Nanoscale Research Letters最新文献

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype and is characterized by the absence of estrogen receptor, progesterone receptor, and HER2 expression; this subtype affects approximately 12–20% of all breast cancer cases, with a disproportionately poor prognosis and limited therapeutic options. The lack of targetable receptors excludes TNBC patients from hormone therapy and HER2-targeted treatments, resulting in the use of chemotherapy as the primary intervention, which is often associated with severe systemic toxicity and drug resistance. Albumin-based nanoplatforms have emerged as promising solutions to address these therapeutic challenges by exploiting the inherent biocompatibility, biodegradability, extended circulation half-life, and natural tumor-targeting properties of albumin through interactions with gp60 and SPARC receptors that are overexpressed in TNBC tissues. This comprehensive review examines the molecular design principles, fabrication strategies, and targeting mechanisms of albumin nanocarriers, including passive targeting via the enhanced permeability and retention (EPR) effect and active targeting through receptor‒ligand interactions with uPAR, EGFR, CD44, CXCR4, and folate receptors. We analyze diverse therapeutic payloads, including conventional chemotherapeutics (paclitaxel, doxorubicin, and docetaxel), natural products (curcumin and resveratrol), and molecular therapeutics (siRNAs and CRISPR/Cas9) delivered via albumin nanoplatforms. The clinical evidence supporting nab-paclitaxel in combination with immune checkpoint inhibitors has demonstrated significant improvements in progression-free survival and objective response rates in PD-L1-positive mTNBC patients, whereas real-world studies have confirmed manageable safety profiles. However, several challenges remain, including drug loading limitations, nanocarrier stability under physiological conditions, interpatient variability in EPR effectiveness, potential immunogenicity of modified albumin, and the inherent molecular heterogeneity of TNBC subtypes, which may require personalized approaches. Future directions emphasize the development of multistimuli-responsive albumin nanocarriers, integration with gene editing and immunotherapy, artificial intelligence-guided design optimization, and precision medicine strategies tailored to individual tumor profiles. The convergence of the natural tumor affinity of albumin with advanced nanotechnology holds substantial promise for overcoming drug resistance, enhancing therapeutic specificity, and improving clinical outcomes in TNBC patients, positioning albumin-based nanomedicine as a transformative approach in precision oncology.

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Plasmonic biosensors, particularly Surface Plasmon Resonance and Surface-Enhanced Raman Spectroscopy, have gained significant attention for real-time, label-free biochemical detection. However, optimizing these sensors for maximum sensitivity and selectivity remains a challenge due to their complex plasmonic interactions with different biomolecules. This work proposes SERA, an AI driven framework that integrates machine learning algorithms with experimental Surface-Enhanced Raman Spectroscopy (SERS) data for the predictive modeling and optimization of plasmonic sensing performance. Using supervised learning techniques, the ML models are trained on a spectral dataset - SERS-DB obtained from various plasmonic nanostructures. The model predicts key parameters such as resonance shift, intensity variations, and molecular binding efficiency, allowing for rapid optimization of biosensor designs without extensive trial-and-error experimentation. This approach accelerates plasmonic biosensor development and enables real-time adaptive sensing based on live data. The results through evaluation on the SERS-DB database with 420 samples for training and 180 for the testing phase, 6 classes like Thiacloprid, Imidacloprid, Thiamethoxam, Nitenpyram, Tetrahydrofolate, and Dihydrofolate, an accuracy of 92%, precision & recall of 90%, and F1-score of 92% were attained. The SERA model excelled with an overall score of around 0.90 in all 6 classes, proving additional superiority in biosensing applications. Further comparative analysis of the proposed approach with conventional methods underscores the best performance in accuracy with 92%, sensitivity, 1000 nm/RIU, and 95% in optimization efficiency. Overall, this research highlights a scalable and cost-effective strategy for advancing biosensor technology in medical diagnostics, environmental monitoring, and bio photonics.

In this study, graphene oxide (GO) derived from rice husk was functionalized with silver nitrate (AgNO₃) through a chemical co-precipitation method, and its biomedical applications were systematically investigated. Drug release experiments revealed a pH-responsive profile, where at pH 4.0 the cumulative release reached 32.6 ± 1.6% after 24 h, compared to 12.4 ± 1.8% at pH 7.4, highlighting its potential for targeted delivery to cancer cells. Reactive oxygen species (ROS) analysis and flow cytometry demonstrated that RH-GO/AgNO₃ treatment elevated oxidative stress and triggered apoptosis in HeLa cells. Furthermore, 5-fluorouracil (FU) was successfully loaded onto the nanocomposite surface via non-covalent interactions. Cytotoxicity assessment by MTT assay showed that FU-loaded RH-GO/AgNO₃ had the strongest anticancer activity, with an IC₅₀ value of 256.3 µg/mL. ROS levels in treated HeLacells increased significantly (40.17%) compared to the control group (19.45%), and flow cytometry confirmed a reduction in cell viability (69.5%) accompanied by enhanced apoptosis (early: 8.3%, late: 4.0%) and necrosis (18.2%). Collectively, these findings indicate that RH-GO/AgNO₃-FU induces cancer cell death predominantly via apoptosis. Overall, this work demonstrates that agricultural waste-derived nanomaterials can serve as cost-effective and sustainable platforms for advanced drug delivery in cancer therapeutics.

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Aim

This study presents a bibliometric analysis of research trends and emerging hotspots in upconversion nanoparticles (UCNPs) for drug delivery and biomedical targeting in photodynamic therapy (PDT).

Methods

We retrieved 474 publications from the Web of Science (2007–2025) and analyzed publication trends, contributions from countries, institutions, and authors, keyword co-occurrence, citation bursts, and co-citation networks using CiteSpace, VOSviewer, HistCite, and R software.

Results

UCNP-PDT research progressed through three distinct phases, with China and the USA contributing the most publications. Nanoscale published the highest number of articles, while high-impact reviews appeared in Chemical Society Reviews and Advanced Materials. Emerging research focuses include the tumor microenvironment, metal–organic frameworks, combination therapies, and antimicrobial PDT.

Conclusion

UCNP-PDT has evolved from simple photosensitizer loading to multifunctional nanoplatforms, expanding applications to cancer therapy, infection control, and immune modulation. Clinical translation remains limited by size–efficiency trade-offs, low-power irradiation, hypoxia, tissue heating under 980 nm excitation, GMP-compliant production, and insufficient long-term biosafety data. Future advances require coordinated strategies integrating material optimization, mechanistic insight, and translational considerations to achieve safe, scalable, and effective UCNP-PDT for clinical use.

A variety of compounds have been treated with lit semiconductors for water pollution treatment. UV irradiation with oxidants or catalysts (TiO₂) can remediate industrial effluent. The goal of this study is to prepare and characterize TiO₂–SnO₂ nanocomposites with different ratios to degradation dyes in wastewater treatment. These nanocomposites will be used to photocatalysis degradation of acid red 37 dye in aqueous solution using UV irradiation as a model pollutant. The characterization of TiO₂–SnO₂ nanocomposites was conducted using XRD, TEM, EDAX, FTIR, and XPS. The photocatalytic degradation was tested with several advanced oxidation processes (AOPs) by adding varying concentrations of SnO₂ (0–20 wt.%), and then by employing an inorganic antioxidant (H₂O₂, Na₂S₂O₈, NaIO₄) with a ratio of UV/TiO₂–SnO₂ (90:10) to high efficiency of degradation of acid red 37 dye using a batch photoreactor. Consequently, the effects of pH, dye concentrations, and different loading (g/L) of nanocomposite on the photocatalytic activity of the SnO₂–TiO₂ nanocrystals were examined. The UV/TiO₂–SnO₂ (90:10) wt.% has higher photocatalytic efficiency for degradation acid red 37 dye from either TiO₂, SnO₂ or the other ratios in this study.

Traditional drug delivery systems often face problems such as low drug accumulation at the target site, rapid clearance in the body, and potential damage to healthy tissues. Under such circumstances, nanoparticle drug delivery systems have been developed. Although they have certain advantages, they still struggle to achieve efficient and specific targeting and may exhibit cytotoxicity. In contrast, neutrophil membrane-coated nanoparticles (NM-NPs) inherit the natural cell surface proteins and ligands of neutrophils, possessing numerous advantages such as low immunogenicity, immune evasion, and the ability to achieve precise targeting, thus showing great potential. This review is the first article to comprehensively summarize the application of neutrophil membrane-coated nanoparticles in targeted therapy. It mainly focuses on the pathophysiological role of neutrophils, the advantages of neutrophil membrane coating, the selection and preparation of nanoparticle cores, the targeting mechanism of neutrophil membrane-coated nanoparticles, the types of nano-drugs for targeted delivery, their application in disease treatment, and discussions on related safety and toxicology.

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Plant-derived extracellular vesicles (PDEVs) have garnered significant attention as crucial mediators of intercellular and cross-species communication in plants, owing to their unique bioactivity and medicinal potential. However, quality control of PDEVs is of paramount importance for their functionality and applications. This review systematically summarizes the key aspects that influence PDEVs quality, including source material preparation, isolation and purification, characterization, and storage conditions. Regarding source material preparation, the genetic background, abiotic factors (such as light, temperature, and moisture), biotic factors (including pathogen infection and probiotic effects), and traditional processing methods significantly affect the composition and function of PDEVs. Plant tissue culture techniques and temporary immersion bioreactor systems (TIBS) have substantial potential for addressing the issue of fluctuating raw material quality. During the isolation and purification processes, existing methods (e.g., ultracentrifugation, polymer precipitation, and size-exclusion chromatography) have their respective advantages and disadvantages, necessitating the optimization of operations based on specific requirements to avoid vesicle damage or impurity introduction. In terms of characterisation, integrating techniques such as transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blotting can comprehensively evaluate the quality of PDEVs. Additionally, storage conditions significantly affect the stability of PDEVs, and appropriate measures should be adopted to reduce degradation. Future research should focus on developing standardized preparation processes and efficient characterization techniques to facilitate the widespread application of PDEVs in drug delivery, functional foods, and other fields.

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MXene/chitosan (MX/CS) composites have recently garnered significant attention due to their unique properties. This synergistic integration has opened new opportunities for various industrial applications. This review provides a comprehensive analysis of recent advancements in the use of MX/CS composites across multiple sectors, including electromagnetic interference (EMI) shielding, electrochemical sensing, water treatment, fire-retardant materials, environmental remediation, and energy storage devices such as supercapacitors and batteries. Each application has its own requirements and standards for the chosen building materials. Fortunately, all the divergent requirements can be achieved in MXene (MX) and chitosan (CS) by relatively moderate treatment. The discussion highlights how the unique interactions between MX nanosheets and CS matrices enhance performance characteristics. Despite these advantages, several critical challenges remain, including long-term stability, material scalability, and cost-effective manufacturing processes. This review summarizes recent advancements by identifying key research gaps and aims to guide further innovation in the fields. The potential of MX/CS composites to contribute to sustainable and high-performance industrial solutions is undeniable, provided that existing challenges are met with innovative approaches.

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This work examines the transient flow and heat transfer characteristics of a Carreau ternary hybrid nanofluid ((hbox {TiO}_2) + Cu + (hbox {Al}_2hbox {O}_3)/CMC–(hbox {H}_2)O) across a stretched sheet subjected to combined electromagnetic and thermal influences. The model integrates suction/injection, heat radiation, Ohmic dissipation, and concentration fluctuations, emphasising entropy generation. The governing nonlinear equations are converted using similarity variables and solved numerically using the BVP5c technique. Multiple linear regression is used to forecast skin friction, Nusselt number, and Sherwood number. Results indicate that magnetic and electric field intensities, Weissenberg number, and thermal radiation substantially affect velocity, temperature, and concentration distributions, but entropy production underscores irreversibility processes. The ternary hybrid nanofluid has enhanced thermal performance relative to mono and binary nanofluids, presenting potential advantages for cooling, extrusion, and coating applications.

A number of different metallic nanoparticles have been extensively investigated in recent years owing to their diverse potential biomedical and cancer applications, antibacterial activities, and chemical properties. Here, silver nitroprusside nanoparticles (AgNPs) were prepared from silver nitrate and sodium nitroprusside, and their anticancer activity was evaluated. AgNPs were prepared and characterized using Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray dispersive energy spectroscopy (EDX), and transmission electron microscopy (TEM). In vitro tests were performed using two breast cancer cell lines, a non-malignant breast epithelial cell line (MCF-10A), and a breast cancer cell line (MCF-7). The results obtained from cytotoxicity assays (MTT and resazurin assays) and bright-field microscopy revealed that AgNPs (3.0 μg/mL) exhibited preferential selectivity for non-malignant breast epithelial cells and were toxic to tumorigenic cells (MCF-7), with preferential cell death via apoptosis. Furthermore, in vivo experiments using a murine breast tumor model demonstrated that AgNP treatment significantly inhibited tumor growth without systemic toxicity, confirming its selective antitumor activity. These results suggest that AgNPs have potential applications in breast cancer treatment. In this study, we focused on the development and application of silver nitroprusside nanoparticles in in vitro and in vivo models to evaluate their antitumor activity and effects in different models of breast cancer.

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