24 resultados para IT function
Resumo:
The contribution of Clostridium difficile toxin A and B (TcdA and TcdB) to cellular intoxication has been extensively studied, but their impact on bacterial colonization remains unclear. By setting-up two- and three-dimensional in vitro models of polarized gut epithelium, we investigated how C. difficile infection is affected by host cell polarity and whether TcdA and TcdB contribute to such events. Indeed, we observed that C. difficile adhesion and penetration of the epithelial barrier is substantially enhanced in poorly polarized or EGTA-treated cells, indicating that bacteria bind preferentially to the basolateral cell surface. In this context, we demonstrated that sub-lethal concentrations of C. difficile TcdA are able to alter cell polarity by causing redistribution of plasma membrane components between distinct surface domains. Taken together, the data suggest that toxin-mediated modulation of host cell organization may account for the capacity of this opportunistic pathogen to gain access to basolateral receptors leading to a successful colonization of the colonic mucosa.
Resumo:
In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.
Resumo:
This thesis will focus on the residual function and visual and attentional deficits in human patients, which accompany damage to the visual cortex or its thalamic afferents, and plastic changes, which follow it. In particular, I will focus on homonymous visual field defects, which comprise a broad set of central disorders of vision. I will present experimental evidence that when the primary visual pathway is completely damaged, the only signal that can be implicitly processed via subcortical visual networks is fear. I will also present data showing that in a patient with relative deafferentation of visual cortex, changes in the spatial tuning and response gain of the contralesional and ipsilesional cortex are observed, which are accompanied by changes in functional connectivity with regions belonging to the dorsal attentional network and the default mode network. I will also discuss how cortical plasticity might be harnessed to improve recovery through novel treatments. Moreover, I will show how treatment interventions aimed at recruiting spared subcortical pathway supporting multisensory orienting can drive network level change.
Resumo:
Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.
Resumo:
Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.
Resumo:
A large fraction of organ transplant recipients develop anti-donor antibodies (DSA), with accelerated graft loss and increased mortality. We tested the hypothesis that erythropoietin (EPO) reduces DSA formation by inhibiting T follicular helper (TFH) cells. We measured DSA levels, splenic TFH, TFR cells, germinal center (GC), and class switched B cells, in murine models of allogeneic sensitization, allogeneic transplantation and in parent-to-F1 models of graft versus host disease (GVHD). We quantified the same cell subsets and specific antibodies, upon EPO or vehicle treatment, in wild type mice and animals lacking EPO receptor selectively on T or B cells, immunized with T-independent or T-dependent stimuli. In vitro, we tested the EPO effect on TFH induction. We isolated TFH and TFR cells to perform in vitro assay and clarify their role. EPO reduced DSA levels, GC, class switched B cells, and increased the TFR/TFH ratio in the heart transplanted mice and in two GVHD models. EPO did also reduce TFH and GC B cells in SRBC-immunized mice, while had no effect in TNP-AECM-FICOLL-immunized animals, indicating that EPO inhibits GC B cells by targeting TFH cells. EPO effects were absent in T cells EPOR conditional KO mice, confirming that EPO affects TFH in vivo through EPOR. In vitro, EPO affected TFH induction through an EPO-EPOR-STAT5-dependent pathway. Suppression assay demonstrated that the reduction of IgG antibodies was dependent on TFH cells, sustaining the central role of the subset in this EPO-mediated mechanism. In conclusion, EPO prevents DSA formation in mice through a direct suppression of TFH. Development of DSA is associated with high risk of graft rejection, giving our data a strong rationale for studies testing the hypothesis that EPO administration prevents their formation in organ transplant recipients. Our findings provide a foundation for testing EPO as a treatment of antibody mediated disease processes.
Resumo:
Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative condition. The aims of this study were to evaluate the association between sleep, the circadian system and autonomic function in a cohort of PSP patients. Methods: Patients with PSP diagnosed according to consensus criteria were recruited prospectively and retrospectively and performed the following tests: body core temperature (BcT), sleep-wake cycle, systolic and diastolic blood pressure (SBP, DBP) continuous monitoring for 48 h under controlled environmental conditions; cardiovascular reflex tests (CRTs). The analysis of circadian rhythmicity was performed with the single cosinor method. For state-dependent analysis, the mean value of variables in each sleep stage was calculated as well as the difference to the value in wake. Results: PSP patients presented a reduced total duration of night sleep, with frequent and prolonged awakenings. During daytime, patients had very short naps, suggesting a state of profound sleep deprivation across the 24-h. REM sleep behaviour disorder was found in 15%, restless legs syndrome in 46%, periodic limb movements in 52% and obstructive sleep apnea in 54%. BcT presented the expected fall during night-time, however, compared to controls, mean values during day and night were higher. However BcT state-dependent modulation was maintained. Increased BcT could be attributed to an inability to properly reduce sympathetic activity favoured by the sleep deprivation. At CRTs, PSP presented mild cardiovascular adrenergic impairment and preserved cardiovagal function. 14% had non-neurogenic orthostatic hypotension. Only 2 PSP presented the expected BP dipping pattern, possibly as a consequence of sleep disruption. State-dependent analysis showed a partial loss of the state-dependent modulation for SBP. Discussion: This study showed that PSP presented abnormalities of sleep, circadian rhythms and cardiovascular autonomic function that are likely to be closely linked one to another.
Resumo:
The role of non-neuronal brain cells, called astrocytes, is emerging as crucial in brain function and dysfunction, encompassing the neurocentric concept that was envisioning glia as passive components. Ion and water channels and calcium signalling, expressed in functional micro and nano domains, underpin astrocytes’ homeostatic function, synaptic transmission, neurovascular coupling acting either locally and globally. In this respect, a major issue arises on the mechanism through which astrocytes can control processes across scales. Finally, astrocytes can sense and react to extracellular stimuli such as chemical, physical, mechanical, electrical, photonic ones at the nanoscale. Given their emerging importance and their sensing properties, my PhD research program had the general goal to validate nanomaterials, interfaces and devices approaches that were developed ad-hoc to study astrocytes. The results achieved are reported in the form of collection of papers. Specifically, we demonstrated that i) electrospun nanofibers made of polycaprolactone and polyaniline conductive composites can shape primary astrocytes’ morphology, without affecting their function ii) gold coated silicon nanowires devices enable extracellular recording of unprecedented slow wave in primary differentiated astrocytes iii) colloidal hydrotalcites films allow to get insight in cell volume regulation process in differentiated astrocytes and to describe novel cytoskeletal actin dynamics iv) gold nanoclusters represent nanoprobe to trigger astrocytes structure and function v) nanopillars of photoexcitable organic polymer are potential tool to achieve nanoscale photostimulation of astrocytes. The results were achieved by a multidisciplinary team working with national and international collaborators that are listed and acknowledged in the text. Collectively, the results showed that astrocytes represent a novel opportunity and target for Nanoscience, and that Nanoglial interface might help to unveil clues on brain function or represent novel therapeutic approach to treat brain dysfunctions.
Resumo:
The arginine methyltransferase CARM1 (PRMT4) is amplified and overexpressed in ~20% of high-grade serous ovarian cancer (HGSOC) and correlates with a poor survival. Therapeutic approaches based on CARM1 expression remain to be an unmet need. Here we show that fatty acid metabolism represents a metabolic vulnerability for HGSOC in a CARM1 expression status dependent manner. CARM1 promotes the de novo synthesis of fatty acids and monounsaturated fatty acids (MUFAs). The disruption of MUFAs synthesis by inhibition of SCD1 results in excessive accumulation of cytotoxic saturated fatty acids and it is synthetic lethal with CARM1 expression. Collectively, our data show that the pharmacological inhibition of MUFAs synthesis via SCD1 inhibition represents a therapeutic strategy for CARM1-high HGSOC. Another arginine methyltransferase, PRMT5, has been identified by our CRISPR screening analysis as a promising candidate for invasive ARID1A-deficient endometrial cancer. Endometrial Cancer frequently harbor somatic inactivating mutation of ARID1A that can promote an invasive phenotype. Our in vitro approach validated the CRISPR screening showing that both PRTM5 knock down and its pharmaceutical inhibition specifically hamper the invasion of ARID1A inactivated cells. Mechanistically, PRMT5 directly regulates the epithelia to mesenchymal transition pathway genes interacting with the SWI/SNF complexes. Moreover, in vivo experiments showed that PRMT5 inhibition contrasted the myometrium invasion highlighting PRMT5 inhibition as promising therapeutic strategy for ARID1A- inactivated aggressive endometrial cancer.