Study of Venturia inaequalis sensitivity to fungicides through molecular and biological methodologies

This study was aimed to correlate the results of relative germination from in vitro tests by trifloxystrobin with those of qPCR on a wide range of V. inaequalis populations and monoconidial isolates. Samples were collected in Italian and Turkish distinct locations from orchards with different scab management. In this study, an allele-specific qPCR with primer sets designed was successfully developed to quantitatively determine the frequency of QoI-resistant allele G143A in populations and monoconidial isolates of V. inaequalis. qPCR followed a similar pattern to that obtained using in vitro conidial germination test in very sensitive and very resistant populations. However, the variability between two test results was observed in hetereogenous populations. Therefore, the results of correlations between in vitro and qPCR showed a positive but not very high correlation for Venturia inaequalis populations (R2=0.70). On the contrary, this correlation between two assessment methods was very high for monoconidial isolates (R2=0.92). Results obtained in quantitative PCR and from traditional spore germination assay differed for the same fungal population and in some cases, it is difficult to assess the resistance in the field by only qPCR. It was concluded that it is not always possible to correlate the frequency of detection of the mutation with biological assessment. In such situations, monitoring by molecular techniques must be supported by standard in vitro resistance assessments and observation of field performance in order to have correct conclusions.

Investigating the role of single point mutations in the human proteome: a computational study

In the post genomic era with the massive production of biological data the understanding of factors affecting protein stability is one of the most important and challenging tasks for highlighting the role of mutations in relation to human maladies. The problem is at the basis of what is referred to as molecular medicine with the underlying idea that pathologies can be detailed at a molecular level. To this purpose scientific efforts focus on characterising mutations that hamper protein functions and by these affect biological processes at the basis of cell physiology. New techniques have been developed with the aim of detailing single nucleotide polymorphisms (SNPs) at large in all the human chromosomes and by this information in specific databases are exponentially increasing. Eventually mutations that can be found at the DNA level, when occurring in transcribed regions may then lead to mutated proteins and this can be a serious medical problem, largely affecting the phenotype. Bioinformatics tools are urgently needed to cope with the flood of genomic data stored in database and in order to analyse the role of SNPs at the protein level. In principle several experimental and theoretical observations are suggesting that protein stability in the solvent-protein space is responsible of the correct protein functioning. Then mutations that are found disease related during DNA analysis are often assumed to perturb protein stability as well. However so far no extensive analysis at the proteome level has investigated whether this is the case. Also computationally methods have been developed to infer whether a mutation is disease related and independently whether it affects protein stability. Therefore whether the perturbation of protein stability is related to what it is routinely referred to as a disease is still a big question mark. In this work we have tried for the first time to explore the relation among mutations at the protein level and their relevance to diseases with a large-scale computational study of the data from different databases. To this aim in the first part of the thesis for each mutation type we have derived two probabilistic indices (for 141 out of 150 possible SNPs): the perturbing index (Pp), which indicates the probability that a given mutation effects protein stability considering all the “in vitro” thermodynamic data available and the disease index (Pd), which indicates the probability of a mutation to be disease related, given all the mutations that have been clinically associated so far. We find with a robust statistics that the two indexes correlate with the exception of all the mutations that are somatic cancer related. By this each mutation of the 150 can be coded by two values that allow a direct comparison with data base information. Furthermore we also implement computational methods that starting from the protein structure is suited to predict the effect of a mutation on protein stability and find that overpasses a set of other predictors performing the same task. The predictor is based on support vector machines and takes as input protein tertiary structures. We show that the predicted data well correlate with the data from the databases. All our efforts therefore add to the SNP annotation process and more importantly found the relationship among protein stability perturbation and the human variome leading to the diseasome.

Land use management in mountainous areas: combining ground-based and EO (Earth Observation) data to investigate the shallow landsliding susceptibility in the Duron valley (Trento, Italy).

Throughout the alpine domain, shallow landslides represent a serious geologic hazard, often causing severe damages to infrastructures, private properties, natural resources and in the most catastrophic events, threatening human lives. Landslides are a major factor of landscape evolution in mountainous and hilly regions and represent a critical issue for mountainous land management, since they cause loss of pastoral lands. In several alpine contexts, shallow landsliding distribution is strictly connected to the presence and condition of vegetation on the slopes. With the aid of high-resolution satellite images, it's possible to divide automatically the mountainous territory in land cover classes, which contribute with different magnitude to the stability of the slopes. The aim of this research is to combine EO (Earth Observation) land cover maps with ground-based measurements of the land cover properties. In order to achieve this goal, a new procedure has been developed to automatically detect grass mantle degradation patterns from satellite images. Moreover, innovative surveying techniques and instruments are tested to measure in situ the shear strength of grass mantle and the geomechanical and geotechnical properties of these alpine soils. Shallow landsliding distribution is assessed with the aid of physically based models, which use the EO-based map to distribute the resistance parameters across the landscape.

Light & Electron beam - the perfect combination for the observation and application of photo active materials

The aim of the present PhD thesis is to investigate the properties of innovative nanomaterials for energy conversion. The materials have been deeply studied by means of a wide spectrum of different techniques based on both light and electron sources, in order to get an insight into the correlation between the properties of each material and the activity towards different energy conversion applications. The activity has been carried out in the framework of a collaboration between the “G.Ciamician” Chemistry Department of the University of Bologna and the CNR-IMM Bologna. Four main topics have been explored: in the first part, luminescent silicon nanocrystals (SiNCs) have been discussed, suggesting a new approach to improve their optical properties as active material in complementary optoelectronic devices and photovoltaic cells. The luminescence of SiNCs have been exploited to increase the efficiency of conventional photovoltaic cells by means of an innovative architecture. Specifically, SiNCs were shown to be very promising light emitters in luminescent solar concentrators (LSC). The second part of the work has been focused on the study of high phosphorescent molecular chromophores, suggesting a new approach in their use as optical sensors successfully applied to the field of polymeric materials. This is due to the enhanced emission of light that appears in rigid, constrained or crystalline state, that is commonly called: "Aggregation-Induced Emission (AIE)". Such phenomenon is characteristic for molecular structures such as persulfurated benzene chromophores, hereafter named asterisks. The last two parts were focused on conventional and in-situ Transmission Electron Microscopy (TEM) morphological and structural characterization of photoactive and catalytic materials for energetic applications and in particular water splitting.

Gut microbiota perturbation induced by emerging dietary habits: an in vitro colon model to predict their effects by a microbiomic and metabolomic approach

Over the past 30 years, unhealthy diets and lifestyles have increased the incidence of noncommunicable diseases and are culprits of diffusion on world’s population of syndromes as obesity or other metabolic disorders, reaching pandemic proportions. In order to comply with such scenario, the food industry has tackled these challenges with different approaches, as the reformulation of foods, fortification of foods, substitution of ingredients and supplements with healthier ingredients, reduced animal protein, reduced fats and improved fibres applications. Although the technological quality of these emerging food products is known, the impact they have on the gut microbiota of consumers remains unclear. In the present PhD thesis, the recipient work was conducted to study different foods with the substitution of the industrial and market components to that of novel green oriented and sustainable ingredients. So far, this thesis included eight representative case studies of the most common substitutions/additions/fortifications in dairy, meat, and vegetable products. The products studied were: (i) a set of breads fortified with polyphenol-rich olive fiber, to replace synthetic antioxidant and preservatives, (ii) a set of Gluten-free breads fortified with algae powder, to fortify the protein content of standard GF products, (iii) different formulations of salami where nitrates were replaced by ascorbic acid and vegetal extract antioxidants and nitrate-reducers starter cultures, (iv) chocolate fiber plus D-Limonene food supplement, as a novel prebiotic formula, (v) hemp seed bran and its alkalase hydrolysate, to introduce as a supplement, (vi) milk with and without lactose, to evaluate the different impact on human colonic microbiota of healthy or lactose-intolerants, (vii) lactose-free whey fermented and/or with probiotics added, to be introduced as an alternative beverage, exploring its impact on human colonic microbiota from healthy or lactose-intolerants, and (viii) antibiotics, to assess whether maternal amoxicillin affects the colon microbiota of piglets.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.