University of Insubria

Abstract Recent observations from the James Webb Space Telescope have revealed unexpectedly luminous galaxies, exhibiting stellar masses and luminosities significantly higher than predicted by theoretical models at Cosmic Dawn. In this study, we present a suite of cosmological zoomed-in simulations targeting high-redshift ( z ≥ 10) galaxies with dark matter halo masses in the range 10 10 –10 11 M ⊙ at z = 10, using state-of-the-art galaxy formation simulation codes ( Enzo , Ramses , Changa , Gadget-3 , Gadget-4 , and Gizmo ). This study aims to evaluate the convergence of the participating codes and their reproducibility of high-redshift galaxies with the galaxy formation model calibrated at relatively low redshift, without additional physics for high-redshift environments. The subgrid physics follows the AGORA CosmoRun framework, with adjustments to resolution and initial conditions to emulate similar physical environments in the early Universe. The participating codes show consistent results for key galaxy properties (e.g., stellar mass), but also reveal notable differences (e.g., metallicity), indicating that galaxy properties at high redshifts are highly sensitive to the feedback implementation of the simulation. Massive halos ( M halo ≥5 × 10 10 M ⊙ at z = 10) succeed in reproducing observed stellar masses, metallicities, and UV luminosities at 10 ≤ z ≤ 12 without requiring additional subgrid physics, but tend to underpredict those properties at higher redshift. We also find that varying the dust-to-metal ratio modestly affects UV luminosity of simulated galaxies, whereas the absence of dust significantly enhances it. In future work, higher-resolution simulations will be conducted to better understand the formation and evolution of galaxies at Cosmic Dawn.

Background/Objectives: Breastfeeding represents a critical developmental window during which maternal biology, environmental exposures, and nutrition converge to influence infant gastrointestinal health and long-term developmental trajectories. From a One Health perspective, breastfeeding can be conceptualized not as a static nutritional act, but as a dynamic and modifiable biological system in which maternal factors shape early-life microbiota assembly and immune programming. This narrative review explores how microbiota-oriented strategies during breastfeeding may foster a favorable trajectory of infant health, potentially extending to transgenerational outcomes. Methods: This narrative review is structured around a ten-point decalogue addressing interconnected domains relevant to the maternal-milk-infant microbiota axis, including maternal diet, microbial diversity, environmental exposures, psychological stress and probiotic use. Current mechanistic and clinical evidence was examined to evaluate how these domains may modulate microbiota composition and function during breastfeeding. Attention was given to probiotic supplementation, including strain specificity, timing of administration, and clinical context, as well as to the broader implications of a One Health framework. Results: Available evidence suggests that maternal nutritional patterns, environmental and psychosocial exposures, and targeted microbiota-modulation strategies may influence the composition and functional properties of human milk and the developing infant microbiota. Probiotic use during breastfeeding appears to have strain-specific and context-dependent effects, with potential benefits in selected clinical scenarios. However, findings remain heterogeneous, and uncertainties persist regarding optimal strains, timing, and long-term outcomes. Conclusions: Breastfeeding can be understood as a dynamic biological interface shaped by maternal and environmental factors. Integrating microbiota-oriented strategies within a One Health framework may support infant gastrointestinal health and possibly contribute to longer-term developmental trajectories. Nevertheless, careful interpretation of the current evidence is warranted to avoid reductionist, supplement-centered approaches and to prevent maternal overmedicalization or blame.

Through 3D hydrodynamical simulations, we explore the impact of Type Ia supernova (SN) explosions on the star formation history and chemical properties of second-generation (SG) stars in young globular clusters with masses of 10 5 −10 6 M ⊙ . We assume that the SG is formed out of the asymptotic giant branch (AGB) ejecta of first-generation stars plus pristine interstellar medium gas which is modelled as a uniform gas moving at a constant velocity towards the cluster. We tested two values for the infalling gas density of 10 −24 and 10 −23 g cm −3 . Type Ia SNe start to explode together with the release of gas from the most massive AGB stars. Three simulated models are analysed. In the low-mass and low-density scenario, we find SNe Ia quench star formation that however restarts when the gas cools down again in between two explosions. The SG stars are dominated by a He-rich population ( Y > 0.33), which is poorly diluted by pristine gas. In the high-mass models, star formation is mildly affected, while the He composition is significantly altered as exploding SNe prevent the accretion of pristine gas, and therefore extremely helium-rich stars form. In the high-density model, such weak gas accretion leads to a maximum enhancement in the helium mass fraction that is much larger than the observed one and that does not correlate with the initial cluster mass as is found in models without Type Ia SNe. As for the iron content, small spreads have been found in all models, but the SG is less homogeneous than the FG, at variance with current observations.

Facial vascularized composite allotransplantation (fVCA) is one of the most complex forms of vascularized composite allotransplantation and requires lifelong immunosuppression to ensure graft survival. Despite significant advances in surgical techniques and postoperative care over the past two decades, the true incidence of cutaneous malignancies in fVCA recipients remains poorly characterized due to the limited number of procedures, heterogeneous immunosuppressive protocols, and relatively short follow-up. This narrative review summarizes current evidence on oncologic risk in facial VCA, focusing on the effects of different immunosuppressive regimens and the challenges posed by the high immunogenicity of skin and mucosa. Available data indicate that malignancies, including cutaneous and other neoplasms, occur in approximately 10% of recipients, based on heterogeneous case-series data with immunosuppressive therapies largely extrapolated from solid organ transplantation. Calcineurin inhibitors, corticosteroids, and azathioprine are associated with increased oncologic risk, whereas mycophenolate mofetil and mTOR inhibitors may confer a more favorable profile. Overall, fVCA, unlike solid organ transplantation, is a life-enhancing procedure, highlighting the need for tailored immunosuppressive strategies, rigorous dermatologic surveillance, and further research supported by dedicated registries to better define long-term malignancy risk.

A monolithic digital Silicon Photomultiplier (SiPM) featuring 1024 microcells with a 30-micrometer pitch and a 50% fill factor has been designed in a 110-nanometer CMOS image sensor technology. The device under consideration integrates both SPAD sensors and front-end electronics in the same substrate. It can count up to 1024 photons in less than 22 ns, while assigning timestamps to the first and last detected photons with a time resolution of less than 100 ps. A parallel counter structure combined with a fast adder tree provides photon counting in digital form with low latency, whereas a carefully balanced fast NAND tree ensures a fixed-pattern time uncertainty not exceeding 26 ps. The architecture incorporates in-pixel memory for individual cell disabling and configurable thresholding on the timing signal for noise mitigation. In order to optimize the fill factor, a part of the electronics is placed outside the array, while the most sensitive elements of the timing and counting circuits are laid out close to the sensor, in the SPAD array. A serial readout is employed to provide a single output connection per SiPM, thereby simplifying system integration.

Accurate classification of ovarian masses is crucial for clinical decision-making. B-mode ultrasound is widely used for imaging adnexal masses, yet complex structures can be difficult to differentiate. We propose a deep learning framework integrating radiomics and mass substructure analysis to enhance diagnostic accuracy. A retrospective cohort of 230 patients with adnexal masses that were imaged via routine ultrasound and subsequently underwent surgery (or had at least 10months of follow-up) were included in this study. Our deep learning model first automatically segments adnexal masses and separately distinguishes fluid and solid components. Next, our multi-modal classification network differentiates benign from malignant adnexal masses. Additionally, we developed an explainability method that enhances clinical interpretability by identifying the top training samples that are the most similar to test cases using feature embedding similarity. Our framework achieved 90% accuracy and 94% AUC at the image level, and 91% accuracy and 92% AUC at the patient level, demonstrating improved classification performance compared to ADNEX (77% accuracy, 92% AUC), O-RADS 2019 (84% accuracy, 89% AUC), and O-RADS 2022 (80% accuracy, 88% AUC). This approach will enable exploring clinical applications where AI assistance can provide malignancy predictions along with visualizations of similar historical cases to enhance decision-making.

Abstract Sequences of block matrices with rectangular Toeplitz blocks arise in several applications, including the numerical discretization of differential problems. We compute the (asymptotic) spectral and singular value distribution of these sequences in the case where the asymptotic block size ratios are not necessarily rational as in [A. Adriani, I. Furci, C. Garoni, and S. Serra-Capizzano, Spectral and singular value distribution of sequences of block matrices with rectangular Toeplitz blocks. Part I: Asymptotically rational block size ratios. J. Numer. Math. DOI: 10.1515/jnma-2025-0091]. Our derivation relies on the recent notion of generalized approximating classes of sequences as well as on a functional-based approach to describe the spectral and singular value distributions. The distribution result is illustrated through numerical experiments, one of which is inspired by the finite element approximation of a system of differential equations.

Brine pockets embedded within Antarctic permafrost and subglacial environments represent natural laboratories for studying microbial life under polyextreme conditions—high salinity, sub-zero temperatures, and oligotrophy. These analogues to extraterrestrial environments, such as the sub-ice oceans of Europa or the briny regolith of Mars, are crucial to astrobiological investigations looking to define the limits of life. As part of the Italian National Research Programme in Antarctica (PNRA) in the framework of the CLICPERECO project, a structured sampling campaign was conducted in the Tarn Flat (TF) area of Northern Victoria Land, where multiple brine inclusions were discovered and sampled. Samples were collected from a triangular sampling grid with vertices TF1, TF2, and TFB, each 18 meters apart, and from a central point (TF3) at three depths: 380, 460, and 510 cm (TF3-380, TF3-460, TF3-510), along with a sediment sample at the lake bottom (SED-TF3). DNA was extracted using the DNeasy PowerSoil Kit, followed by 16S rRNA gene amplicon sequencing on the Illumina HiSeqX platform. Taxonomic assignment was performed using the SILVA 138.1 database. The prokaryotic community displayed substantial spatial and vertical heterogeneity. Across all samples, Actinomycetota, Bacteroidota, and Proteobacteria were the dominant phyla. In the triangular grid, Actinomycetota reached over 32% at TF1 and TFB, while Cyanobacteriota dominated TF2 (29.4%), suggesting influence from light exposure or surface dynamics. In the central borehole, clear depth-related stratification was observed. Actinomycetota decreased from 48.9% at TF3-380 to 14.6% at TF3-510, whereas anaerobic lineages like Thermodesulfobacteriota (from 0.02% to 4.3%) and Campylobacterota (up to 2.1%) increased with depth, indicating a shift toward more reduced conditions. At the genus level, “Candidatus Aquiluna” and Ilumatobacter dominated surface layers, while deep samples harbored sulfate reducers such as Desulfoconvexum, Desulfuromusa, and Geopsychrobacter. The genus Thiomicrorhabdus surged from 11.6% at 460 cm, further indicating sulfur-driven metabolisms in deeper brines. The detection of high abundances of Patescibacteria (up to 7.5% at TF3-460), a superphylum comprising ultra-small, often symbiotic bacteria, suggests that deep brine ecosystems may support complex, syntrophic microbial interactions.These findings highlight the presence of stratified, diverse microbial consortia finely tuned to microenvironmental gradients within analysed brines. The ecological novelty and functional potential of these communities extend the known boundaries of microbial life on Earth and offer compelling analogies for life detection strategies beyond our planet. Future work integrating metagenomics, metabolomics, and in situ geochemical measurements will be crucial to uncover the evolutionary and adaptive mechanisms underlying life in these cryo-habitats.