizing that the different conductivity of the substrate influences the electric field at the cell/electrolyte or cell/material interfaces, favouring, respectively, the Ca2+ release from intracellular stores or the extracellular Ca2+ influx. This research provides a simple tool to selectively control distinct Ca2+ signals in brain astrocytes in neuroscience and bioelectronic medicine.

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The benzoquinone was found as an effective co-catalyst in the ruthenium/NaOEt-catalyzed Guerbet reaction. The co-catalyst behavior has therefore been investigated through experimental and computational methods. The reaction products distribution shows that the reaction speed is improved by the benzoquinone supplement since the beginning of the process, having a minimal effect on the selectivity toward alcoholic species. DFT calculations were performed to investigate two hypotheses for the kinetic effects: i) a hydrogen storage mechanism or ii) a basic co-catalysis of 4-hydroxiphenolate. The most promising results were found for the latter hypothesis, where a new mixed mechanism for the aldol condensation step of the Guerbet process involves the hydroquinone (i.e. the reduced form of benzoquinone) as proton source instead of ethanol. This mechanism was found to be energetically more favorable than an aldol condensation in absence of additive, suggesting that the hydroquinone derived from benzoquinone could be the key species affecting the kinetics of the overall process. To verify this theoretical hypothesis, new phenol derivatives were tested as additives in the Guerbet reaction. The outcomes confirmed that an aromatic acid (stronger than ethanol) could improve the reaction kinetics. Lastly, theoretical products distributions were simulated and compared to the experimental one, using the DFT computations to build the kinetic models.

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Characterized for the first time in erythrocytes, phosphatidylinositol phosphate kinases (PIP kinases) belong to a family of enzymes that generate various lipid messengers and participate in several cellular processes, including gene expression regulation. Recently, the PIPKIIα gene was found to be differentially expressed in reticulocytes from two siblings with hemoglobin H disease, suggesting a possible relationship between PIPKIIα and the production of globins. Here, we investigated PIPKIIα gene and protein expression and protein localization in hematopoietic-derived cells during their differentiation, and the effects of PIPKIIα silencing on K562 cells. PIPKIIα silencing resulted in an increase in α and γ globins and a decrease in the proliferation of K562 cells without affecting cell cycle progression and apoptosis. In conclusion, using a cell line model, we showed that PIPKIIα is widely expressed in hematopoietic-derived cells, is localized in their cytoplasm and nucleus, and is upregulated during erythroid differentiation. We also showed that PIPKIIα silencing can induce α and γ globin expression and decrease cell proliferation in K562 cells.

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Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.

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Thiamine deficiency (TD) is the underlying cause of Wernicke's encephalopathy (WE), an acute neurological disorder characterized by structural damage to key periventricular structures in the brain. Increasing evidence suggests these focal histological lesions may be representative of a gliopathy in which astrocyte-related changes are a major feature of the disorder. These changes include a loss of the glutamate transporters GLT-1 and GLAST concomitant with elevated interstitial glutamate levels, lowered brain pH associated with increased lactate production, decreased levels of GFAP, reduction in the levels of glutamine synthetase, swelling, alterations in levels of aquaporin-4, and disruption of the blood-brain barrier. This review focusses on how these manifestations contribute to the pathophysiology of TD and possibly WE.

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Prosopis rubriflora and Prosopis ruscifolia are important species in the Chaquenian regions of Brazil. Because of the restriction and frequency of their physiognomy, they are excellent models for conservation genetics studies. The use of microsatellite markers (Simple Sequence Repeats, SSRs) has become increasingly important in recent years and has proven to be a powerful tool for both ecological and molecular studies. In this study, we present the development and characterization of 10 new markers for P. rubriflora and 13 new markers for P. ruscifolia. The genotyping was performed using 40 P. rubriflora samples and 48 P. ruscifolia samples from the Chaquenian remnants in Brazil. The polymorphism information content (PIC) of the P. rubriflora markers ranged from 0.073 to 0.791, and no null alleles or deviation from Hardy-Weinberg equilibrium (HW) were detected. The PIC values for the P. ruscifolia markers ranged from 0.289 to 0.883, but a departure from HW and null alleles were detected for certain loci; however, this departure may have resulted from anthropic activities, such as the presence of livestock, which is very common in the remnant areas. In this study, we describe novel SSR polymorphic markers that may be helpful in future genetic studies of P. rubriflora and P. ruscifolia.

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Islet neogenesis-associated protein (INGAP) is a peptide found in pancreatic exocrine-, duct- and islet- non-β-cells from normal hamsters. Its increase induced by either its exogenous administration or by the overexpression of its gene enhances β-cell secretory function and increases β-cell mass by a combination of stimulation of cell replication and islet neogenesis and reduction of β-cell apoptosis. We studied the potential modulatory role of endogenous INGAP in insulin secretion using two different experimental approaches. Hamster islets transfected with INGAP-small interfering RNA (INGAP-siRNA) were used to study glucose-stimulated insulin secretion (GSIS). In parallel, freshly isolated islets were incubated with high glucose and the same concentration of either a specific anti-INGAP rabbit serum or normal rabbit serum. INGAP-siRNA transfected islets reduced their INGAP mRNA and protein content by 35.1% and 47.2%, respectively whereas GSIS decreased by 25.8%. GSIS by transfected islets attained levels comparable to those recorded in control islets when INGAP pentadecapeptide (INGAP-PP) was added to the culture medium. INGAP antibody in the medium decreased significantly GSIS in a dose-dependent manner. These results indicate that endogenous INGAP plays a physiological positive modulatory role in insulin secretion, supporting its possible use in the treatment of prediabetes and Type 2 diabetes.

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Taurine is a sulfur-containing amino acid that exerts protective effects on vascular function and structure in several models of cardiovascular diseases through its antioxidant and anti-inflammatory properties. Early protein malnutrition reprograms the cardiovascular system and is linked to hypertension in adulthood. This study assessed the effects of taurine supplementation in vascular alterations induced by protein restriction in post-weaning rats. Weaned male Wistar rats were fed normal- (12%, NP) or low-protein (6%, LP) diets for 90 days. Half of the NP and LP rats concomitantly received 2.5% taurine supplementation in the drinking water (NPT and LPT, respectively). LP rats showed elevated systolic, diastolic and mean arterial blood pressure versus NP rats; taurine supplementation partially prevented this increase. There was a reduced relaxation response to acetylcholine in isolated thoracic aortic rings from the LP group that was reversed by superoxide dismutase (SOD) or apocynin incubation. Protein expression of p47phox NADPH oxidase subunit was enhanced, whereas extracellular (EC)-SOD and endothelial nitric oxide synthase phosphorylation at Ser 1177 (p-eNOS) were reduced in aortas from LP rats. Furthermore, ROS production was enhanced while acetylcholine-induced NO release was reduced in aortas from the LP group. Taurine supplementation improved the relaxation response to acetylcholine and eNOS-derived NO production, increased EC-SOD and p-eNOS protein expression, as well as reduced ROS generation and p47phox expression in the aortas from LPT rats. LP rats showed an increased aortic wall/lumen ratio and taurine prevented this remodeling through a reduction in wall media thickness. Our data indicate a protective role of taurine supplementation on the high blood pressure, endothelial dysfunction and vascular remodeling induced by post-weaning protein restriction. The beneficial vascular effect of taurine was associated with restoration of vascular redox homeostasis and improvement of NO bioavailability.