In this work, we propose a novel Biased Random-Key Genetic Algorithm (BRKGA) to solve the Maximum Flow with Minimum Number of Labels (MF-ML) problem, a challenging NP-Complete variant of the classical Maximum Flow problem defined on graphs in which arcs have both capacities and labels assigned. Labels give a qualitative characterization of each connection, in contexts where a solution that is as homogeneous as possible is sought. The MF-ML problem aims to maximize the flow from a source to a sink on a capacitated network while minimizing the number of distinct arc labels used, a modeling framework with applications such as water purification in distribution systems. Our proposed algorithm encodes solutions as random-key vectors, which are decoded into feasible solutions. The BRKGA demonstrates superior performance when compared to a Skewed Variable Neighborhood Search (VNS) approach previously proposed to solve MF-ML. In particular, on the largest considered graphs, BRKGA-MFML outperformed VNS in 55 out of 81 scenarios, with an average improvement per scenario that reaches 7.18%.

The ability of network users to influence other users’ behavior has deep implications for fields such as marketing, epidemiology, misinformation control, and cybersecurity. While traditional models have extensively studied the cascading effects of influence without considering the speed of propagation, this work highlights methodologies that account for this aspect, reviewing the recent advancements in the study of rapid influence (i.e., influence propagation limited to a fixed number of hops or within a minimal time frame from the initial seed set). We provide a comprehensive review of the different variants of this problem studied in the literature, discussing both the theoretical aspects and practical implications, as well as the proposed solution approaches.

In this contribution, we provide an overview of the EMM (Earth and Mars Research Network) research infrastructure, outlining its main components and the potential scientific products that can be derived through its use. The presentation delves into selected aspects in greater detail, particularly where they resonate with the multiple scientific and technological challenges associated with the FORUM mission.

Group 3 (G3) is one of the most common and aggressive subtypes of the paediatric cerebellar tumour Medulloblastoma (MB), primarily driven by the MYC oncogene. The challenging targeting of MYC, coupled with gaps in understanding G3 MB molecular bases, has hindered the development of targeted therapies. The unconventional oncogenic roles of long noncoding RNAs (lncRNAs) offer opportunities to address this complexity, to provide insights and to identify novel targets. Using -omics approaches and molecular/cellular assays, we elucidate the mode-of-action of lncMB3, a MYC-dependent, anti-apoptotic lncRNA in G3 MB. LncMB3 regulates the TGF-beta pathway, critically altered in G3 medulloblastomagenesis, via direct binding and translational inhibition of the mRNA for the epigenetic factor HMGN5. This regulatory axis affects apoptosis through photoreceptor lineage genes, including the G3 driver OTX2. The synergistic effects between lncMB3 targeting and cisplatin treatment underscore the relevance of this network. Additionally, we propose novel ferritin-based nanocarriers for the efficient delivery of antisense oligonucleotides against lncMB3. LncMB3 crucially links MYC amplification and apoptosis inhibition through a circuit involving RNA-based mechanisms, G3 MB key determinants and underexplored factors. This integrated framework deepens the understanding of G3 MB landscape and supports the potential for translating lncRNA research into future applications.

Supporto 3D

Il presente volume raccoglie i long abstracts dei contributi presentati durante la quinta edizione della “Young Applied Mathematicians Conference” (YAMC, www.yamc.it). Ospitato dal Dipartimento di Ingegneria Civile, Edile e Ambientale (DICEA) dell’Università di Padova, in collaborazione con il Dipartimento di Matematica “Tullio Levi-Civita”, il convegno si è svolto dal 22 al 26 settembre 2025. L’edizione ha riunito 108 partecipanti provenienti da 52 università e centri di ricerca di 12 Paesi, coinvolgendo principalmente giovani ricercatori, tra dottorandi e post-doc.

We present a comprehensive and automated methodology for processing two-dimensional X-ray diffraction (2D-XRD) patterns. The proposed workflow involves three sequential stages: (i) precise localization of the diffraction center, (ii) removal of high-frequency noise, and (iii) suppression of non-physical background signals. This method enables improved data quality for subsequent quantitative analysis such as radial integration, phase identification, and structural refinement. Application to experimental datasets from both the Synchrotron Radiation Facility and a table-top X-ray diffractometer demonstrates the method’s robustness, accuracy, and computational efficiency.

We report a numerical study addressing the dynamics of compound vesicles confined in a channel under shear flow. The system comprises a smaller vesicle embedded within a larger one and can be used to mimic, for example, leukocytes or nucleate cells. A two-dimensional model, which combines molecular dynamics and mesoscopic hydrodynamics including thermal fluctuations, is adopted to perform an extended investigation. We are able to vary independently the swelling degree and the relative size of vesicles, the viscosities of fluids internal and external to vesicles, and the Capillary number, so to observe a rich dynamical phenomenology which goes well beyond what observed for single vesicles, matching quantitatively with experimental findings. Tank-treading, tumbling, and trembling motions are enriched by dynamical states where inner and outer vesicles can perform different motions. We show that thermal fluctuations are crucial during trembling and swinging dynamics, as observed in experiments. Undulating motion of the external vesicle, characterized by periodic oscillation of the inclination and buckling of the membrane, is observed at high filling fractions. This latter state exhibits features that are shown to depend on the relative size, the swelling degree of both vesicles as well as on thermal noise lacking in previous analytical and numerical studies.

Background: The expression of imprinted genes, which depends on their gamete of origin, is regulated by DNA sequences characterized by differential methylation between the maternal and paternal alleles (also known as germline differentially methylated regions or gDMRs). The most common molecular defect associated with Beckwith-Wiedemann syndrome (BWS), a condition linked to overgrowth and tumours, is the loss of methylation of the KCNQ1OT1-TSS gDMR located on chromosome 11p15.5 (also known as IC2 LoM). Approximately one-third of BWS patients with IC2 LoM exhibit multi-locus imprinting disturbances (MLID). While maternal-effect variants in proteins of the oocyte subcortical maternal complex (SCMC) have been linked to MLID, the underlying mechanisms and health impact of this epigenetic disturbance remain unclear. Results: We used the Infinium EPIC methylation array to investigate whole-genome CpG methylation in 64 BWS patients with IC2 LoM and 37 control subjects. We distinguished two patient groups, one with a variable methylation level of 24 gDMRs and the other with single-locus IC2 LoM. We observed that the mothers of the former patient group carried more variants in maternal-effect genes than those of the latter group, and 50% of them, but none of the latter group had variants in the SCMC genes. Additionally, in the former group, the mothers were older at the time of pregnancy, and the patients showed higher variation in methylation levels of thousands of CpGs located in non-imprinted loci, including protochaderins and cancer-associated genes. We found no differences in clinical features or in the incidence of assisted reproductive technology between the two patient groups. However, multiple affected siblings and recurrent miscarriages were observed only among cases with biallelic maternal-effect SCMC gene variants. Conclusions: This study demonstrates that the BWS patients with MLID exhibit highly variable methylation changes that affect both imprinted and non-imprinted loci in a seemingly stochastic manner throughout the genome. These findings support the hypothesis that MLID results from the interaction of maternal-effect genes and environmental factors in aged oocytes, leading to disordered DNA methylation in the whole genome. Future research should investigate whether and how these epimutations impact the health of affected individuals, particularly in adulthood.

The immune regulatory defects that promote neuroinflammation in multiple sclerosis (MS) remain unclear. We show that a specific regulatory T (Treg) cell subpopulation expressing Notch3 was increased in individuals with MS and in mice with experimental autoimmune encephalomyelitis (EAE). Notch3+ Treg cells were induced by the gut microbiota via Toll-like receptor (TLR)-dependent mechanisms. They then translocated to the central nervous system (CNS) in EAE where they promoted disease severity. Notch3 interacted with delta-like ligand 1 (DLL1) on microglia to subvert Treg cells into T helper 17 (Th17) cells. Notch3 deletion in Treg cells prevented EAE onset by stabilizing Treg cells and by simultaneously promoting the expansion of a tissue-resident Treg cell population that expressed neuropeptide Y receptor 1 (NPY1R) and which suppressed pathogenic IFN-γ+ and GM-CSF+ T cells. Our studies thus identify altered Treg cell population dynamics as a fundamental pathogenic mechanism in autoimmune neuroinflammation.

Background: Genomic imprinting is required for normal development, and abnormal methylation of differentially methylated regions (iDMRs) controlling the parent of origin-dependent expression of the imprinted genes has been found in congenital disorders affecting growth, metabolism, neurobehavior, and in cancer. In most of these cases the cause of the imprinting abnormalities is unknown. Also, these studies have generally been performed on a limited number of CpGs, and a systematic investigation of iDMR methylation in the general population is lacking. Results: By analysing a vast number of either in-house generated or online available whole-genome methylation array datasets of unaffected individuals, and patients with complex and rare disorders, we determined the most common iDMR methylation profiles in a large population and identified many genetic and non-genetic factors contributing to their variability in blood DNA. We found that methylation variability was not homogeneous within the iDMRs and that the CpGs closer to the ZFP57 binding sites are less susceptible to methylation changes. We demonstrated the methylation polymorphism of three iDMRs and the atypical behaviour of several others, and reported the association of 25 disease- and 47 non-disease-complex traits as well as 15 Mendelian and chromosomal disorders with iDMR methylation changes. The most significantly associated complex traits included ageing, intracytoplasmic sperm injection, African versus European ancestry, female sex, pre- and postnatal exposure to pollutants and blood cell type compositions, while the associated genetic diseases included Down syndrome and the developmental disorders with molecular defects in the DNA methyltransferases DNMT1 and DNMT3B, H3K36 methyltransferase SETD2, chromatin remodelers SRCAP and SMARCA4 and transcription factor ADNP. Conclusions: These findings identify several genetic and non-genetic factors including new genes associated with genomic imprinting maintenance in humans, which may have a role in the aetiology of the diseases with imprinting abnormalities and have clear implications in molecular diagnostics.

Background: Splenomegaly represents a frequent non-infectious manifestation in Common Variable Immunodeficiency (CVID) and associates with specific clinical and immunophenotypic characteristics. Objective: To investigate the association between splenomegaly, infections, and immunophenotype in CVID patients. Methods: A cohort of 32 CVID patients (13 with splenomegaly) was enrolled. Infectious workup encompassed a detailed medical history and data derived from routine diagnostic assessments including specific virological analysis of blood and stool samples, and QuantiFERON assay for tuberculosis. Immunophenotype was assessed by multiparametric flow cytometry. Statistical analyses were performed using Prism and Jamovi software. Results: CMV viraemia was detected in 40 % of splenomegalic CVID (sCVID) and was absent in non-sCVID patients. Of all infectious agents, CMV was the only one associated with splenomegaly (p = 0.009). The inclusion of CMV replication as a causative factor for splenomegaly in CVID is in line with the knowledge that splenomegaly is a hallmark of acute CMV infection and could help explain in the present CVID cohort 75 % of otherwise unexplained splenomegalies. Flow cytometric analysis in sCVID vs. non-sCVID confirmed decreases in NK cell numbers and activation, in circulating inflammatory precursors (Lin−CD16+), and increased T cell activation as defined by HLA-DR/CD69/CD38 expression. Conclusion: Splenomegaly in CVID patients may associate also with CMV replication. The combined identification in CMV+ sCVID of NK cell, inflammatory precursor and T cell imbalances suggests a possible combined cellular defect at precursor level in a subset of sCVID patients. When integrated into everyday clinical management, CMV viraemia could become a useful additional parameter for patient characterization and stratification.

TBX1, a T-box transcription factor, is essential for pharyngeal apparatus development and marks cardiopharyngeal mesoderm (CPM) in various species. However, in mammals, we have an incomplete knowledge of the molecular pathways driving CPM diversification and of the role of TBX1 in this context. Using CPM-relevant in vitro differentiation of wild-type and Tbx1−/− mouse embryonic stem cells, we performed simultaneous single-nucleus RNA-seq and ATAC-seq at two stages, validated findings in embryos, and found that TBX1 loss affects gene expression and chromatin remodeling in a cell subpopulationspecific manner. TBX1 regulates chromatin accessibility and gene expression of distinct and evolutionarily conserved transcriptional modules for branchiomeric and cardiac development, and for tissue morphogenesis. Computational analyses predicted a feed-forward regulatory relationship between TBX1 and SIX factors. Notably, selected Tbx1 mutant CPM cell populations showed an altered differentiation trajectory, exhibiting activation of a mesothelial-like transcriptional program. We also observed cell death later in development. Thus, TBX1 is crucial for maintaining CPM transcriptional identity.

Electrical stimulation (ES) is widely employed in both clinical therapies and research settings where it has shown promise in promoting tissue regeneration, wound healing, and inflammation control. Research has also highlighted ES as a regulator of DNA demethylation, which plays a critical role in nerve regeneration and cellular repair mechanisms. While the impact of ES on epigenetic processes is recognized, its broader effects on cellular functions, particularly in inflammation and wound healing, are less understood. We recently showed how ES impacts inflammatory states by modulating transcriptomic and metabolomic profiles in a 3Din vitromodel where human fibroblasts and keratinocytes are included in a collagen matrix, i.e., even in the absence of the nervous system. Here, we propose to deepen our exploration on the differential effects on DNA methylation, including an investigation of the correlation with age acceleration using a mitotic clock. These results confirm and caution on the differential effect of DC on inflamed and non-inflamed samples and suggest an involvement of direct current stimuli at 1 V ((Formula presented.)) in the control of senescent processes associated with mitosis and inflammation; the mechanistic details of these will have to be clarified with additional experiments.

The paper focuses on the improvement of the existing nsparse Nagasaka et al. algorithm and its extension to the multi-GPU setting for the application of real engineering problems. In this work, we propose a distributed multi-GPU framework for SpGEMM that is designed specifically for the nsparse like algorithms. The results show similar to 2 times speed-up for nsparse and close to ideal scalability of the multi-GPU extension with the number of GPUs. Finally, we test the proposed algorithm in the AMG setting by computing the double SpGEMM product.

Linear solvers are key components in any software platform for scientific and engineering computing. The solution of large and sparse linear systems lies at the core of physics-driven numerical simulations relying on partial differential equations (PDEs) and often represents a significant bottleneck in data-driven procedures, such as scientific machine learning. In this paper, we present an efficient implementation of the preconditioned s-step Conjugate Gradient (CG) method, originally proposed by Chronopoulos and Gear in 1989, for large clusters of Nvidia GPU-accelerated computing nodes. The method, often referred to as communication-reduced or communication-avoiding CG, reduces global synchronizations and data communication steps compared to the standard approach, enhancing strong and weak scalability on parallel computers. Our main contribution is the design of a parallel solver that fully exploits the aggregation of low-granularity operations inherent to the s-step CG method to leverage the high throughput of GPU accelerators. Additionally, it applies overlap between data communication and computation in the multi-GPU sparse matrix-vector product. Experiments on classic benchmark datasets, derived from the discretization of the Poisson PDE, demonstrate the potential of the method.

Many paintings from the 19th century have exhibited signs of fading and discoloration, often linked to cadmium yellow, a pigment widely used by artists during that time. In this work, we develop a mathematical model of the cadmium sulfide photo catalytic reaction responsible for these damages. By employing nonlo cal integral operators, we capture the interplay between chemical processes and environmental factors, offering a detailed representation of the degradation mechanisms. Furthermore, we present a second order positivity-preserving numerical method designed to accurately simulate the phenomenon and ensure reliable predictions across different scenarios, along with a comprehensive sensitivity analysis of the model.

In this work, we focus on the computation of the zeros of a monic Laguerre–Sobolev orthogonal polynomial of degree n. Taking into account the associated four–term recurrence relation, this problem can be formulated as a generalized eigenvalue problem, involving a lower bidiagonal matrix and a 2–banded lower Hessenberg matrix of order n. Unfortunately, the considered generalized eigenvalue problem is very ill–conditioned, and classical balancing procedures do not improve it. Therefore, customary techniques for solving the generalized eigenvalue problem, like the QZ method, yield unreliable results. Here, we propose a novel balancing procedure that drastically reduces the ill–conditioning of the eigenvalues of the involved matrix pencil. Moreover, we propose a fast and reliable algorithm, with O(n2) computational complexity and O(n) memory, exploiting the structure of the considered matrix pencil.

A fast and weakly stable method for computing the zeros of a particular class of hypergeometric polynomials is presented. The studied hypergeometric polynomials satisfy a higher order differential equation and generalize Laguerre polynomials. The theoretical study of the asymptotic distribution of the spectrum of these polynomials is an active research topic. In this article we do not contribute to the theory, but provide a practical method to contribute to further and better understanding of the asymptotic behavior. The polynomials under consideration fit into the class of Sobolev orthogonal polynomials, satisfying a four–term recurrence relation. This allows computing the roots via a generalized eigenvalue problem. After condition enhancing similarity transformations, the problem is transformed into the computation of the eigenvalues of a comrade matrix, which is a symmetric tridiagonal modified by a rank–one matrix. The eigenvalues are then retrieved by relying on an existing structured rank based fast algorithm. Numerical examples are reported studying the accuracy, stability and conforming the efficiency for various parameter settings of the proposed approach.

We consider equations of the type: (Formula presented) , for general linear operators R in any spatial dimension. We prove that such equations almost always exhibit finite-time singularities for smooth and localised solutions. Singularities can even form in settings where solutions dissipate an energy. Such equations arise naturally as models in various physical settings such as inviscid and complex fluids.