Background: Thyroid cancer (TC) is the most prevalent endocrine malignancy, and is categorized into well-differentiated and aggressive anaplastic types. Novel therapeutic modalities are needed for TC. Nanomedicine is a promising strategy for the development of precision medicine. In this context, we investigated the use of nanogels (NGs) to deliver agents with different physicochemical properties, specifically the hydrophilic agent doxorubicin (DOX) and the hydrophobic compound curcumin (CUR), in TC cell lines. Methods: Nα-9-fluorenylmethoxycarbonyl-diphenylalanine (Fmoc-FF) peptide-based NGs loaded with DOX and CUR were formulated using the solvent-switch method. DOX-loaded NGs were previously characterized. CUR-loaded NGs were characterized through rheology, scanning electron microscopy (SEM), dynamic light scattering (DLS), nanoparticle tracking analysis (NTA), and Fourier transform infrared (FT-IR) spectroscopy. Confocal microscopy, q-RT-PCR, and ATP lite assays were performed to evaluate the uptake and delivery of DOX- and CUR-loaded NGs on TC cell lines. Results: CUR-loaded NGs exhibited a mean diameter of approximately 204.3 nm and a zeta potential of −34.6 mV, indicative of a good stability. In vitro release studies revealed a sustained release profile of CUR over 72 h. Functional analyses demonstrated that Fmoc-FF-loaded NGs were internalized into TC cell lines. They were primarily localized in the cytoplasm rather than in early endosomes, thereby ensuring intracellular stability. Furthermore, Fmoc-FF NGs reduced the nuclear uptake kinetics of DOX in TC cells, suggesting a potential reduction in dose-limiting toxicity. Comparative studies with CUR-loaded NGs revealed similar internalization and delayed nuclear uptake, highlighting the efficacy of Fmoc-FF NGs in delivering hydrophobic agents. Conclusions: Overall, the data suggest that Fmoc-FF NGs represent a promising strategy for delivering agents with diverse physicochemical properties in TC, enhancing their efficacy and safety and warranting further investigation.

Non-covalent forces are the primary drivers of biomolecular interactions. They also represent a key factor in the unexpected tendency for proteins, peptides, and even individual amino acids to self-assemble into precise supramolecular assemblies, often characterized by a β-rich, amyloid-like structure. Studies carried out in the last few decades have shown that peptides/proteins self-assembly not only has structural consequences but also generates spectroscopic properties whose origin remains debated. Here, we investigated the spectroscopic properties of four peptides, GAIIGL, NNQQ, SSTSAA, and GNNQQNG (a derivative of the frequently studied GNNQQNY peptide), devoid of aromatic residues, whose crystallographic characterization has been seminal in elucidating the basis of the aggregation process. The spectroscopic behavior of these peptides was analyzed in two different media and in the solid state, highlighting the conditions that favor UV–visible fluorescence emission. These investigations have also prompted the use of this fluorescence as a potential diagnostic tool in nanomedicine. Importantly, the identification of intrinsic fluorescence signatures in these amyloid-like assemblies may support the development of label-free optical approaches for the early detection and monitoring of aggregation-related pathological processes. For all peptides, the emitted fluorescence spans a rather wide range of wavelengths. Although centered in the blue region, a significant signal is also observed in the green region, independent of their physical state. The structural analysis of the solid used to collect the spectroscopic data reveals features related to the packings in the crystal state. This observation suggests that their three-dimensional crystal structures may serve as reliable models for studies aimed at correlating structural and spectroscopic features.

Electrochemical (bio)sensors fabricated by fused deposition modeling (FDM) represent a versatile and cost-effective platform for customizable analytical devices. However, their performance often requires surface modification strategies that improve electrocatalytic activity while maintaining sustainable fabrication approaches. Here, we introduce a waste-to-sensor strategy based on the upcycling of lithium cobalt oxide (LiCoO₂, LCO) recovered from spent lithium-ion batteries as an electroactive modifier for FDM 3D-printed carbon-based electrodes. Although spent batteries represent an increasing environmental challenge, their functional components can be repurposed as valuable secondary resources for high-value technological applications. The developed LCO-modified electrodes were investigated for the electrochemical detection of hydrogen peroxide (H₂O₂), a key reactive oxygen species (ROS) involved in cellular signaling and oxidative stress-related diseases. LCO modification was optimized and characterized by cyclic voltammetry and chronoamperometry, demonstrating enhanced electrocatalytic performance compared with unmodified electrodes. The optimized sensor exhibited a linear response toward H₂O₂ detection in DMEM over the 0-2.5 mM concentration range, with a limit of detection of 0.02 mM and a limit of quantification of 0.06 mM, demonstrating analytical performance suitable for monitoring biologically relevant concentrations. The applicability of the platform was demonstrated using C2C12 muscle and HeLa cervical cancer cell models subjected to oxidative stress conditions, with or without glutathione antioxidant treatment. Electrochemical measurements showed consistent trends with the conventional DCFH-DA fluorescence assay, confirming the ability of the sensor to monitor ROS variations associated with oxidative stress and antioxidant protection. Overall, this work demonstrates that battery-derived LCO can be effectively repurposed as a sustainable electrocatalytic modifier for 3D-printed electrochemical sensors, bridging circular economy principles with biomedical sensing technologies. The proposed platform provides a low-cost, customizable, and environmentally conscious approach for future ROS monitoring and point-of-care biosensing applications.