Hydrometallurgical process modeling using advanced mathematical tools

Hydrometallurgical process modeling is the main objective of this Master’s thesis work. Three different leaching processes namely, high pressure pyrite oxidation, direct oxidation zinc concentrate (sphalerite) leaching and gold chloride leaching using rotating disc electrode (RDE) are modeled and simulated using gPROMS process simulation program in order to evaluate its model building capabilities. The leaching mechanism in each case is described in terms of a shrinking core model. The mathematical modeling carried out included process model development based on available literature, estimation of reaction kinetic parameters and assessment of the model reliability by checking the goodness fit and checking the cross correlation between the estimated parameters through the use of correlation matrices. The estimated parameter values in each case were compared with those obtained using the Modest simulation program. Further, based on the estimated reaction kinetic parameters, reactor simulation and modeling for direct oxidation zinc concentrate (sphalerite) leaching is carried out in Aspen Plus V8.6. The zinc leaching autoclave is based on Cominco reactor configuration and is modeled as a series of continuous stirred reactors (CSTRs). The sphalerite conversion is calculated and a sensitivity analysis is carried out so to determine the optimum reactor operation temperature and optimum oxygen mass flow rate. In this way, the implementation of reaction kinetic models into the process flowsheet simulation environment has been demonstrated.

Catalytic dehydration of glycerol to acrolein: catalysts and processes

The valorization of glycerol has been widely studied notably due to the oversupply of the latter from biodiesel production. Among the different upgrading reactions, dehydration to acrolein is of high interest due to the importance of acrolein as an intermediate for polymer industry (via acrylic acid) and for feed additive (synthon for DL-methionine). It is known that acrolein can be obtained by glycerol catalytic dehydration over acid catalysts. Zeolites and heteropolyacid catalysts are initially highly active, but deactivate rapidly with time on stream by coking, whilst mixed metal oxides are more stable catalytic systems but less selective and in addition they require an activation period. In this talk, the strategy we followed is described. It consisted in a parallel approach in which we developed supported heteropolyacid-based catalysts with increased stability and acrolein selectivity by using a ZrO2-grafted SBA-15 playing the role of the support for silico-tungstic acid active phase, as well as a new concept based on a two zones fluidized bed reactor (TZFBR) to tackle the unavoidable deactivation issue of the HPA catalysts. This type of reactor comprises – in one single capacity – reaction and regeneration zones. In the second part of the lecture the REALCAT platform was introduced. REALCAT (French acronym standing for ‘Advanced High-Throughput Technologies Platform for Biorefineries Catalysts Design’) is an highly integrated platform devoted to the acceleration of innovation in all the fields of industrial catalysis with an emphasis on emergent biorefinery catalytic processes. In this extremely competitive field, REALCAT consists in a versatile High-Throughput Technologies (HTT) platform devoted to innovation in heterogeneous, homogeneous or biocatalysts AND their combinations under the ultra-efficient very novel concept of hybrid catalysis.

The role of oxidative stress as an underlying mechanism in life-history trade-offs

A key aspect underpinning life-history theory is the existence of trade-offs. Trade-offs occur because resources are limited, meaning that individuals cannot invest in all traits simultaneously, leading to costs for traits such as growth and reproduction. Such costs may be the reason for the sub-maximal growth rates that are often observed in nature, though the fitness consequences of these costs would depend on the effects on lifetime reproductive success. Recently, much attention has been given to the physiological mechanism that might underlie these life-history trade-offs, with oxidative stress (OS) playing a key role. OS is characterised by a build-up of oxidative damage to tissues (e.g. protein, lipids and DNA) from attack by reactive species (RS). RS, the majority of which are by-products of metabolism, are usually neutralised by antioxidants, however OS occurs when there is an imbalance between the two. There are two main theories linking OS with growth and reproduction. The first is that traits like growth and reproduction, being metabolically demanding, lead to an increase in RS production. The second involves the diversion of resources away from self-maintenance processes (e.g. the redox system) when individuals are faced with enhanced growth or reproductive expenditure. Previous research investigating trade-offs involving growth or reproduction and self-maintenance has been equivocal. One reason for this could be that associations among redox biomarkers can vary greatly so that the biomarker selected for analysis can influence the conclusion reached about an individual’s oxidative status. Therefore the first aim of my thesis was to explore the strength and pattern of integration of five biomarkers of OS (three antioxidants, one damage and one general oxidation measure) in wild blue tit (Cyanistes caeruleus) adults and nestlings (Chapter 2). In doing so, I established that all five biomarkers should be included in future analyses, thus using this collection of biomarkers I explored my next aims; whether enhanced growth (Chapters 3 and 4) or reproductive effort (Chapter 5) can lead to increased OS levels, if these traits are traded off against self-maintenance. I accomplished these aims using both a meta-analytic and experimental approach, the latter involving manipulation of brood size in wild blue tits in order to experimentally alter growth rate of nestlings and provisioning rate (a proxy for reproductive expenditure) of adults. I also investigated the potential for redox integration to be used as an index of body condition (Chapter 2), allowing predictions about future fitness consequences of changes to oxidative state to be made. A growth – self-maintenance trade off was supported by my meta-analytic results (Chapter 4) which found OS to be a constraint on growth. However, when faced with experimentally enhanced growth, animals were typically not able to adjust this trade-off so that oxidative damage resulted. This might support the idea that energetically expensive growth causes resources to be diverted away from the redox system; however, antioxidants did not show an overall reduction in response to growth in the meta-analysis suggesting that oxidative costs of growth may result from increased RS production due to the greater metabolism needed for enhanced growth. My experimental data (Chapter 3) showed a similar pattern, with raised protein damage levels (protein carbonyls; PCs) in the fastest growing blue tit chicks in a brood, compared with their slower growing sibs. These within-brood differences in OS levels likely resulted from within-brood hierarchies and might have masked any between-brood differences, which were not observed here. Despite evidence for a growth – self-maintenance trade off, my experimental results on blue tits found no support for the hypothesis that self-maintenance is also traded off against reproduction, another energetically demanding trait. There was no link between experimentally altered reproductive expenditure and OS, nor was there a direct correlation between reproductive effort and OS (Chapter 5). However, there are various factors that likely influence whether oxidative costs are observed, including environmental conditions and whether such costs are transient. This emphasises the need for longitudinal studies following the same individuals over multiple years and across a wide range of habitats that differ in quality. This would allow investigation into how key life events interact; it might be that raised OS levels from rapid early growth have the potential to constrain reproduction or that high parental OS levels constrain offspring growth. Any oxidative costs resulting from these life-history trade-offs have the potential to impact on future fitness. Redox integration of certain biomarkers might prove to be a useful tool in making predictions about fitness, as I found in Chapter 2, as well as establishing how the redox system responds, as a whole, to changes to growth and reproduction. Finally, if the tissues measured can tolerate a given level of OS, then the level of oxidative damage might be irrelevant and not impact on future fitness at all.

Evaluation of the protective effects of kolaviron on Kolanut-induced oxidative stress in developing rat brain

The brain is exposed throughout life to oxidative stress, and certain diseases of the brain and nervous system are thought to involve free radical processes and oxidative damage. This study is aimed at evaluating the effect of kolaviron on kolanut-induced oxidative stress in developing rat brain. Twenty-five adult pregnant Wistar rats weighing between 160 and 180g were used for the experiment. They were randomly divided into five groups of five animals each. The animals were fed with standard diets of mice cubes and water provided ad libitum. The control rats received water and cornoil, while the experimental animals received 200 mg/kg body weight of kolanut (kn), 200 mg/kg of kolaviron (kv), and 200 mg/kg body weight of vitamin E which served as a standard antioxidant with cornoil as vehicle orally in pre- and post-natal life. After birth, gross morphometry and behavioural changes of the pups of days 1, 7, 14, 21 and 28 postpartum were evaluated. Blood samples were collected from pups of day 21 for hematological, liver and renal function analyses, while the brains of pups of day 21 postpartum were preserved in phosphate buffer at a temperature of 4oC and pH 7.4 for biochemical analysis. There were significant alterations in the gross morphometry and behavioural parameters studied in the treated animals compared with the control at p< 0.05. There were elevated levels of RBC, WBC and platelets in the treated group compared with the control at p< 0.05. However, no significant change was observed in the PCV, Hb, liver and renal function parameters studied at p>0.05. A non-significant increase in levels of malondialdehyde, MDA, a bye-product of lipid peroxidation in the kolanut group was observed. However, administration of kolaviron and vitamin E non-significantly (p>0.05) reversed these changes. In conclusion, maternal consumption of kolanut induced mild oxidative stress and the administration of kolaviron and vitamin E decreased the rate at which kolanut induced oxidative stress in developing rat brain.

Modelling and analysing cargo screening processes: a project outline

The efficiency of current cargo screening processes at sea and air ports is unknown as no benchmarks exists against which they could be measured. Some manufacturer benchmarks exist for individual sensors but we have not found any benchmarks that take a holistic view of the screening procedures assessing a combination of sensors and also taking operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role. For such systems more advanced assessment methods need to be used, taking into account that the cargo screening process is of a dynamic and stochastic nature. Our project aim is to develop a decision support tool (cargo-screening system simulator) that will map the right technology and manpower to the right commodity-threat combination in order to maximize detection rates. In this paper we present a project outline and highlight the research challenges we have identified so far. In addition we introduce our first case study, where we investigate the cargo screening process at the ferry port in Calais.

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

Effects of advanced glycation end-products (AGEs) on retinal pigment epithelial (RPE) cells lysosomal function:implications for age-related macular degeneration (AMD)

Purpose: RPE lysosomal dysfunction is a major contributor to AMD pathogenesis. Controlled activity of a major class of RPE proteinases, the cathepsins, is crucial in maintaining correct lysosomal function. Advanced glycation end-products (AGEs) accumulate in the Bruch’s membrane (BM) with age, impacting critical RPE functions and in turn, contributing to the development of AMD. The aim of this study was to assess the effect of AGEs on lysosomal function by analysing the expression, processing and activity of the cysteine proteinases cathepsins B, L and S, and the aspartic proteinase cathepsin D. Methods: ARPE-19 cells were cultured on AGE-containing BM mimics (matrigel) for 14 days and compared to untreated substrate. Expression levels and intracellular processing of cathepsins B, D, L and S, were assessed by qPCR and immunoblotting of cell lysates. Lysosomal activity was investigated using multiple activity assays specific to each of the analysed cathepsins. Statistical analysis was performed using the Student’s independent T-test. Results: AGE exposure produced a 36% decrease in cathepsin L activity when compared to non-treated controls (p=0.02, n= 3) although no significant changes were observed in protein expression/processing under these conditions. Both the pro and active forms of cathepsin S decreased by 40% (p=0.04) and 74% (p=0.004), respectively (n=3). In contrast, the active form of the cathepsin D increased by 125% (p=0.005, n= 4). However, no changes were observed in the activity levels of both cathepsins S and D. In addition, cathepsin B expression, processing and activity also remained unaltered following AGE exposure. Conclusions: AGEs accumulation in the extracellular matrix, a phenomenon associated with the natural aging process of the BM, attenuates the expression, intracellular processing and activity of specific lysosomal effectors. Altered enzymatic function may impair important lysosomal processes such as endocytosis, autophagy and phagocytosis of photoreceptor outer segments, each of which may influence the age-related dysfunction of the RPE and subsequently, AMD pathogenesis.

Physicochemical and antioxidant properties of the pequi (Caryocar brasiliense Camb.) almond oil obtained by handmade and cold-pressed processes.

Abstract: The aim of this study is to characterize physical and chemically and determine the antioxidant capacity of pequi almond oils (PAO) extracted by handmade and by cold-pressing. Both oils showed good quality by acid, peroxide and thiobarbituric acid values. The fatty acid (FA) profile showed a significant presence of monounsaturated FA, mainly oleic acid (53.48 to 55.41%); saturated FA, such as palmitic acid (33.30 to 35.89 %); and polyunsaturated FA (PUFA), such as linoleic acid (5.85 to 7.23%). The total phenolic (TP) and carotenoid content ranged in concentration from 87.56 to 392.00 mg GAE/100 g and 36.03 to 262.40 mg/100 g, respectively. The tocopherol and phytosterol results indicated the predominant presence of α-tocopherol (52 to 67%) and stigmasterol (63 to 68 %). The antioxidant capacity of PAO as measured using the 2,2-diphenyl-1-picrylhydrazyl (DPPH?) method oscillated from 58.48 mg/mL to 76.46 mg/mL (IC50), from 10.61 to 40.46 µmol TE/g by the 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS?+) method, and from 113.93 to 280.85 µmol TE/100 g and 164.49 to 277.86 µmol TE/100 g, by the lipophilic and hydrophilic oxygen radical absorbance capacity (ORAC) methods, respectively. The oils presented a good oxidative and thermal stability by Rancimat method (IP of 7.33 a 15.91 h) and curves thermogravimetric and differential scanning calorimetry (To 337-363 °C and 159-184 °C, respectively). The results confirmed the presence of compounds that conferred antioxidant capacity and oxidative and thermal resistance for PAO made by handmade or cold-pressing, indicating that these oils can potentially be used for food and non-food applications.

Design and Off-design modelling of advanced Power-to-Gas energy storage systems

Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.

Advanced voxel-based CAD modelling for FSI simulations for automotive structures design

Additive Manufacturing (AM) is nowadays considered an important alternative to traditional manufacturing processes. AM technology shows several advantages in literature as design flexibility, and its use increases in automotive, aerospace and biomedical applications. As a systematic literature review suggests, AM is sometimes coupled with voxelization, mainly for representation and simulation purposes. Voxelization can be defined as a volumetric representation technique based on the model’s discretization with hexahedral elements, as occurs with pixels in the 2D image. Voxels are used to simplify geometric representation, store intricated details of the interior and speed-up geometric and algebraic manipulation. Compared to boundary representation used in common CAD software, voxel’s inherent advantages are magnified in specific applications such as lattice or topologically structures for visualization or simulation purposes. Those structures can only be manufactured with AM employment due to their complex topology. After an accurate review of the existent literature, this project aims to exploit the potential of the voxelization algorithm to develop optimized Design for Additive Manufacturing (DfAM) tools. The final aim is to manipulate and support mechanical simulations of lightweight and optimized structures that should be ready to be manufactured with AM with particular attention to automotive applications. A voxel-based methodology is developed for efficient structural simulation of lattice structures. Moreover, thanks to an optimized smoothing algorithm specific for voxel-based geometries, a topological optimized and voxelized structure can be transformed into a surface triangulated mesh file ready for the AM process. Moreover, a modified panel code is developed for simple CFD simulations using the voxels as a discretization unit to understand the fluid-dynamics performances of industrial components for preliminary aerodynamic performance evaluation. The developed design tools and methodologies perfectly fit the automotive industry’s needs to accelerate and increase the efficiency of the design workflow from the conceptual idea to the final product.

Processi e pratiche di Innovazione Responsabile: il ruolo dell' Advanced Design nella trasformazione collaborativa dei territori

La ricerca indaga il rapporto tra Design e Innovazione Responsabile calandolo all’interno della relazione tra territorio e pratiche collaborative guidate dal design, ma anche legate al patrimonio culturale immateriale e a un sistema di conoscenza a quintupla elica. La necessità emergente di cura del futuro porta a rivedere il contesto del territorio come campo strumentale per la trasformazione degli individui e della comunità e a domandarsi in che modo il design possa supportare questo cambiamento, abilitando la produzione di conoscenza collaborativa. La ricerca parte dal dimostrare come il modello di innovazione recentemente proposto dalla Comunità Europea attraverso il concetto di Responsible Research Innovation (RRI), poi ripreso nella nozione di Responsible Innovation (RI), sia un campo aperto e responsivo: se integrato con altre discipline, in particolare con il design, può supportare lo sviluppo di processi, politiche, prodotti, servizi e comportamenti che rispettino la relazione tra società, ambiente, identità individuale e collettiva e i ritmi ad essi connessi. Partendo dal contesto sopra descritto, ci si chiede come il design e il designer possano integrare le dimensioni RI nei processi di progettazione, per innovare in modo collaborativo i territori. Si individua quindi nell’Advanced Design la metodologia che, grazie alla sua natura anticipatrice, collaborativa, trasformativa, riesce a coniugarsi virtuosamente con l’approccio RI e supportare il cambiamento in atto. L’intersezione di questi elementi porta alla creazione del Modello Advanced Design per/con l’Innovazione Responsabile (ADIR): un sistema multidimensionale per gruppi di innovazione (quintupla elica) che hanno l’obiettivo di rigenerare in modo collaborativo e inclusivo i territori. L’esperienza sul campo ha confermato come la struttura del modello, formata da un corpus di semi-lavorati, permetta di creare un proprio ritmo, una compenetrazione tra azioni e forme progettuali volti a mantenere il senso di comunità e il coinvolgimento degli attori, a creare relazioni, a sviluppare una trasformazione continua.

Development of functional MRI protocols in the study of neurodegenerative diseases: MRI study in patients with REM sleep behavior disorder, idiopathic Parkinson's disease and multisystem atrophy

In the central nervous system, iron in several proteins is involved in many important processes: oxygen transportation, oxidative phosphorylation, mitochondrial respiration, myelin production, the synthesis and metabolism of neurotransmitters. Abnormal iron homoeostasis can induce cellular damage through hydroxyl radical production, which can cause the oxidation, modification of lipids, proteins, carbohydrates, and DNA, lead to neurotoxicity. Moreover increased levels of iron are harmful and iron accumulations are typical hallmarks of brain ageing and several neurodegenerative disorders particularly PD. Numerous studies on post mortem tissue report on an increased amount of total iron in the substantia nigra in patients with PD also supported by large body of in vivo findings from Magnetic Resonance Imaging (MRI) studies. The importance and approaches for in vivo brain iron assessment using multiparametric MRI is increased over last years. Quantitative MRI may provide useful biomarkers for brain integrity assessment in iron-related neurodegeneration. Particularly, a prominent change in iron- sensitive T2* MRI contrast within the sub areas of the SN overlapping with nigrosome 1 were shown to be a hallmark of Parkinson's Disease with high diagnostic accuracy. Moreover, differential diagnosis between Parkinson's Disease (PD) and atypical parkinsonian syndromes (APS) remains challenging, mainly in the early phases of the disease. Advanced brain MR imaging enables to detect the pathological changes of nigral and extranigral structures at the onset of clinical manifestations and during the course of the disease. The Nigrosome-1 (N1) is a substructure of the healthy Substantia Nigra pars compacta enriched by dopaminergic neurons; their loss in Parkinson’s disease and atypical parkinsonian syndromes is related to the iron accumulation. N1 changes are supportive MR biomarkers for diagnosis of these neurodegenerative disorders, but its detection is hard with conventional sequences, also using high field (3T) scanner. Quantitative susceptibility mapping (QSM), an iron-sensitive technique, enables the direct detection of Neurodegeneration

Analytics and optimization for emergency healthcare processes

This thesis deals with the analysis and management of emergency healthcare processes through the use of advanced analytics and optimization approaches. Emergency processes are among the most complex within healthcare. This is due to their non-elective nature and their high variability. This thesis is divided into two topics. The first one concerns the core of emergency healthcare processes, the emergency department (ED). In the second chapter, we describe the ED that is the case study. This is a real case study with data derived from a large ED located in northern Italy. In the next two chapters, we introduce two tools for supporting ED activities. The first one is a new type of analytics model. Its aim is to overcome the traditional methods of analyzing the activities provided in the ED by means of an algorithm that analyses the ED pathway (organized as event log) as a whole. The second tool is a decision-support system, which integrates a deep neural network for the prediction of patient pathways, and an online simulator to evaluate the evolution of the ED over time. Its purpose is to provide a set of solutions to prevent and solve the problem of the ED overcrowding. The second part of the thesis focuses on the COVID-19 pandemic emergency. In the fifth chapter, we describe a tool that was used by the Bologna local health authority in the first part of the pandemic. Its purpose is to analyze the clinical pathway of a patient and from this automatically assign them a state. Physicians used the state for routing the patients to the correct clinical pathways. The last chapter is dedicated to the description of a MIP model, which was used for the organization of the COVID-19 vaccination campaign in the city of Bologna, Italy.

Data assimilation for advanced cross-scale unstructured-grid ocean modeling.

The coastal ocean is a complex environment with extremely dynamic processes that require a high-resolution and cross-scale modeling approach in which all hydrodynamic fields and scales are considered integral parts of the overall system. In the last decade, unstructured-grid models have been used to advance in seamless modeling between scales. On the other hand, the data assimilation methodologies to improve the unstructured-grid models in the coastal seas have been developed only recently and need significant advancements. Here, we link the unstructured-grid ocean modeling to the variational data assimilation methods. In particular, we show results from the modeling system SANIFS based on SHYFEM fully-baroclinic unstructured-grid model interfaced with OceanVar, a state-of-art variational data assimilation scheme adopted for several systems based on a structured grid. OceanVar implements a 3DVar DA scheme. The combination of three linear operators models the background error covariance matrix. The vertical part is represented using multivariate EOFs for temperature, salinity, and sea level anomaly. The horizontal part is assumed to be Gaussian isotropic and is modeled using a first-order recursive filter algorithm designed for structured and regular grids. Here we introduced a novel recursive filter algorithm for unstructured grids. A local hydrostatic adjustment scheme models the rapidly evolving part of the background error covariance. We designed two data assimilation experiments using SANIFS implementation interfaced with OceanVar over the period 2017-2018, one with only temperature and salinity assimilation by Argo profiles and the second also including sea level anomaly. The results showed a successful implementation of the approach and the added value of the assimilation for the active tracer fields. While looking at the broad basin, no significant improvements are highlighted for the sea level, requiring future investigations. Furthermore, a Machine Learning methodology based on an LSTM network has been used to predict the model SST increments.

Design, synthesis and biological evaluation of dual inhibitors of GSK-3B and Fyn kinases for the study of inflammatory pathways in neurodegenerative diseases

Neuroinflammation represents a key hallmark of neurodegenerative diseases and is the result of a complex network of signaling cascades within microglial cells. A positive feedback loop exists between inflammation, microglia activation and protein misfolding processes, that, together with oxidative stress and excitotoxicity, lead to neuronal degeneration. Therefore, targeting this vicious cycle can be beneficial for mitigating neurodegeneration and cognitive decline in central nervous system disorders. At molecular level, GSK-3B and Fyn kinases play a crucial role in microglia activation and their deregulation has been associated to many neurodegenerative diseases. Thus, we envisioned their combined targeting as an effective approach to disrupt this toxic loop. Specifically in this project, a hit compound, based on a 7-azaindole-3-aminothiazole structure, was first identified in a virtual screening campaign, and displayed a weak dual inhibitory activity on GSK-3B and Fyn, unbalanced towards the former. Then, in a commitment to uncover the structural features required for modulating the activity on the two targets, we systematically manipulated this compound by inserting various substitution patterns in different positions. The most potent compounds obtained were advanced to deeper investigations to test their ability of tackling the inflammatory burden also in cellular systems and to unveil their binding modes within the catalytic pocket. The new class of molecules synthesized emerged as a valuable tool to deepen our understanding of the complex network governing the inflammatory events in neurodegenerative disorders.