Development of advanced tools and methods for the assessment and management of risk due to atypical major accident scenarios

Proper hazard identification has become progressively more difficult to achieve, as witnessed by several major accidents that took place in Europe, such as the Ammonium Nitrate explosion at Toulouse (2001) and the vapour cloud explosion at Buncefield (2005), whose accident scenarios were not considered by their site safety case. Furthermore, the rapid renewal in the industrial technology has brought about the need to upgrade hazard identification methodologies. Accident scenarios of emerging technologies, which are not still properly identified, may remain unidentified until they take place for the first time. The consideration of atypical scenarios deviating from normal expectations of unwanted events or worst case reference scenarios is thus extremely challenging. A specific method named Dynamic Procedure for Atypical Scenarios Identification (DyPASI) was developed as a complementary tool to bow-tie identification techniques. The main aim of the methodology is to provide an easier but comprehensive hazard identification of the industrial process analysed, by systematizing information from early signals of risk related to past events, near misses and inherent studies. DyPASI was validated on the two examples of new and emerging technologies: Liquefied Natural Gas regasification and Carbon Capture and Storage. The study broadened the knowledge on the related emerging risks and, at the same time, demonstrated that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards. Moreover, in order to tackle underlying accident causes of atypical events, three methods for the development of early warning indicators were assessed: the Resilience-based Early Warning Indicator (REWI) method, the Dual Assurance method and the Emerging Risk Key Performance Indicator method. REWI was found to be the most complementary and effective of the three, demonstrating that its synergy with DyPASI would be an adequate strategy to improve hazard identification methodologies towards the capture of atypical accident scenarios.

Modeling Alzheimer disease with iPSCs and mouse model for the identification of risk factors, new targets, and potential therapeutical strategies

Alzheimer's disease (AD) is the most common neurodegenerative disease in elderly. Donepezil is the first-line drug used for AD. In section one, the experimental activity was oriented to evaluate and characterize molecular and cellular mechanisms that contribute to neurodegeneration induced by the Aβ1-42 oligomers (Aβ1-42O) and potential neuroprotective effects of the hybrids feruloyl-donepezil compound called PQM130. The effects of PQM130 were compared to donepezil in a murine AD model, obtained by intracerebroventricular (i.c.v.) injection of Aβ1-42O. The intraperitoneal administration of PQM130 (0.5-1 mg/kg) after i.c.v. Aβ1-42O injection improved learning and memory, protecting mice against spatial cognition decline. Moreover, it reduced oxidative stress, neuroinflammation and neuronal apoptosis, induced cell survival and protein synthesis in mice hippocampus. PQM130 modulated different pathways than donepezil, and it is more effective in counteracting Aβ1-42O damage. The section two of the experimental activity was focused on studying a loss of function variants of ABCA7. GWA studies identified mutations in the ABCA7 gene as a risk factor for AD. The mechanism through which ABCA7 contributes to AD is not clear. ABCA7 regulates lipid metabolism and critically controls phagocytic function. To investigate ABCA7 functions, CRISPR/Cas9 technology was used to engineer human iPSCs and to carry the genetic variant Y622*, which results in a premature stop codon, causing ABCA7 loss-of-function. From iPSCs, astrocytes were generated. This study revealed the effects of ABCA7 loss in astrocytes. ABCA7 Y622* mutation induced dysfunctional endocytic trafficking, impairing Aβ clearance, lipid dysregulation and cell homeostasis disruption, alterations that could contribute to AD. Though further studies are needed to confirm the PQM130 neuroprotective role and ABCA7 function in AD, the provided results showed a better understanding of AD pathophysiology, a new therapeutic approach to treat AD, and illustrated an innovative methodology for studying the disease.

Advancing of risk assessment of pesticides on insect pollinators: beyond honey bees (Apis mellifera L.)

The western honey bee, Apis mellifera L., is currently the model specie for pesticide risk assessment on pollinators with the assumption that the worst-case scenarios for this species are sufficiently conservative to protect other insect pollinators. However, recent studies have showed that wild species may be more sensitive to plant protection products, due to differences in biology and life cycles. Therefore, there is the need to extend the risk assessment within a more ecological approach, in order to ensure that there are no irreversible effects on non-target organisms and in the environment. My dissertation aims to expand the risk assessment to other insect pollinators (including wild and managed pollinators), in order to cover some of the gaps of the current schemes. In this thesis, it is presented three experiments that cover the early stages of a solitary bee (chapter 1), the development of molecular tools for early detection of sub-lethal effects (chapter 2) and the development of protocols to access lethal and sub-lethal effects on other pollinator taxa (Diptera; chapter 3).

Risk analysis of tractor rollover in the normal operation in field

Tractor rollover represent a primary cause of death or serious injury in agriculture and despite the mandatory Roll-Over Protective Structures (ROPS), that reduced the number of injuries, tractor accidents are still of great concern. Because of their versatility and wide use many studies on safety are concerned with the stability of tractors, but they often prefer controlled tests or laboratory tests. The evaluation of tractors working in field, instead, is a very complex issue because the rollover could be influenced by the interaction among operator, tractor and environment. Recent studies are oriented towards the evaluation of the actual working conditions developing prototypes for driver assistance and data acquisition. Currently these devices are produced and sold by manufacturers. A warning device was assessed in this study with the aim to evaluate its performance and to collect data on different variables influencing the dynamics of tractors in field by monitoring continuously the working conditions of tractors operating at the experimental farm of the Bologna University. The device consists of accelerometers, gyroscope, GSM/GPRS, GPS for geo-referencing and a transceiver for the automatic recognition of tractor-connected equipment. A microprocessor processes data and provides information, through a dedicated algorithm requiring data on the geometry of the tested tractor, on the level of risk for the operator in terms of probable loss of stability and suggests corrective measures to reduce the potential instability of the tractor.