An analytical approach for quantifying the influence of nanoparticle polydispersity on cellular delivered dose

Advancing Gastrointestinal Health: Curcumin's Efficacy and Nanopreparations

Curcumin (CCM) is a polyphenol compound extracted from the turmeric rhizome. It has various biological activities, including antibacterial, anti-inflammatory, anti-cancer, and antioxidant. Due to its diverse activities, it is often used by researchers to study the therapeutic effects on various diseases. However, its poor solubility leads to poor bioavailability, and it is necessary to increase the water solubility with the help of carriers to improve the therapeutic effect. Gastrointestinal disease is a major global health problem that continues to affect human health. In this review, we have summarized the possible mechanism and therapeutic effect of CCM in various gastrointestinal diseases, and the improvement in the curative effect of CCM with nanopreparation. Finally, we concluded that there have been many clinical trials of CCM in combination with other drugs for the treatment of gastrointestinal disease, but so far, few have used CCM nanomaterials for treatment. Although in vitro and preclinical experiments have shown that nanopreparations can improve the efficacy of CCM, there are still insufficient studies on the safety of carriers.

Nanomechanical changes in probiotic bacteria under antibiotics exposure: Implications on Lactobacillus biofilm formation

Recognition of the microbial cell's surface constituents' biophysical properties is an important research topic, allowing a better understanding of the cell's behaviour under different conditions. Atomic force microscopy (AFM) was employed in this study to analyse the basis of the nanomechanical changes in probiotic bacteria under nitrofurantoin, furazolidone, and nitrofurazone exposure. Recorded significant changes in the two Lactobacillus strains cells morphology, topography, and adhesion parameters resulted in the increase of the cells' longitude (up to 2.58 μm), profile height (by around 0.50 μm), and decrease in the adhesion force (up to 13.58 nN). Young's modulus and adhesion energy decreased within 96 h, however with no negative effect on the cells' morphology or loss of structural integrity. Observed modifications present the mode of action of the 5-nitrofuran derivative antibiotics on probiotic biofilm formation and suggest activation of the multilevel adaptation mechanisms to counteract unfavorable environments. A visual change in bacterial morphology such as an increased surface-to-volume ratio might be a link between molecular-level events and outcomes in individual cells and biofilms. This paper for the first time shows, that these antibiotics affect the properties of non-target microorganisms as lactobacilli, and might impair biofilm formation. However, the degree of such transformations depends on the delivered active substance.

The Influence of Liquid Menisci on Nanoparticle Dosimetry in Submerged Cells

Understanding the interaction between cells and nanoparticles (NPs) is vital to understand the hazard associated with nanoparticles. This requires quantifying and interpreting dose-response relationships. Experiments with cells cultured in vitro and exposed to particle dispersions mainly rely on mathematical models that estimate the received nanoparticle dose. However, models need to consider that aqueous cell culture media wets the inner surface of hydrophilic open wells, which results in a curved liquid-air interface called the meniscus. Here the impact of the meniscus on nanoparticle dosimetry is addressed in detail. Experiments and build an advanced mathematical model, to demonstrate that the presence of the meniscus may bring about systematic errors that must be considered to advance reproducibility and harmonization is presented. The script of the model is co-published and can be adapted to any experimental setup. Finally, simple and practical solutions to this problem, such as covering the air-liquid interface with a permeable lid or soft rocking of the cell culture well plate is proposed.

Data-Driven Quantitative Intrinsic Hazard Criteria for Nanoproduct Development in a Safe-by-Design Paradigm: A Case Study of Silver Nanoforms

The current European (EU) policies, that is, the Green Deal, envisage safe and sustainable practices for chemicals, which include nanoforms (NFs), at the earliest stages of innovation. A theoretically safe and sustainable by design (SSbD) framework has been established from EU collaborative efforts toward the definition of quantitative criteria in each SSbD dimension, namely, the human and environmental safety dimension and the environmental, social, and economic sustainability dimensions. In this study, we target the safety dimension, and we demonstrate the journey toward quantitative intrinsic hazard criteria derived from findable, accessible, interoperable, and reusable data. Data were curated and merged for the development of new approach methodologies, that is, quantitative structure-activity relationship models based on regression and classification machine learning algorithms, with the intent to predict a hazard class. The models utilize system (i.e., hydrodynamic size and polydispersity index) and non-system (i.e., elemental composition and core size)-dependent nanoscale features in combination with biological in vitro attributes and experimental conditions for various silver NFs, functional antimicrobial textiles, and cosmetics applications. In a second step, interpretable rules (criteria) followed by a certainty factor were obtained by exploiting a Bayesian network structure crafted by expert reasoning. The probabilistic model shows a predictive capability of ≈78% (average accuracy across all hazard classes). In this work, we show how we shifted from the conceptualization of the SSbD framework toward the realistic implementation with pragmatic instances. This study reveals (i) quantitative intrinsic hazard criteria to be considered in the safety aspects during synthesis stage, (ii) the challenges within, and (iii) the future directions for the generation and distillation of such criteria that can feed SSbD paradigms. Specifically, the criteria can guide material engineers to synthesize NFs that are inherently safer from alternative nanoformulations, at the earliest stages of innovation, while the models enable a fast and cost-efficient in silico toxicological screening of previously synthesized and hypothetical scenarios of yet-to-be synthesized NFs.

Polymer-based particles against pathogenic fungi: A non-uptake delivery of compounds

The therapy of life-threatening fungal infections is limited and needs urgent improvement. This is in part due to toxic side effects of clinically used antifungal compounds or their limited delivery to fungal structures. Until today, it is a matter of debate how drugs or drug-delivery systems can efficiently reach the intracellular lumen of fungal cells and how this can be improved. Here, we addressed both questions by applying two different polymeric particles for delivery of compounds. Their formulation was based on two biocompatible polymers, i.e., poly(lactic-co-glycolic acid)_50:50 and poly(methyl methacrylate-stat-methacrylic acid)_90:10 yielding particles with hydrodynamic diameters ranging from 100 to 300 nm. The polymers were covalently labeled with the fluorescent dye DY-550 to monitor the interaction between particles and fungi by confocal laser scanning microscopy. Furthermore, the fluorescent dye coumarin-6 and the antifungal drug itraconazole were successfully encapsulated in particles to study the fate of both the cargo and the particle when interacting with the clinically most important human-pathogenic fungi Aspergillus fumigatus, A. terreus, Candida albicans, and Cryptococcus neoformans. While the polymers were exclusively located on the fungal surface, the encapsulated cargo was efficiently transported into fungal hyphae, indicated by increased intracellular fluorescence signals due to coumarin-6. In accordance with this finding, compared to the pristine drug a reduced minimal inhibitory concentration for itraconazole was determined, when it was encapsulated. Together, the herein used polymeric particles were not internalized by pathogenic fungi but were able to efficiently deliver hydrophobic cargos into fungal cells.

On predicting heterogeneity in nanoparticle dosage

Nanoparticles are increasingly employed as a vehicle for the targeted delivery of therapeutics to specific cell types. However, much remains to be discovered about the fundamental biology that dictates the interactions between nanoparticles and cells. Accordingly, few nanoparticle-based targeted therapeutics have succeeded in clinical trials. One element that hinders our understanding of nanoparticle-cell interactions is the presence of heterogeneity in nanoparticle dosage data obtained from standard experiments. It is difficult to distinguish between heterogeneity that arises from stochasticity in nanoparticle-cell interactions, and that which arises from heterogeneity in the cell population. Mathematical investigations have revealed that both sources of heterogeneity contribute meaningfully to the heterogeneity in nanoparticle dosage. However, these investigations have relied on simplified models of nanoparticle internalisation. Here we present a stochastic mathematical model of nanoparticle internalisation that incorporates a suite of relevant biological phenomena such as multistage internalisation, cell division, asymmetric nanoparticle inheritance and nanoparticle saturation. Critically, our model provides information about nanoparticle dosage at an individual cell level. We perform model simulations to examine the influence of specific biological phenomena on the heterogeneity in nanoparticle dosage in the absence of heterogeneity in the cell population. Under certain modelling assumptions, we derive analytic approximations of the nanoparticle dosage distribution. We demonstrate that the analytic approximations are accurate, and show that nanoparticle dosage can be described by a Poisson mixture distribution with rate parameters that are a function of Beta-distributed random variables. We discuss the implications of the analytic results with respect to parameter estimation and model identifiability from standard experimental data. Finally, we highlight extensions and directions for future research.

Equation learning to identify nano-engineered particle-cell interactions: an interpretable machine learning approach

Designing nano-engineered particles capable of the delivery of therapeutic and diagnostic agents to a specific target remains a significant challenge. Understanding how interactions between particles and cells are impacted by the physicochemical properties of the particle will help inform rational design choices. Mathematical and computational techniques allow for details regarding particle-cell interactions to be isolated from the interwoven set of biological, chemical, and physical phenomena involved in the particle delivery process. Here we present a machine learning framework capable of elucidating particle-cell interactions from experimental data. This framework employs a data-driven modelling approach, augmented by established biological knowledge. Crucially, the model of particle-cell interactions learned by the framework can be interpreted and analysed, in contrast to the 'black box' models inherent to other machine learning approaches. We apply the framework to association data for thirty different particle-cell pairs. This library of data contains both adherent and suspension cell lines, as well as a diverse collection of particles. We consider hyperbranched polymer and poly(methacrylic acid) particles, from 6 nm to 1032 nm in diameter, with small molecule, monoclonal antibody, and peptide surface functionalisations. Despite the diverse nature of the experiments, the learned models of particle-cell interactions for each particle-cell pair are remarkably consistent: out of 2048 potential models, only four unique models are learned. The models reveal that nonlinear saturation effects are a key feature governing particle-cell interactions. Further, the framework provides robust estimates of particle performance, which facilitates quantitative evaluation of particle design choices.

Bone-Targeting Nanoparticles of a Dendritic (Aspartic acid)3-Functionalized PEG-PLGA Biopolymer Encapsulating Simvastatin for the Treatment of Osteoporosis in Rat Models

Simvastatin (SIM) is a lipid-lowering drug that also promotes bone formation, but its high liver specificity may cause muscle damage, and the low solubility of lipophilic drugs limits the systemic administration of SIM, especially in osteoporosis (OP) studies. In this study, we utilized the bone-targeting moiety of dendritic oligopeptides consisting of three aspartic acid moieties (_dAsp₃) and amphiphilic polymers (poly(ethylene glycol)-block-poly(lactic-co-glycolic acid); PEG-PLGA) to create _dAsp₃-PEG-PLGA (APP) nanoparticles (NPs), which can carry SIM to treat OP. An in vivo imaging system showed that gold nanocluster (GNC)-PLGA/APP NPs had a significantly higher accumulation rate in representative bone tissues. In vivo experiments comparing low-dose SIM treatment (0.25 mg/kg per time, 2 times per week) showed that bone-targeting SIM/APP NPs could increase the bone formation effect compared with non-bone-targeting SIM/PP NPs in a local bone loss of hindlimb suspension (disuse) model, but did not demonstrate good bone formation in a postmenopausal (ovariectomized) model of systemic bone loss. The APP NPs could effectively target high mineral levels in bone tissue and were expected to reduce side effects in other organs affected by SIM. However, in vivo OP model testing showed that the same lower dose could not be used to treat different types of OP.

Synthesis of Alginate Nanogels with Polyvalent 3D Transition Metal Cations: Applications in Urease Immobilization

Biocompatible nanogels are highly in demand and have the potential to be used in various applications, e.g., for the encapsulation of sensitive biomacromolecules. In the present study, we have developed water-in-oil microemulsions of sodium alginate sol/hexane/Span 20 as a template for controlled synthesis of alginate nanogels, cross-linked with 3d transition metal cations (Mn²⁺, Fe³⁺, and Co²⁺). The results suggest that the stable template of 110 nm dimensions can be obtained by microemulsion technique using Span 20 at concentrations of 10mM and above, showing a zeta potential of −57.3 mV. A comparison of the effects of the cross-links on the morphology, surface charge, protein (urease enzyme) encapsulation properties, and stability of the resulting nanogels were studied. Alginate nanogels, cross-linked with Mn²⁺, Fe³⁺, or Co²⁺ did not show any gradation in the hydrodynamic diameter. The shape of alginate nanogels, cross-linked with Mn²⁺ or Co²⁺, were spherical; whereas, nanogels cross-linked with Fe³⁺ (Fe–alginate) were non-spherical and rice-shaped. The zeta potential, enzyme loading efficiency, and enzyme activity of Fe–alginate was the highest among all the nanogels studied. It was found that the morphology of particles influenced the percent immobilization, loading capacity, and loading efficiency of encapsulated enzymes. These particles are promising candidates for biosensing and efficient drug delivery due to their relatively high loading capacity, biocompatibility, easy fabrication, and easy handling.

Spatio-temporal analysis of nanoparticles in live tumor spheroids impacted by cell origin and density

Nanoparticles hold great preclinical promise in cancer therapy but continue to suffer attrition through clinical trials. Advanced, three dimensional (3D) cellular models such as tumor spheroids can recapitulate elements of the tumor environment and are considered the superior model to evaluate nanoparticle designs. However, there is an important need to better understand nanoparticle penetration kinetics and determine how different cell characteristics may influence this nanoparticle uptake. A key challenge with current approaches for measuring nanoparticle accumulation in spheroids is that they are often static, losing spatial and temporal information which may be necessary for effective nanoparticle evaluation in 3D cell models. To overcome this challenge, we developed an analysis platform, termed the Determination of Nanoparticle Uptake in Tumor Spheroids (DONUTS), which retains spatial and temporal information during quantification, enabling evaluation of nanoparticle uptake in 3D tumor spheroids. Outperforming linear profiling methods, DONUTS was able to measure silica nanoparticle uptake to 10 μm accuracy in both isotropic and irregularly shaped cancer cell spheroids. This was then extended to determine penetration kinetics, first by a forward-in-time, center-in-space model, and then by mathematical modelling, which enabled the direct evaluation of nanoparticle penetration kinetics in different spheroid models. Nanoparticle uptake was shown to inversely relate to particle size and varied depending on the cell type, cell stiffness and density of the spheroid model. The automated analysis method we have developed can be applied to live spheroids in situ, for the advanced evaluation of nanoparticles as delivery agents in cancer therapy.

Acetylated cashew gum and fucan for incorporation of lycopene rich extract from red guava (Psidium guajava L.) in nanostructured systems: Antioxidant and antitumor capacity

Industrial application of lycopene is limited due to its chemical instability and low bioavailability. This study proposes the development of fucan-coated acetylated cashew gum nanoparticles (NFGa) and acetylated cashew gum nanoparticles (NGa) for incorporation of the lycopene-rich extract from red guava (LEG). Size, polydispersity, zeta potential, nanoparticles concentration, encapsulation efficiency, transmission electron microscopy (TEM) and atomic force microscopy (AFM) were used to characterize nanoparticles. The antioxidant activity was determinated and cell viability was evaluated in the human breast cancer cells (MCF-7) and human keratinocytes (HaCaT) by MTT assay. The toxic effect was evaluated by hemolysis test and by Galleria mellonella model. NFGa showed higher stability than NGa, having a size of 162.10 ± 3.21 nm, polydispersity of 0.348 ± 0.019, zeta potential -30.70 ± 0.53 mV, concentration of 6.4 × 10⁹ nanoparticles/mL and 60% LEG encapsulation. Microscopic analysis revealed a spherical and smooth shape of NFGa. NFGa showed antioxidant capacity by ABTS method and ORAC assay. The NFGa presented significant cytotoxicity against MCF-7 from the lowest concentration tested (6.25-200 μg/mL) and did not affect the cell viability of the HaCaT. NFGa showed non-toxic effect in the in vitro and in vivo models. Therefore, NFGa may have a promising application in LEG stabilization for antioxidant and antitumor purposes.

Settling dynamics of nanoparticles in simple and biological media

The biological response of organisms exposed to nanoparticles is often studied in vitro using adherent monolayers of cultured cells. In order to derive accurate concentration-response relationships, it is important to determine the local concentration of nanoparticles to which the cells are actually exposed rather than the nominal concentration of nanoparticles in the cell culture medium. In this study, the sedimentation-diffusion process of different sized and charged gold nanoparticles has been investigated in vitro by evaluating their settling dynamics and by developing a theoretical model to predict the concentration depth profile of nanoparticles in solution over time. Experiments were carried out in water and in cell culture media at a range of controlled temperatures. The optical phenomenon of caustics was exploited to track nanoparticles in real time in a conventional optical microscope without any requirement for fluorescent labelling that potentially affects the dynamics of the nanoparticles. The results obtained demonstrate that size, temperature and the stability of the nanoparticles play a pivotal role in regulating the settling dynamics of nanoparticles. For gold nanoparticles larger than 60 nm in diameter, the initial nominal concentration did not accurately represent the concentration of nanoparticles local to the cells. Finally, the theoretical model proposed accurately described the settling dynamics of the nanoparticles and thus represents a promising tool to support the design of in vitro experiments and the study of concentration-response relationships.

Chitosan-Coated PLGA Nanoparticles Encapsulating Triamcinolone Acetonide as a Potential Candidate for Sustained Ocular Drug Delivery

The current treatment for the acquired retinal vasculopathies involves lifelong repeated intravitreal injections of either anti-vascular endothelial growth factor (VEGF) therapy or modulation of inflammation with steroids. Consequently, any treatment modification that decreases this treatment burden for patients and doctors alike would be a welcome intervention. To that end, this research aims to develop a topically applied nanoparticulate system encapsulating a corticosteroid for extended drug release. Poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) supports the controlled release of the encapsulated drug, while surface modification of these NPs with chitosan might prolong the mucoadhesion ability leading to improved bioavailability of the drug. Triamcinolone acetonide (TA)-loaded chitosan-coated PLGA NPs were fabricated using the oil-in-water emulsion technique. The optimized surface-modified NPs obtained using Box-Behnken response surface statistical design were reproducible with a particle diameter of 334 ± 67.95 to 386 ± 15.14 nm and PDI between 0.09 and 0.15. These NPs encapsulated 55-57% of TA and displayed a controlled release of the drug reaching a plateau in 27 h. Fourier-transform infrared spectroscopic (FTIR) analysis demonstrated characteristic peaks for chitosan (C-H, CONH2 and C-O at 2935, 1631 and 1087 cm-1, respectively) in chitosan-coated PLGA NPs. This result data, coupled with positive zeta potential values (ranged between +26 and +33 mV), suggests the successful coating of chitosan onto PLGA NPs. Upon coating of the NPs, the thermal stability of the drug, polymer, surfactant and PLGA NPs have been enhanced. The characteristics of the surface-modified NPs supports their use as potential candidates for topical ocular drug delivery for acquired retinal vasculopathies.

Targeted Intracellular Delivery of Trastuzumab Using Designer Phage Lambda Nanoparticles Alters Cellular Programs in Human Breast Cancer Cells

| Several diseases exhibit a high degree of heterogeneity and diverse reprogramming of cellular pathways. To address this complexity, additional strategies and technologies must be developed to define their scope and variability with the goal of improving current treatments. Nanomedicines derived from viruses are modular systems that can be easily adapted for combinatorial approaches, including imaging, biomarker targeting, and intracellular delivery of therapeutics. Here, we describe a "designer nanoparticle" system that can be rapidly engineered in a tunable and defined manner. Phage-like particles (PLPs) derived from bacteriophage lambda possess physiochemical properties compatible with pharmaceutical standards, and in vitro particle tracking and cell targeting are accomplished by simultaneous display of fluorescein-5-maleimide (F5M) and trastuzumab (Trz), respectively (Trz-PLPs). Trz-PLPs bind to the oncogenically active human epidermal growth factor receptor 2 (HER2) and are internalized by breast cancer cells of the HER2 overexpression subtype, but not by those lacking the HER2 amplification. Compared to treatment with Trz, robust internalization of Trz-PLPs results in higher intracellular concentrations of Trz, prolonged inhibition of cell growth, and modulated regulation of cellular programs associated with HER2 signaling, proliferation, metabolism, and protein synthesis. Given the implications to cancer pathogenesis and that dysregulated signaling and metabolism can lead to drug resistance and cancer cell survival, the present study identifies metabolic and proteomic liabilities that could be exploited by the PLP platform to enhance therapeutic efficacy. The lambda PLP system is robust and rapidly modifiable, which offers a platform that can be easily "tuned" for broad utility and tailored functionality.

Au@Ag Core@Shell Nanoparticles Synthesized with Rumex hymenosepalus as Antimicrobial Agent

In this work, we used a sequential method of synthesis for gold-silver bimetallic nanoparticles with core@shell structure (Au@AgNPs). Rumex hymenosepalus root extract (Rh), which presents high content in catechins and stilbenes, was used as reductor agent in nanoparticles synthesis. Size distribution obtained by Transmission Electron Microscopy (TEM) gives a mean diameter of 36 ± 11 nm for Au@AgNPs, 24 ± 4 nm for gold nanoparticles (AuNPs), and 13 ± 3 nm for silver nanoparticles (AgNPs). The geometrical shapes of NPs were principally quasi-spherical. The thickness of the silver shell over AuNPs is around 6 nm and covered by active biomolecules onto the surface. Nanoparticles characterization included high angle annular dark field images (HAADF) recorded with a scanning transmission electron microscope (STEM), Energy-Dispersive X-ray Spectroscopy (EDS), X-Ray Diffraction (XRD), UV-Vis Spectroscopy, Zeta Potential, and Dynamic Light Scattering (DLS). Fourier Transform Infrared Spectrometer (FTIR), and X-ray Photoelectron Spectroscopy (XPS) show that nanoparticles are stabilized by extract molecules. A growth kinetics study was performed using the Gompertz model for microorganisms exposed to nanomaterials. The results indicate that AgNPs and Au@AgNPs affect the lag phase and growth rate of Escherichia coli and Candida albicans in a dose-dependent manner, with a better response for Au@AgNPs.

Characterization of Liposomes Using Quantitative Phase Microscopy (QPM)

The rapid development of nanomedicine and drug delivery systems calls for new and effective characterization techniques that can accurately characterize both the properties and the behavior of nanosystems. Standard methods such as dynamic light scattering (DLS) and fluorescent-based assays present challenges in terms of system's instability, machine sensitivity, and loss of tracking ability, among others. In this study, we explore some of the downsides of batch-mode analyses and fluorescent labeling, while introducing quantitative phase microscopy (QPM) as a label-free complimentary characterization technique. Liposomes were used as a model nanocarrier for their therapeutic relevance and structural versatility. A successful immobilization of liposomes in a non-dried setup allowed for static imaging conditions in an off-axis phase microscope. Image reconstruction was then performed with a phase-shifting algorithm providing high spatial resolution. Our results show the potential of QPM to localize subdiffraction-limited liposomes, estimate their size, and track their integrity over time. Moreover, QPM full-field-of-view images enable the estimation of a single-particle-based size distribution, providing an alternative to the batch mode approach. QPM thus overcomes some of the drawbacks of the conventional methods, serving as a relevant complimentary technique in the characterization of nanosystems.

Understanding nano-engineered particle-cell interactions: biological insights from mathematical models

Understanding the interactions between nano-engineered particles and cells is necessary for the rational design of particles for therapeutic, diagnostic and imaging purposes. In particular, the informed design of particles relies on the quantification of the relationship between the physicochemical properties of the particles and the rate at which cells interact with, and subsequently internalise, particles. Quantitative models, both mathematical and computational, provide a powerful tool for elucidating this relationship, as well as for understanding the mechanisms governing the intertwined processes of interaction and internalisation. Here we review the different types of mathematical and computational models that have been used to examine particle-cell interactions and particle internalisation. We detail the mathematical methodology for each type of model, the benefits and limitations associated with the different types of models, and highlight the advances in understanding gleaned from the application of these models to experimental observations of particle internalisation. We discuss the recent proposal and ongoing community adoption of standardised experimental reporting, and how this adoption is an important step toward unlocking the full potential of modelling approaches. Finally, we consider future directions in quantitative models of particle-cell interactions and highlight the need for hybrid experimental and theoretical investigations to address hitherto unanswered questions.

A quantitative view on multivalent nanomedicine targeting

Although the concept of selective delivery has been postulated over 100 years ago, no targeted nanomedicine has been clinically approved so far. Nanoparticles modified with targeting ligands to promote the selective delivery of therapeutics towards a specific cell population have been extensively reported. However, the rational design of selective particles is still challenging. One of the main reasons for this is the lack of quantitative theoretical and experimental understanding of the interactions involved in cell targeting. In this review, we discuss new theoretical models and experimental methods that provide a quantitative view of targeting. We show the new advancements in multivalency theory enabling the rational design of super-selective nanoparticles. Furthermore, we present the innovative approaches to obtain key targeting parameters at the single-cell and single molecule level and their role in the design of targeting nanoparticles. We believe that the combination of new theoretical multivalent design and experimental methods to quantify receptors and ligands aids in the rational design and clinical translation of targeted nanomedicines.

Isolating the sources of heterogeneity in nano-engineered particle-cell interactions

Nano-engineered particles have the potential to enhance therapeutic success and reduce toxicity-based treatment side effects via the targeted delivery of drugs to cells. This delivery relies on complex interactions between numerous biological, chemical and physical processes. The intertwined nature of these processes has thus far hindered attempts to understand their individual impact. Variation in experimental data, such as the number of particles inside each cell, further inhibits understanding. Here, we present a mathematical framework that is capable of examining the impact of individual processes during particle delivery. We demonstrate that variation in experimental particle uptake data can be explained by three factors: random particle motion; variation in particle-cell interactions; and variation in the maximum particle uptake per cell. Without all three factors, the experimental data cannot be explained. This work provides insight into biological mechanisms that cause heterogeneous responses to treatment, and enables precise identification of treatment-resistant cell subpopulations.

Magnetic compass of garden warblers is not affected by oscillating magnetic fields applied to their eyes

The magnetic compass is an important element of the avian navigation system, which allows migratory birds to solve complex tasks of moving between distant breeding and wintering locations. The photochemical magnetoreception in the eye is believed to be the primary biophysical mechanism behind the magnetic sense of birds. It was shown previously that birds were disoriented in presence of weak oscillating magnetic fields (OMF) with frequencies in the megahertz range. The OMF effect was considered to be a fingerprint of the photochemical magnetoreception in the eye. In this work, we used miniaturized portable magnetic coils attached to the bird’s head to specifically target the compass receptor. We performed behavioural experiments on orientation of long-distance migrants, garden warblers (Sylvia borin), in round arenas. The OMF with the amplitude of about 5 nT was applied locally to the birds’ eyes. Surprisingly, the birds were not disoriented and showed the seasonally appropriate migratory direction. On the contrary, the same birds placed in a homogeneous 5 nT OMF generated by large stationary coils showed clear disorientation. On the basis of these findings, we suggest that the disruption of magnetic orientation of birds by oscillating magnetic fields is not related to photochemical magnetoreceptors in their eyes.

Particokinetics and in vitro dose of high aspect ratio nanoparticles

Computational particokinetics models become essential in the design and interpretation of in vitro nanoparticle toxicology assays involving submerged adherent cell cultures. Yet, none of the current models offers the possibility of addressing the delivered dose of high-aspect ratio nanoparticles, including nanorods, nanotubes, and nanofibers. Here we present a straightforward method that lends this ability to any of the models used currently.