Archivio Istituzionale della Ricerca - Università degli Studi di Pavia
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Epigenetics of Covid-19: A Systems Biology Approach
No full textThis thesis investigates how DNA methylation serves as a critical regulatory layer that explains the extreme variability in COVID-19 outcomes, moving beyond the limitations of purely genetic explanations. By conducting an epigenome-wide association study on blood samples, the research initially identified 880 CpG sites significantly associated with disease severity, many of which are located within genes central to immune and inflammatory responses like SAMHD1 and NLRP3. While these individual probes highlighted biological processes such as interferon signaling and antiviral defense, they were initially insufficient for clear patient classification on their own.
To gain a deeper understanding, the study adopted a systems biology approach using Weighted Gene Co-expression Network Analysis to identify modules of coordinated methylation. This revealed that COVID-19 severity is linked to broad shifts in immune, metabolic, and structural pathways, including B-cell signaling and viral entry mechanisms. From these networks, a refined signature of 55 CpGs was extracted using advanced statistical modeling. This signature proved highly effective at separating mild from severe cases across different patient cohorts, maintaining its predictive power regardless of the age or sex of the individual.
The research culminated in the development of predictive machine learning models which were made transparent through the use of SHAP values. This allowed for both global insights into which methylation changes drive disease progression and local, patient-specific explanations of clinical risk. Despite limitations such as a modest sample size and the use of blood rather than lung tissue, the work demonstrates that DNA methylation encodes vital information about disease pathology. Ultimately, the thesis provides a reproducible framework for using epigenomics and machine learning to bridge the gap between genetic risk and clinical reality, offering potential new biomarkers for infectious and chronic diseases.This thesis investigates how DNA methylation serves as a critical regulatory layer that explains the extreme variability in COVID-19 outcomes, moving beyond the limitations of purely genetic explanations. By conducting an epigenome-wide association study on blood samples, the research initially identified 880 CpG sites significantly associated with disease severity, many of which are located within genes central to immune and inflammatory responses like SAMHD1 and NLRP3. While these individual probes highlighted biological processes such as interferon signaling and antiviral defense, they were initially insufficient for clear patient classification on their own.
To gain a deeper understanding, the study adopted a systems biology approach using Weighted Gene Co-expression Network Analysis to identify modules of coordinated methylation. This revealed that COVID-19 severity is linked to broad shifts in immune, metabolic, and structural pathways, including B-cell signaling and viral entry mechanisms. From these networks, a refined signature of 55 CpGs was extracted using advanced statistical modeling. This signature proved highly effective at separating mild from severe cases across different patient cohorts, maintaining its predictive power regardless of the age or sex of the individual.
The research culminated in the development of predictive machine learning models which were made transparent through the use of SHAP values. This allowed for both global insights into which methylation changes drive disease progression and local, patient-specific explanations of clinical risk. Despite limitations such as a modest sample size and the use of blood rather than lung tissue, the work demonstrates that DNA methylation encodes vital information about disease pathology. Ultimately, the thesis provides a reproducible framework for using epigenomics and machine learning to bridge the gap between genetic risk and clinical reality, offering potential new biomarkers for infectious and chronic diseases
Determination of hair cortisol by liquid chromatography coupled to mass spectrometry (LC-MS/MS) as biomarker of chronic stress and application to academic students
No full textHair cortisol concentration (HCC), a non-invasive biomarker reflecting long-term cortisol exposure, offers valuable insight into chronic stress, complementing established acute stress measures such as salivary or blood cortisol. At the moment, the most valuable use of hair cortisol bio-analysis is to study trends and associations within specific populations rather than establishing a single cut-off value for stress level assessment. In this frame, a rapid LC-MS/MS method for HCC determination has been developed and applied to measure chronic stress in university students with the aim to correlate the analytical results with the perceived stress during the preparation of the exams. A total of 100 students from different academic programs were recruited providing hair samples and data on academic and lifestyle stressors. The method has been validated in accordance with forensic toxicological guidelines ensuring high sensitivity (LOD 2 pg/mg; LOQ 5 pg/mg) and robust performance across selectivity, linearity, accuracy, and stability parameters. Method linearity was assessed in the range 5–50 pg/mg; accuracy and precision calculated on QC were always below 7 %; prepared samples were stable for 4 days at refrigerated temperature. HCC was detectable in 94 % of samples in the range 5––47.7 pg/mg. Students attending Law and Biology courses exhibited the highest mean HCC values. Dietary changes and smoking were associated with higher stress perception. Among academic stressors, balancing work and study, as well as difficulties in study organization, were linked to greater perceived stress. No statistically significant correlation was found between perceived stress and HCC, underscoring the complexity of chronic stress assessment and the value of combining subjective and physiological indicators
Anomalie, multiparità e grandezza corporea: alla ricerca delle cause negli "Animali" di Avicenna
No full textWhen chemistry mimics Nature: nitrenes as tools for N-heterocycles Synthesis
No full textQuesta tesi presenta due nuove strategie sintetiche per la costruzione di azacicli -
unità strutturali fondamentali per la sintesi di prodotti naturali biorilevanti e agenti
farmaceutici. La prima strategia prevede una ciclizzazione a cascata biomimetica di
diossazoloni aril-alchenilici promossa da acil nitrenoidi, utilizzando iridio e rame
come catalizzatori, per ottenere δ-lattami stereodefiniti. Per questa metodologia è
stata sviluppata anche la versione asimmetrica, con un grado di enantioselettività
moderato. In particolare, i sistemi catalizzati da rame associati a ligandi bis
ossazolidinici hanno mostrato un notevole potenziale. La seconda strategia consiste
in un’amminazione ossidativa interrotta di alcheni non attivati, che genera
transitoriamente un sale di aza-allenio. Questa reattività apre l’accesso a imidazoline - strutture altrimenti difficili da ottenere.This thesis presents two novel synthetic strategies for the construction of azacycles - key structural motifs in the synthesis of biologically relevant natural products and
pharmaceutical agents. The first strategy involves a biomimetic cascade cyclization
of arylalkenyl dioxazolones, mediated by metal-acyl nitrenoid intermediates using
iridium and copper catalysts, to furnish stereodefined δ-lactams. The asymmetric
version of this methodology has also been developed, with moderate to good
enantioselectivity. Notably, copper-catalyzed systems paired with bis(oxazoline)
ligands demonstrated significant promise in asymmetric catalysis. The second
strategy is an interrupted oxidative amination of unactivated alkenes, which
transiently generates aza-allenium intermediates. This transformation provides
streamlined access to imidazolines - which are otherwise difficult to construct
L’amore e le armi. “Questioni Private” e lotta partigiana nei romanzi resistenziali di Calvino, Fenoglio, Pavese, Vittorini
No full text“Ecce Europa”. Storia di un’idea nelle destre radicali in Italia e Germania dai lunghi anni Settanta alla fine della guerra fredda
No full textQuesto studio esamina l’evoluzione del concetto di "Europa" all’interno delle culture politiche dell’estrema destra in Italia e in Germania, dalla fine degli anni Settanta fino al termine della Guerra Fredda. Attraverso l’analisi di fonti interne (periodici, saggi e altri materiali a stampa) la ricerca indaga le motivazioni e le modalità con cui l’idea di Europa venne adottata come piattaforma per la costruzione di un’identità collettiva e come alternativa ideale allo Stato-nazione, nonché il modo in cui fu impiegata per rispondere alla crisi – reale o percepita – di ordine politico e valoriale. Superando le interpretazioni incentrate esclusivamente sui partiti politici o sull’euroscetticismo, lo studio mette in luce la pluralità di linguaggi, simboli e narrazioni presenti in queste culture politiche. L’immagine di Europa che ne emerge è tutt’altro che unitaria, ma si configura come una chiave di lettura significativa per comprendere le dinamiche condivise dei movimenti della destra radicale nei due Paesi, nei quali antiamericanismo, nostalgia per un passato idealizzato e rifiuto della modernità liberale rappresentano elementi ricorrenti e persistenti.This study examines the evolution of the concept of "Europe" within the political cultures of the far right in Italy and Germany, from the late 1970s to the end of the Cold War. Through the analysis of internal sources – such as periodicals, essays, and other printed materials – the research investigates the motivations and the ways in which the idea of Europe was adopted as a platform for constructing a collective identity and as an ideal alternative to the nation-state, as well as how it was used to respond to a political and value crisis, whether real or perceived. Moving beyond interpretations focused exclusively on political parties or Euroscepticism, the study highlights the plurality of languages, symbols, and narratives present within these political cultures. The image of Europe that emerges is far from unified, yet it serves as a meaningful interpretive lens for understanding the shared dynamics of radical right-wing movements in both countries, in which anti-Americanism, nostalgia for an idealised past, and rejection of liberal modernity appear as persistent and recurring themes
Un atlante digitale 4D dell’ovario di topo dalla nascita all’età adulta e durante l’invecchiamento
No full textL’Organizzazione Mondiale della Sanità (OMS) definisce l’infertilità come una patologia che colpisce circa il 15-20% delle coppie, con fattori femminili responsabili di oltre un terzo dei casi. Ampliare le conoscenze sull’ovario, sulla follicologenesi e sulla maturazione degli oociti è quindi cruciale per lo sviluppo di trattamenti efficaci. In particolare, è sempre più necessario studiare la struttura e le dinamiche ovariche in un contesto tridimensionale (3D), superando i limiti delle tradizionali analisi bidimensionali, al fine di comprendere i complessi processi che regolano la maturazione follicolare.
In questo contesto, la presente tesi si propone di ottimizzare una pipeline multimodale per la generazione di un atlante digitale 4D dell’ovario di topo, descrivendo i cambiamenti morfologici e funzionali dalla nascita all’età adulta e durante l’invecchiamento, e integrandoli in ricostruzioni 3D dell’organo.
Ovari fissati e inclusi in paraffina sono stati analizzati mediante nano-Tomografia Computerizzata (nanoCT), una tecnica di imaging a raggi X che consente ricostruzioni 3D isotropiche ad alta risoluzione (0,85-0,25 μm/pixel). Questo approccio ha permesso di identificare tutti gli stadi follicolari, dal T1 primordiale al T8 preovulatorio, i corpi lutei e marcatori morfologici di atresia follicolare, inclusi i zona pellucida remnants (ZPRs). La nanoCT ha inoltre consentito la quantificazione, la localizzazione spaziale e la valutazione della vitalità dei follicoli dal T3 al T8.
L’analisi dei volumi 3D ha rivelato una distribuzione quantitativamente simmetrica dei follicoli in base allo stadio di sviluppo e allo stato atretico, suggerendo un’omogenea regolazione dei processi di reclutamento e crescita. Tale simmetria si instaura in età prepuberale e viene mantenuta durante l’età adulta e l’invecchiamento, nonostante la riduzione del numero di follicoli associata all’età. La nanoCT è una tecnica non distruttiva, che preserva l’integrità tissutale per analisi successive.
A questo scopo, è stato ottimizzato un protocollo di sezionamento e colorazione per la microscopia confocale, al fine di visualizzare l’organizzazione della cromatina degli oociti, un parametro associato all’attività trascrizionale. Tecniche di co-registrazione hanno permesso di integrare la distribuzione spaziale degli oociti e i loro stati cromatinici nelle ricostruzioni 3D, associandoli a condizioni fisiologiche quali crescita, atresia e maturazione funzionale. L’approccio, validato in ovari di 25 giorni di età, è estendibile alle altre età studiate per il completamento dell’atlante 4D.
I dati quantitativi ottenuti mediante nanoCT hanno inoltre consentito un approccio matematico alla descrizione della follicologenesi. In particolare, il processo dai 19 giorni ai 4 mesi di età è stato modellizzato come una finite-state machine per stimare i tassi di transizione tra gli stadi follicolari. Questo modello ha permesso di individuare regole matematiche alla base del mantenimento della simmetria ovarica. I tassi di transizione stimati, analizzati per settori anatomici, hanno suggerito l’esistenza di un legame tra le dinamiche di crescita ed eliminazione follicolare e la conservazione della simmetria spaziale.
Considerando l’elevato impegno richiesto dall’analisi manuale dei dataset nanoCT, la parte finale della tesi presenta risultati preliminari di proof-of-concept per la realizzazione di un modello di deep learning in grado di segmentare i follicoli e di classificarli nelle diverse tipologie.
In conclusione, questa tesi propone una pipeline multimodale per la costruzione di un atlante digitale morfo-funzionale 4D dell’ovario di topo, fornendo nuove informazioni sull’evoluzione della follicologenesi lungo l’arco della vita e aprendo la possibilità di applicazioni a condizioni patologiche e ad altre specie.The World Health Organization (WHO) defines infertility as a disease affecting approximately 15-20% of couples, with female factors accounting for more than one-third of cases. Expanding our knowledge of the ovary, folliculogenesis, and oocyte maturation is therefore crucial for developing effective infertility treatments. In particular, there is a growing need to investigate ovarian structure and dynamics in a three-dimensional (3D) context, overcoming the limitations of traditional two-dimensional analyses. A 3D approach enables a more comprehensive understanding of the complex processes governing follicle maturation.
Within this framework, this thesis aims to optimise a multimodal pipeline for the generation of a 4D digital atlas of the mouse ovary, describing morphological and functional changes from birth to adulthood and throughout ageing, and integrating these data into comprehensive 3D reconstructions.
Fixed and paraffin-embedded ovaries were analysed using nano-Computed Tomography (nanoCT), an X-ray imaging technique enabling isotropic 3D reconstructions at high resolution (0.85-0.25 μm/pixel). This approach allowed the identification of all follicle stages, from primordial T1 to preovulatory T8, as well as corpora lutea. Morphological markers of follicular atresia were also detected, including zona pellucida remnants (ZPRs). NanoCT enabled quantification and spatial localisation of follicles from T3 to T8 and assessment of their viability.
Analysis of the 3D volumes revealed a quantitatively symmetric distribution of follicles by developmental stage and atretic status, suggesting homogeneous regulation of recruitment and growth dynamics. This symmetry was established during the prepubertal period and maintained throughout adulthood and ageing, despite the age-related decline in follicle numbers. Importantly, nanoCT is a non-destructive technique, preserving tissue integrity for subsequent analyses.
Accordingly, a protocol for sectioning and staining was optimised for confocal microscopy to visualise oocyte chromatin organisation, a parameter associated with transcriptional activity. Co-registration techniques enabled integration of oocyte spatial distribution and chromatin states into the 3D reconstructions, linking them to physiological conditions such as growth, atresia, and maturation. This approach, validated in 25 days post birth ovaries, supports its extension to other ages for 4D atlas completion.
Quantitative data derived from nanoCT also enabled a mathematical approach to describe folliculogenesis. Specifically, this process, from 19 days to 4 months of age, was modelled as a finite-state machine, with the goal of estimating transition rates between follicle stages. This model provided insight into the mathematical rules underlying the maintenance of ovarian symmetry. The estimated transition rates, when analysed across anatomical sectors, suggested a link between follicle growth, elimination, and the preservation of spatial symmetry.
Manual analysis of nanoCT datasets required substantial effort for follicle classification, annotation, and localisation, highlighting the need for automated methods. For this reason, the final part of this thesis presents preliminary proof-of-concept results for the development of a deep learning model capable not only of segmenting follicles but also of classifying them into their respective types.
In conclusion, this thesis presents a multimodal pipeline for the construction of a 4D digital morpho-functional atlas of the mouse ovary.
Its application has provided new and detailed insights into the evolution of folliculogenesis across the lifespan. Furthermore, this approach opens the possibility of extending functional analyses to all investigated ages to complete the atlas, applying it to ovarian pathological conditions, and adapting it to other species
A machine-learning approach for classifying fluvial sandbody types from vertical facies sequences using geological analogues
No full text
