Introduction. Nanocrystalline cellulose (NCC) has unique physico-chemical properties and is considered an effective substitute for microcrystalline cellulose (E460i). However, the use of NCC in food production is hindered by a lack of knowledge about the risks of its effects on the human body during prolonged consumption with food.

Methods. The potential neurotropic properties of NCC were studied using a complex of neurophysiological methods (CRPA, EPM) with the daily consumption of NCC by Wistar rats at doses of 1-100 mg/kg b.w. for 56 days.

Results. The consumption of NCC in the entire dose range had an effect on the motor activity of animals in the EPM. In animals that consumed NCC at a dose of 100 mg/ kg b.w., a whole range of significant changes in behavioral reactions were revealed compared with the control, among which there were signs of anxiety-like behavior. As shown by an analysis of the movement of rats around the maze, there was an almost threefold increase in the ratio of stay in the open and closed arms of the maze. During the development of a conditioned reflex in the CRPA installation, rats that consumed NCC in the highest dose were characterized by a significant decrease in latency time before entering the dark compartment of the installation. There was no significant effect of NCC on the indicators of short-term and long-term memory.

Conclusion. Dietary intake of NCC, especially in high doses of 10-100 mg/kg b.w., is accompanied by neurotropic effects in rats. The NOAEL of NCC for a 56-day intake with a diet is, according to the study of behavioral indicators, in any case, less than 1 mg/kg b.w.

Funding. Ministry of Education and Science of the Russian Federation (FGMF-2025-0004).

Syringaldehyde and vanillin are used as flavorings and odorants in the food, pharmaceutical, and cosmetic industries. Moreover, their concentration ratio is considered a significant parameter for brandy and cognac quality characterization, allowing for the identification of adulteration. Thus, the simultaneous quantification of syringaldehyde and vanillin is in high demand. Voltammetric sensors are a promising tool to solve this problem due to their high sensitivity, sufficient selectivity, fast response, and possibility of miniaturization. A glassy carbon electrode modified with carboxylated multi-walled carbon nanotubes and electropolymerized indicator phenol red was developed as a voltammetric sensor for the simultaneous determination of syringaldehyde and vanillin. The electropolymerization conditions were optimized using the voltammetric parameters of the syringaldehyde and vanillin mixture. The best resolution of anodic peaks (121 mV) with sufficient currents was obtained for 100 μM phenol red electropolymerized in 0.1 M sodium hydroxide by 10-fold potential cycling from 0.1 to 1.0 V with a scan rate of 75 mV s^-1. Polymeric coverage provides an increase in the electroactive surface area of the electrode and a higher heterogeneous electron transfer rate constant vs. bare glassy carbon electrode. The irreversible diffusion-driven electrode reaction with the participation of two electrons and two protons was confirmed for both aldehydes. The linear dynamic ranges of sensor response for both analytes are 0.10-2.5 and 2.5-25 μM, with limits of detection equal to 44 and 33 nM for syringaldehyde and vanillin, respectively.

The development of multifunctional nanomaterials capable of simultaneously delivering drugs and inducing localized hyperthermia represents a promising strategy in advanced cancer therapies. In this work, we report the synthesis and characterization of thermoresponsive magnetic hydrogels (GMag) based on poly(N-isopropylacrylamide) (PNIPAM) and superparamagnetic iron oxide nanoparticles (Fe₃O₄) for synergistic chemotherapy and magnetic hyperthermia applications. The superparamagnetic Fe₃O₄ nanoparticles were synthesized via a reverse co-precipitation method, with polyethylene glycol (PEG-8000) incorporated in situ, allowing simultaneous surface modification to improve colloidal stability, dispersion in aqueous media, and biocompatibility. To enhance the mechanical strength and elasticity of the hydrogel matrix, 2.5% (w/w) TEMPO-oxidized cellulose nanofibers (TOCNFs) were incorporated into the formulation. These nanofibers introduced a reinforcing network, improving structural integrity while maintaining responsiveness. The GMag were synthesized through free radical polymerization with varying nanoparticle loadings (2.5% to 10%). The hybrid hydrogels retained superparamagnetic behavior and demonstrated a significant heating response under an alternating magnetic field, reaching a temperature of up to 43.2 °C—suitable for magnetic hyperthermia treatment. These GMag were characterized by XRD, FTIR, and TGA to confirm structural integrity and thermal properties and were subsequently evaluated as platforms for the controlled release of the chemotherapeutic agent doxorubicin (DOX). Drug loading studies revealed a high encapsulation efficiency (up to 8.3 × 10⁻² mg DOX/mg hydrogel), while in vitro release experiments confirmed temperature- and magnetically triggered release. In the in vitro drug release at 37 °C and physiological pH, GMag2.5 released 63% of DOX within 6 hours, followed by sustained release. When exposed to a magnetic field, a burst release of 18% was observed within 10 minutes, demonstrating controllable, on-demand delivery. Biocompatibility was validated via MTT assays on MDA-MB-231 breast cancer cells. These results highlight the potential of GMag hydrogels as dual-action nanoplatforms for targeted, localized, and stimulus-responsive cancer treatment, combining controlled drug delivery with magnetic hyperthermia for enhanced therapeutic efficacy.

Semiconductor p–n heterojunctions are widely used in modern electronic and optoelectronic devices, typically generating unipolar photocurrents. By integrating a photoelectrochemical cell (PEC), it becomes possible to achieve more versatile behavior, including bidirectional photocurrents with polarity switching under different applied biases. In this study, we fabricated and optimized PEC photodetectors based on solution-processed p-type CuI thin films combined with n-type 1D TiO₂ nanorods. The optimization was performed by adjusting the number of CuI layers via spin-coating and the applied voltage to enhance the photoresponse. Interestingly, dual-polarity photocurrent was observed in the p-CuI/n-TiO₂ PEC device under visible light illumination (420 nm). Although the 1D n-TiO₂ nanorods are transparent to this blue light and the p-CuI itself typically produces a negative photocurrent, a positive photocurrent was generated under a specific biased voltage. This unique behavior is attributed to the built-in electric field at the p–n junction, which enables bidirectional photocurrent under varying bias conditions. The findings suggest that the device's photocurrent polarity can be effectively tuned by adjusting the applied bias and material configuration. This behavior presents a promising strategy for improving the performance and efficiency of PEC-based photodetectors, offering potential applications in advanced optoelectronic devices for energy conversion, light sensing, and future nanotechnology-based applications in renewable energy systems.

In this study, we present a groundbreaking approach to designing high-efficiency solar cells by combining nanophotonics with machine learning (ML). Our objective is to develop a plasmonic-enhanced solar cell that incorporates 2D material heterostructures such as MoS₂ and graphene. These advanced materials can be coupled with silver (Ag) nanoparticle arrays to boost light absorption through localized surface plasmon resonance (LSPR). To fine-tune the design, we employed AI-assisted simulations that predict the optimal configuration of nanoparticle size, inter-particle spacing, and the thickness of the 2D material layers.

The simulation process is based on finite-difference time-domain (FDTD) modeling, implemented in Python using the pyFDTD library. This approach allowed us to simulate and analyze how light interacts with the plasmon-enhanced solar cell structure. We then trained a neural network using TensorFlow, drawing from a dataset of over 1,000 simulation results. This model predicts the maximum light absorption efficiency for varying design parameters, including nanoparticle radius, particle spacing, and the wavelength of incoming light.

Through this AI-guided process, we discovered that the ideal nanoparticle size is 42 nm with a spacing of 55 nm, which maximizes absorption efficiency in the visible light spectrum. The final design demonstrated an exceptional light absorption efficiency of 92.7% across the 400–700 nm wavelength range, surpassing traditional solar cell performance by more than 30%. Furthermore, integrating machine learning reduced simulation times by approximately 80%, offering a highly efficient and scalable solution for advancing solar energy technology.

Two-dimensional materials, with their atomic-scale thickness and novel physical properties, represent promising candidates for designing highly integrated artificial intelligence chips. However, their atomic thickness, while advantageous for integration, results in weak light absorption, resulting in a limited photoresponse and hindering their use in artificial vision devices. To address this issue, we propose an optical synaptic device based on an R6G/InSe hybrid structure. In this hybrid device, R6G serves as a photosensitive layer, effectively enhancing the photoresponse of the 2D InSe sensing layer, with this effect attributed to charge transfer between the dye molecules and the channel material. We employed a non-destructive spectroscopic technique, surface-enhanced Raman spectroscopy (SERS), in conjunction with electrical testing, to demonstrate the charge transfer mechanism. Furthermore, we introduced an oxide layer on the InSe surface through oxygen plasma treatment. The presence of the oxide layer hindered the charge transfer process, providing further evidence for the charge transfer mechanism. The proposed hybrid-structure device exhibits outstanding optical synaptic performance, facilitating image denoising preprocessing similar to that achieved by artificial neural network functions. We realized encryption and decryption of image information using artificially introduced noise backgrounds and further proposed a design concept for an anti-counterfeiting chip by designing a hybrid device array. In summary, the design of the R6G/InSe hybrid-structure device we propose offers a reference solution for enhancing the optical response of 2D material devices. Additionally, our encryption and anti-counterfeiting applications present new directions for the use of 2D materials in optoelectronic devices.

Repositioning amiodarone, an antiarrhythmic agent, for cancer therapy has garnered increasing interest due to its inhibitory effects on carnitine palmitoyltransferase 1A (CPT1A), a key enzyme upregulated in ovarian cancer (OC)¹. OC is particularly aggressive and prone to peritoneal metastasis, with a metabolic profile characterized by elevated fatty acid oxidation driven by CPT1A overexpression. Despite its therapeutic potential, the clinical application of amiodarone in oncology is hindered by its systemic toxicity. To address this limitation, drug delivery systems (DDSs) offer a promising strategy, with liposomes emerging as an ideal candidate due to their high biocompatibility and tumor-targeting capabilities. Liposomes can exploit the Enhanced Permeability and Retention (EPR) effect or be surface-modified to enhance receptor-mediated targeting, thereby improving drug accumulation and pharmacokinetics². The production method of liposomes critically influences their physicochemical properties, with conventional techniques often requiring post-processing steps to achieve clinical-grade formulations. Microfluidics has recently gained attention as a scalable and precise alternative, offering fine control over parameters such as vesicle size, lamellarity, and distribution³. Using a microfluidic approach, amiodarone was successfully encapsulated into liposomes, with simultaneous generation of amiodarone-containing lipidic particles. Optimization of process parameters, including temperature and flow rate ratio, enabled the production of a stable, uniform DDS. Both formulations were extensively characterized and demonstrated significant efficacy in in vitro models of ovarian cancer, underscoring their potential for further development in targeted cancer therapy⁴.

[1] Sawyer B.T., Qamar L., Yamamoto T.M., McMellen A., Watson Z. L., Richer, J. K., Behbakht K., Schlaepfer I.R., Bitler B. G. 2020, Molecular Cancer Research, 18, 1088.

[2] Bitounis D., Fanciullino R., Iliadis A., Ciccolini J. 2012, ISRN Pharmaceutics, 2012, 1, 11.

[3] Carugo D., Bottaro E., Owen J., Stride E., Nastruzzi, C. 2016, Scientific Reports, 6, 25876.

[4] Saorin A., Saorin G., Duzagac F., Parisse P., Cao N., Corona G., Cavarzerani E., Rizzolio F. 2024, Scientific Reports, 14, 6280.

Thermoset polymers are the most common matrix used for manufacturing fiber-reinforced polymer composites, with their exceptional properties leading to their usage in highly demanding fields such as aerospace. Monitoring such materials for structural deformation is key when it comes to maintaining their continual usage and avoiding catastrophic failure. Here, we explore how single-walled carbon nanotube (SWCNTs) nano–macro arrangements can be used to monitor composites under tensile loading without causing a loss in host material properties. Sensors of various thicknesses (23, 37, and 53 nm) were investigated to determine optimized monitoring parameters: electrode materials, configuration, and embedding within or surface application. Tensile loading was conducted with a crosshead speed of 1mm/min, and strain measurements were obtained using digital image correlation. It was found that thinner sensors provided higher sensitivity to mechanical deformation and load, and that embedded sensors outperform surface-applied ones (gauge factors between 23 and 86 and 4 and 10, respectively). All sensors were shown to accurately measure strain, and were shown to self-adjust to elastic and plastic deformation regimes during mechanical loading. We show that monitoring of the mechanical deformation and loading of popular industrial polymers and composites can be accurately conducted using optimized SWCNT structures, and that their application causes no degradation in thermoset polymer material performance.

Glioblastoma multiforme (GBM) is one of the most aggressive and treatment-resistant forms of brain cancer, characterized by rapid progression, high recurrence, and a limited response to conventional therapies. This clinical challenge highlights the urgent need for advanced, multimodal therapeutic strategies. In this study, we present a dual-responsive nanoplatform engineered from iron oxide (Fe₃O₄) nanoparticles and gold nanorods, specifically designed to facilitate synchronized magnetic hyperthermia (MHT) and photothermal therapy (PTT) in combination with chemotherapeutic delivery and in vivo imaging. The nanohybrid was synthesized through a seed-mediated thermal decomposition approach, yielding uniform, stable, and biocompatible structures with high magnetic responsiveness and strong near-infrared absorption. Upon external application of an alternating magnetic field and NIR irradiation, the system generated localized heat sufficient to induce therapeutic hyperthermia. In vitro experiments using U87-MG glioblastoma cells demonstrated significant cytotoxicity under combined MHT and PTT, with this combination clearly outperforming either modality alone. In vivo studies in a murine GBM model showed efficient tumor accumulation, pronounced tumor regression, and no detectable systemic toxicity. For added functionality, doxorubicin was conjugated for chemotherapeutic synergy, and a near-infrared fluorescent dye was co-loaded to facilitate real-time biodistribution analysis and image-guided therapy. This multifunctional nanoplatform represents a promising minimally invasive strategy for effective glioblastoma treatment through thermally synchronized, targeted intervention.

The assembly of nanoparticles into mesoscopic structures, known as superparticles (SPs), leads to new emergent properties arising from interactions among their components [1, 2]. Indeed, various types of nanoparticles, ranging from metal chalcogenide and perovskite quantum dots (QDs) to metal nanoparticles and magnetite nanocubes, can act as functional building blocks for artificial solids displaying unique properties that transcend those of their constituents. Within this landscape, SPs based on plasmonic metal nanoparticles [3-5] have attracted significant interest owing to the unique coupling effects between the plasmonic fields of the constituent nanoparticles, holding great promise for several applications, including ultra-efficient surface-enhanced Raman scattering [6,7]. Despite this promising outlook, the understanding of the fundamental factors driving the behaviour of metal SPs is still incomplete.

Here, we assembled gold nanoparticles (AuNPs) into 200 SPs with varying interparticle distances. After performing a structural characterisation of the resulting SPs by TEM, DLS, and SAXS, we leveraged transient absorption spectroscopy (TA) and transient absorption microscopy (μPP) to unravel their ultrafast photophysics. Our results shed light on the role of interactions between plasmon resonances in determining the overall optical response of metal SPs. In fact, both spectral shape and kinetics show a dependence upon the interparticle distance, revealing the emergence of a collective response of the SP to photoexcitation due to interactions between the constituent nanoparticles. The results pave the way to the engineering of functional metal-based superstructures for a variety of possible applications in photonics and optoelectronics.

[1] ACS Nano 2020, 14, 10, 13806–13815.

[2] Nat Synth, 2023, 10.1038/s44160-023-00407-2.

[3] Chem. Rev. 2020, 120, 2, 464–525.

[4] Nanoscale Adv., 2020, 2, 3764-3787.

[5] Nat. Comm, 11, 2771, 2020.

[6] Adv. Funct. Mater. 2020, 30, 2005400.

[7] Nanoscale, 2019, 11, 17444-17459.