Developing a molecular identification assay of old landraces for the genetic authentication of typical agro-food products: The case study of the barley 'Agordino'

The orzo Agordino is a very old local variety of domesticated barley (Hordeum vulgare ssp. distichum L.) that is native to the Agordo District, Province of Belluno, and is widespread in the Veneto Region, Italy. Seeds of this landrace are widely used for the preparation of very famous dishes of the dolomitic culinary tradition such as barley soup, bakery products and local beer. Understanding the genetic diversity and identity of the Agordino barley landrace is a key step to establish conservation and valorisation strategies of this local variety and also to provide molecular traceability tools useful to ascertain the authenticity of its derivatives. The gene pool of the Agordino barley landrace was reconstructed using 60 phenotypically representative individual plants and its genotypic relationships with commercial varieties were investigated using 21 pure lines widely cultivated in the Veneto Region. For genomic DNA analysis, following an initial screening of 14 mapped microsatellite (SSR) loci, seven discriminant markers were selected on the basis of their genomic position across linkage groups and polymorphic marker alleles per locus. The genetic identity of the local barley landrace was determined by analysing all SSR markers in a single multi-locus PCR assay. Extent of genotypic variation within the Agordino barley landrace and the genotypic differentiation between the landrace individuals and the commercial varieties was determined. Then, as few as four highly informative SSR loci were selected and used to develop a molecular traceability system exploitable to verify the genetic authenticity of food products deriving from the Agordino landrace. This genetic authentication assay was validated using both DNA pools from individual Agordino barley plants and DNA samples from Agordino barley food products. On the whole, our data support the usefulness and robustness of this DNA-based diagnostic tool for the orzo Agordino identification, which could be rapidly and efficiently exploited to guarantee the authenticity of local varieties and the typicality of food products

Cloud and mobile infrastructure monitoring for latency and bandwidth sensitive applications

This PhD thesis involves the study of cloud computing infrastructures (from the networking perspective) to assess the feasibility of applications gaining increasing popularity over recent years, including multimedia and telemedicine applications, demanding low, bounded latency and sufficient bandwidth. I also focus on the case of telemedicine, where remote imaging applications (for example, telepathology or telesurgery) need to achieve a low and stable latency for the remote transmission of images, and also for the remote control of such equipment. Another important use case for telemedicine is denoted as remote computation, which involves the offloading of image processing to help diagnosis; also in this case, bandwidth and latency requirements should be enforced to ensure timely results, although they are less strict compared to the previous scenario. Nowadays, the capability of gaining access to IT resources in a rapid and on-demand fashion, according to a pay-as-you-go model, has made the cloud computing a key-enabler for innovative multimedia and telemedicine services. However, the partial obscurity of cloud performance, and also security concerns are still hindering the adoption of cloud infrastructure. To ensure that the requirements of applications running on the cloud are satisfied, there is the need to design and evaluate proper methodologies, according to the metric of interest. Moreover, some kinds of applications have specific requirements that cannot be satisfied by the current cloud infrastructure. In particular, since the cloud computing involves communication to remote servers, two problems arise: firstly, the core network infrastructure can be overloaded, considering the massive amount of data that has to flow through it to allow clients to reach the datacenters; secondly, the latency resulting from this remote interaction between clients and servers is increased. For these, and many other cases also beyond the field of telemedicine, the Edge and Fog computing paradigms were introduced. In these new paradigms, the IT resources are deployed not only in the core cloud datacenters, but also at the edge of the network, either in the telecom operator access network or even leveraging other users' devices. The proximity of resources to end-users allows to alleviate the burden on the core network and at the same time to reduce latency towards users. Indeed, the latency from users to remote cloud datacenters encompasses delays from the access and core networks, as well as the intra-datacenter delay. Therefore, this latency is expected to be higher than that required to interconnect users to edge servers, which in the envisioned paradigm are deployed in the access network, that is, nearby final users. Therefore, the edge latency is expected to be reduced to only a portion of the overall cloud delay. Moreover, the edge and central resources can be used in conjunction, and therefore attention to core cloud monitoring is of capital importance even when edge architectures will have a widespread adoption, which is not the case yet. While a lot of research work has been presented for monitoring several network-related metrics, such as bandwidth, latency, jitter and packet loss, less attention was given to the monitoring of latency in cloud and edge cloud infrastructures. In detail, while some works target cloud-latency monitoring, the evaluation is lacking a fine-grained analysis of latency considering spatial and temporal trends. Furthermore, the widespread adoption of mobile devices, and the Internet of Things paradigm further accelerate the shift towards the cloud paradigm for the additional benefits it can provide in this context, allowing energy savings and augmenting the computation capabilities of these devices, creating a new scenario denoted as mobile cloud. This scenario poses additional challenges for its bandwidth constraints, accentuating the need for tailored methodologies that can ensure that the crucial requirements of the aforementioned applications can be met by the current infrastructure. In this sense, there is still a gap of works monitoring bandwidth-related metrics in mobile networks, especially when performing in-the-wild assessment targeting actual mobile networks and operators. Moreover, even the few works testing real scenarios typically consider only one provider in one country for a limited period of time, lacking an in-depth assessment of bandwidth variability over space and time. In this thesis, I therefore consider monitoring methodologies for challenging scenarios, focusing on latency perceived by customers of public cloud providers, and bandwidth in mobile broadband networks. Indeed, as described, achieving low latency is a critical requirement for core cloud infrastructures, while providing enough bandwidth is still challenging in mobile networks compared to wired settings, even with the adoption of 4G mobile broadband networks, expecting to overcome this issue only with the widespread availability of 5G connections (with half of total traffic expected to come from 5G networks by 2026). Therefore, in the research activities carried on during my PhD, I focused on monitoring latency and bandwidth on cloud and mobile infrastructures, assessing to which extent the current public cloud infrastructure and mobile network make multimedia and telemedicine applications (as well as others having similar requirements) feasible

On the calibration measurement of stripline beam position monitor for the ELI-NP facility

Stripline Beam Position Monitor (BPM) will be installed in the Compton Gamma Source in construction at the ELI Nuclear Physics facility in Romania. A test bench for the calibration of BPM has been built to characterize the device with stretched wire measurement in order to get the BPM response map. A full S-parameters characterization is performed as well to measure the electrical offset with the “Lambertson method”. This paper discusses the extensive simulations performed with full 3D electromagnetic CAD codes of the above measurements to investigate measurement accuracy, possible measurement artefacts and beam position reconstruction

Critical Aspects on the Use of Microsatellite Markers for Assessing Genetic Identity of Crop Plant Varieties and Authenticity of their Food Derivatives

A total of 90 original articles concerning the varietal characterization and identification by means of SSR analysis of the five most economically relevant crops in Italy (i.e., Olea europaea L., Solanum lycopersicum L., Vitis vinifera L., Triticum spp. and Malus × domestica Borkh.) have been selected and reviewed. Since the genetic traceability of processed products may result more complex, wine and olive oil have been considered too. Specifically, this chapter deals with three main aspects: (i) the criteria adopted for the selection of the most appropriate number, type, and distribution of SSR marker loci to be employed for varietal genotyping, (ii) the use of genetic statistics and parameters for the evaluation of the discriminant ability and applicability of SSR marker loci, and (iii) how to make different experimental works on the same species that are standardized, reliable, and comparable. What emerges from the studies reviewed here is a lack of wider consensus among the authors regarding the strategy to design and to adopt for genotyping plant varieties with SSR markers. This finding highlights the urgent need to establish a common procedure, especially for characterizing and preserving landraces, and for supporting its rediscovery and valorization locally

Venetian local corn (Zea mays L.) germplasm: Disclosing the genetic anatomy of old landraces suited for typical cornmeal mush production.

Due to growing concern for the genetic erosion of local varieties, four of the main corn landraces historically grown in Veneto (Italy) \u2014 Sponcio, Marano, Biancoperla and Rosso Piave \u2014 were characterized in this work. A total of 197 phenotypically representative plants collected from field populations were genotyped at 10 SSR marker loci, which were regularly distributed across the 10 genetic linkage groups and were previously characterized for high polymorphism information content (PIC), on average equal to 0.5. The population structure analysis based on this marker set revealed that 144 individuals could be assigned with strong ancestry association (>90%) to four distinct clusters, corresponding to the landraces used in this study. The remaining 53 individuals, mainly from Sponcio and Marano, showed admixed ancestry. Among all possible pairwise comparisons of individual plants, these two landraces exhibited the highest mean genetic similarity (approximately 67%), as graphically confirmed through ordination analyses based on PCoA centroids and UPGMA trees. Our findings support the hypothesis of direct gene flow between Sponcio and Marano, likely promoted by the geographical proximity of these two landraces and their overlapping cultivation areas. Conversely, consistent with its production mainly confined to the eastern area of the region, Rosso Piave scored the lowest genetic similarity (<59%) to the other three landraces and firmly grouped (with average membership of 89%) in a separate cluster, forming a molecularly distinguishable gene pool. The elite inbred B73 used as tester line scored very low estimates of genetic similarity (on average <45%) with all the landraces. Finally, although Biancoperla was represented at K = 4 by a single subgroup with individual memberships higher than 80% in almost all cases (57 of 62), when analyzed with an additional level of population structure for K = 6, it appeared to be entirely (100%) constituted by individuals with admixed ancestry. This suggests that the current population could be the result of repeated hybridization events between the two accessions currently bred in Veneto. The genetic characterization of these heritage landraces should prove very useful for monitoring and preventing further genetic erosion and genetic introgression, thus preserving their gene pools, phenotypic identities and qualitative traits for the future

Development of molecular markers for breeding hybrid varieties and their genetic traceability in fennel (Foeniculum vulgare L.)

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Toxic Tau Oligomers Modulated by Novel Curcumin Derivatives

The pathological aggregation and accumulation of tau, a microtubule-associated protein, is a common feature amongst more than 18 different neurodegenerative diseases that are collectively known as tauopathies. Recently, it has been demonstrated that the soluble and hydrophobic tau oligomers are highly toxic in vitro due to their capacity towards seeding tau misfolding, thereby propagating the tau pathology seen across different neurodegenerative diseases. Modulating the aggregation state of tau oligomers through the use of small molecules could be a useful therapeutic strategy to target their toxicity, regardless of other factors involved in their formation. In this study, we screened and tested a small library of newly synthesized curcumin derivatives against preformed recombinant tau oligomers. Our results show that the curcumin derivatives affect and modulate the tau oligomer aggregation pathways, converting to a more aggregated non-toxic state as assessed in the human neuroblastoma SH-SY5Y cell line and primary cortical neuron cultures. These results provide insight into tau aggregation and may become a basis for the discovery of new therapeutic agents, as well as advance the diagnostic field for the detection of toxic tau oligomers

The Molecular Determination of Hybridity and Homozygosity Estimates in Breeding Populations of Lettuce (Lactuca sativa L.)

The development of new varieties of horticultural crops bene\ufb01ts from the integration of conventional and molecular marker-assisted breeding schemes in order to combine phenotyping and genotyping information. In this study, a selected panel of 16 microsatellite markers were used in di\ufb00erent steps of a breeding programme of lettuce (Lactuca sativa L., 2 n = 18). Molecular markers were \ufb01rst used to genotype 71 putative parental lines and to plan 89 controlled crosses designed to maximiserecombinationpotentials. Theresulting871progenyplantswerethenmolecularlyscreened, and their marker allele pro\ufb01les were compared with the pro\ufb01les expected based on the parental lines. Theaveragecross-pollinationsuccessratewas68\ub133%,so602F1hybridswerecompletelyidenti\ufb01ed. Unexpected genotypes were detected in 5% of cases, consistent with this species\u2019 spontaneous out-pollination rate. Finally, in a later step of the breeding programme, 47 di\ufb00erent F3 progenies, selected by phenotyping for a number of morphological descriptors, were characterised in terms of their observed homozygosity and within-population genetic uniformity and stability. Ten of these populations had a median homozygosity above 90% and a median genetic similarity above 95% and are, therefore, particularly suitable for pre-commercial trials. In conclusion, this study shows the synergistic e\ufb00ects and advantages of conventional and molecular methods of selection applied in di\ufb00erent steps of a breeding programme aimed at developing new varieties of lettuce