Search Results (168)

Atomic force microscopy (AFM)-based nanoindentation enables investigation of the mechanical response of biological materials at a subcellular scale. However, quantitative estimates of mechanical parameters such as the elastic modulus (E) remain unreliable because the influence of sample roughness on E measurements at the nanoscale is still poorly understood. This study re-examines the interpretation of roughness from a more rigorous perspective and validates an experimental methodology to extract roughness at each nanoindentation site—i.e., the local roughness γ_s—with which the corresponding E value can be accurately correlated. Cortical regions of a murine tibia cross-section, characterized by complex nanoscale morphology, were selected as a testbed. Eighty non-overlapping nanoindentations were performed using two different AFM tips, maintaining a maximum penetration depth of 10 nm for each measurement. Our results show a slight decreasing trend of E versus γ_s (Spearman’s rank correlation coefficient ρ = −0.27187). A total of 90% of the E values are reliable when γ_s < 10 nm (coefficient of determination R² > 0.90), although low γ_s values are associated with significant dispersion around E (γ_s = 0) = E₀ = 1.18 GPa, with variations exceeding 50%. These findings are consistent with a qualitative tip-to-sample contact model that accounts for the pronounced roughness heterogeneity typical of bone topography at the nanoscale. Full article

The structural units with different characteristic scales in gradient nanostructured (GS) 316L stainless steel act synergistically to achieve the matching of strength and plasticity, and the intrinsic plasticity of nanoscale and ultrafine grains is fully demonstrated. The macroscopic stress–strain responses of each material unit in the GS surface layer can be measured directly by tension or compression tests on microspecimens. However, the experimental results based on microspecimens do not reflect either the extraordinary strengthening effect caused by non-uniform deformation or the intrinsic plasticity of nanoscale and ultrafine grains. In this paper, a method for constructing depth-dependent constitutive relationships of GS materials was proposed, which combines strain hardening parameter (hardness) with physics-informed neural networks (PINNs). First, the microhardness distribution on the specimen cross-sections was measured after stretching to different strains, and the hardness–strain–force test data were used to construct the depth-dependent PINNs model for the true strain–hardness relationship (PINNs_εH). Hardness–strain–force test data from specimens with uniform coarse grains were used to pre-train the PINNs model for hardness and true stress (PINNs_Hσ), on the basis of which the depth-dependent PINNs_Hσ model for GS materials was constructed by transfer learning. The PINNs_εσ model, which characterizes the depth-dependent constitutive relationships of GS materials, was then constructed using hardness as an intermediate variable. Finally, the accuracy and validation of the PINNs_εσ model were verified by a three-point flexure test and finite element simulation. The modeling method proposed in this study can be used to determine the position-dependent constitutive relationships of heterogeneous materials. Full article

Exosomes are nanoscale extracellular vesicles (EVs) that carry biomolecular signatures reflective of their parent cells, making them powerful tools for non-invasive diagnostics and therapeutic monitoring. Despite their potential, clinical application is hindered by challenges such as low abundance, heterogeneity, and the complexity of biological samples. To address these limitations, plasmonic biosensing technologies—particularly propagating surface plasmon resonance (PSPR), localized surface plasmon resonance (LSPR), and surface-enhanced Raman scattering (SERS)—have been developed to enable label-free, highly sensitive, and multiplexed detection at the single-vesicle level. This review outlines recent advancements in nanoplasmonic platforms for exosome detection and profiling, emphasizing innovations in nanostructure engineering, microfluidic integration, and signal enhancement. Representative applications in oncology, neurology, and immunology are discussed, along with the increasingly critical role of artificial intelligence (AI) in spectral interpretation and diagnostic classification. Key technical and translational challenges—such as assay standardization, substrate reproducibility, and clinical validation—are also addressed. Overall, this review highlights the synergy between exosome biology and plasmonic nanotechnology, offering a path toward real-time, precision diagnostics via sub-femtomolar detection of exosomal miRNAs through next-generation biosensing strategies. Full article

A salient feature of modern material surfaces used in cutting-edge technologies is their structural and spatial complexity, which endows them with novel properties and multifunctionality. The quantitative characterization of material complexity is a challenge that must be addressed to optimize their production and performance. While numerous metrics exist to quantify the complexity of spatial structures in various scientific domains, methods specifically tailored for characterizing the spatial complexity of material surface morphologies at the micro- and nanoscale are relatively scarce. In this paper, we utilize the concept of multiscale entropy to quantify the complexity of surface morphologies of rough surfaces across different scales and investigate the effects of amplitude fluctuations (i.e., surface height distribution) in both stepwise and smooth self-affine rough surfaces. The crucial role of the binning scheme in regulating amplitude effects on entropy and complexity measurements is highlighted and explained. Furthermore, by selecting an appropriate binning strategy, we analyze the impact of 2D imaging on the complexity of a rough surface and demonstrate that imaging can artificially introduce peaks in the relationship between complexity and surface amplitude. The results demonstrate that entropy-based spatial complexity effectively captures the scale-dependent heterogeneity of stepwise rough surfaces, providing valuable insights into their structural properties. Full article

Ultra-high-molecular-weight polyethylene (UHMWPE) is a pivotal material in engineering and biomedical applications due to its exceptional mechanical strength, wear resistance, and impact performance. However, its extreme melt viscosity, caused by extensive chain entanglements, severely limits processability via conventional melt-processing techniques. Recent advances in catalytic synthesis have enabled the production of disentangled UHMWPE (dis-UHMWPE), which exhibits enhanced processability while retaining superior mechanical properties. Notably, heterogeneous catalytic systems, utilizing supported fluorinated bis (phenoxy-imine) titanium (FI) catalysts, polyhedral oligomeric silsesquioxanes (POSS)-modified Z-N catalysts, and other novel catalysts, have emerged as promising solutions, combining structural control with industrial feasibility. Moreover, optimizing polymerization conditions further enhances chain disentanglement while maintaining ultra-high molecular weights. These systems utilize nanoscale supports and ligand engineering to spatially isolate active sites, tailor the chain propagation/crystallization kinetics, and suppress interchain entanglement during polymerization. Furthermore, characterization techniques such as melt rheology and differential scanning calorimetry (DSC) provide critical insights into chain entanglement, revealing distinct reorganization kinetics and bimodal melting behavior in dis-UHMWPE. This development of hybrid catalytic systems opens up new avenues for solid-state processing and industrial-scale production. This review highlights recent advances concerning interaction between catalyst design, polymerization control, and material performance, ultimately unlocking the full potential of UHMWPE for next-generation applications. Full article

Porous media have great application prospects, such as transpiration cooling for the aerospace industry. The main challenge for the prediction of gas permeability includes the geometrical complexity and high Knudsen number of gas flow at the nano-scale to micro-scale, leading to failure of the conventional Darcy’s law. To address these issues, the Quartet Structure Generation Set (QSGS) method is improved to construct anisotropic and heterogeneous three-dimensional porous media, and the lattice Boltzmann method (LBM) with the multiple relaxation time (MRT) collision operator is adopted. Using MRT-LBM, the pressure boundary conditions at the inlet and outlet are firstly dealt with using the moment-based boundary conditions, demonstrating good agreement with the analytical solutions in two benchmark tests of three-dimensional Poiseuille flow and flow through a body-centered cubic array of spheres. Combined with the Bosanquet-type effective viscosity model and Maxwellian diffuse reflection boundary condition, the gas flow at high Knudsen (Kn) numbers in three-dimensional porous media is simulated to study the relationship between pore-scale anisotropy, heterogeneity and Kn, and permeability and micro-scale slip effects in porous media. The slip factor is positively correlated with the anisotropic factor, which means that the high Kn effect is stronger in anisotropic structures. There is no obvious correlation between the slip factor and heterogeneity factor. Full article

The stress sensitivity of shale caprock permeability is a critical factor influencing the long-term security of CO₂ geological sequestration systems. Substantial amounts of clay minerals and nanoscale pore structures reduce shale permeability by trapping water films and throat contraction. Conventional permeability models, which are based on homogeneous pore compressibility, tend to overestimate the contribution of non-effective pores to water mobility, resulting in significant inaccuracies in predicting stress-dependent permeability. Therefore, this study conducted NMR–seepage experiments under varying confining pressures on four shale samples with distinct lithologies to investigate pore compression deformation and permeability stress sensitivity. The T₂ cutoff was subsequently determined through displacement tests to distinguish seepage and adsorption pores. Two distinct constitutive models were calculated with respective compressibility coefficients. Finally, the effects of seepage and adsorption pores on shale permeability stress sensitivity were investigated. The results indicate the following. (1) Increasing confining pressure from 15 to 19 MPa reduces porosity by 14.2–39.6%, with permeability exhibiting a significant decline of 35.6–67.8%. (2) Adsorption pores, stabilized by bound water films of clay minerals, exhibit limited closure under stress. In contrast, seepage pores, influenced by brittle minerals, experience significant deformation, which predominantly contributes to permeability decline. (3) A dual-spring model, differentiating the compressibility of seepage and adsorption pores, reduces prediction errors by 92–96% compared to traditional models. These results highlight that neglecting pore-type-specific compressibility leads to overestimated permeability in heterogeneous shale, with critical implications for optimizing CO₂ storage integrity and hydrocarbon recovery strategies. Full article

This review explores recent advances in data processing for atomic force microscopy (AFM) nanoindentation on soft samples, with a focus on “apparent” or “average” Young’s modulus distributions used for cancer diagnosis and treatment monitoring. Young’s modulus serves as a potential key biomarker, distinguishing normal from cancerous cells or tissue by assessing stiffness variations at the nanoscale. However, user-independent, reproducible classification remains challenging due to assumptions in traditional mechanics models, particularly Hertzian theory. To enhance accuracy, depth-dependent mechanical properties and polynomial corrections have been introduced to address sample heterogeneity and finite thickness. Additionally, AFM measurements are affected by tip imperfections and the viscoelastic nature of biological samples, requiring careful data processing and consideration of loading conditions. Furthermore, a quantitative approach using distributions of mechanical properties is suitable for tissue classification and for evaluating treatment-induced changes in nanomechanical properties. As part of this review, the use of AFM-based mechanical properties as a tool for monitoring treatment outcomes—including treatments with antifibrotic drugs and photodynamic therapy—is also presented. By analyzing nanomechanical property distributions before and after treatment, AFM provides insights for optimizing therapeutic strategies, reinforcing its role in personalized cancer care and expanding its applications in research and clinical settings. Full article

Background: Exosomes are nanoscale extracellular vesicles actively secreted by cells that play critical roles in disease biomarker discovery, drug delivery, and direct therapeutic applications. However, in vivo pharmacokinetic (PK) studies of exosomes remain limited, hindering their clinical translation. Due to their complex and heterogeneous composition, most existing PK methods rely on chemical or genetic labeling, which may alter their native behavior and complicate accurate analysis. Methods: To address this challenge, we developed a label-free liquid chromatography–tandem mass spectrometry (LC-MS/MS) method to investigate the PK of naive exosome-based therapeutic modalities. Exosomes were isolated from rat plasma using size exclusion chromatography (SEC) and quantified using multiple reaction monitoring (MRM) targeting specific exosomal peptides as surrogate analytes. Following intravenous administration of exosomes via the tail vein, plasma concentrations were determined by peptide peak areas, and PK parameters were calculated using a non-compartmental model. Results: The method was rigorously validated for specificity, linearity, sensitivity, and reproducibility. Its feasibility was further confirmed by successfully characterizing the PK profile of HEK 293F-derived exosomes in rats. Conclusions: This analytical strategy enables direct, label-free quantification of exosomes in plasma and provides a robust platform for advancing exosome-based drug development and translational research. Full article

Bacterial extracellular vesicles (BEVs) have emerged as pivotal mediators of host–microbe interactions, profoundly influencing cancer biology. These nanoscale vesicles, produced by both Gram-positive and Gram-negative bacteria, carry diverse biomolecular cargo such as proteins, lipids, nucleic acids, and metabolites. BEVs play dualistic roles in tumor promotion and suppression by modulating the tumor microenvironment, immune responses, and genetic regulation. This review synthesizes the current understanding of BEVs in various cancers, including gastrointestinal, ovarian, breast, lung, brain, and renal malignancies. BEVs are highlighted for their potential as diagnostic biomarkers, prognostic indicators, and therapeutic agents, including their applications in immunotherapy and advanced engineering for precision medicine. Challenges such as heterogeneity, standardization, and clinical scalability are critically analyzed, with case examples providing actionable insights. Future directions emphasize interdisciplinary collaborations, emerging technologies, and the integration of BEV-based tools into clinical workflows. This review underscores the transformative potential of BEVs in advancing cancer diagnostics and therapeutics, paving the way for innovations in precision oncology. Full article

Exosomes have emerged as pivotal players in precision oncology, offering innovative solutions to longstanding challenges such as metastasis, therapeutic resistance, and immune evasion. These nanoscale extracellular vesicles facilitate intercellular communication by transferring bioactive molecules that mirror the biological state of their parent cells, positioning them as transformative tools for cancer diagnostics and therapeutics. Recent advancements in exosome engineering, artificial intelligence (AI)-driven analytics, and isolation technologies are breaking barriers in scalability, reproducibility, and clinical application. Bioengineered exosomes are being leveraged for CRISPR-Cas9 delivery, while AI models are enhancing biomarker discovery and liquid biopsy accuracy. Despite these advancements, key obstacles such as heterogeneity in exosome populations and the lack of standardized isolation protocols persist. This review synthesizes pioneering research on exosome biology, molecular engineering, and clinical translation, emphasizing their dual roles as both mediators of tumor progression and tools for intervention. It also explores emerging areas, including microbiome–exosome interactions and the integration of machine learning in exosome-based precision medicine. By bridging innovation with translational strategies, this work charts a forward-looking path for integrating exosomes into next-generation cancer care, setting it apart as a comprehensive guide to overcoming clinical and technological hurdles in this rapidly evolving field. Full article

The transition to sustainable energy has given biodiesel prominence as a renewable alternative to diesel. This review highlights the development and optimization of solid transesterification catalysts, contributing greatly to the efficiency of biodiesel synthesis. These heterogeneous catalysts are constituted of titanium-, zinc-, and bio-based systems and significant advantages such as reusability, thermal stability, and the ability to be synthesized from low-grade feedstocks. Recent advancements in structural optimization, with nano-structured titanium dioxide having the potential of yielding higher biodiesel production up to a yield of 96–98% within 5–7 cycles, render improved stability and catalytic performance. Several characterization techniques, such as the Brunauer–Emmett–Teller method, X-ray diffraction, and temperature-programmed desorption, are instrumental in the characterization of these catalysts and their effective design. However, despite their substantial promise, there are still problems to be dealt with in the large-scale production, regeneration, and service life stability of these catalysts. This account collates recent innovations, analytical mechanisms, and prospective directions which elucidate the potential of solid transesterification catalysts in furthering biodiesel technology and the sustainable production of chemicals. Full article

Human milk is a complex biofluid containing a diverse array of cells crucial for infant health. Despite their importance, our understanding of these cells remains incomplete due to technical challenges. To fully comprehend human milk cells, high-resolution imaging technologies that can directly measure biological processes are required. We have developed a specialized imaging platform combining light and electron microscopy for human milk cell imaging. To identify different cell types, human milk cells were first stained with several specific cell markers (e.g., EpCAM and MUC1 for lactocytes, CD16 and CD66b for neutrophils, and HLA-DR and CD68 for macrophages) prior to light (confocal) microscopy. Following this, the same cells were processed with osmium staining, resin embedding, and sectioning for electron microscopy, allowing us to observe ultrastructural details. Our imaging workflow has enabled nanoscale visualization of human milk cells, resulting in a first-of-its-kind comprehensive database profiling the organelle-level ultrastructure of different cell types present in human milk. The cells in the human milk are highly heterogenous, featuring a large proportion of lactocytes and lipid droplets, binucleated lactocytes, neutrophil aggregation, neutrophil extracellular traps, dendritic cells/macrophages with bacteria, and immunophagocytosis. This study provides valuable cellular insights contributing to a deeper understanding of human milk biology. Full article

An Integrated Process Intensification (IPI) technology-based roadmap is proposed for the utilization of renewables (water, air and biomass/unavoidable waste) in the small-scale distributed production of the following primary products: electricity, H₂, NH₃, HNO₃ and symbiotic advanced (SX) fertilizers with CO₂ mineralization capacity to achieve negative CO₂ emission. Such a production platform is an integrated intensified biorefinery (IIBR), used as an alternative to large-scale centralized production which relies on green electricity and CCUS. Hence, the capacity and availability of the renewable biomass and unavoidable waste were examined. The critical elements of the IIBR include gasification/syngas production; syngas cleaning; electricity generation; and the conversion of clean syngas (which contains H₂, CO, CH₄, CO₂ and N₂) to the primary products using nonthermal plasma catalytic reactors with in situ NH₃ sequestration for SA fertilizers. The status of these critical elements is critically reviewed with regard to their techno-economics and suitability for industrial applications. Using novel gasifiers powered by a combination of CO₂, H₂O and O₂-enhanced air as the oxidant, it is possible to obtain syngas with high H₂ concentration suitable for NH₃ synthesis. Gasifier performances for syngas generation and cleaning, electricity production and emissions are evaluated and compared with gasifiers at 50 kWe and 1–2 MWe scales. The catalyst and plasma catalytic reactor systems for NH₃ production with or without in situ reactive sequestration are considered in detail. The performance of the catalysts in different plasma reactions is widely different. The high intensity power (HIP) processing of perovskite (barium titanate) and unary/binary spinel oxide catalysts (or their combination) performs best in several syntheses, including NH₃ production, NO_x from air and fertigation fertilizers from plasma-activated water. These catalysts can be represented as BaTi_1−vO_3−x{#}_yN_z (black, piezoelectric barium titanate, bp-{BTO}) and M⁽¹⁾_3−jM⁽²⁾_kO_4−m{#}_nN_r/SiO₂ (unary (k = 0) or a binary (k > 0) silane-coated SiO₂-supported spinel oxide catalyst, denoted as M/Si = X) where {#} infers oxygen vacancy. HIP processing in air causes oxygen vacancies, nitrogen substitution, the acquisition of piezoelectric state and porosity and chemical/morphological heterogeneity, all of which make the catalysts highly active. Their morphological evaluation indicates the generation of dust particles (leading to porogenesis), 2D-nano/micro plates and structured ribbons, leading to quantum effects under plasma catalytic synthesis, including the acquisition of high-energy particles from the plasma space to prevent product dissociation as a result of electron impact. M/Si = X (X > 1/2) and bp-{BTO} catalysts generate plasma under microwave irradiation (including pulsed microwave) and hence can be used in a packed bed mode in microwave plasma reactors with plasma on and within the pores of the catalyst. Such reactors are suitable for electric-powered small-scale industrial operations. When combined with the in situ reactive separation of NH₃ in the so-called Multi-Reaction Zone Reactor using NH₃ sequestration agents to create SA fertilizers, the techno-economics of the plasma catalytic synthesis of fertilizers become favorable due to the elimination of product separation costs and the quality of the SA fertilizers which act as an artificial root system. The SA fertilizers provide soil fertility, biodiversity, high yield, efficient water and nutrient use and carbon sequestration through mineralization. They can prevent environmental damage and help plants and crops to adapt to the emerging harsh environmental and climate conditions through the formation of artificial rhizosphere and rhizosheath. The functions of the SA fertilizers should be taken into account when comparing the techno-economics of SA fertilizers with current fertilizers. Full article

In this work, Al–Mg alloys fabricated by combining continuous rheo-extrusion (CRE) and Sc modification were proposed for producing Al–Mg alloys with high efficiency and superior mechanical performance. The microstructural evolution and mechanical property response of the CREed Al–5Mg alloy with Sc modification were investigated. The grain refinement and strengthening mechanisms induced by nanoscale Al₃Sc-phase particles in the alloy were discussed. The results showed that an obvious grain refinement effect was achieved in the CREed Al–5Mg alloy as the Sc content increased from 0 to 0.5 wt%, and the average grain size decreased from 52.6 μm to 2.4 μm, respectively. The primary Al₃Sc-phase particles formed during solidification behaved as heterogeneous nucleation sites for the α-Al matrix, while the nanoscale Al₃Sc-phase particles achieved during CRE enhanced the driving force of continuous dynamic recrystallization and the Zener drag force. As a result, a superior grain refinement effect was observed. The ultimate tensile strength, yield strength, and hardness of the alloy were enhanced as the Sc content increased from 0 to 0.5 wt%. Grain boundary strengthening, second-phase strengthening, and dislocation strengthening were the main strengthening mechanisms of the CREed Al–Mg–Sc alloys. Full article