Diagnosis and classification of kidney transplant rejection using machine learning-assisted surface-enhanced Raman spectroscopy using a single drop of serum.

The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technologies. These technologies aim to detect antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR), which are asymptomatic and pose a risk of potential kidney damage. The protocols for managing rejection caused by ABMR and TCMR differ, and diagnosis has traditionally relied on invasive biopsy procedures. Therefore, a convergence system using a nano-sensing chip, Raman spectroscopy, and AI technology was introduced to facilitate diagnosis using serum samples obtained from patients with no major abnormality, ABMR, and TCMR after kidney transplantation. Tissue biopsy and Banff score analysis were performed across the groups for validation, and 5 µL of serum obtained at the same time was added onto the Au-ZnO nanorod-based Surface-Enhanced Raman Scattering sensing chip to obtain Raman spectroscopy signals. The accuracy of machine learning algorithms for principal component-linear discriminant analysis and principal component-partial least squares discriminant analysis was 93.53% and 98.82%, respectively. The collagen (an indicative of kidney injury), creatinine, and amino acid-derived signals (markers of kidney function) contributed to this accuracy; however, the high accuracy was primarily due to the ability of the system to analyze a broad spectrum of various biomarkers.

Nano-sized magnetic molecularly imprinted polymer solid-phase microextraction for highly selective recognition and enrichment of sulfamethoxazole from spiked water samples.

This research, described ultrasound-assisted dispersive magnetic solid-phase microextraction, which is efficient for the enrichment and determination of sulfamethoxazole, based on magnetic molecularly imprinted polymer (USA-DMSPME-MIP). Meanwhile, the initial characterization of Fe3O4-MIP was completed by conventional methods and well-known protocols to obtain recognition and adsorbing performance at pre-specified optimum conditions. Fe3O4-MIP exhibited information regarding its selective recognition pattern towards sulfamethoxazole. The USA-DMSPME-MIP parameters were optimized by response surface methodology, and based on optimum conditions, this efficient method for the extraction and enrichment of sulfamethoxazole from spiked water samples and quantification by HPLC-UV was used. The enhanced technique indicates the limit of detection is 2 ng mL-1 for sulfamethoxazole, along with excellent linear range with coefficients of determination >0.99 and good recoveries for spiked water samples (94.2 and 98.2 %) with RSDs less than 3.5 %.

Development of an ultrasound-mediated nano-sized drug-delivery system for cancer treatment: from theory to experiment.

Aim: To establish a methodology for understanding how ultrasound (US) induces drug release from nano-sized drug-delivery systems (NSDDSs) and enhances drug penetration and uptake in tumors. This aims to advance cancer treatment strategies. Materials & methods: We developed a multi-physics mathematical model to elucidate and understand the intricate mechanisms governing drug release, transport and delivery. Unique in vitro models (monolayer, multilayer, spheroid) and a tailored US exposure setup were introduced to evaluate drug penetration and uptake. Results: The results highlight the potential advantages of US-mediated NSDDSs over conventional NSDDSs and chemotherapy, notably in enhancing drug release and inducing cell death. Conclusion: Our sophisticated numerical and experimental methods aid in determining and quantifying drug penetration and uptake into solid tumors.

Nano-sized microplastics exposure induces skin cell senescence via triggering the mitochondrial localization of GSDMD.

Nano-sized microplastic pollution is distributed worldwide. Nano-sized microplastics can enter the blood through the digestive tract, and then transported to various tissues and organs of the body, resulting in a series of toxicological effects. In addition, nano-sized microplastics can penetrate the skin barrier. However, the toxicological effects of nano-sized microplastics on the skin are still not completely understood. Two skin cell lines were used as in vitro models to investigate the toxicological effects of nano-sized microplastics on skin cells and their potential molecular mechanisms. First, cellular behavioral research results showed that nano-sized microplastics can be internalized into skin cells in a time- and dose-dependent manner. Further experiments using western blotting, indirect immunofluorescence, and ELISA assays demonstrated that nano-sized microplastics cause an increase in skin cell inflammation levels. Additionally, our research showed that nano-sized microplastics caused skin cell senescence damage by evaluating aging-marker molecules such as p16 and p21. Subsequently, we studied the potential molecular mechanism by which nano-sized microplastics cause pathological skin injury and found that they induce mitochondrial oxidative stress, depolarize the mitochondrial membrane potential, and recruit GSDMD to the mitochondria. Subsequently, mtDNA enters the cytoplasm via GSDMD pores, which then activates the AIM2 Inflammasome. Ultimately, it causes a series of biochemical reactions such as inflammation and aging in cells. In an in vivo model, we tested the effect of nano-sized microplastics on skin regeneration and found that they acted as an inhibitor to skin regeneration and aggravated the inflammatory reaction of the skin. Overall, our results provide new evidence of the skin toxicity of nano-sized microplastics. This study provides a theoretical foundation for further research on the potential toxicological effects of nano-sized microplastics on the skin.

Preliminary performance study of synthetic Alumina nanoparticles for retention of cobalt and cesium cations.

In the present study, a facile nano-sized gamma alumina was synthesized and then examined for immobilization of cobalt and cesium ions individually from aqueous solutions. The comprehensive analysis of functional groups, phase composition, surface morphology and sorption characteristics of the synthesized nano-sized ϒ alumina was executed. It was deduced that acquired material was low-crystalline with a high elimination efficacy towards the concerned cations under slightly alkali and acidic conditions. Time-transient elimination scrutiny was executed and cobalt elimination rate was found relatively faster than cesium cations. Equilibrium sorption examinations confirmed that the sorption is proceeding via two diverse sites on the scavenger surface. Cobalt and cesium elimination is a spontaneous endothermic reaction of increased chaos. The attained results proved the high proficiency of the synthesized scavenger in the cations immobilization.

Micro and nano plastics release from a single absorbable suture into simulated body fluid.

Synthetic polymers are widely used in medical devices and implants where biocompatibility and mechanical strength are key enablers of emerging technologies. One concern that has not been widely studied is the potential of their microplastics (MPs) release. Here we studied the levels of MP debris released following 8-week in vitro tests on three typical polyglycolic acid (PGA) based absorbable sutures (PGA 100, PGA 90 and PGA 75) and two nonabsorbable sutures (polypropylene-PP and polyamide-PA) in simulated body fluid. The MP release levels ranked from PGA 100 > > PGA 90 > PGA 75 > > PP ∼ PA. A typical PGA 100 suture released 0.63 ± 0.087 million micro (MPs > 1 µm) and 1.96 ± 0.04 million nano (NPs, 200-1000 nm) plastic particles per centimeter. In contrast, no MPs were released from the nonabsorbable sutures under the same conditions. PGA that was co-blended with 10-25% L-lactide or epsilon-caprolactone resulted in a two orders of magnitude lower level of MP release. These results underscore the need to assess the release of nano- and microplastics from medical polymers while applied in the human body and to evaluate possible risks to human health.

Ultrasound-mediated nano-sized drug delivery systems for cancer treatment: Multi-scale and multi-physics computational modeling.

Computational modeling enables researchers to study and understand various complex biological phenomena in anticancer drug delivery systems (DDSs), especially nano-sized DDSs (NSDDSs). The combination of NSDDSs and therapeutic ultrasound (TUS), that is, focused ultrasound and low-intensity pulsed ultrasound, has made significant progress in recent years, opening many opportunities for cancer treatment. Multiple parameters require tuning and optimization to develop effective DDSs, such as NSDDSs, in which mathematical modeling can prove advantageous. In silico computational modeling of ultrasound-responsive DDS typically involves a complex framework of acoustic interactions, heat transfer, drug release from nanoparticles, fluid flow, mass transport, and pharmacodynamic governing equations. Owing to the rapid development of computational tools, modeling the different phenomena in multi-scale complex problems involved in drug delivery to tumors has become possible. In the present study, we present an in-depth review of recent advances in the mathematical modeling of TUS-mediated DDSs for cancer treatment. A detailed discussion is also provided on applying these computational models to improve the clinical translation for applications in cancer treatment. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Early-stage diagnosis of bladder cancer using surface-enhanced Raman spectroscopy combined with machine learning algorithms in a rat model.

Early diagnosis and accurate assessment of tumor development facilitate early bladder cancer resection and initiation of drug therapy. This study enabled an early, accurate, label-free, noninvasive diagnosis of bladder tumors by analyzing nano-biomarkers in a single drop of urine through surface-enhanced Raman spectroscopy (SERS). In a standard N-butyl-N-4-hydroxybutyl nitrosamine-induced rat model of bladder cancer, cancer stage and polyp tumor development were monitored using a small endoscope with a diameter of 1.2 mm in a minimally invasive manner without the need to kill the rats. Samples were divided into cancer-free, early-stage, and polyp-form cancer. Training data were classified according to micro-cystoscopic 5-aminolevulinic acid fluorescence diagnosis, and specimens were postmortem verified through histopathological analysis. A drop of urine from each sample group was placed on an Au-coated zinc oxide nanoporous chip to filter nano-biomaterials and selectively enhance the Raman signals of nanoscale analytes via SERS. Principal component analysis was used to reduce the dimensionality of the collected Raman spectra, and partial least squares discriminant analysis was used to find diagnostic clusters based on the labeled samples. The combination of SERS and machine learning achieved an accuracy ≥99.6% in diagnosing both early- and polyp-stage bladder tumors. With an area under the receiver operating characteristic curve greater than 0.996, the accuracy of the diagnosis in the rat model suggests that SERS-based diagnostic methods are promising when coupled with machine learning. Low-cost, label-free, and noninvasive surface-enhanced Raman spectra are ideal for developing clinically relevant point-of-care diagnostic techniques.

Recent progress, perspectives, and issues of engineered PD-L1 regulation nano-system to better cure tumor: A review.

Currently, immune checkpoint blockade (ICB) therapies that target the programmed cell death ligand-1 (PD-L1) have been used as revolutionary cancer treatments in the clinic. Apart from restoring the antitumor response of cytotoxic T cells by blocking the interaction between PD-L1 on tumor cells and programmed cell death-1 (PD-1) on T cells, PD-L1 proteins were also newly revealed to possess the capacity to accelerate DNA damage repair (DDR) and enhance tumor growth through multiple mechanisms, leading to the impaired efficacy of tumor therapies. Nevertheless, current free anti-PD-1/PD-L1 therapy still suffered from poor therapeutic outcomes in most solid tumors due to the non-selective tumor accumulation, ineludible severe cytotoxic effects, as well as the common occurrence of immune resistance. Recently, nanoparticles with efficient tumor-targeting capacity, tumor-responsive prosperity, and versatility for combination therapy were identified as new avenues for PD-L1 targeting cancer immunotherapies. In this review, we first summarized the multiple functions of PD-L1 protein in promoting tumor growth, accelerating DDR, as well as depressing immunotherapy efficacy. Following this, the effects and mechanisms of current clinically widespread tumor therapies on tumor PD-L1 expression were discussed. Then, we reviewed the recent advances in nanoparticles for anti-PD-L1 therapy via using PD-L1 antibodies, small interfering RNA (siRNA), microRNA (miRNA), clustered, regularly interspaced, short palindromic repeats (CRISPR), peptide, and small molecular drugs. At last, we discussed the challenges and perspectives to promote the clinical application of nanoparticles-based PD-L1-targeting therapy.

Application of Response Surface Methodology to Improve the Tableting Properties of Poorly Compactable and High-Drug-Loading Canagliflozin Using Nano-Sized Colloidal Silica.

Designing a robust direct compression (DC) formulation for an active pharmaceutical ingredient (API) with poor flow and compaction properties at a high API load is challenging. This study tackled two challenges: the unfavorable flow characteristics and tableting problems associated with a high-drug-loading canagliflozin (CNG), facilitating high-speed DC tableting. This was accomplished through a single-step dry coating process using hydrophilic nano-sized colloidal silica. A 32 full-factorial experimental design was carried out to optimize the independent process variables, namely, the weight percent of silica nanoparticles (X1) and mixing time (X2). Flow, bulk density, and compaction properties of CNG-silica blends were investigated, and the optimized blend was subsequently compressed into tablets using the DC technique. A regression analysis exhibited a significant (p ≤ 0.05) influence of both X1 and X2 on the characteristics of CNG with a predominant effect of X1. Additionally, robust tablets were produced from the processed powders in comparison with those from the control batch. Furthermore, the produced tablets showed significantly lower tablet ejection forces than those from the control batch, highlighting the lubrication impact of the silica nanoparticles. Interestingly, these tablets displayed improved disintegration time and dissolution rates. In conclusion, a dry coating process using silica nanoparticles presents a chance to address the poor flow and tableting problems of CNG, while minimizing the need for excessive excipients, which is crucial for the effective development of a small-sized tablet and the achievement of a cost-effective manufacturing process.

Adsorption Affinities of Small Volatile Organic Molecules on Graphene Surfaces for Novel Nanofiller Design: A DFT Study.

The adsorption of organic molecules on graphene surfaces is a crucial process in many different research areas. Nano-sized carbon allotropes, such as graphene and carbon nanotubes, have shown promise as fillers due to their exceptional properties, including their large surface area, thermal and electrical conductivity, and potential for weight reduction. Surface modification methods, such as the "pyrrole methodology", have been explored to tailor the properties of carbon allotropes. In this theoretical work, an ab initio study based on Density Functional Theory is performed to investigate the adsorption process of small volatile organic molecules (such as pyrrole derivatives) on graphene surface. The effects of substituents, and different molecular species are examined to determine the influence of the aromatic ring or the substituent of pyrrole's aromatic ring on the adsorption energy. The number of atoms and presence of π electrons significantly influence the corresponding adsorption energy. Interestingly, pyrroles and cyclopentadienes are 10 kJ mol-1 more stable than the corresponding unsaturated ones. Pyrrole oxidized derivatives display more favorable supramolecular interactions with graphene surface. Intermolecular interactions affect the first step of the adsorption process and are important to better understand possible surface modifications for carbon allotropes and to design novel nanofillers in polymer composites.

The beneficial role of nano-sized Fe3O4 entrapped in ultra-stable Y zeolite for the complete mineralization of phenol by heterogeneous photo-Fenton under solar light.

Highly efficient, separable, and stable magnetic iron-based-photocatalysts produced from ultra-stable Y (USY) zeolite were applied, for the first time, to the photo-Fenton removal of phenol under solar light. USY Zeolite with a Si/Al molar ratio of 385 was impregnated under vacuum with an aqueous solution of Fe2+ ions and thermally treated (500-750 °C) in a reducing atmosphere. Three catalysts, Fe-USY500°C-2h, Fe-USY600°C-2h and Fe-USY750°C-2h, containing different amounts of reduced iron species entrapped in the zeolitic matrix, were obtained. The catalysts were thoroughly characterized by absorption spectrometry, X-ray powder diffraction with synchrotron source, followed by Rietveld analysis, X-ray photoelectron spectroscopy, N2 adsorption/desorption at -196 °C, high-resolution transmission electron microscopy and magnetic measurements at room temperature. The catalytic activity was evaluated in a recirculating batch photoreactor irradiated by solar light with online analysis of evolved CO2. Photo-Fenton results showed that the catalyst obtained by thermal treatment at 500 °C for 2 h under a reducing atmosphere (FeUSY-500°C-2h) was able to completely mineralize phenol in 120 min of irradiation time at pH = 4 owing to the presence of a higher content of entrapped nano-sized magnetite particles. The latter promotes the generation of hydroxyl radicals in a more efficient way than the Fe-USY catalysts prepared at 600 and 750 °C because of the higher Fe3O4 content in ultra-stable Y zeolite treated at 500 °C. The FeUSY-500°C-2h catalyst was recovered from the treated water through magnetic separation and reused five times without any significant worsening of phenol mineralization performances. The characterization of the FeUSY-500°C-2h after the photo-Fenton process demonstrated that it was perfectly stable during the reaction. The optimized catalyst was also effective in the mineralization of phenol in tap water. Finally, a possible photo-Fenton mechanism for phenol mineralization was assessed based on experimental tests carried out in the presence of scavenger molecules, demonstrating that hydroxyl radicals play a major role.

Nano polystyrene induced changes in anxiety and learning behaviour are mediated through oxidative stress and gene disturbance in mouse brain regions.

It is widely reported now that nanoplastic particles have potential neurotoxic effects and may disturb central nervous system (CNS) function. However, the mechanism behind these toxic effects still needs to be elucidated. In the current study, we investigated the effects of polystyrene nanoplastics (PS-NPs) on changes in learning, memory, and anxiety-related behavior in mice based on some selected biochemical, molecular, and histopathological changes in three important brain regions (Cortex, Hypothalamus, and Hippocampus). Male mice were orally administered daily with two doses of 50 nm PS-NPs (0.2 mg/ml and 1 mg/ml) for 8 weeks. We observed decreased expression of neurotransmitter-related genes (VAChT, GAD, and SYP) in the cortex, hypothalamus, and hippocampus areas of the mouse brain. Other biochemical variables including, antioxidant enzymes, biomarkers for oxidative stress, and acetylcholinesterase activity showed significant alterations in all three brain regions. Molecular and neurochemical data thus suggest significant neurobehavioral changes following sub-chronic exposure to PS-NPs which may lead to enhanced anxiety-related and spatial learning and memory-related impairments by affecting limbic areas of the brain.

Size-dependent promotion of micro(nano)plastics on the horizontal gene transfer of antibiotic resistance genes in constructed wetlands.

Constructed wetlands (CWs) have been identified as significant sources of micro(nano)plastics (MPs/NPs) and antibiotic resistance genes (ARGs) in aquatic environments. However, little is known about the impact of MPs/NPs exposure on horizontal gene transfer (HGT) of ARGs and shaping the corresponding ARG hosts' community. Herein, the contribution of polystyrene (PS) particles (control, 4 mm, 100 µm, and 100 nm) to ARG transfer was investigated by adding an engineered fluorescent Escherichia coli harboring RP4 plasmid-encoded ARGs into CWs. It was found MPs/NPs significantly promoted ARG transfer in a size-dependent manner in each CW medium (p < 0.05). The 100 µm-sized PS exhibited the most significant promotion of ARG transfer (p < 0.05), whereas 100 nm-sized PS induced limited promotion due to its inhibitory activity on microbes. The altered RP4-carrying bacterial communities suggested that MPs/NPs, especially 100 µm-PS, could recruit pathogenic and nitrifying bacteria to acquire ARGs. The increased sharing of RP4-carrying core bacteria in CW medium further suggested that ARGs can spread into CW microbiome using MPs/NPs as carriers. Overall, our results highlight the high risks of ARG dissemination induced by MPs/NPs exposure and emphasize the need for better control of plastic disposal to prevent the potential health threats.

Ionic Conductivity and Cycling Performance in PEO Polymer Electrolyte Enhanced by Non-Milled In Situ Nano-LLZO Powders.

High Li+ conductivity, good interfacial compatibility, and nano-scale particle size have always been essential conditions for selecting inorganic fillers in high-performance composite solid electrolytes. In this study, non-milled in situ LLZO fillers with nanosize was synthesized via the sol-gel method by rapid heating sintering, which resulted in more surface defects and fewer impurities in LLZO. Compared with milled LLZO fillers, these non-milled LLZO fillers with more surface defects and fewer impurities can effectively reduce the crystallinity of PEO and agglomeration in PEO, which can form composite electrolytes with high Li+ conductivity. Most importantly, the discharge capacity of the 7.5% non-milled LLZO-PEO-based LiFePO4/Li battery is about 135.5 mA h g-1 at 1C and 60 °C. After 100 cycles, the discharge specific capacity remains at 99%. It is worth noting that nano-sized non-milled LLZO will improve the discharge capacity of LiFePO4/Li batteries to 122.1 mA h g-1 at 0.2C and 30 °C.

Occurrences of typical PPCPs during wastewater treatment and the composting of sewage sludge with micron-sized and nano-sized Fe3O4.

New pollutants, pharmaceuticals and personal care products (PPCPs), accumulate in sewage sludge (SS) in wastewater treatment plants (WWTPs), posing risks to the environment and to human health. In the present study, the fates of typical PPCPs, carbamazepine (CBZ), triclosan (TCS), ibuprofen (IBU) and galaxolide (HHCB), were examined during WW treatment. Additionally, SS collected from a WWTP was used for aerobic composting to investigate the influences of micron-sized Fe3O4 (M-Fe) and nano-sized Fe3O4 (N-Fe) on the degradation of these PPCPs and the succession of microbial communities during the composting process. The results showed that the mean concentrations of CBZ, TCS, IBU and HHCB in the influent of the WWTP were 926.5, 174.4, 8869, and 967.3 ng/g, respectively, and in the effluent were 107.6, 47.0, 283.4, and 88.4 ng/g, respectively. The removal rate averaged ∼80%, while the enrichment rates of the PPCPs in SS ranged from 37.2% to 60.5%. M-Fe and N-Fe reduced NH3 emissions by 32.9% and 54.1% and N2O emissions by 26.2% and 50.8%, respectively. Moreover, the addition of M-Fe and N-Fe effectively increased PPCP degradation rates 1.12-1.66-fold. During the whole process, the additions of M-Fe and N-Fe significantly shifted microbial community structure, and the abundances of Proteobacteria, Chloroflexi, and Actinobacteria were increased during the thermophilic stage, marking them as key PPCP-degrading phyla. Taken together, our results indicated that the addition of M-Fe and N-Fe is an effective method for improving the quality of end compost and accelerating the degradation of PPCPs.

The co-presence of polystyrene nanoplastics and ofloxacin demonstrates combined effects on the structure, assembly, and metabolic activities of marine microbial community.

Nanoplastic is increasing in environments and can address toxic effects on various organisms. Particle size, concentration, and surface functionalization most influence nanoplastic toxicity. Besides, nanoplastic can adsorb other contaminants (e.g., antibiotics) to aggravate its adverse effects. The combined effects of nanoplastics and antibiotics on planktonic/benthic microbial communities, however, are still largely unknown. In this study, the combined effects of polystyrene nanoplastic and ofloxacin on the structure, assembly, and metabolic activities of marine microbial communities were investigated based on amplicon sequencing data. The results mainly demonstrate that: (1) nanoplastic and ofloxacin have greater impacts on prokaryotic communities than eukaryotic ones; (2) niche breadths of planktonic prokaryotes and benthic eukaryotes were shrank with both high nanoplastic and ofloxacin concentrations; (3) increased ofloxacin mainly reduces nodes/edges of co-occurrence networks, while nanoplastic centralizes network modularity; (4) increased nanoplastic under high ofloxacin concentration induces more differential prokaryotic pathways in planktonic communities, while benthic communities are less influenced. The present work indicates that co-presence of nanoplastics and ofloxacin has synergistic combined effects on community structure shifts, niche breadth shrinking, network simplifying, and differential prokaryotic pathways inducing in marine microbial communities, suggesting nanoplastics and its combined impacts with other pollutions should be paid with more concerns.

Label-free atherosclerosis diagnosis through a blood drop of apolipoprotein E knockout mouse model using surface-enhanced Raman spectroscopy validated by machine learning algorithm.

The direct preventative detection of flow-induced atherosclerosis remains a significant challenge, impeding the development of early treatments and prevention measures. This study proposes a method for diagnosing atherosclerosis in the carotid artery using nanometer biomarker measurements through surface-enhanced Raman spectroscopy (SERS) from single-drop blood samples. Atherosclerotic acceleration is induced in apolipoprotein E knockout mice which underwent a partial carotid ligation and were fed a high-fat diet to rapidly induce disturbed flow-induced atherosclerosis in the left common carotid artery while using the unligated, contralateral right carotid artery as control. The progressive atherosclerosis development of the left carotid artery was verified by micro-magnetic resonance imaging (micro-MRI) and histology in comparison to the right carotid artery. Single-drop blood samples are deposited on chips of gold-coated ZnO nanorods grown on silicon wafers that filter the nanometer markers and provide strong SERS signals. A diagnostic classifier was established based on principal component analysis (PCA), which separates the resultant spectra into the atherosclerotic and control groups. Scoring based on the principal components enabled the classification of samples into control, mild, and severe atherosclerotic disease. The PCA-based analysis was validated against an independent test sample and compared against the PCA-PLS-DA machine learning algorithm which is known for applicability to Raman diagnosis. The accuracy of the PCA modification-based diagnostic criteria was 94.5%, and that of the machine learning algorithm 97.5%. Using a mouse model, this study demonstrates that diagnosing and classifying the severity of atherosclerosis is possible using a single blood drop, SERS technology, and machine learning algorithm, indicating the detectability of biomarkers and vascular factors in the blood which correlate with the early stages of atherosclerosis development.

Design and advanced characterization of quercetin-loaded nano-liposomes prepared by high-pressure homogenization.

Quercetin-loaded nano-liposomes were prepared by high-pressure homogenization (HPH) at different pressures (up to 150 MPa) and number of passes (up to 3) to define the best processing conditions allowing the lowest particle size and the highest encapsulation efficiency (EE). The process at 150 MPa for 1 pass was the best, producing quercetin-loaded liposomes with the lowest particle size and 42% EE. Advanced techniques (multi-detector asymmetrical-flow field flow fractionation and analytical ultracentrifugation combined with transmission electron microscopy) were further used for the characterization of the liposomes which were oblong in shape (ca. 30 nm). Results highlight the need for several techniques to study nano-sized, polydisperse samples. The potential of quercetin-loaded liposomes against colon cancer cells was demonstrated. Results prove that HPH is an efficient and sustainable method for liposome preparation and highlight the remarkable role of process optimisation as well as the powerfulness of advanced methodologies for the characterisation of nano-structures.

A spatiotemporal computational model of focused ultrasound heat-induced nano-sized drug delivery system in solid tumors.

Focused Ultrasound (FUS)-triggered nano-sized drug delivery, as a smart stimuli-responsive system for treating solid tumors, is computationally investigated to enhance localized delivery of drug and treatment efficacy. Integration of thermosensitive liposome (TSL), as a doxorubicin (DOX)-loaded nanocarrier, and FUS, provides a promising drug delivery system. A fully coupled partial differential system of equations, including the Helmholtz equation for FUS propagation, bio-heat transfer, interstitial fluid flow, drug transport in tissue and cellular spaces, and a pharmacodynamic model is first presented for this treatment approach. Equations are then solved by finite element methods to calculate intracellular drug concentration and treatment efficacy. The main objective of this study is to present a multi-physics and multi-scale model to simulate drug release, transport, and delivery to solid tumors, followed by an analysis of how FUS exposure time and drug release rate affect these processes. Our findings not only show the capability of model to replicate this therapeutic approach, but also confirm the benefits of this treatment with an improvement of drug aggregation in tumor and reduction of drug delivery in healthy tissue. For instance, the survival fraction of tumor cells after this treatment dropped to 62.4%, because of a large amount of delivered drugs to cancer cells. Next, a combination of three release rates (ultrafast, fast, and slow) and FUS exposure times (10, 30, and 60 min) was examined. Area under curve (AUC) results show that the combination of 30 min FUS exposure and rapid drug release leads to a practical and effective therapeutic response.