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The instability of structures due to compression is one of the most critical issues related to aircraft components. Especially in composite materials, which have poor out-of-plane mechanical properties, the buckling load must be assessed to ensure that the structures are within the safe limits compared to the operating loads. In the presence of delamination, the compression instability of structures becomes catastrophic, as the propagation of delamination can dramatically reduce the stiffness of the structure almost instantaneously. During the operational life of composite aircraft components, one of the most common events that can occur is low-velocity impact with foreign objects, which is one of the primary reasons for delamination. In this paper, a sensitivity analysis is presented on a typical aerospace reinforced panel with a circular delamination, representative of an impact damage. Different configurations have been analysed, varying the radius and position along the thickness of the delamination. Furthermore, some geometric parameters of the panel have been modified to evaluate how the buckling load and the propagation of interlaminar damage evolve.

The beneficial effects of physical activity for the prevention and management of several chronic diseases are widely recognized. Mathematical modeling of the effects of physical exercise in body metabolism and in particular its influence on the control of glucose homeostasis is of primary importance in the development of eHealth monitoring devices for a personalized medicine. Nonetheless, to date only a few mathematical models have been aiming at this specific purpose. We have developed a whole-body computational model of the effects on metabolic homeostasis of a bout of physical exercise. Built upon an existing model, it allows to detail better both subjects' characteristics and physical exercise, thus determining to a greater extent the dynamics of the hormones and the metabolites considered.

Background The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology of the disease and simulates the immunological and metabolic alterations linked to type-2 diabetes subjected to clinical, physiological, and behavioural features of prototypical human individuals. Results We analysed the time course of 46,170 virtual subjects , experiencing different lifestyle conditions. We then set up a statistical model able to recapitulate the simulated outcomes. Conclusions The resulting machine learning model adequately predicts the synthetic dataset and can, therefore, be used as a computationally-cheaper version of the detailed mathematical model, ready to be implemented on mobile devices to allow self-assessment by informed and aware individuals. The computational model used to generate the dataset of this work is available as a web-service at the following address: http://kraken.iac.rm.cnr.it/T2DM .

Interleukin-6 (IL-6) has been recently shown to play a central role in glucose homeostasis, since it stimulates the production and secretion of Glucagon-like Peptide-1 (GLP-1) from intestinal L-cells and pancreas, leading to an enhanced insulin response. In resting conditions, IL-6 is mainly produced by the adipose tissue whereas, during exercise, skeletal muscle contractions stimulate a marked IL-6 secretion as well. Available mathematical models describing the effects of exercise on glucose homeostasis, however, do not account for this IL-6 contribution. This study aimed at developing and validating a system model of exercise's effects on plasma IL-6 dynamics in healthy humans, combining the contributions of both adipose tissue and skeletal muscle. A two-compartment description was adopted to model plasma IL-6 changes in response to oxygen uptake's variation during an exercise bout. The free parameters of the model were estimated by means of a cross-validation procedure performed on four different datasets. A low coefficient of variation (<10%) was found for each parameter and the physiologically meaningful parameters were all consistent with literature data. Moreover, plasma IL-6 dynamics during exercise and post-exercise were consistent with literature data from exercise protocols differing in intensity, duration and modality. The model successfully emulated the physiological effects of exercise on plasma IL-6 levels and provided a reliable description of the role of skeletal muscle and adipose tissue on the dynamics of plasma IL-6. The system model here proposed is suitable to simulate IL-6 response to different exercise modalities. Its future integration with existing models of GLP-1-induced insulin secretion might provide a more reliable description of exercise's effects on glucose homeostasis and hence support the definition of more tailored interventions for the treatment of type 2 diabetes.

The thermo-structural design of the wing leading edge of hypersonic vehicles is a very challenging task as high gradients in thermal field, and hence high thermal stresses, are expected. Indeed, when employing passive hot structures based thermal protection systems, very high temperatures (e.g., 1400 °C) are expected on the external surface of the wing leading edge, while the internal structural components are required to not exceed a few hundred degrees Celsius (e.g., 400 °C) at the interface with the internal cold structure. Hence, ceramic matrix composites (CMC) are usually adopted for the manufacturing of the external surface of the wing leading edge since they are characterized by good mechanical properties at very high temperatures (up to 1900 °C) together with an excellent thermal shock resistance. Furthermore, the orthotropic behavior of these materials together with the possibility to tailor their lamination sequence to minimize the heat transferred to internal components, make them very attractive for hot structure based thermal protection systems applications. However, the numerical predictions of the thermo-mechanical behavior of such materials, taking into account the influence of each ply (whose thickness generally ranges between 0.2 and 0.3 mm), can be very expensive from a computational point of view. To overcome this limitation, usually, sub-models are adopted, able to focus on specific and critical areas of the structure where very detailed thermo-mechanical analyses can be performed without significantly affecting the computational efficiency of the global model. In the present work, sub-modeling numerical approaches have been adopted for the analysis of the thermo-mechanical behavior of a ceramic matrix composite wing leading edge of a hypersonic vehicle. The main aim is to investigate the feasibility, in terms of computational efficiency and accuracy of results, in using sub-models for dimensioning complex ceramic matrix components. Hence, a comprehensive study on the size of sub-models and on the choice of their boundaries has been carried out in order to assess the advantages and the limitations in approximating the thermo-mechanical behavior of the investigated global ceramic matrix composite component.

Delamination in reinforced panels is one of the primary challenges facing the safety and reliability of aerospace structures. This article presents a sensitivity analysis of the fatigue behaviour during the compression of a composite aeronautical stiffened panel experiencing delamination. The main objective is to assess the impact of delamination size and depth on the lifecycle and structural integrity of the panel. Different dimensions and positions of delamination are considered to cover a comprehensive range of damage scenarios. The key feature of this sensitivity analysis is the adoption of a numerical procedure that is mesh- and load-step-independent, ensuring reliable results and providing valuable insight into the criticality of delamination and its impact on the fatigue behaviour during the compression of reinforced aeronautical panels. Sensitivity analyses are essential for enhancing the design process of aerospace structures, thereby contributing to the increased safety and reliability of structural components. In this regard, the use of robust and effective numerical procedures is of crucial significance. This may be seen as the real added value of this paper.

This work evaluates the effectiveness of commonly adopted local damage evolution methods and failure criteria in finite element analysis for the simulation of intralaminar damage propagation in composites under static loading conditions. The proposed numerical model is based on a User Defined Material subroutine (USERMAT) implemented in Ansys. This model is used to predict the evolution of damage within each specific lamina of a composite laminate by introducing both sudden and gradual degradation rules. The main purpose of the simulations is to quantitatively assess the influence of the adopted failure criteria in conjunction with degradation laws on the accuracy of the numerical predictions in terms of damage evolution and failure load. The mechanical behavior of an open hole tension specimen and of a notched stiffened composite panel under shear loading conditions have been numerically simulated by Progressive Damage Models (PDM). Different failure criteria have been implemented in the developed Ansys USERMAT, together with sudden and gradual degradation rules based on the Continuum Damage Mechanics (CDM) approach. Numerical results have been validated against experimental data to assess the effects of the different failure criteria and damage evolution law on the global mechanical response and local damage predictions in composite laminates.

Precision medicine is facing a critical transition driven by the growing complexity of biological data and the insufficient ability of current models to translate such data into clinically meaningful information. Linear, single-gene approaches are no longer adequate to explain the multifactorial nature of most modern diseases, whose phenotypes emerge from combinations of genetic, molecular, and environmental factors. Network-based precision medicine addresses this by providing a systemic framework capable of integrating heterogeneous omics data, interactomes, and clinical information to identify disease modules and novel therapeutic opportunities. The distinct novelty of this review is its focus on the potential of “network language” as the primary driver for realizing precision medicine through professional collaboration. We argue that networks are not merely tools that achieve precision “per se”; rather, their transformative power lies in their ability to serve as a shared and interpretable interface grounded in network theory. By offering this common conceptual ground, the paradigm bridges the deep cultural and methodological gaps between clinicians and data analysts, enabling effective cooperation between figures with fundamentally different, and often divergent, backgrounds. Practical tools—such as biological network analysis and Molecular Tumor Boards—demonstrate how computational modeling and clinical expertise can be successfully combined to generate actionable insights. Ultimately, network-based precision medicine represents a decisive step toward reconstructing the patient’s complexity and promoting a genuinely personalized clinical approach in which quantitative analysis and medical reasoning act synergistically through multidisciplinary integration.

We developed an approach that integrates different network-based methods to analyze the correlation network arising from large-scale gene expression data. By studying grapevine [Vitis vinifera) and tomato [Solanum lycopersicum) gene expression atlases and a grapevine berry transcriptomic data set during the transition from immature to mature growth, we identified a category named \"fight-club hubs\" characterized by a marked negative correlation with the expression profiles of neighboring genes in the network. A special subset named \"switch genes\" was identified, with the additional property of many significant negative correlations outside their own group in the network. Switch genes are involved in multiple processes and include transcription factors that may be considered master regulators of the previously reported transcriptome remodeling that marks the developmental shift from immature to mature growth. All switch genes, expressed at low levels in vegetative/green tissues, showed a significant increase in mature/woody organs, suggesting a potential regulatory role during the developmental transition. Finally, our analysis of tomato gene expression data sets showed that wild-type switch genes are downregulated in ripening-deficient mutants. The identification of known master regulators of tomato fruit maturation suggests our method is suitable for the detection of key regulators of organ development in different fleshy fruit crops.

The maintainance of a stable periodicity during the yeast metabolic cycle involving approximately half of the genome requires a very strict and efficient control of gene expression. For this reason, the metabolic cycle is a very good candidate for testing the role of a class of post-transcriptional regulators, the so called PUF-family, whose genome-wide mRNA binding specificity was recently experimentally assessed. Here we show that an integrated computational analysis of gene expression time series during the metabolic cycle and the mRNA binding specificity of PUF-family proteins allow for a clear demonstration of the very specific role exerted by selective post-transcriptional mRNA degradation in yeast metabolic cycle global regulation.