Journal of materials chemistry. B最新文献

The advancement of molecular diagnostics for lung cancer stratification and monitoring is essential for the strategic planning and prompt modification of treatments, aiming to enhance clinical results. To address this need, we suggest a nanocavity structure designed to sensitively analyze the protein signature on small extracellular vesicles (sEVs). This approach facilitates precise, noninvasive staging and treatment monitoring of lung cancer. The nanocavity is created through molecular recognition, involving the interaction of sEVs with nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and asymmetric, mirrorlike gold microelectrodes. By applying an alternating current to the gold microelectrodes, a nanofluidic shear force was generated, promoting the binding of sEVs and the effective assembly of the nanoboxes. This interaction induced a nanocavity between the nanobox and the gold microelectrode, which significantly amplified the electromagnetic field. This amplification enhanced Raman signals from four SERS barcodes simultaneously, allowing the generation of patient-specific molecular sEV signatures. When tested on a cohort of clinical samples (n = 76) using the nanocavity architecture, these patient-specific sEV molecular signatures accurately identified, stratified, and monitored lung cancer patients' treatment, demonstrating its potential for clinical application.

Complex pathogenesis and diverse clinical features pose many challenges in selecting appropriate cancer treatment strategies. Recent studies have shown that tumor-associated macrophages (TAMs) play dual roles in both promoting and inhibiting tumor growth. TAMs not only contribute to tumor survival and metastasis but also impact the response to therapy. Nanomaterial-based photothermal therapy (PTT) strategies have been widely used as ablative therapies for various cancers. Many studies have demonstrated that nanomaterial-mediated PTT effectively shifts TAMs towards an anticancer phenotype, thus inducing tumor apoptosis. Therefore, a comprehensive understanding of the tumor immune microenvironment will undoubtedly accelerate advancements in tumor therapy. This paper summarizes the application of nanomaterial-mediated PTT for cancer treatment by modulating TAMs. It highlights the types of nanomaterials and near-infrared laser modes used in the treatment process, analyzes the physicochemical factors that influence the distribution of different isoforms in TAMs, and finally explores the specific therapeutic parameters and mechanisms of nanomaterial-mediated PTT to guide future research in related fields.

The applicability of magnetic nanoparticles (MNP) highly depends on their physical properties, especially their size. Synthesizing MNP with a specific size is challenging due to the large number of interdepend parameters during the synthesis that control their properties. In general, synthesis control cannot be described by white box approaches (empirical, simulation or physics based). To handle synthesis control, this study presents machine learning based approaches for predicting the size of MNP during their synthesis. A dataset comprising 17 synthesis parameters and the corresponding MNP sizes were analyzed. Eight regression algorithms (ridge, lasso, elastic net, decision trees, random forest, gradient boosting, support vectors and multilayer perceptron) were evaluated. The model performance was assessed via root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and standard deviation of residuals. Support vector regression (SVR) exhibited the lowest RMSE values of 3.44 and a standard deviation for the residuals of 5.13. SVR demonstrated a favorable balance between accuracy and consistency among these methods. Qualitative factors like adaptability to online learning and robustness against outliers were additionally considered. Altogether, SVR emerged as the most suitable approach to predict MNP sizes due to its ability to continuously learn from new data and resilience to noise, making it well-suited for real-time applications with varying data quality. In this way, a feasible optimization framework for automated and self-regulated MNP synthesis was implemented. Key challenges included the limited dataset size, potential violations of modeling assumptions, and sensitivity to hyperparameters. Strategies like data regularization, correlation analysis, and grid search for model hyperparameters were employed to mitigate these issues.

This review explores the potential of biomolecule-based nanomaterials, i.e., protein, peptide, nucleic acid, and polysaccharide-based nanomaterials, in cancer nanomedicine. It highlights the wide range of design possibilities for creating multifunctional nanomedicines using these biomolecule-based nanomaterials. This review also analyzes the primary obstacles in cancer nanomedicine that can be resolved through the usage of nanomaterials based on biomolecules. It also examines the unique in vivo characteristics, programmability, and biological functionalities of these biomolecule-based nanomaterials. This summary outlines the most recent advancements in the development of two-dimensional semiconductor-based nanomaterials for cancer theranostic purposes. It focuses on the latest developments in molecular simulations and modelling to provide a clear understanding of important uses, techniques, and concepts of nanomaterials in drug delivery and synthesis processes. Finally, the review addresses the challenges in molecular simulations, and generating, analyzing, and developing biomolecule-based and two-dimensional semiconductor-based nanomaterials, and highlights the barriers that must be overcome to facilitate their application in clinical settings.

The on-demand delivery and release of chemotherapeutic drugs have attracted great attention, among which photoresponsive prodrug systems have shown specific advantages for effective cancer treatment due to their spatiotemporal control, non-invasive nature and easy operation. Unlike the traditional strategy of physical encapsulation of drugs in liposomes, we herein report a biomimetic and photoresponsive drug delivery system (DDS) based on a lipid prodrug liposomal formulation (LNC), which combines the features of the prodrug and nanomedicines, and can realize photocontrollable release of anticancer drugs. The lipid prodrug comprises three functional moieties: a single-arm phospholipid (Lyso PC), an o-nitrobenzyl alcohol (NB) and chlorambucil (CBL). Before irradiation, LNC formed liposomal assemblies in water with an average size of about 200 nm, and upon light irradiation, the efficient photocleavage reaction of NB facilitated the disintegration of liposomal assemblies and the release of drug CBL. Photolysis analysis showed that LNC exhibited accurate and controllable drug release in response to UV 365 nm irradiation. Cell viability assays showed that LNC liposomes demonstrated very low cytotoxicity in the dark and high cellular toxicity upon light irradiation, with toxicity even higher than free CBL. Our results suggest that our photoresponsive lipid prodrug represents a promising strategy to construct controlled DDS for cancer therapy.

The successful delivery of nanoparticles (NPs) to cancer cells is dependent on various factors, including particle size, shape, surface properties such as hydrophobicity/hydrophilicity, charges, and functional moieties. Tailoring these properties has been explored extensively to enhance the efficacy of NPs for drug delivery. Single-chain polymer nanoparticles (SCNPs), notable for their small size (sub-20 nm) and tunable properties, are emerging as a promising platform for drug delivery. However, the impact of surface charge on the biological performance of SCNPs in cancer cells remains underexplored. In this study, we prepared a library of SCNPs with varying charge types (neutral, anionic, cationic, and zwitterionic), charge densities, charge positions, and crosslinking densities to evaluate their effects on cellular uptake in MCF-7 breast cancer cells. Key findings include that cationic SCNPs are more likely to translocate into cells than neutral, anionic, or zwitterionic counterparts. Furthermore, cellular uptake was enhanced with increased charge density (from 10 to 15 mol%) before reaching a critical point (20 mol%) where excessive positive charge led to NP adhesion to the cell membrane, resulting in cell death. We also found that the position of the charge on the polymer chain also impacted the delivery of NPs to cancer cells, with tadpole-shaped SCNPs achieving the highest uptake. Furthermore, crosslinking density significantly influenced cellular uptake, with SCNPs at 50% crosslinking conversion showing the highest cytosolic localization, while other densities resulted in retention primarily at the cell membrane. This study offers valuable insights into how charge type, density, position, and crosslinking density affect the biological performance of SCNPs, guiding the rational design of more effective and safer drug delivery systems.

The complex battlefield environment often puts great pressure on the treatment of open wounds caused by burns and trauma, which cannot heal for a long time due to the lack of medical resources. Once wounds are not sutured and severely infected, they can lead to infective endocarditis, sepsis, and even death. Therefore, it is urgent to develop advanced dressings to replace sutures and antibiotics, which can quickly seal wounds and maintain long-term stability of antibacterial and antioxidant properties. In this study, novel biobased antibacterial adhesive gels composed of natural small molecule lipoic acid and eugenol were prepared via a one-pot solvent-free reaction for wound management. The gels were crosslinked via the ring-opening polymerization of lipoic acid and hydrogen bond interaction. Due to its structure feature, the PLA-E1 gel displayed excellent flexibility, transparency, self-healing and adhesiveness. The gel system showed long-term high antioxidant activity (95%) after exposure to air at room temperature for one year. Meanwhile, the reactive oxygen species (ROS) scavenging efficacy was kept around 52%. Both trauma and burn in vivo experiments demonstrated that the PLA-E1 gel could accelerate wound healing through antibacterial, antioxidant, angiogenic and tissue regenerative effects, indicating the potential applications of cutaneous wound healing on the battlefield.

Osteosarcoma is one of the most common primary malignant bone tumours in children and adolescents, frequently arising from mesenchymal tissue in the distal femur. It is highly aggressive, often metastasising to the lungs. Current treatments, which include surgery combined with neoadjuvant chemotherapy and radiotherapy, are often unsatisfactory due to the inability of surgery to control metastasis and the side effects and drug resistance associated with chemotherapy. Thus, there is an urgent need for new treatment technologies. This study explored the use of nanoparticles for gene and drug delivery in osteosarcoma treatment. The nanoparticles were composed of biodegradable and biocompatible polymers, chitosan and PLGA, and were loaded with miRNA-34a, a short RNA molecule that functions as a tumour suppressor by inducing cell cycle arrest and apoptosis in osteosarcoma cells. Recognising that the co-delivery of multiple drugs can enhance treatment efficacy while reducing systemic toxicity and drug resistance, three additional classes of nanoparticles were developed by adding doxorubicin and resveratrol to the chitosan-PLGA-miRNA-34a core. A layer-by-layer technique was employed to create a bilayer nanocoating using pectin and chitosan as polyelectrolytes, for encapsulating the therapeutic payloads. The manufactured nanoparticles were tested on U2OS and Saos-2 cells to assess cell viability, metabolic activity, and morphology before and after treatment. Cells were treated in both two-dimensional cultures and three-dimensional osteosarcoma spheroids, creating a biomimetic cellular model. Increased apoptotic activity and disruption of cellular functions were primarily observed with nanoparticles co-delivering miRNA-34a and drugs, particularly those functionalised with the LbL nanocoating, as confirmed by PCR analysis.

Multimodal therapy based on nanozyme is expected to become a novel option for tumor treatment. However, the catalytic efficiency of nanozymes and the hypoxia microenvironment of tumors limit the therapeutic effect of nanozymes. Herein, we screened a small molecule of midazole-2-carboxaldehyde (ICA) to prepare ZIF-90 and embedded gold and platinum nanoparticles to obtain ZAAP. ZAAP possessed a multi-enzymatic cascade of catalytic processes including greatly enhanced peroxidase activity via a "bionic" catalytic microenvironment (enhanced 23-fold), catalase and glucose oxidase activities, resulting in glucose decomposition to continuously supply H₂O₂, peroxidases for the catabolism of H₂O₂ to generate ROS and peroxidase-induced oxygen generation for continuous oxidation of glucose. All the above processes built a catalysis cycle that greatly promotes the generation of ROS and oxygen as well as the consumption of glucose, leading to the chemical dynamic therapy function and alleviating tumor hypoxia. In addition to the photothermal effect of ZAAP, a synergistic treatment of chemical dynamic/photothermal/starvation therapy was achieved, and the tumor inhibition rate reached 96.4% within 2 weeks, indicating that ZAAP shows great potential in nanozyme-based synergistic multimodal tumor treatment.

Seasonal influenza infection poses great threat to public health systems. The flu vaccine remains the most effective method to reduce transmission and mortality. However, its effectiveness is limited due to the challenges in protecting against all influenza variants, as well as the weaker immune response observed in the adult population. Here, combining machine learning, synchrotron small angle X-ray scattering, we design an adjuvanted influenza vaccine composing mosaic epitope peptides selected from the hemagglutinin proteins of influenza A and B virus. These epitopes share similar physiochemical properties cognate to host antimicrobial peptides (AMPs) allowing them to form supramolecular assembly with poly(I:C), a synthetic toll-like receptor 3 (TLR3) agonist, through electrostatic interaction. The poly(I:C) is arranged into columnar lattice with the average inter-poly(I:C) distance commensurate with TLR3 and thereby capable of inducing multivalent TLR3 binding and hyperactivating the downstream inflammatory pathway. Interestingly, multiple AMP-like epitopes (Ampitopes) with compatible lattice parameter can co-crystalize into the same lattice to form 'alloy'-like composite with better poly(I:C) arrangement which allows the co-delivery of mosaic Ampitopes. The designed Ampitope-poly(I:C) nanocrystalline (and alloy) successfully activates interferon regulatory factor 3 (IRF3)-mediated pathway in antigen presenting cells. The intramuscular delivery of the nanocrystalline to the mice strongly trigger IL-6 and IFN-α release, which well-mimics the cytokines release pattern in influenza infected patients. After the third boost, the antigen-specific T cell response is 55 times higher compared to the free Ampitopes treatment group. Together, this vaccine offers a versatile way of eliciting strong and broad anti-flu protection.