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Nanomaterials have gained huge importance in various fields, such as healthcare, electronics, and environmental management, due to their unique characteristics. However, the potent toxicity is a big concern regarding their utility. Toxicological assessment becomes an important step to ensure their safe applications. The significant hazards of nanomaterials have risen from their shape, size, charge, and makeup, which leads to genetic damage, cellular uptake, and internalization with oxidative stress (OS) and harm to specific organs. This review focuses on toxicity profiles and their possible interactions with cellular organelles leading to apoptosis (Apop) and long-term bioaccumulation.Size, surface area, and dissolving capability may affect the toxicity of nanomaterials. Different measures such as encapsulation methods, increasing surface area, and enhancing biodegradability are being considered to reduce toxicity from innovative nanomaterials. Knowledge gaps encompass uneven toxicity evaluations, inadequate chronic exposure data, and insufficient attention to individualized reactions. The integration of standardized models, computational predictions, mechanistic investigations, and regulatory compliance is crucial for the safer design of nanomaterials. The review highlights toxicological issues caused by nanomaterials such as nanoformulation, quantum dots, and nanoparticles. It also directs future strategies in nanotoxicology, highlighting increasing assessment models, strategies, and collaborative research efforts. Bringing together regulatory and research efforts in the context of nanomaterials is important for ensuring the safe application of nanomaterials across pharmacy and other industries. This review offers a comprehensive viewpoint connecting physicochemical factors, sophisticated in vitro models, and developing regulatory frameworks, emphasizing emerging trends including microphysiological systems and animal-free risk assessment methodologies.
Variable thermal conductivity plays important role in precisely modeling of hybrid nanofluid (HNF) flow and heat transfer. In practical applications, thermal conductivity frequently varies with temperature, nanoparticle concentration, and fluid composition, affecting the rate of energy transfer within the system. The present investigation offers an inclusive investigation of heat transfer in magnetized flow of a HNF consisting of zinc (Zn) and silicon dioxide (SiO2) nanoparticles dispersed in water (H2O), towards a rotating stretchable surface. The management of thermal energy in rotating, high-speed environments can be significantly enhanced through the use of magnetized nanofluids with optimized nanoparticle shapes. This study incorporates the effects velocity slip, and convective boundary conditions. The principal objective is to explore the transport phenomena of heat and mass transfer, as well as the bioconvective behavior induced by motile microorganisms within the hybrid nanofluid. By applying similarity transformation, the governing flow model of PDE's for momentum, energy, concentration, and motile microorganism distribution are condensed to a set of coupled nonlinear ODE's. These equations are numerically solved with MATLAB software, which employs a vigorous shooting method. A thoroughly parametric investigation is performed to assess the influence of several physical parameters, including the magnetic field strength (Μ), rotational parameter (λ), velocity slip coefficient (β), thermal radiation parameter ([Formula: see text]), variable thermal conductivity (ε), and the volume fractions of the nanoparticles ([Formula: see text]), along with the nanoparticle shape factor. Furthermore, the effects of the Lewis number ([Formula: see text]), Peclet number ([Formula: see text]) and bioconvective Lewis number ([Formula: see text]) are examined with respect to species concentration and microorganism. The numerical fallouts are presented both graphically and in tabular format, demonstrating that enhancements in magnetic field strength and radiation parameter notably affect the thermal and flow characteristics. The legitimacy of the suggested model is confirmed through excellent agreement with benchmark outcomes from existing literature across various Prandtl number ([Formula: see text]) values, thereby signifying the reliability and practical relevance of the current approach in advanced hybrid nanofluid-based thermal management systems.
Polyvinyl alcohol (PVA) is a widely used polymer in many applications. The nanoparticles' incorporation into the polyvinyl alcohol structure can significantly modify the electrical characteristics by benefiting the properties of both polymer and nanofillers. Although the dielectric constant of PVA-based nanocomposites has been comprehensively measured, no general predictive model currently exists for its estimation. So, this study develops a robust, data-driven framework to predict the dielectric constant of PVA nanocomposites as a function of nanofiller type, filler concentration, temperature, and frequency. First, a comprehensive dataset of 1698 experimental measurements was gathered from the literature, covering nanofillers including CuO, TiO2, ZnO, Al2O3, GO, V2O5, SrTiO3, and PbO. Feature relevance was first analyzed using multiple linear regression, followed by the implementation and comparison of six machine learning models, i.e., categorical boosting, gradient boosting (GradBoost), extreme gradient boosting, least-squares support vector regression, multilayer perceptron neural network, and adaptive neuro-fuzzy inference system. Among these, the GradBoost model demonstrated superior predictive performance and generalization capability. The GradBoost model achieved high accuracy in cross-validation (1359 samples) with AARD = 3.38%, RMSE = 3.49, MAE = 0.83, and R = 0.99926, and maintained strong performance on the external test set (339 samples) with AARD = 9.32%, RMSE = 4.24, MAE = 1.76, and R = 0.99877. The proposed model represents the first generalized predictive tool for estimating the dielectric constant of PVA-based nanocomposites across multiple nanofillers and operating conditions. This approach provides a practical and accurate alternative to experimental study, enabling accelerated design and optimization of polymer nanocomposites for electronic and dielectric applications.
We have found activated carbon nanoparticles (ACNP) can be used as carriers of nanodrug delivery systems to treat cervical cancer. But how ACNP to enter into the HeLa cell, how to distribute, translocate and, metabolize and develop therapeutic effects has been unknown. In this paper, we invested the action of ACNP on HaLa cells in comparison with single walled carbon nanotubes (SWCNT) and quantum dots (QDs) in vitro. The effects of the nanoparticles on the HeLa cells were observed by tetrazolium bromide reduction (MTT) assay, lactate dehydrogenase leakage determination (LDH), flow cytometry, apoptotic rate, DNA comet assay. The morphological influences of nanoparticles on HeLa cells were observed with inverted microscope and atomic force microscopy (AFM); The mechanism of across cell membrane translocation of ACNP, SWCNT and QDs was investigated by treating the cells with endocytosis inhibitors and 4 °C low temperature. The three nanoparticles can inhibit the proliferation of HeLa cells in time- and concentration-dependent manners. Under the light microscope, the volume of HeLa cells treated by ACNP and SWCNT became smaller than that of control group. ACNP and SWCNT can induce HeLa cells shrinkage, weaken cell adhesion and increase the number of free cells in culture media. Under AFM, ACNP caused ill-defined cell membranes and membrane rupture; SWCNT caused cell shrinkage, reduced adhesion properties and "collapse-like" structure; QDs induced cell surface roughness and cell membrane folds. There are many irregular depressions in the cells. Flow cytometry showed that the three nanoparticles induced apoptosis of Hela cells. Electrophoresis showed the three nanoparticles induced DNA damage. Transmission electron microscopy(TEM) revealed that ACNP can pass through the cell membrane into the cytoplasm and further into the nucleus, causing disappearance of surface microvilli, mitochondrial swelling and nuclear shrinkage; SWCNT can enter into HeLa cells in the medium without inhibitors under room temperature, inducing cell and nuclear shrinkage, SWCNT was not found in the HeLa cells treated by inhibitors and low temperature; QDs was found accumulated in the cell membranes and can also cause swelling of mitochondria and increase cytoplasmic vacuoles. The three kinds of nanoparticles can inhibit the growth and cause apoptosis of HeLa cells; the mechanism may be nuclear DNA damage and increased membrane permeability; The internalization of SWCNT by HeLa cells is energy dependent while the internalization of ACNP is independent of energy. The DNA damage effects of ACNP may be realized through two ways, one of which is to injure cell membranes and the other is to act on DNA directly. QDs damage DNA mainly through the action of cell membranes.
High-risk human papillomavirus (HPV) infection, particularly HPV16 and HPV18, is the primary etiological factor in cervical cancer development. The oncogenic potential of these viruses stems from the action of viral E6 and E7 oncoproteins, which drive malignant transformation by degrading tumor suppressor proteins p53 and pRb, disrupting cell cycle regulation, and inducing genomic instability [1, 2]. These mechanistic insights underscore the critical need for sensitive, rapid, and reliable diagnostic tools suitable for point-of-care settings to enable early detection and intervention. We designed, synthesized, and evaluated bimetallic nano mixture-based lateral flow assays (LFAs) employing Au-Cu, Ag-Cu, and Ag-Au nano mixtures for detection of HPV16 L1 and HPV18 L1 capsid proteins. Nanoparticles were characterized by dynamic light scattering (DLS), zeta potential analysis, scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, UV-Vis spectroscopy, and X-ray photoelectron spectroscopy (XPS) before and after functionalization with CTAB and monoclonal antibodies. Analytical performance including linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, specificity, and stability was systematically validated. Clinical evaluation was conducted using 100 cervical samples, with performance parameters calculated against PCR as reference standard. Additional experiments were performed to assess early infection detection capability, correlation with E6/E7 oncoprotein expression, and specificity in the presence of p53 and pRb tumor suppressor proteins. Physicochemical characterization revealed successful antibody conjugation across all formulations, with predictable increases in hydrodynamic size (5-7 nm) and shifts toward less negative zeta potentials (-30 to -35 mV). Among monometallic systems, Au nanoparticles demonstrated the highest analytical sensitivity (LOD = 1 ng/mL), while Cu nanoparticles showed the poorest performance (LOD = 12 ng/mL). Remarkably, bimetallic nano mixtures dramatically outperformed monometallic counterparts, with Ag-Au nano mixtures achieving the lowest LOD (0.15 ng/mL), highest linearity (R2 = 0.998), and most rapid response time (10 min). Time-course experiments revealed that Ag-Au LFA detected infection as early as day 3 post-infection, 4 days before detection of integrated viral DNA. Among 20 PCR-positive clinical samples, 18 (90%) showed detectable E6/E7 oncoprotein expression, with strong correlations between LFA signal intensity and both E6 (r = 0.82) and E7 (r = 0.79) levels. No cross-reactivity was observed with p53, pRb, or E6/E7 oncoproteins. Clinical evaluation demonstrated that Ag-Au formulations achieved superior clinical performance (95% sensitivity, 91-92% specificity for both HPV targets), 96% positive predictive value (PPV), and 89-90% negative predictive value (NPV). Bimetallic nano mixture-based LFAs, particularly the Ag-Au formulation, represent a highly sensitive, specific, and rapid point-of-care diagnostic platform for HPV detection. By enabling early identification of high-risk HPV infection-the critical initiating event in cervical carcinogenesis driven by E6/E7-mediated disruption of p53 and pRb tumor suppressor pathways-this platform addresses a crucial need in cervical cancer prevention.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder with limited disease-modifying treatment options, partly because many therapeutic agents show insufficient brain exposure and dose-limiting systemic adverse effects after conventional administration. Nose-to-brain (N2B) delivery has emerged as a non-invasive strategy to transport therapeutics to the central nervous system through the olfactory and trigeminal pathways, thereby partially bypassing the blood-brain barrier. Recent advances in nanomedicine and biomaterial engineering have further improved this approach by enhancing drug stability, nasal residence, mucosal transport, and brain-targeting efficiency. This review examines nanocarrier-enabled N2B delivery strategies for AD from a mechanism-guided perspective, highlighting how AD-related pathological processes shape the selection of therapeutic cargos and formulation designs. We discuss recent progress in the intranasal delivery of repurposed small molecules, natural products, insulin-related agents, peptides and proteins, extracellular vesicles, antibodies, and nucleic acid-based therapeutics. We further summarize major nanocarrier and formulation platforms, including lipid-based systems, polymeric nanoparticles, micelles, extracellular vesicles, in situ gels, and device-assisted delivery technologies. Particular attention is given to the design parameters that influence N2B performance, including particle size distribution/PDI, surface charge, mucus interaction, cargo protection, targeting modification, biodistribution, and deposition reproducibility. Finally, we critically evaluate the translational challenges that continue to limit clinical application, including species differences in nasal anatomy, dose-volume restrictions, device-dependent variability, limited human pharmacokinetic evidence, manufacturing complexity, long-term safety, and regulatory requirements. By integrating disease mechanisms, nanocarrier design, and translational considerations, this review provides a structured perspective for developing more rational and clinically feasible N2B nanodelivery systems for AD.
This study investigates the Darcy-Forchheimer stagnation point flow and heat transfer characteristics of Williamson hybrid nanofluid (Cu-TiO2 -Kerosene) over a stretching cylinder under the influence of convective boundary conditions and Cattaneo-Christov heat flux. The mathematical model is formulated by considering nonlinear heat source/sink, activation energy, Brownian motion, thermophoresis and porous medium effects. Appropriate similarity transformations are utilized to convert the governing partial differential equations into a system of nonlinear ordinary differential equations. The transformed equations are solved numerically using the MATLAB BVP4C technique. The novelty of the present work lies in the simultaneous investigation of Williamson hybrid nanofluid flow with Darcy-Forchheimer resistance, Cattaneo-Christov heat flux, nonlinear heat generation/absorption and stagnation point effects over a stretching cylinder. The obtained numerical results are validated through comparison with previously published studies, showing excellent agreement. The impacts of important physical parameters on velocity, temperature and concentration profiles are examined graphically and numerically for both nanofluid and hybrid nanofluid cases. The results reveal that increasing the Darcy-Forchheimer parameter and porosity parameter reduces the velocity profile due to enhanced resistance within the porous medium. The temperature profile increases significantly with higher Brownian motion, thermophoresis and Biot number parameters, while the Prandtl number reduces thermal boundary layer thickness. Concentration distribution decreases with increasing Schmidt number, whereas activation energy enhances concentration behavior. It is further observed that the hybrid nanofluid exhibits superior thermal performance compared to conventional nanofluid, making it more effective for advanced thermal management and industrial heat transfer applications.
Pesticides have long been essential in agriculture for controlling pests, diseases, and weeds; however, their extensive use has led to serious concerns regarding resistance development, environmental contamination, and human health risks. Nano-biopesticides have emerged as a sustainable alternative, offering enhanced efficacy, reduced toxicity, improved target specificity, and controlled release behaviour. These formulations are typically developed either by employing nanomaterials with intrinsic pesticidal activity or by encapsulating active ingredients within nanoscale carriers to improve stability, solubility, and bioavailability. This review focuses on the formulation and characterization of nano-biopesticides via nanosuspension technology, highlighting preparation methods, key components, and mechanisms of action. In addition, special emphasis is placed on the role of advanced packaging design in maintaining physicochemical stability, preventing degradation, and extending shelf-life through the use of biodegradable polymers, UV-protective materials, and smart controlled-release systems. Despite their potential, challenges related to toxicity, environmental fate, and regulatory frameworks remain. Further research is essential to ensure the safe and scalable application of nano-biopesticides in sustainable agriculture.
Treatment protocols of cancer combining radiotherapy and nanoparticles are rapidly evolving. To evaluate their efficacy, spheroids provide a 3D in vitro model that better reflects tumor architecture than traditional 2D cell cultures. This article presents a workflow to prepare and characterize spheroids, optimize the protocols for irradiation with medical photon and ion beams and for exposure to nanoparticles, and, finally, to evaluate the effects of radiation, nanoparticles, and their combination on spheroids. Illustrations with HeLa, U-87 MG, and BxPC-3 tumor cell lines and HDFn are reported. Using this workflow, we observed that spheroids exhibit variable cell organization and interstitial spaces, which affect nutrient and oxygen diffusion and, consequently, cell proliferation. These structural differences also affect enzyme diffusion, limiting the applicability of the clonogenic assay in densely packed spheroids, as the assay requires enzymatic disaggregation of the spheroids. The clonogenic assay remains essential for quantitatively comparing spheroid irradiation results with 2D cell culture experiments. It has long been used as the reference method in radiobiology because it assesses mitotic death and long-term proliferative capacity. Protocols were adapted to ensure the feasibility of the clonogenic assay when possible, depending on cell line characteristics. Interstitial spaces also influenced nanoparticle internalization, which was more efficient in spheroids with larger interstitial spaces. This workflow and associated techniques verified the characteristic effect of carbon ion irradiation with a relative biological effectiveness of ~ 3 and demonstrated a ~ 30% radioenhancing effect of platinum nanoparticles at 2 Gy under 6 MV photons.
The composites inspired by nacre, bone and teeth etc, often display anisotropic mechanical properties due to the high aspect ratio of their structural units, resulting in sudden failures under specific loading conditions. It still remains great challenge for fabricating the nanocomposites with weakly anisotropic mechanical properties. Herein, we discover the unique structure of the Raphia hookeri seed with a weakly anisotropic crack resistance in multiple directions. The remarkable mechanical properties stem from its tightly bonded, isodiametric cells and interlocking pits. Drawing inspiration from Raphia hookeri seed, we demonstrate an artificial Raphia hookeri seed nanocomposites by assembling layered polymethyl methacrylate-graphene microspheres with pits, which were then interwoven with polymethyl methacrylate to mimic the essential hierarchical structure. The artificial Raphia hookeri seed exhibits effective toughening performance across all crack orientations, and achieves a fracture toughness of up to 4.84 MPa m1/2 and specific toughness of 4.28 MPa m1/2/(Mg m-3), which are higher than both natural Raphia hookeri seed and previously fabricated weakly anisotropic polymer nanocomposites. The optimal distribution of pits and enhanced interfacial interactions between microspheres effectively inhibit crack propagation, contributing to the artificial Raphia hookeri seed's superior toughness in all directions. This pit-enabled granular microsphere architecture provides an avenue for fabrication high-performance weakly anisotropic nanocomposites.
Radiotherapy is one of the most basic clinical tumor treatment methods, yet its efficacy is often limited by radioresistance and off-target toxicity. Nanoradiosensitizers have emerged as a promising strategy for enhancing local dose deposition and regulating tumor microenvironment (TME). Despite the rapid development of the nanoradiosensitizer field, a comprehensive roadmap describing its evolution remains lacking. We analyzed 1,866 publications on nanoradiosensitizers in the Web of Science Core Collection (WoSCC) database up to 2024. The global landscape is drawn using advanced visualization tools, including Bibliometrix, VOSviewer, CiteSpace, and Scimago Graphica. Our analysis reveals that the field has undergone exponential growth and a distinct paradigm shift, with research focus evolving from initial material synthesis (e.g., high-Z metals for physical dose enhancement) to complex biological regulation (e.g., hypoxia relief, TME regulation). Notably, keywords and trend analysis have identified that the integration of nanoradiosensitizers with immunotherapy has become the frontier of the current research field, such as enhanced immunogenic cell death (ICD) and immune checkpoint blockade (ICB). Overall, this study highlights the shift of nanoradiosensitizers from material-driven exploration toward mechanism-based biological and translational studies. Future research must prioritize overcoming translational barriers, including biosafety, large-scale manufacturing, and clinical evaluation, to enable the clinical application of radioimmunotherapy strategies.
The ability to manipulate and probe individual nano-particles, viruses, and organelles with high sensitivity and specificity is an essential part of modern nanoscience and molecular biology. Plasmonic optical tweezers (POT), which use localized surface plasmons to create nanoscale-confined optical fields, have emerged as a powerful platform for trapping and manipulating single nano-bio entities at low optical powers. When combined with surface-enhanced Raman spectroscopy (SERS) from the same plasmonic nanostructures, these platforms offer a unique multi-modal capability: simultaneous optical manipulation and label-free chemical fingerprinting of a single specimen. However, the field faces critical challenges, including low throughput, thermal noise, photothermal damage, and the overwhelming complexity of interpreting dynamic, single-molecule SERS data. This review examines the transformation of plasmonic optical trapping and spectroscopy as they evolve toward autonomous operation and intelligent decision-making. We begin with the fundamental principles that enable these tools to manipulate and probe single viruses, organelles, and nano-particles. Building on this foundation, we explore how computational intelligence is being integrated into the field to address long-standing challenges. This includes the emergence of data-driven methods for designing optimized plasmonic nanostructures, for decoding the complex molecular fingerprints hidden in single-molecule SERS spectra, and for creating feedback-driven systems capable of adaptive, real-time experiment control. By synthesizing these developments, we illustrate a clear trajectory: from manually operated instruments toward fully integrated intelligent nanophotonic laboratories that can autonomously discover and characterize the nano-world. We conclude by discussing the remaining challenges-from data acquisition and model interpretability to the mitigation of photothermal effects-and the most promising pathways toward realizing this transformative vision for virology, cell biology, and nanomedicine.
This work examines magnetohydrodynamic (MHD) flow of a nanoliquid through on a porous surface. The mathematical model includes the collective effects of thermophoresis and Brownian motion to accurately describe nanoparticle behavior. It further analyzes the effect of Arrhenius activation energy on chemically reactive species. The flow is administrated by a convective heating condition, while the concentration field is subjected to a physically realistic zero mass flux condition. The bvp4c approach is used in this work to solve the modeled equations in dimension-free form. It is revealed as outcomes of this work that, for augmentation in magnetic factor, inter-particle spacing and porosity factor there is lessening in primary and secondary flows. Both the velocities augmented with progression in radius of nanoparticles. Thermal profiles augmented with growth in thermal Biot number, and magnetic factor while declined with augmentation in thermal relaxation time factor. Concentration panels augmented with progression in thermophoresis factor and activation energy factor while weakened with augmentation in Schmidt number and Brownian motion factor. A comparative analysis with established results confirms the accuracy and validity of the present model. The close agreement between our numerical outputs and the published data verifies the correctness of the solution methodology and the physical consistency of the formulated problem. This study demonstrates that the simultaneous adjustment of inter-particle spacing and nanoparticle size provides a strategic approach for enhancing thermal performance relative to pumping in nanofluid-based systems, with immediate ramifications for the design of advanced microelectronics coolants and magnetically guided delivery platforms.
Osteoporosis (OP) is a prevalent chronic metabolic bone disorder characterized by decreased bone mineral density, deterioration of bone microarchitecture, and increased fracture risk. Traditional Chinese medicines (TCM) have demonstrated considerable therapeutic potential in OP management due to their osteogenic and anti-resorptive activities. However, the therapeutic efficacy of TCM is often limited by the drawbacks of conventional delivery systems, underscoring the need for advanced formulation strategies to fully exploit their potential in OP prevention and treatment. In recent years, nanomedicine has emerged as a transformative platform for drug delivery, offering new avenues to enhance the pharmacological performance of herbal medicines. Nano-based delivery systems for anti-osteoporotic herbal compounds provide multiple benefits, including protection of active ingredients from degradation, improved bioavailability, reduced gastrointestinal irritation, and superior therapeutic outcomes. This review provides a comprehensive overview of the nanocarriers employed in the delivery of TCM, summarizes the current status and therapeutic efficacy of herb-loaded nanomedicines in OP management, and discusses the challenges and future directions for clinical translation. By highlighting recent advances and addressing existing hurdles, this review aims to contribute valuable insights for optimizing TCM-based nanotherapeutics in the prevention and treatment of osteoporosis.
The rise of multidrug-resistant microbes, rapidly evolving viruses, and recurring pandemics underscores the urgent need for advanced vaccine technologies. Nanoparticle-based vaccines have emerged as a transformative approach capable of overcoming the major shortcomings of traditional immunization methods. Their nanoscale architecture allows precise antigen targeting, enhanced stability, and controlled release, leading to more potent and durable immune protection. These smart systems can carry multiple antigens or adjuvants, mimic natural pathogens, and efficiently activate immune cells to elicit strong humoral and cellular responses. Various nanoparticle types, lipid-based, polymeric, inorganic, and biomimetic, demonstrate broad potential against infectious, inflammatory, and neoplastic diseases in both humans and animals. However, critical barriers remain in mass production, regulatory harmonization, and long-term safety assurance. The integration of nanotechnology with artificial intelligence (AI) and bioengineering now enables rational vaccine design, predictive modeling, and personalized immunization strategies. AI-driven optimization of nanoparticle formulations and immune response prediction are accelerating translational progress. The convergence of these disciplines is shaping a new generation of vaccines that are safer, more effective, and adaptable to global health challenges, paving the way toward precision vaccination for the modern era.
This research aims to describe the flow characteristics and entropy creation of an Oldroyd-B tri hybrid nanofluid under conditions of MHD with heat transfer through a hybrid numerical-machine learning framework. The nonlinear boundary layer governing equations for momentum and heat transport are transformed to a commonly used ordinary differential equations (ODE) form via similarity transformations and solved using MATLAB's bvp4c solver. A mesh independence study has verified numerical. The main innovation of this study is combining ANN modelling with the nonlinear numerical calculation of Oldroyd-B tri hybrid nanofluid flow to create an accurate predictive surrogate modelling tool for complex thermofluid systems. Data collected from the bvp4c solver was then used to train a feed forward ANN, using Levenberg-Marquardt backpropagation algorithm. The trained ANN was able to accurately predict velocity, temperature and entropy creation, with regression accuracies above 0.999 and mean square error values less than [Formula: see text], indicating a high degree of predictive power. Parametric analysis indicated that increasing the magnetic parameter caused a large reduction in velocity field (approximately 18-25%) as a result of the Lorentz force acting in against the flow. Also, the generation of heat increased the temperature profile by approximately 20%, therefore increasing Entropy Generation within the thermal boundary layer. In addition, tri-hybrid nanoparticles have better thermal conductivity and heat transfer performance than nanofluids made from conventional materials because of their ability to improve the thermal performance of fluids. A predictive framework for ANN-based modelling of nonlinear fluid transport has been developed that reduces the computational cost of obtaining accurate numerical solutions compared with traditional methods. This new framework has the potential to allow engineers and scientists to model advanced nanofluids with greater accuracy than previous approaches, thereby providing valuable information for thermal management, high-performance cooling systems, and energy conversion technologies.
Lipid nanocarriers (LNCs), including liposomes, lipid nanoparticles (LNPs), and extracellular vesicles (EVs), are promising platforms for targeted drug delivery. However, their clinical translation is hindered by multi-level heterogeneity and complex behaviors at the bio-nano interface. Interest in mechanotargeted delivery strategies has grown rapidly, as the mechanical properties of LNCs are increasingly recognized as critical determinants of their in vivo behavior. Establishing a comprehensive database of mechanical properties to decipher the underlying regulatory mechanisms is a prerequisite for the active modulation of LNCs' mechanics and the rational design of delivery vehicles. Although studies on LNC mechanics are increasing, several challenges remain, including mechanical heterogeneity, unbalanced research across different carriers, low-throughput mechanical characterization and limited comparability among results from different laboratories. This review systematically summarizes the intrinsic mechanical parameters of the three types of LNCs, outlines the structural determinants of these properties, highlights their roles as key modulators at the bio-nano interface, and discusses advanced engineering strategies for mechanical modulation. The goal of this review is to facilitate mechanics-informed design of next-generation nanomedicines for precision therapy.
Borehole instability driven by reactive shale hydration and excessive filtrate invasion remains a critical challenge in drilling operations. To address this, we synthesized a novel nitrogen and sulfur co-doped reduced graphene oxide/cuprous oxide (N,S-rGO/Cu2O) nanocomposite to reinforce the rheological and filtration properties of environmentally friendly water-based muds. The nanocomposite, prepared via a facile one-pot hydrothermal method, was characterized structurally and compositionally, then evaluated in both polymeric and high-solid base fluids. Performance was assessed through standard and high-pressure/high-temperature (HPHT) filtration, rheological modeling, and hot-rolling shale recovery tests. Results demonstrated that an optimal nanocomposite concentration of 1000 ppm maximized fluid efficiency, with rheological behavior conforming closely to the Herschel-Bulkley model. Crucially, the additive significantly mitigated fluid loss, achieving a 58.8% and 61.3%reduction in API filtrate volume for polymeric and high-solid fluids, respectively, alongside HPHT fluid loss reductions of 57.6% and 64.1%. Furthermore, hot-rolling experiments confirmed enhanced shale stability, yielding a 20% increase in shale recovery. These targeted improvements are attributed to the formation of a dense, hydrophobic nanoplug that physically seals pore throats and chemically inhibits clay swelling, though concentrations exceeding 1000 ppm caused particle agglomeration and diminished returns. Ultimately, the N,S-rGO/Cu2O nanocomposite operates through a synergistic mechanism of robust physical plugging and rheological networking, providing a highly effective solution for stabilizing reactive shales in complex subterranean environments.
Unopposed estrogen refers to prolonged estrogenic stimulation in the absence of adequate progesterone-mediated counter-regulation. Unopposed estrogen is strongly implicated in endometrial hyperplasia and type I endometrial carcinogenesis, and it is also biologically relevant to estrogen receptor-positive breast cancer. Evidence linking estrogen exposure to ovarian cancer is more heterogeneous and appears to vary by menopausal status, hormone therapy formulation, duration of exposure, and histologic subtype; therefore, ovarian cancer risk should be interpreted as an association rather than a definitive causal consequence of unopposed estrogen. Ongoing estrogen signaling can drive cell proliferation, oxidative DNA damage, and chronic inflammation in estrogen target tissues. Until now, conventional hormone assays, such as enzyme-linked immunosorbent assay (ELISA) have only been able to measure the amount of hormones in the circulation, but may not effectively detect dynamic, tissue-specific, or early-stage estrogenic activity. This review is unique in focusing on unopposed estrogen as a clinically significant biosensing target and critically reviewing estrogen receptor functionalized nanoprobe platforms for the detection of unopposed estrogen and the diagnosis of cancer, unlike other reviews, which have broadly discussed estrogen biosensors or nanoprobe-formatted cancer diagnostics. It focuses on platforms using estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) as well as strategies for receptor immobilization, nanomaterials design, signal transduction, and applications in biofluids, cells, and tissues. The review also discusses a translational aspect by considering obstacles to clinical implementation, such as probe stability, specificity of chemical analysis in complex biological matrices, required assay standardization, validation, and compatibility with use in a portable or point-of-care system. Newer trends like multiplex hormone profiling, smart devices integration, and signal interpretation with the help of machine learning (ML) are also discussed. This review aims to place unopposed estrogen biology in the context of ER-functionalized nanobiosensing and clinical translation problems, establishing a focused framework for future precision diagnostic tool development for cancer risk assessment and early detection by estrogen.
Heat transfer enhancement techniques play a crucial role in improving the thermal efficiency of heat exchangers while minimizing energy usage and operational expenses. In this study, the thermo-hydraulic performance of a circular tube equipped with wire-coil inserts and operating with graphene oxide (GO) nanofluid was predicted using an artificial neural network (ANN) model. Experiments were conducted over a Reynolds number range of 5000-18,000 using GO nanofluid with weight concentrations of 0.025-0.1 wt% and wire-coil inserts having pitch-to-diameter ratios (P/D) of 1, 1.5, and 2. The experimental findings revealed that the combined use of GO nanofluid and wire-coil inserts significantly enhanced the Nusselt number, although it also resulted in an increase in the friction factor. At a GO concentration of 0.05 weight% and a P/D ratio of 1.5, the maximum Thermal Performance Factor of 1.21 was attained, signifying an ideal thermo-hydraulic balance. A feed-forward backpropagation ANN model was created with the Reynolds number, nanoparticle concentration, and P/D ratio as input parameters and the Nusselt number and friction factor as outputs in order to forecast system performance. The correctness and dependability of the suggested model were confirmed by the ANN predictions having outstanding agreement with the experimental findings.