Luisa Di Paola

Algal carotenoids play a promising role in handling chronic diseases due to their diverse bioactive properties, including anti-inflammatory, antioxidant, and anticancer effects. This study assesses the activity of the antioxidant xanthophyll diatoxanthin (Dt), derived from marine diatoms, against triple-negative breast cancer (TNBC) cells using in vitro models, gene expression evaluation, and explores its role in potentiating the cytotoxic effect of chemotherapy. Dt exhibited selective activity against MDA-MB-231 and BT-549 TNBC cells at concentrations ≥12.5 ng/mL, with maximal effects observed at 25 ng/mL while sparing human umbilical vein endothelial cells (HUVECs) at these doses. When combined with doxorubicin (0.1–0.5 μM), Dt enhanced the anti-tumor efficacy in both TNBC cell lines, further reducing cell viability compared with doxorubicin alone (p < 0.05–0.001). Dt also exerted its activity in inhibiting migration and chemotaxis by approximately 30–50% compared with the controls (p < 0.01) and suppressing 3D-tumor spheroid growth at day 12 (up to >50% reduction, p < 0.001). Notably, secretome analysis revealed Dt-induced changes in inflammatory, oxidative and angiogenic mediators, highlighting its ability to modulate the TNBC microenvironment. Dt also downregulated key pro-survival, pro-angiogenic and pro-tumorigenic genes in both TNBC cell lines, supporting its role in disrupting oncogenic pathways. Angiogenesis-related genes were significantly reduced. Dt also decreased the expression of angiogenic mediators in HUVECs, supporting Dt’s role in inhibiting tumor vascularization. Results on gene expression regulation were also confirmed by RNA-Seq analysis. These findings pose Dt as a promising chemopreventing candidate in the challenging fight against TNBC, a well-known type of cancer that is aggressive and resistant to conventional therapies, targeting critical pathways for tumor survival, such as inflammation, angiogenesis, tumor cell growth, and cell migration. Given its selective activity against TNBC cells, ability to enhance chemotherapy efficacy, and modulation of the tumor microenvironment, Dt holds promise as a complementary drug for cancer prevention and interception. Future studies should focus on validating these effects in vivo and exploring Dt’s potential in combinatorial treatment strategies for cancer.

Commercial crustacean species represent some of the most economically valuable fishery products; however, their full potential remains underexploited due to the routine disposal of shellfish waste, which is rich in high‐value bioactive compounds. Among these, carotenoid pigments have garnered increasing interest for their antioxidant and anti‐inflammatory properties. In this study, we investigate the potential of recovering bioactive compounds from the shells of the European lobster ( Homarus gammarus Linnaeus, 1758) and the Atlantic blue crab ( Callinectes sapidus Rathbun, 1896), with a particular focus on carotenoprotein complexes with promising applications in the pharmaceutical and cosmetic industries. We adopted a computational approach integrating protein contact networks, molecular docking, and molecular dynamics simulations to characterize the structural and functional properties of crustacean carotenoproteins as nanocarriers for astaxanthin. Then, we explored in silico the antioxidant activity of astaxanthin, as claimed by many studies. Specifically, we applied the computational analyses to the interaction between astaxanthin and Kelch‐like ECH‐associated protein 1 (Keap1‐DC domain), a key regulator of the Nrf2 signaling pathway involved in oxidative stress. Results suggest that astaxanthin would compete with Nrf2 at the Keap1‐DC domain, then promote Nrf2 induction and activate the antioxidant cellular machinery. These findings are supported by preliminary experimental evidence and highlight the potential of astaxanthin extracted from crustacean shell waste as a bioactive agent, with possible applications in diseases associated with oxidative stress, including cancer. Further preclinical and clinical in vivo studies are needed to validate astaxanthin and the carotenoprotein–astaxanthin complex for efficacy and safety, with potential relevance for oncology.

Algal carotenoids play a promising role in handling chronic disease due to their diverse bioactive properties, including anti-inflammatory, antioxidant, and anticancer effects. This study assesses the activity of the antioxidant xanthophyll diatoxanthin (Dt), derived from marine diatoms, against triple-negative breast cancer (TNBC) cells using in vitro models, gene expression evaluation and explorings its role in potentiating the cytotoxic effect of chemotherapy. Dt exhibited selective activity against MDA-MB-231 and BT-549 TNBC cells and when combined with doxorubicin synergistically enhanced anti-tumor efficacy in both TNBC cell lines by further reducing cell viability. Dt also exerted its activity in inhibiting migration, chemotaxis, and suppressing 3D-tumor spheroid growth, and downregulating angiogenesis-related genes. Notably, secretome analysis revealed that Dt-induced changes in inflammatory, oxidative and angiogenic mediators, highlighting its ability to modulate the TNBC microenvironment. Dt also downregulated key pro-survival, proangiogenic and pro-tumorigenic genes in both TNBC cell lines, supporting its role in disrupting oncogenic pathways. Angiogenesis-related genes were significantly reduced. Dt also decreased the expression of angiogenic mediators in HUVEC cells, supporting Dt’s role in inhibiting tumor vascularization. Results on gene expression regulation were confirmed by RNAseq analysis. These findings pose Dt as a multifaceted candidate for contrasting TNBC, capable of targeting inflammation, angiogenesis, tumor cell growhth, and cell migration. Given its selective activity against TNBC cells, ability to enhance chemotherapy efficacy, and modulation of the tumor microenvironment, Dt holds promise as complementary drug for cancer prevention and interception. Future studies should focus on validating these effects in vivo and exploring Dt’s potential in combinatorial treatment strategies for cancer.

This study investigates the structural dynamics of the TRAF2 C-terminal domain (TRAF2-C), a key adaptor protein in TNF receptor signaling. TRAF2 usually forms trimers, but its ability to dissociate into monomers is critical for regulating apoptosis, inflammation, and cell survival. Using Fluorescence Fluctuation Spectroscopy, dynamic light scattering, circular dichroism, and Small Angle Neutron Scattering, we analyzed TRAF2-C over a wide concentration range. At nanomolar levels, the protein dissociates easily, with trimers representing only a minor fraction, while micromolar concentrations strongly favor trimerization. Dissociation also reduces α-helical content without disrupting the overall fold. Molecular dynamics simulations and protein contact network analysis support this analysis, identifying interfacial residues and hydrogen bonds as key factors stabilizing oligomers and enabling dynamic asymmetry. Overall, these findings highlight TRAF2-C’s capacity to switch between monomeric and trimeric states as a crucial regulatory mechanism, offering insights into TRAF-mediated signaling and potential therapeutic strategies.

The molecular approach to understanding the mechanisms of emerging diseases, like COVID-19, has largely accelerated the search for successful therapeutical strategies. In this work, we present an extensive molecular dynamics (MD) analysis of two forms of the SARS-CoV-2 main protease M^Pro. We analyzed the free form (apo) and compared the results with those coming from the (holo) form bound to the inhibitor Boceprevir, an FDA-approved drug repurposed for COVID-19 therapy. We applied Dynamic Cross Correlation (DCC) analysis to the MD simulations to trace the concerted motion patterns within the protein structure. Although symmetric, the homodimer in the bound form showed clearly asymmetric dynamical behavior. In particular, the presence of concerted motions was detected in the protomer where the expulsion of the substrate from the active site happened. Such behavior was not observed in the same time lapses in the apo form. These results highlight a sort of ‘symmetry breaking’, making a symmetric structure to display functional induced asymmetric behavior in response to a perturbation. This highly coordinated dynamics in response to an external cue confirms the character of ‘complex molecular machines’ of biopolymers.

In the past two decades, advancements in thermochemical technologies have improved biomass gasification for distributed power generation, enhancing efficiency, scalability, and emission control. This study aims to optimize syngas production from biomass gasification by comparing two computational models: a quasi-equilibrium thermodynamic model implemented in Aspen Plus and an artificial neural network (ANN) model. Operating at 850 °C with varying steam-to-biomass (S/B) ratios, both models were validated against experimental data. Results show that hydrogen concentration in syngas increased from 19.96% to 43.28% as the S/B ratio rose from 0.25 to 0.5, while carbon monoxide concentration decreased from 24.6% to 19.1%, consistent with the water–gas shift reaction. The ANN model provided rapid predictions, showing a mean absolute error of 3% for hydrogen and 2% for carbon monoxide compared to experimental data, though it lacks thermodynamic constraints. Conversely, the Aspen Plus model ensures mass and energy balance compliance, achieving a cold gas efficiency of 95% at an S/B ratio of 0.5. A Multivariate Statistical Analysis (MVA) further clarified correlations between input and output variables, validating model reliability. This combined modelling approach reduces experimental costs, enhances gasification process control and offers practical insights for improving syngas yield and composition.

This paper presents a quasi-analytical method that allows the derivation of a rigorous series-form representation for the mutual inductance of two co-axial coil antennas located above an arbitrarily layered earth structure. Starting from Biot–Savart law, which gives the integral representation for the primary vector potential generated by the source coil, the potential reflected by the layered ground is derived, and the resulting total vector potential is then integrated along the external circumference of the receiving coil to give the mutual inductance of the two antennas. The obtained representation for the flux is then evaluated analytically through the usage of the Gegenbauer addition theorem once an accurate, rational approximation is used in place of the factor of the integrand that exhibits branch cuts. It is shown how the resulting explicit solution exhibits the same degree of accuracy as purely numerical approaches like the finite-difference time-domain (FDTD) method and conventional numerical quadrature schemes, while it is less time-demanding than the latter methods.

Biomass gasification has obtained great interest over the last few decades as an effective and trustable technology to produce energy and fuels with net-zero carbon emissions. Moreover, using biomass waste as feedstock enables the recycling of organic wastes and contributing to circular economy goals, thus reducing the environmental impacts of waste management. Even though many studies have already been carried out, this kind of process must still be investigated and optimized, with the final aim of developing industrial plants for different applications, from hydrogen production to net-negative emission strategies. Modeling and development of process simulations became an important tool to investigate the chemical and physical behavior of plants, allowing raw optimization of the process and defining heat and material balances of plants, as well as defining optimal geometrical parameters with cost- and time-effective approaches. The present review paper focuses on the main literature models developed until now to describe the biomass gasification process, and in particular on kinetic models, thermodynamic models, and computational fluid dynamic models. The aim of this study is to point out the strengths and the weakness of those models, comparing them and indicating in which situation it is better to use one approach instead of another. Moreover, theoretical shortcut models and software simulations not explicitly addressed by prior reviews are taken into account. For researchers and designers, this review provides a detailed methodology characterization as a guide to develop innovative studies or projects.

Biomass gasification acquired great interest over the past decades as an effective and trustable technology to produce energy and fuels with net-zero carbon emissions. Moreover, using biomass waste as feedstock enables to recycle organic wastes and to fit the circular economy goals thus reducing the environmental impacts of waste management. Even if many studies have been already carried on, this kind of process must still be investigated and optimized with the final aim to develop industrial plants for different applications, from the hydrogen production to net-negative emission strategies. Modeling and developing of process simulations became an important tool to investigate the chemical and physical behavior of the plant, allowing to make a first raw optimization of the process and to define heat and material balances of the plant as well as to define optimal geometrical parameters with cost and time effective approaches. The present review paper focuses on the main literature models developed until now to describe biomass gasification process, and in particular on kinetic models, thermodynamic models, and computational fluid dynamic models. The aim of this study is to point out the strengths and the weakness of those models, comparing them and indicating in which situation is better to use an approach instead of another. Moreover, theoretical shortcut models and software simulations, not explicitly addressed by prior reviews, are taken into account. For researchers and designers this review provides a detailed methodology characterization as a guide to develop innovative study or project.