Extended-spectrum β-lactamase-producing Escherichia coli from extraintestinal infections in humans and from food-producing animals in Italy: a 'One Health' study

In recent years, Escherichia coli producing extended spectrum beta-lactamases (ESBL) have become a serious public health problem and food-producing animals (FPA) have been suggested as a potential reservoir/source. In this study, we aimed to compare ESBL-producing E. coli isolates from different sources. ESBL-producing E. coli isolates were collected from humans (n=480) and FPA (n=445) in Italy (2016-2017). Isolates were screened for the presence of ESBL and carbapenemase genes and classified according to phylogenetic group and MLST genotyping. mcr-1 to -5 genes were searched for in colistin resistant isolates. CTX-M was the most frequent ESBL-type in both human and animal isolates. CTX-M-15 prevailed in humans (75%) and cattle (51.1%) but not in poultry (36.6%). CTX-M-1 was common (58%) in pigs. SHV-type and CMY-2-like were found in FPA, especially in poultry (17.0% and 29.9%, respectively). 29 isolates were mcr-1 carriers (3 from humans and 26 from FPA). No carbapenemase genes were detected. Human isolates mostly belonged to phylogroup B2 (76.5%). Animal isolates were distributed among groups A (35.7%), B1 (26.1%) and C (12.4%). Few animal isolates (almost all from poultry) were classified into group B2 (4.3%). Most human isolates (83.4%) belonged to the pandemic ST131 clone and frequently carried CTX-M-15 (75.9%). ST131 was rarely detected in FPA (n=3 isolates from poultry). Nineteen STs were shared in both sources with ST10, ST410 and ST69 being more frequently detected. According to our results the potential exchange of ESBL genes from animals to humans is feasible, underlying the need for a strict monitoring based on an "One Health" approach

Desmoglein 1 in ovine muzzle skin detected by immunohistochemistryand immunoblotting

SUMMARY Desmosomes are epithelial adhesion structures that assure the mechanical cell-cell adhesion, by linking the intermediate filaments of two adjacent cells. Several proteins have been characterised as component of these structures and, among them, desmogleins are known to be the autoantigens in some autoimmune diseases that go by the name of pemphigus complex diseases. In particular Desmoglein 1 is the targeted antigen in Pemphigus foliaceus. This study aims at revealing the presence of Desmoglein 1 in the ovine muzzle skin using a commercial monoclonal antibody, raised against human desmoglein-1, on samples obtained from sheep muzzle. Immunohistochemical analyses (streptavidin-peroxidase method) and immunoblotting analyses (chemiluminescence method) have been performed. Immunohistochemical evaluation allowed for detection of a pericellular staining of keratinocyte cell membranes in the spinous and the basal layers of epidermis. A positive immunoreaction was obtained when the anti-Dsg-1 antibody was reacted with human cheek epidermis used as positive control. Specificity of the immune reaction was confirmed by the lack of staining in samples incubated with the anti-vimentin antibody used as negative control. Densitometric analyses of the chemiluminescence film showed three bands. One of them could be referred to Desmoglein 1, the second one to Desmoglein 3 and the last one to a Desmoglein-Plakoglobin complex. RIASSUNTO I desmosomi sono strutture di adesione tipiche dei tessuti epiteliali che connettono i filamenti intermedi del citoscheletro di due cellule adiacenti, assicurando la loro adesione meccanica. Tra le proteine che compongono queste strutture, le desmogleine sono note come antigene target in alcune malattie autoimmuni riunite sotto il nome di malattie del complesso del pemfigo. La desmogleina 1, in particolare, si comporta da auto antigene nel pemfigo foliaceo. Lo scopo della presente ricerca è stato quello di mettere in evidenza questa proteina su campioni di cute prelevate da musello di pecora con l’utilizzo di un anticorpo monoclonale indotto contro la desmogleina 1 dell’uomo. Su di essi sono state condotte indagini immunoistochimiche (metodo streptavidina-perossidasi) e di immunoblotting (metodo della chemiluminescenza). L’indagine immunoistochimica ha rilevato una distribuzione della proteina uniforme e pericellulare negli strati basale e spinoso dell’epidermide. La reazione positiva si è ottenuta anche su cute di guancia di uomo usata come controllo positivo. La specificità del test è stata confermata dall’assenza di positività in campioni incubati con un anticorpo antivimentina, utilizzato come controllo negativo. L’indagine di immunoblotting ha evidenziato tre bande di cui una potrebbe corrispondere alla desmogleina 1, la seconda alla desmogleina 3 e la terza ad un complesso Desmogleina-Placoglobina

From Knowledge Management to Knowledge Augmentation: Boosting Effectiveness and Efficiency in Managing Digital Transformation through Data

Sommario L'ascesa di Industria 4.0 e della Data Science ha portato a un crescente interesse delle aziende nel raccogliere, immagazzinare e analizzare grandi quantità di dati sia strutturati che non strutturati. A causa della complessità dei dati, della loro eterogeneità, della loro scarsa strutturazione, le aziende che cercano di catturare conoscenza da essi dovrebbero affrontare una sfida di Knowledge Capture/Extraction e Management. Gli strumenti classici non sono più sufficienti: questa tesi mira a sviluppare strumenti e metodi accessibili per aumentare l'efficienza e l'efficacia dei processi, supportando così le industrie nella transizione verso la nuova Industria 4.0. Per raggiungere questo obiettivo, ho raccolto e analizzato dati appartenenti a diverse funzioni aziendali, in modo da trattare dati di diverso tipo e con impatto su diversi stakeholder. Questa tesi ha portato allo sviluppo e all'applicazione di diversi strumenti e metodologie: - uno strumento per la gestione delle risorse umane per misurare l'impatto di Industria 4.0 sul lavoro profili di lavoro dell'azienda Whirlpool è stato sviluppato; - un metodo per mappare automaticamente l'uso dei dati nella progettazione ingegneristica; - uno strumento per la funzione acquisti per estrarre i requisiti dai documenti di acquisto dell'azienda AnsaldoBreda S.p.A; - una metodologia per estrarre concetti rilevanti per la manutenzione dai manuali di manutenzione dell'azienda BOBST SA; - uno strumento di misurazione applicato sperimentalmente sia per la misurazione di tempi e metodi nelle Operations che per la costruzione automatica di Spaghetti Charts nella logistica interna. I risultati ottenuti in questo lavoro sono promettenti e mostrano il potenziale delle metodologie e degli strumenti data-driven per le aziende per affrontare la Digital Transformation. Summary The rise of Industry 4.0 and Data Science led to a growing interest of companies in collecting, storing and analyzing vast amount of both structured and unstructured data. Due to the complexity of data, its heterogeneity, its poor structuring, companies trying to catch knowledge from them should face a Knowledge Capture/Extraction and Management challenge. Classic tools are no longer enough: this thesis aims to develop affordable tools and methods for boosting process efficiency and efficacy, thus supporting industries in the transition to the new Industry 4.0. To achieve this goal, I collect and analyze data belonging to different business functions, so to deal with data of different types and impacting on different stakeholders. This thesis led to the development and application of several tools and methodologies: - a tool for Human Resources Management to measure the Industry 4.0 impact on the job profiles of Whirlpool company has been developed; - a method to automatically map the use of data in Engineering Design; - a tool for the purchasing function to extract requirements from the purchasing documents of AnsaldoBreda S.p.A. company; - a methodology to extract maintenance-relevant concepts from the maintenance manuals of BOBST SA company; - a measurement tool experimentally applied both for the measurement of time and methods in operations and for the automatic construction of Spaghetti Charts in internal logistics. The results achieved in this work are promising and show the potential of data-driven methodologies and tools for companies to face the Digital Transformation

Concurrent Data Mining techniques for Discovering 4.0 Skills and Jobs

Industry 4.0 is defined as a trend of automation and data exchange based on the use of new technologies and their interconnections. While rapid and epochal changes are taking place, the issue of skills and job profiles assumes, for sure, a critical role. The literature highlights not only the necessary integration of new skills in existing professional profiles, but also the inevitable creation of new ones. The state of the art, however, tends to offer qualitative approaches to the topic, making the results uncertain; this research proposes a quantitative data driven approach. In order to formulate the new 4.0 job profiles, a bottom-up methodology was designed: using Wikipedia as data source and starting from the expression “Industry 4.0”, through the reiteration of expansion-cleaning processes, a set of 4.0 technologies was drawn up. Therefore, these were clustered and associated to Porter’s business functions, in order to identify the new 4.0 Workers. In order to define the resilient job profiles, those who will be directly affected by a competences integration without being penalised by the change, a top-down approach was applied. Starting from different heterogeneous data sources, a dictionary of skills was built and their ”4.0 level” quantified. Once the stronger 4.0 skills were identified, a process of matching on O*NET allowed a first approximation of the most impacted job profiles, and, in complementarity, those that will probably disappear. The data-driven approach and the achieved results make us confident in methodology improvement, through the integration with new data sources. L’Industria 4.0 è definita come un trend di automazione e scambio di dati basato sull'uso di nuove tecnologie e delle loro interconnessioni. Di fronte a questo rapido ed epocale cambiamento, il tema delle competenze e dei profili professionali assume, per certo, un ruolo critico. Nella letteratura si evidenzia non solo la necessaria integrazione di nuove competenze nei profili professionali esistenti, ma anche l’inevitabile creazione di nuovi. Lo stato dell'arte però offre tendenzialmente approcci qualitativi al topic, rendendo i risultati incerti; questa ricerca propone invece un approccio quantitativo data-driven. Per la formulazione dei nuovi profili professionali 4.0, è stata disegnata una metodologia bottom-up: utilizzando Wikipedia come fonte e partendo dall'espressione "Industria 4.0”, mediante la reiterazione di processi di espansione-pulizia, è stata stilata una lista di tecnologie 4.0. Queste sono state poi clusterizzate e associate alle funzioni aziendali di Porter, per individuare i nuovi Workers 4.0. Per definire invece i profili professionali resilienti, ovvero coloro i quali subiranno una integrazione di competenze, ma che non verranno penalizzati dal cambiamento, è stato applicato un approccio top-down: partendo fonti eterogenee, è stato costruito un dizionario di competenze delle quali è stato quantificato il "livello 4.0". Una volta identificate quelle più spiccatamente 4.0, un processo di matching sulle skill di O*NET ha consentito di avere una prima approssimazione dei profili professionali maggiormente impattati e, complementariamente, quelli che con più probabilità scompariranno. L’approccio data-driven e i risultati raggiunti ci rendono confidenti nel miglioramento della metodologia, attraverso l'integrazione con nuove fonti di dati

CULTURAL AND CREATIVE INDUSTRIES IMPACT CANVAS

The Impact Canvas and the visualised guidelines to fill out the impact canvas are outcomes of the research project Me-Mind. The aim of these visual materials is to support the self-assessment of cultural and creative organisations to understand their potential impact and to identify the necessary data to measure the impact of a cultural and creative industry organisation

Towards Automatic building of Human-Machine Conversational System to support Maintenance Processes

Companies are dealing with many cognitive changes with the introduction of the Industry 4.0 paradigm. In this constantly changing environment, knowledge management is a key factor. Dialog systems, being able to hold a conversation with humans, could support the knowledge management in business environment. Although, these systems are currently hand-coded and need the intervention of a human being in writing all the possible questions and answers, and then planning the interactions. This process, besides being time-consuming, is not scalable. Conversely, a dialog system, also referred to as chatbot, can be built from scratch by simply extracting rules from technical documentation. So, the goal of this research is designing a methodology for automatic building of human-machine conversational system, able to interact in an industrial environment. An initial taxonomy, containing entities expected to be found in maintenance manuals, is used to identify the relevant sentences of a manual provided by the company BOBST SA and applying text mining techniques, it is automatically expanded. The final result is a taxonomy network representing the entities and their relation, that will be used in future works for managing the interactions of a maintenance chatbot