Progetti di Dottorato e Finanziamenti Europei

PhD student : Greta Gallo

Supervisor: Marco E. Bianchi

Abstract

We design antisense oligonucleotides (LNA-ASOs) that inhibit SARS-CoV-2 replication: by analysing in-vivo probing data we select regions with a high degree of conservation among SARS-CoV-2 variants, SARS-CoV, and MERS-CoV. We found genomic regions displaying high sequence conservation and low propension to form secondary structures. We will perform assays in vitro and cells, and later in a HyACE2 mouse model.

Objectives

Our aim is to find LNA-ASOs that inhibit replication of all SARS-CoV-2, to design a proper delivery system and to study their therapeutic effect in a SARS-CoV-2 sensitive mouse model.

Results achieved

We found 4 LNA-ASOs able to reduce by more than 90% SARS-CoV-2 genomic presence in a HuH-7.5 cell line for SARS-CoV-2 B.1, B.1.617.2, BA.1 e BA.2.

PhD student: Carolina Bezzi

Supervisor: Maria Picchio

Abstract

To apply and validate the role of advanced image analysis (radiomics, AI algorithms), especially in the field of Positron Emission Tomography (PET), in different oncological settings and key clinical purposes (staging, treatment planning, tumor segmentation, etc.). For each investigation, scans are processed, and relevant imaging patterns are identified and analyzed through statistical analysis and AI, using clinical gold standards as ground truth. Models’ predictions are then compared with accuracy rates of experts’ qualitative examinations and/or biopsy specimens.

Objectives

To gain improvements and valuable insights on the role of advanced image analysis in the oncological field, and to develop innovative diagnostic/prognostic imaging approaches to support clinical decision-making.  

Results achieved

Advanced image analysis is proving its role in supporting the diagnosis/prognosis in pancreatic neuroendocrine tumors, gynaecological tumors, and prostate cancer, providing additional, still unexploited information.

PhD student: Sofia Sisti

Supervisor: Nicola Clementi

Abstract

In the last few years, the COVID-19 pandemic heavily impacted the social behavior and economic aspects of our society. The rapid diffusion of different SARS-CoV-2 variants of interest (VOI) was associated with the transmission through direct contact (droplets, aerosol, and person-to-person transmission) but also with indirect contact. Therefore, this project will investigate the possible mechanisms leading to indirect transmission of SARS-CoV-2 through different fomites.

Objectives

The main goals are to investigate the persistence of SARS-CoV-2 VOI on environmental surfaces and to study the inhibitory activity of sterilization approaches against SARS-CoV-2 variants.

Results achieved

Until now, we validated an in vitro model useful to mimic the in vivo SARS-CoV-2 variants infections and we obtained preliminary results of the persistence of VOI on different surfaces.

PhD Student: Damiano Mistri

Supervisor: Rocca Maria Assunta

Abstract:

Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating and neurodegenerative disease of the central nervous system. Pediatric-onset MS (POMS) occurs in an estimated 3-10% of MS patients. Cognitive decline affects 30-50% of POMS patients, impacting memory, attention, and processing speed. MRI is crucial for diagnosis and monitoring disease progression and the application of advanced MRI techniques is contributing to identify the substrates associated with cognitive dysfunction in POMS.

Objectives

The project aims to understand the neural substrates of cognitive dysfunction in POMS using advanced MRI techniques and machine learning. Additionally, the research aims to develop a new tool for assessing cognitive processing speed.

Results achieved

Using a machine learning approach, three cognitive phenotypes were identified in POMS, each associated with a distinct pattern of structural and functional MRI abnormalities.

PhD student: Alessandro Anzà

Supervisor: Francesca De Vecchi

Abstract

At the heart of my research is the relationship between present and future generations, which is particularly relevant in the context of climate change and the crisis of democratic representation. I want to introduce a phenomenological perspective to the current debates, that analyses the transgenerational constitution of our natural, social, and historical world in which we share. It assesses how and if age as well as generational belonging play a role in shaping personal identity and the nature of the social groups in which we live.

Objectives

The aim is to identify the main characteristics and general dynamics of a specific group of people that I call “future-maker generations” (FMG) who can jointly cope with the challenges of the contemporary world, overcoming generational boundaries and other conflicting patterns of social injustice and discriminations.

Results achieved

The phenomenological perspective (Husserl, Schütz, Arendt) allows social ontology (Searle, Gilbert) to be enriched with a gaze into the transgenerational social world of individual person and of plural subjects.

PhD student: Luca Ausili

Supervisor: Carlo Martini

Abstract

This research project’s aim is to study the causes of the current spread of scientific disinformation within the
infosphere, with a particular focus on the disinformation relative to climate change. Through the
understanding of the dynamics related to this phenomenon, and their description, the attempt will be to offer
useful recommendations to contrast the negative effects of scientific disinformation and depict the status of
the relation between science and society.

Objectives

- Define which possible changes of the current communication between science and society could be
implemented to prevent the spread of scientific disinformation.
- Define the socio-epistemic reasons that motivate people’s acceptance of openly anti-scientific
contents.

Achieved results

- Analysis of people’s ability to evaluate the scientific reliability of the information found online.
- Definition of a theory that categorizes scientific disinformation as a socio-epistemic phenomenon.

PhD student: Gemmani Gianluca

Supervisor: Francesco Valagussa

Abstract

The project aims to examine the concepts of production and storytelling through the study of landscape as a theoretical object. This means considering landscape as a 'symbolic form,' as an instrument capable of expressing the tendencies and worldview of an entire age. If it is to be understood as the boundary in which the categories of nature and culture act reciprocally, the living space between the two, then landscape becomes the reflexive device through which it is possible, from a social aesthetics perspective, to highlight the practices through which we shape, signify and build the environment that surrounds.

Objectives

To show, through the study of landscape as a reflexive device, how the aesthetic and social dimensions are inseparable and mutually dependent, and how the production and storytelling of our surroundings are linked.

Achieved results

Through seminars, conferences and publications, arguments have been made emphasizing two key points. First: it is always necessary to distinguish landscape and environment in order to protect both. Second: landscape is the clash site of opposing epistemic models.

PhD student: Maurizio Mascitti

Supervisor: Bianca Cepollaro

Abstract

My research project investigates the phenomenon of fake news concerning climate change by adopting the prospective of cognitive pragmatics. The whole project can be divided in two sections. In the first one I summarise current positions within the epistemological debate over fake news; then, I put forth a new general theory of fake news as news that violate specific norms of journalism. In the second section, instead, this new theory is readily used in order to develop a case study of disinformation about the topic of climate change.

Objectives

- The development of a new theory of fake news that set them apart from ‘ordinary’ disinformation

- The development of a case study on fake news around climate change

Results achieved

- The development of the theory of fake news as the byproduct of a violation of specific norms of journalism

PhD student: Alessandro Volpi

Supervisor: Roberta Sala

Abstract

The project addresses the relationship between the concept and practices associated with political sovereignty, on the one hand, and the global challenge of anthropogenic climate change, on the other hand. A political theory perspective is adopted, supported by a critical analysis of the current situation and a genealogical investigation on the concept of sovereignty and the public-private distinction, as well as enriched by political ecology and political economy perspectives.

Objectives

The project aims to propose a political ecology and social justice-based critique of the current conformations of political sovereignty and globalization regime, and to consequently develop alternative theoretical and policy proposals.

Results achieved

The research work has been concerned so far with identifying method and literature appropriate for the project, with partial results being in process of publication in international journals.

PhD Student: Yasmin Harrington

Supervisor: Sara Poletti

Abstract

Postpartum depression (PPD) is a disorder that results in physical, emotional, and behavioral changes after giving birth. It is the most common maternal complication of pregnancy, yet its biological underpinnings remain largely unknown. Past research has suggested PPD may arise in part due to immunological alterations and brain changes; however, results are mixed and inconclusive, and therefore, more studies are needed.

Objectives

We aim to identify differences in grey and white matter structure, functional connectivity, and neuroimmune patterns associated with PPD in the context of the COVID-19 pandemic.

Results achieved

We have recruited 150 women for prospective analyses and have identified structural grey and white matter variances related to history of PPD in preliminary retrospective analyses.

PhD student: Mariagrazia Palladini

Supervisor: Prof. Francesco Benedetti

Abstract

COVID-19 survivors struggling with organic and psychopathological complications referred to as “Post-Acute Covid Syndrome” (PACS), posing an outstanding challenge to the health care system. Immune-mediated pathway and brain-enhanced susceptibility to systemic inflammation gained attention as leading mechanism behind neuropsychiatric outcomes. However, the open issue persists about the exact linkage between inflammatory-induced CNS alterations and post-COVID condition phenotypes.

Objectives

The current project primary aimed at integrating multimodal imaging measures, along with peripheral inflammatory biomarkers in a clustering-based machine learning procedure to identify long-term clinically meaningful sub-populations of COVID-19 survivors.

Results achieved

Structural and functional preprocessing of COVID-19 survivors’ neuroimaging data. Exploratory analysis on association between CNS alterations and post-COVID-19 neuropsychiatric symptoms.