Application of a virtual scientific experiment model in different educational contexts

E-learning practice is continuously using experimentation in order to enhance the basic information transfer model where knowledge is passed from the system/ tutors to the students. Boosting student productivity through on-line experimentation is not simple since many organizational, educational and technological issues need to be dealt with. This work describes the application of a Learning Model for Virtual Scientific Experiments (VSEs) in two different scenarios: Information and Communication Technologies and Physics. As part of the first, a VSE for Wireless Sensor Networks was specified and deployed while the second involved the specification and design of a collaborative VSE for physics experiments. Preliminary implementation and deployment results are also discussed

An Integrated Solution among Social, Personal and Formal Learning for Lifelong Competences

In the Knowledge Society the worker should benefit from learning experiences which intersect formal learning moments with both individual and collaborative informal learning, according to a vision of authentic lifelong edu-cation” The paper suggests an innovative answer to the “lifelong competence” management approach. In this context a Lifelong Learning Model (LLM) finds its realization through an integrated solution among the personal, social and formal learning. The vision is sustained by a conceptual architecture, which represents a distinctive and enabling factor for the management of competence allowing to customize training paths on the worker profile. The idea is related to the integration between a Personal Learning Environment (PLE), a learning community and the solution of the Polo di Eccellenza L&K, the learning plat-form IWT (Intelligent Web Teacher)

Personalization and Contextualization of Learning Experiences based on Semantics

Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e-learning content more relevant and suitable for the learner in his/her situation. The purpose of this paper is to demonstrate that an ontological approach can be used to define leaning contexts and to allow contextualizing learning experiences finding out relevant topics for each context. To do that, we defined a context model able to formally describe a learning context, an ontology-based model enabling the representation of a teaching domain (including context information) and a methodology to generate personalized and context-aware learning experiences starting from them. Based on these theoretical components we improved an existing system for personalized e-learning with contextualisation features and experimented it with real users in two University courses. The results obtained from this experimentation have been compared with those achieved by similar systems

Digital Storytelling and Mathematical Thinking: An Educational Psychology Embrace

This article proposes Digital Storytelling as an education model that combines science, narrative thinking and art. This model has been implemented in Italian school settings over recent years. After a short introduction of the theoretical foundations of narrative thinking in the history of Educational Psychology, the paper focuses on Digital Storytelling as a co-constructive educational method that uses digital technologies for promoting an active, situated, meaningful and reflexive learning process. The proposed intervention in the Italian settings adds the artistic digital component (the use of avatar, comics and science fiction) to the Digital Storytelling systems. The set of implemented activities, as well as the individual and group actions taken, promote both the cognitive and emotional aspects of the learning process. The findings show that Digital Storytelling, spiced with artistic features, prompts the engagement of students in learning activities and offers a platform to enhance behavioural, emotional and cognitive commitment in mathematics education

Molecular modeling of antibodies for the treatment of TNFα-related immunological diseases

Therapeutic monoclonal antibodies (mAbs) have high efficacy in treating TNF α-related immunological diseases. Other than neutralizing TNF α, these IgG1 antibodies exert Fc receptor-mediated effector functions such as the complement-dependent cytotoxicity (CDC) and antibody-dependent cell cytotoxicity (ADCC). The crystallizable fragment (Fc) of these IgG1 contains a single glycosylation site at Asn 297/300 that is essential for the CDC and ADCC. Glycosylated antibodies lacking core fucosylation showed an improved ADCC. However, no structural data are available concerning the ligand-binding interaction of these mAbs used in TNF α-related diseases and the role of the fucosylation. We therefore used comparative modeling for generating complete 3D mAb models that include the antigen-binding fragment (Fab) portions of infliximab, complexed with TNF α (4G3Y.pdb), the Fc region of the human IGHG1 fucosylated (3SGJ) and afucosylated (3SGK) complexed with the Fc receptor subtype Fcγ RIIIA, and the Fc region of a murine immunoglobulin (1IGT). After few thousand steps of energy minimization on the resulting 3D mAb models, minimized final models were used to quantify interactions occurring between Fcγ RIIIA and the fucosylated/afucosylated Fc fragments. While fucosylation does not affect Fab-TNF α interactions, we found that in the absence of fucosylation the Fc-mAb domain and Fcγ RIIIA are closer and new strong interactions are established between G129 of the receptor and S301 of the Chimera 2 Fc mAb; new polar interactions are also established between the Chimera 2 Fc residues Y299, N300, and S301 and the Fcγ RIIIA residues K128, G129, R130, and R155. These data help to explain the reduced ADCC observed in the fucosylated mAbs suggesting the specific AA residues involved in binding interactions

Efficacy of nilotinib therapy in patient with CML diagnosed in pre-TKI era and resistant to imatinib

Here we report a case of a 32-year-old man, who was diagnosed as having chronic myeloid leukaemia in 1998. After cytoreduction with hydroxyurea, the patient was submitted to high dose chemotherapy with haemopoietic stem cells rescue and reinfusion, and then he started therapy with IFNα without achievement of a cytogenetic response. On November 2000 he took imatinib 400 mg/day and he reached a complete cytogenetic response (CCyR) at 14 months, but not the major molecular response: therefore he was considered a sub-optimal responder according to European LeukemiaNet criteria of 2006. For this reason he increased imatinib dose to 800 mg/day, but after one year he lost CCyR. Considering the patient as a failure, at this time, he switched to second-generation tyrosine kinase inhibitor, nilotinib at the dose of 800 mg/day. After 3 months he reached complete CCyR and after 6 months the major molecular response, maintained until last molecular evaluation

Modeling SARS-CoV-2 spike/ACE2 protein–protein interactions for predicting the binding affinity of new spike variants for ACE2, and novel ACE2 structurally related human protein targets, for COVID-19 handling in the 3PM context

Aims The rapid spread of new SARS-CoV-2 variants has highlighted the crucial role played in the infection by mutations occurring at the SARS-CoV-2 spike receptor binding domain (RBD) in the interactions with the human ACE2 receptor. In this context, it urgently needs to develop new rapid tools for quickly predicting the affinity of ACE2 for the SARS-CoV-2 spike RBD protein variants to be used with the ongoing SARS-CoV-2 genomic sequencing activities in the clinics, aiming to gain clues about the transmissibility and virulence of new variants, to prevent new outbreaks and to quickly estimate the severity of the disease in the context of the 3PM. Methods In our study, we used a computational pipeline for calculating the interaction energies at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface for a selected group of characterized infectious variants of concern/interest (VoC/ VoI). By using our pipeline, we built 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for the VoC B.1.1.7-United Kingdom (carrying the mutations of concern/interest N501Y, S494P, E484K at the RBD), P.1- Japan/Brazil (RBD mutations: K417T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 (RBD mutations: N439K), and the recent B.1.617.1- India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Then, we used the obtained 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for predicting the interaction energies at the protein–protein interface. Results Along SARS-CoV-2 mutation database screening and mutation localization analysis, it was ascertained that the most dangerous mutations at VoC/VoI spike proteins are located mainly at three regions of the SARS-CoV-2 spike “boat-shaped” receptor binding motif, on the RBD domain. Notably, the P.1 Japan/Brazil variant present three mutations, K417T, E484K, N501Y, located along the entire receptor binding motif, which apparently determines the highest interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, among those calculated. Conversely, it was also observed that the replacement of a single acidic/hydrophilic residue with a basic residue (E484K or N439K) at the “stern” or “bow” regions, of the boat-shaped receptor binding motif on the RBD, appears to determine an interaction energy with ACE2 receptor higher than that observed with single mutations occurring at the “hull” region or with other multiple mutants. In addition, our pipeline allowed searching for ACE2 structurally related proteins, i.e., THOP1 and NLN, which deserve to be investigated for their possible involvement in interactions with the SARS-CoV-2 spike protein, in those tissues showing a low expression of ACE2, or as a novel receptor for future spike variants. A freely available web-tool for the in silico calculation of the interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, starting from the sequences of the investigated spike and/or ACE2 variants, was made available for the scientific community at: https:// www. mitoa irm. it/ covid 19aff​initi es. Conclusion In the context of the PPPM/3PM, the employment of the described pipeline through the provided webservice, together with the ongoing SARS-CoV-2 genomic sequencing, would help to predict the transmissibility of new variants sequenced from future patients, depending on SARS-CoV-2 genomic sequencing activities and on the specific amino acid replacement and/or on its location on the SARS-CoV-2 spike RBD, to put in play all the possible counteractions for preventing the most deleterious scenarios of new outbreaks, taking into consideration that a greater transmissibility has not to be necessarily related to a more severe manifestation of the disease

A Cultural Re-mediation Model for Storytelling in Pre-school Education

The use of the emotional language of stories and the amplification of the empathic driver thanks to the identification with story characters, makes the storytelling a valuable educational approach, especially for children. In accordance with embodied and situated cognition theories, manipulative storytelling proposes interactive environments where it is also possible for learners to manipulate the story through objects and tangible interfaces. In line with this vision, we propose in this paper a new model enabling the design and the execution of educational stories for children aged from 3 to 6. Stories are seen as sequences of missions: game experiences where children can interact to reach the educational objective. A re-mediation strategy, able to adapt the story on three different axis (immediacy-hypermediation, similarity-dissimilarity and aggregation-disaggregation) on the basis of assessment results, is also presented. A proof of concept based on the popular Brother Grimm's Hansel and Gretel tale is then discussed to demonstrate the capabilities of the model in the construction and deconstruction of the building blocks of a story

Urban expansion and forest reserves: Drivers of change and persistence on the coast of São Paulo State (Brazil)

Landscapes changes are a result of a wide range of interactions between actors and driving forces (DFs). In this study, we quantify the contribution of different types of DFs to processes of land change in the Northern Coast of São Paulo State (NCSP), Brazil, an important region for tourism and the energy sector. We analysed the relationship between DFs and the processes of land change from 1985 to 2000 and from 2000 to 2015 with partial least squares path modelling. The political and technological DFs were the most important groups of drivers for explaining the observed processes, especially the most dominant ones: policies on land use and environment (political DF), distances to the main transportation infrastructure (technological DF), and the presence of steep slopes in Serra do Mar (natural DF) influenced forest persistence and were also determinants for urban settlement distribution. The State Parks and the zones for nature conservation (political DF) were important for the maintenance of forest cover and overall the importance of political DF increased after 2000. In general, the DFs in NCSP were similar to those observed in other coastal and tourist regions, but surprisingly, despite a rapid population increase, demography did not explain urban and peri-urban growth. Urban growth was happening foremost in the zones for urban development and was accompanied by increases in water provision services and waste collection, whereas peri-urban sprawl was concentrated in conservation and agricultural zones, without investments in basic services. We conclude that an increasing demand for housing must be considered in future policies in NCSP, instead of solely focussing on economic interests in tourism and the energy sectors