A Preliminary Analysis of Software Metrics in Decentralised Applications

This study examines software metrics in decentralized applications (dApps) to analyze their structural and behavioral characteristics as they grow in complexity. Sixty dApps were categorized into Small (3 to 29 contracts), Medium (30 to 46 contracts), and Large (47 to 206 contracts) based on their contract count. Initial analysis showed a non-normal data distribution, leading to the use of Spearman's correlation method. Findings revealed that Medium dApps have strong correlations between metrics like 'Average Local Variables' and 'Maximum Local Variables', while Large dApps show higher correlations between 'Number of Functions' and 'State Variable Count', indicating more complex contract structures. The higher Coupling Between Objects (CBO) in large dApps suggests increased interactions with other contracts or libraries, potentially elevating security risks. These insights are valuable for developers and stakeholders in the blockchain and IoT sectors, aiding in understanding how dApps evolve with increasing complexity and the implications on software metric relationships.Ethereum Foundation grant FY23-1048

MindTheDApp: A Toolchain for Complex Network-Driven Structural Analysis of Ethereum-based Decentralised Applications

This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach. Unlike existing tools, our toolchain combines the power of ANTLR4 and Abstract Syntax Tree (AST) traversal techniques to transform the architecture and interactions within smart contracts into a specialized bipartite graph. This enables advanced network analytics to highlight operational efficiencies within the DApp’s architecture. The bipartite graph generated by the proposed tool comprises two sets of nodes: one representing smart contracts, interfaces, and libraries, and the other including functions, events, and modifiers. Edges in the graph connect functions to smart contracts they interact with, offering a granular view of interdependencies and execution flow within the DApp. This network-centric approach allows researchers and practitioners to apply complex network theory in understanding the robustness, adaptability, and intricacies of decentralized systems. Our work contributes to the enhancement of security in smart contracts by allowing the visualisation of the network, and it provides a deep understanding of the architecture and operational logic within DApps. Given the growing importance of smart contracts in the blockchain ecosystem and the emerging application of complex network theory in technology, our toolchain offers a timely contribution to both academic research and practical applications in the field of blockchain technology.10.13039/501100015595-Ethereum Foundation (Grant Number: FY23-1048

RBM20 Mutations Induce an Arrhythmogenic Dilated Cardiomyopathy Related to Disturbed Calcium Handling

BACKGROUND: Mutations in RBM20 (RNA-binding motif protein 20) cause a clinically aggressive form of dilated cardiomyopathy, with an increased risk of malignant ventricular arrhythmias. RBM20 is a splicing factor that targets multiple pivotal cardiac genes, such as Titin (TTN) and CAMK2D (calcium/calmodulin-dependent kinase II delta). Aberrant TTN splicing is thought to be the main determinant of RBM20-induced dilated cardiomyopathy, but is not likely to explain the increased risk of arrhythmias. Here, we investigated the extent to which RBM20 mutation carriers have an increased risk of arrhythmias and explore the underlying molecular mechanism

Titin circular RNAs create a back-splice motif essential for SRSF10 splicing

Background: Titin (TTN), the largest protein in humans, forms the molecular spring that spans half of the sarcomere to provide passive elasticity to the cardiomyocyte. Mutations that disrupt the TTN transcript are the most frequent cause of hereditary heart failure. We showed before that TTN produces a class of circular RNAs (circRNAs) that depend on RBM20 to be formed. In this study we show that the backsplice junction formed by this class of circRNAs creates a unique motif, which binds SRSF10 to enable it to regulate splicing. Furthermore, we show that one of these circRNAs (cTTN1) distorts both localization of and splicing by RBM20. Methods: We calculated genetic constraint of the identified motif in 125.748 exomes collected from the gnomAD database. Furthermore, we focused on the highest expressed RBM20-dependent circRNA in the human heart, which we named cTTN1. We used shRNAs directed to the backsplice junction to induce selective loss of cTTN1 in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). Results: Human genetics suggests reduced genetic tolerance of the generated motif, indicating that mutations in this motif might lead to disease. RNA immunoprecipitation confirmed binding of circRNAs with this motif to SRSF10. Selective loss of cTTN1 in hiPSC-CM induced structural abnormalities, apoptosis and reduced contractile force in engineered heart tissue. In line with its SRSF10 binding, loss of cTTN1 caused abnormal splicing of important cardiomyocyte SRSF10 targets like MEF2A and CASQ2. Strikingly, loss of cTTN1 also caused abnormal splicing of TTN itself. Mechanistically, we show that loss of cTTN1 distorts both localization of and splicing by RBM20. Conclusions: We demonstrate that circRNAs formed from the TTN transcript are essential for normal splicing of key muscle genes by enabling splice regulators RBM20 and SRSF10. This shows that the TTN transcript also has regulatory roles, besides its well-known signaling and structural function. In addition, we demonstrate that the specific sequence created by the backsplice junction of these circRNAs has important functions. This highlights the existence of functionally important sequences that cannot be recognized as such in the human genome, but provides a yet unrecognized source for functional sequence variation

Staphylococcus aureus Keratinocyte Invasion Is Dependent upon Multiple High-Affinity Fibronectin-Binding Repeats within FnBPA

Staphylococcus aureus is a commensal organism and a frequent cause of skin and soft tissue infections, which can progress to serious invasive disease. This bacterium uses its fibronectin binding proteins (FnBPs) to invade host cells and it has been hypothesised that this provides a protected niche from host antimicrobial defences, allows access to deeper tissues and provides a reservoir for persistent or recurring infections. FnBPs contain multiple tandem fibronectin-binding repeats (FnBRs) which bind fibronectin with varying affinity but it is unclear what selects for this configuration. Since both colonisation and skin infection are dependent upon the interaction of S. aureus with keratinocytes we hypothesised that this might select for FnBP function and thus composition of the FnBR region. Initial experiments revealed that S. aureus attachment to keratinocytes is rapid but does not require FnBRs. By contrast, invasion of keratinocytes was dependent upon the FnBR region and occurred via similar cellular processes to those described for endothelial cells. Despite this, keratinocyte invasion was relatively inefficient and appeared to include a lag phase, most likely due to very weak expression of α5β1 integrins. Molecular dissection of the role of the FnBR region revealed that efficient invasion of keratinocytes was dependent on the presence of at least three high-affinity (but not low-affinity) FnBRs. Over-expression of a single high-affinity or three low-affinity repeats promoted invasion but not to the same levels as S. aureus expressing an FnBPA variant containing three high-affinity repeats. In summary, invasion of keratinocytes by S. aureus requires multiple high-affinity FnBRs within FnBPA, and given the importance of the interaction between these cell types and S. aureus for both colonisation and infection, may have provided the selective pressure for the multiple binding repeats within FnBPA

Characterization of the circRNome in the heart: A bioinformatic approach

In this thesis, we performed studies that add new insights into the biology of circular RNAs (circRNAs) in the heart. We characterized the human circRNA landscape in the heart from RNA-sequencing data and identified thousands of circRNAs, with some of them regulated in disease. We found that an unusually high number of circRNAs are produced from the Titin (TTN) gene and show that RNA binding motif 20 (Rbm20)-dependent exon skipping within Ttn's I-band region is associated with circRNA formation. We performed RNA-sequencing on mouse (wildtype and Rbm20 knockout) hearts to investigate Rbm20-regulated circRNA production. We show that the tight correlation between Rbm20-mediated exon skipping and circRNA formation observed in the Ttn gene does not appear a common mechanism for Rbm20 target genes, indicating that circRNA formation is not a general function of Rbm20. In addition, integrated analyses of alternative splicing and circRNA production in human and mouse hearts revealed that alternative splicing only accounts for a small proportion (~10%) of the circRNAs, with the vast majority of the circRNAs arising from constitutive exons indicating that these circRNAs are generated at the expense of their linear counterpart. Finally, we present circRNAprofiler, an R-based computational framework for a comprehensive in silico analysis of identified circRNAs. CircRNAprofiler covers different aspects of circRNA analysis ranging from differential expression analysis, genomic context, evolutionary conservation, biogenesis to functional analysis. The results obtained by running the circRNA analysis workflow implemented by circRNAprofiler can serve as a starting point for further investigation in the role of specific circRNAs in any physiological and pathological condition

Characterization of the circRNome in the heart:A bioinformatic approach

In this thesis, we performed studies that add new insights into the biology of circular RNAs (circRNAs) in the heart. We characterized the human circRNA landscape in the heart from RNA-sequencing data and identified thousands of circRNAs, with some of them regulated in disease. We found that an unusually high number of circRNAs are produced from the Titin (TTN) gene and show that RNA binding motif 20 (Rbm20)-dependent exon skipping within Ttn's I-band region is associated with circRNA formation. We performed RNA-sequencing on mouse (wildtype and Rbm20 knockout) hearts to investigate Rbm20-regulated circRNA production. We show that the tight correlation between Rbm20-mediated exon skipping and circRNA formation observed in the Ttn gene does not appear a common mechanism for Rbm20 target genes, indicating that circRNA formation is not a general function of Rbm20. In addition, integrated analyses of alternative splicing and circRNA production in human and mouse hearts revealed that alternative splicing only accounts for a small proportion (~10%) of the circRNAs, with the vast majority of the circRNAs arising from constitutive exons indicating that these circRNAs are generated at the expense of their linear counterpart. Finally, we present circRNAprofiler, an R-based computational framework for a comprehensive in silico analysis of identified circRNAs. CircRNAprofiler covers different aspects of circRNA analysis ranging from differential expression analysis, genomic context, evolutionary conservation, biogenesis to functional analysis. The results obtained by running the circRNA analysis workflow implemented by circRNAprofiler can serve as a starting point for further investigation in the role of specific circRNAs in any physiological and pathological condition

Development of a reduced order model for fuel burnup analysis

Fuel burnup analysis requires a high computational cost for full core calculations, due to the amount of the information processed for the total reaction rates in many burnup regions. Indeed, they reach the order of millions or more by a subdivision into radial and axial regions in a pin-by-pin description. In addition, if multi-physics approaches are adopted to consider the effects of temperature and density fields on fuel consumption, the computational load grows further. In this way, the need to find a compromise between computational cost and solution accuracy is a crucial issue in burnup analysis. To overcome this problem, the present work aims to develop a methodological approach to implement a Reduced Order Model (ROM), based on Proper Orthogonal Decomposition (POD), in fuel burnup analysis. We verify the approach on 4 years of burnup of the TMI-1 unit cell benchmark, by reconstructing fuel materials and burnup matrices over time with different levels of approximation. The results show that the modeling approach is able to reproduce reactivity and nuclide densities over time, where the accuracy increases with the number of basis functions employed

Void Coefficient Sensitivity Analysis for the Triga Mark II Reactor at L.E.N.A. (UniPV)

Sensitivity analysis studies the effect of a change in a given parameter to a response function of the system under investigation. In reactor physics, this usually translates into the study of how cross sections and fission spectrum modifications affect the value of the multiplication factor, the delayed neutron fraction or the void coefficient for example. Generalized Perturbation Theory provides a useful tool for the assessment of adjoint weighed functions such as keff and void coefficient sensitivities. In this work, the capability of SERPENT code to perform sensitivity calculation based on GPT is used to study the TRIGA Mark II research reactor installed at L.E.N.A. of University of Pavia. A general sensitivity analysis to the most important reactor’s cross sections has been performed in order to highlight the biggest reactivity contributions. Two numerically challenging tasks related to GPT calculation have been performed thanks to the relatively quick Monte Carlo approach allowed by this reactor: investigating the linearity of the reactivity injection caused by the flooding of the central channel, and calculating the fuel void coefficient sensitivity to the coolant density