Identification of surface protein complexes of Streptococcus pyogenes through protein microarray technology

A systematic characterization of the composition and structure of the bacterial cell-surface proteome and its complexes can provide an invaluable tool for its comprehensive understanding. The knowledge of protein complexes composition and structure could offer new, more effective targets for a more specific and consequently effective immune response against a complex instead of a single protein. Large-scale protein-protein interaction screens are the first step towards the identification of complexes and their attribution to specific pathways. Currently, several methods exist for identifying protein interactions and protein microarrays provide the most appealing alternative to existing techniques for a high throughput screening of protein-protein interactions in vitro under reasonably straightforward conditions. In this study approximately 100 proteins of Group A Streptococcus (GAS) predicted to be secreted or surface exposed by genomic and proteomic approaches were purified in a His-tagged form and used to generate protein microarrays on nitrocellulose-coated slides. To identify protein-protein interactions each purified protein was then labeled with biotin, hybridized to the microarray and interactions were detected with Cy3-labelled streptavidin. Only reciprocal interactions, i. e. binding of the same two interactors irrespective of which of the two partners is in solid-phase or in solution, were taken as bona fide protein-protein interactions. Using this approach, we have identified 20 interactors of one of the potent toxins secreted by GAS and known as superantigens. Several of these interactors belong to the molecular chaperone or protein folding catalyst families and presumably are involved in the secretion and folding of the superantigen. In addition, a very interesting interaction was found between the superantigen and the substrate binding subunit of a well characterized ABC transporter. This finding opens a new perspective on the current understanding of how superantigens are modified by the bacterial cell in order to become major players in causing disease.

Glycomics as an innovative technology to identify biomarkers of aging

Introduction. Glycomic analysis allows investigating on the global glycome within body fluids (as serum/plasma), this could eventually lead to identify new types of disease biomarkers, or as in this study, biomarkers of human aging studying specific aging models. Recent studies demonstrated that the plasma N-glycome is modified during human aging, suggesting that measurements of log-ratio of two serum/plasma N-glycans (NGA2F and NA2F), named GlycoAge test could provide a non-invasive biomarker of aging. Down syndrome (DS) is a genetic disorder in which multiple major aspects of senescent phenotype occur much earlier than in healthy age-matched subjects and has been often defined as an accelerated aging syndrome. The aim of this study was to compare plasma N-glycome of patients affected by DS with age- and sex matched non-affected controls, represented by their siblings (DSS), in order to assess if DS is characterized by a specific N-glycomic pattern. Therefore, in order to investigate if N-glycans changes that occur in DS were able to reveal an accelerated aging in DS patients, we enrolled the mothers (DSM) of the DS and DSS, representing the non-affected control group with a different chronological age respect to DS. We applied two different N-glycomics approaches on the same samples: first, in order to study the complete plasma N-glycome we applied a new high-sensitive protocol based on a MALDI-TOF-MS approach, second, we used DSA-FACE technology. Results: MALDI-TOF/MS analysis detected a specific N-glycomics signature for DS, characterized by an increase of fucosylated and bisecting species. Moreover, in DS the abundance of agalactosylated (as NA2F) species was similar or higher than their mothers. The measurement of GlycoAge test with DSA-FACE, validated also by MALDI-TOF, demonstrated a strongly association with age, moreover in DS, it’s value was similar to their mothers, and significantly higher than their age- and sex matched not-affected siblings

Dry grinding technology for automotive gears manufacturing: process modeling and optimization

The following thesis focused on the dry grinding process modelling and optimization for automotive gears production. A FEM model was implemented with the aim at predicting process temperatures and preventing grinding thermal defects on the material surface. In particular, the model was conceived to facilitate the choice of the grinding parameters during the design and the execution of the dry-hard finishing process developed and patented by the company Samputensili Machine Tools (EMAG Group) on automotive gears. The proposed model allows to analyse the influence of the technological parameters, comprising the grinding wheel specifications. Automotive gears finished by dry-hard finishing process are supposed to reach the same quality target of the gears finished through the conventional wet grinding process with the advantage of reducing production costs and environmental pollution. But, the grinding process allows very high values of specific pressure and heat absorbed by the material, therefore, removing the lubricant increases the risk of thermal defects occurrence. An incorrect design of the process parameters set could cause grinding burns, which affect the mechanical performance of the ground component inevitably. Therefore, a modelling phase of the process could allow to enhance the mechanical characteristics of the components and avoid waste during production. A hierarchical FEM model was implemented to predict dry grinding temperatures and was represented by the interconnection of a microscopic and a macroscopic approach. A microscopic single grain grinding model was linked to a macroscopic thermal model to predict the dry grinding process temperatures and so to forecast the thermal cycle effect caused by the process parameters and the grinding wheel specification choice. Good agreement between the model and the experiments was achieved making the dry-hard finishing an efficient and reliable technology to implement in the gears automotive industry.

Temporary teams learning and performance: the case of 3D printing technology in orthopaedic surgery

This dissertation contributes to the scholarly debate on temporary teams by exploring team interactions and boundaries.The fundamental challenge in temporary teams originates from temporary participation in the teams. First, as participants join the team for a short period of time, there is not enough time to build trust, share understanding, and have effective interactions. Consequently, team outputs and practices built on team interactions become vulnerable. Secondly, as team participants move on and off the teams, teams’ boundaries become blurred over time. It leads to uncertainty among team participants and leaders about who is/is not identified as a team member causing collective disagreement within the team. Focusing on the above mentioned challenges, we conducted this research in healthcare organisations since the use of temporary teams in healthcare and hospital setting is prevalent. In particular, we focused on orthopaedic teams that provide personalised treatments for patients using 3D printing technology. Qualitative and quantitative data were collected using interviews, observations, questionnaires and archival data at Rizzoli Orthopaedic Institute, Bologna, Italy. This study provides the following research outputs. The first is a conceptual study that explores temporary teams’ literature using bibliometric analysis and systematic literature review to highlight research gaps. The second paper qualitatively studies temporary relationships within the teams by collecting data using group interviews and observations. The results highlighted the role of short-term dyadic relationships as a ground to share and transfer knowledge at the team level. Moreover, hierarchical structure of the teams facilitates knowledge sharing by supporting dyadic relationships within and beyond the team meetings. The third paper investigates impact of blurred boundaries on temporary teams’ performance. Using quantitative data collected through questionnaires and archival data, we concluded that boundary blurring in terms of fluidity, overlap and dispersion differently impacts team performance at high and low levels of task complexity.