Genetic diversity and introgression by AFLP analisys in Phaseolus vulgaris L.

Phaseolus vulgaris L. is an economically important species whose origin is in the America continent where domestication took place and diverged in Mesoamerican and Andean gene pools. After Columbus’s voyage common bean was introduced into the Iberian Peninsula from which this species spread into the European countries and around the world. In this study investigate the extent of diversity of European germplasm compared to the American germplasm and to define the level of introgression between the European Mesoamerican and Andean gene pools are investigated. 68 accessions representative of Mesoamerican and Andean American gene pools and 241 accessions from 24 different countries belonging to an European bean core collection were analysed for three morphologic quantitative (length, height and width ) and 4 qualitative (shape, lighter colour, darker colour and coat pattern of seed) seed characters and for 4 AFLP primer combinations: E-AGT/MGAC, E-AGT/M-GTA, E-ACC/M-AGA and E-ACC/M-ATG. A total of 138 polymorphic bands were scored among the 309 accessions analysed. The European and the Mesoamerican gene pools had a number of common and very common AFLP polymorphic bands higher than the American and the Andean gene pools. The European accessions moreover were used for Structure and cpSSR analysis to identify pure and introgressed lines. These groups were compared for morphological traits and AFLP profiles. Results showed significative differences among diverse groups for morphological traits and for AFLP band frequencies, even though the diversity index were the same (He = 0.23). Hypothesis of introgression among American and European, Mesoamerican and Andean gene pools are discussed

Introduction bottleneck and the contribute of Mesoamerican and Andean gene pools to common bean (Phaseolus vulgaris L.) diversity in Europe.

Common bean (Phaseolus vulgaris L., 2n = 2x = 22) is the most important edible food legume for direct human consumption in Europe and in the world as it represents a valuable source of proteins, vitamins, fibres, and minerals. Genetic and archaeological studies have shown that domestication of P. vulgaris was originated and domesticated in the New World and has two major gene pools, the Andean and the Mesoamerican, based on their centers of origin in South and Central America, respectively. After the first voyages of Columbus (1492) common bean was brought to Europe but historical and linguistic sources provide little evidence of the introduction and expansion of common bean in Europe. In common bean a large number of nuclear microsatellite markers (nuSSRs) have been already developed and mapped that show relatively high levels of polymorphism, thus providing an attractive choice for describing population structure. However, to the best of our knowledge, population studies of the European common bean, using nuSSRs, so far have been performed with only a small number of landraces or a small number of samples from a few geographic regions. In the present study, we used thirteen highly polymorphic nuSSRs to assess the genetic structure and level of diversity of a large collection of European landraces (256 individuals), in comparison with a representative American sample (89 individuals). Moreover, to obtain a detailed picture and to elucidate the effects of bottleneck of introduction and selection for adaptation during the expansion of common bean over the whole Europe, we also complemented the nuSSRs analysis by information provided by a Bayesian analysis implemented in STRUCTURE. Here, we present and discuss the role that inter-gene pool hybridization have had in shaping the genetic structure of the European bean landraces. The implication for evolution and the advantages for common bean breeding are also discussed

Shell evolution of stable N = 50-56 Zr and Mo nuclei with respect to low-lying octupole excitations

For the N = 50-56 zirconium (Z = 40) and molybdenum (Z = 42) isotopes, the evolution of subshells is evaluated by extracting the effective single-particle energies from available particle-transfer data. The extracted systematic evolution of neutron subshells and the systematics of the excitation energy of the octupole phonons provide evidence for type-II shape coexistence in the Zr isotopes. Employing a simplistic approach, the relative effective single-particle energies are used to estimate whether the formation of low-lying octupole-isovector excitations is possible at the proposed energies. The results raise doubts about this assignment

Artifact and Artifact Categorization: Comparing Humans and Capuchin Monkeys

International audienceWe aim to show that far-related primates like humans and the capuchin monkeys show interesting correspondences in terms of artifact characterization and categorization. We investigate this issue by using a philosophically-inspired definition of physical artifact which, developed for human artifacts, turns out to be applicable for cross-species comparison. In this approach an artifact is created when an entity is intentionally selected and some capacities attributed to it (often characterizing a purpose). Behavioral studies suggest that this notion of artifact is not specific to the human kind. On the basis of the results of a series of field observations and experiments on wild capuchin monkeys that routinely use stone hammers and anvils, we show that the notions of intentional selection and attributed capacity appear to be at play in capuchins as well. The study also suggests that functional criteria and contextualization play a fundamental role in terms of artifact recognition and categorization in nonhuman primates

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

Background: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. Materials and methods: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. Results: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. Conclusion: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice