Diffusion of Nanoparticles in Heterogeneous Hydrogels as Vitreous Humour Substitutes

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Kearns, Eann A. Patterson, Judith M. Curran This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3997364/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Jul, 2024 Read the published version in Scientific Reports → Version 1 posted 19 You are reading this latest preprint version Abstract Nanomedicine has the potential to increase the biostability of drugs to treat retinal diseases, improving their performance and decreasing the required number of intravitreal injections. However, accurate pharmacokinetic studies of these nanoparticle-drug conjugates, nanoparticle motion across the vitreous humour and interaction with the retinal cell layers still need to be investigated. Existing nanoparticle tracking techniques require fluorescent labels, which can impact cytotoxicity, nanoparticles’ motion, protein interactions, and cell internalization. In this study, a real-time label-free tracking technology, for single nanoparticles in an optical microscope based on the optical phenomena of caustics, was used to characterise the diffusion of nanoparticles in agar-hyaluronic acid hydrogels, previously validated as vitreous humour substitutes for in vitro models. The results demonstrated that the diffusion of nanoparticles through these hydrogels was heterogeneous and that nanoparticle size had an important role in nanoparticle distribution across and within in vitro vitreous substitutes. These findings suggest that nanoparticle diameter is a critical parameter for designing novel therapeutics for retinal diseases. Moreover, nanoparticle charge did not affect nanoparticle diffusion or distribution in these synthetic hydrogels. The use of caustics in optical microscopy has been demonstrated to be a reproducible, inexpensive technique for screening novel therapeutics in eye in vitro models. retinal diseases in vitro models hydrogels nanomedicine drug delivery label-free tracking Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Vision impairment creates an economic burden of £25 billion in the UK alone [ 1 ], and diseases affecting the retina, such as macular degeneration (MD) and diabetic retinopathy (DR), affect more than 12 million people globally [ 2 ]. These numbers will grow as a result of an increase in life expectancy worldwide. Considering that current treatments for retinal diseases involve monthly or bimonthly intravitreal injections of anti-vascular endothelium growth factor (anti-VEGF) and corticoids, there is an urgent need to optimize drug delivery and increase the sustained efficacy of treatment in the retina [ 3 ], [ 4 ] so that the patient’s quality of life can be increased and the economic burden on health care systems can be reduced. Numerous advancements have been noted in ocular drug delivery systems with the goal of optimising intraocular drug delivery[ 5 ], [ 6 ]. Among these, the conjugation of first-line approved drugs with functionalized nanoparticles (NPs) has the potential to increase bioavailability in the posterior chamber, increase the concentration in the retinal cell layer, and minimize side effects by decreasing the number of intravitreal injections[ 7 ], [ 8 ]. To optimize the drug delivery profile of these NP-drug conjugates, experimental models are required to characterize the diffusion of nanoparticle delivery systems across the vitreous humour (VH). The well-characterized drawbacks of in vivo animal testing, such as ethical concerns and poor representation of human models make the use of small animals, to test retinal-targeted drugs, inadequate and a waste of resources [ 9 ], [ 10 ]. The utilization of cadaveric eyes for ex vivo analysis presents issues of stability once the vitreous humour is detached from the retina for analysis, at the same time, the cadaveric nature will affect the stability of the biomechanical and biochemical properties, affecting the accuracy, and replicability of the results [ 11 ], [ 12 ]. The development of a pre-clinical in vitro model of the eye reduces the need for living or cadaveric donors, could improve the stability of the vitreous-like biomechanical properties, could increase the replicability of the results, and could lower the economic cost of screening novel therapeutics. The first biological barrier that a NP-drug conjugate faces following intravitreal injection is the vitreous humour, hence significant effort has been made to replicate its biomechanical properties to evaluate pharmacokinetics, to optimize dosage and to formulate the design of novel therapeutics as well as to characterize the real concentration that reaches the targeted retinal cell layer [ 13 ], [ 14 ], [ 15 ]. Despite this effort, there is still no clear understanding of nanoparticle diffusion and distribution through the vitreous humour for back-of-the-eye in vitro pre-clinical models [ 16 ]. In 2020, Thakur et al., validated previously studied agar-hyaluronic acid hydrogels as vitreous humour substitutes for in vitro drug delivery screening [ 13 ], [ 18 ]. The authors evaluated the rheological properties of the hydrogels and compared them to bovine-extracted vitreous humour, the data showed that the hydrogel with the lowest viscosity (LV) was the closest to mimicking the biomechanical properties of bovine vitreous humour [ 14 ]. Moreover, for polystyrene nanoparticles that had been fluorescently tagged, their data suggested that the rate of diffusion in low and medium viscosity synthetic hydrogels was the same as that in vitreous humour. However, nanoparticle-labelling has several limitations; including photobleaching and the requirement for meticulous sample preparation, which translates into time-consuming and expensive practices[ 19 ]. In particular, when used for in vitro purposes, we need to take into consideration that some dyes exhibit cytotoxicity due to the production of free radicals after excitation or phototoxicity induced by the laser or light beams used to detect them, affecting the overall aim of the test [ 20 ]. Moreover, a recent study has stated that the use of different labelling methods will have a direct impact on the diffusive behavior of particles, creating a large burden on the standardization, accuracy, and replicability of in vitro models, where the results are dependent on the nature of the fluorescent dye [ 21 ]. Single-particle tracking has emerged as a potential tool to better understand particle diffusion and interactions with hydrogels and other soft matter systems [ 22 ]. This is mainly due to the possibility of tracking nanoparticles in real-time in the media of interest, as opposed to other high-resolution (nanoscale) techniques, such as electronic microscopy [ 23 ]. Recently, Foreman and Tran-Ba used this technique to analyze nanoparticle diffusive behavior in polymer solutions, revealing the size-dependent and steric-dependent behavior of carboxylic fluorescently modified nanoparticles and quantum dots[ 24 ]. However, this label-based technique can affect the physicochemical-surface properties of nanoparticles, impacting their dynamics and distribution through the hydrogels. Considering the previously highlighted disadvantages of fluorescence microscopy, and the clinical motivations of our experimental design, we have used a label-free, single-particle tracking technique that enables the visualization and localization of nanoparticles in real-time. This technique exploits the naturally-occurring optical phenomenon of caustics and applies it in a standard, inverted optical microscope, by increasing the coherence of the source of light [ 25 ]. The optical phenomenon of caustics generates optical signatures several orders of magnitude larger than the particle’s actual size (Fig. 1 ), thus allowing the nanoparticles to be visualized and tracked without fluorescent dye, in a fast and cost-effective manner [ 26 ], see for example Fig. 1 . In this study, we analysed the effects of nanoparticle surface charge and size on the diffusion through agar-hyaluronic acid hydrogels, which have been previously validated as in vitro vitreous humour substitutes. Gold nanoparticles were used to validate the experimental technique, as these nanoparticles have been widely studied and characterized in the literature [ 27 ], [ 28 ]. The motion of the particles through the hydrogels was characterized with the label-free technique in an inverted optical microscope. The results revealed the heterogeneous nature of the hydrogels, which contained regions of low and medium viscosity, thus affecting nanoparticle diffusion and distribution. As the NPs exhibit different degrees of diffusion depending on their location within the hydrogel, it is inappropriate to characterize their diffusion in a hydrogel by a single arbitrary value. This paper shows the potential of this label-free technique for nanoparticle tracking in complex heterogeneous polymeric hydrogels. Materials and methods Materials Gold nanoparticles : 50 nm (-34.5 mV), 100 nm (-32.7 mV) and 200 nm diameter (-31 mV) spherical citrate-capped gold nanoparticles (AuNPs) were purchased from BBI Solutions (Crumlin, UK), and 100 nm diameter (28.7 mV) branched polyethylenimine (BPEI) capped AuNPs were obtained from NanoComposix. These nanoparticle stock solutions were diluted in ultra-pure deionized water to obtain the desired constant concentration of 10 − 4 mg/mL when added to the hydrogels, see Table 2 . Table 1 : Agar-hyaluronic acid hydrogels characterization. Agar and hyaluronic acid concentrations were determined as by Thakur et al. Viscosity and rheological analysis were performed at 34˚C via in-house characterization. H ydrogel A gar (mg/mL) H yaluronic acid (mg/mL) Z eta potential (mV) s tatic viscosity (Pa· s) G’ (P a) G’’ (P a) pH LV A-HA 0.95 0.70 - 6.7 3 1.03 0.15 7.23 MV A-HA 1.80 2.21 3.0 38 6.81 0.83 7.27 HV A-HA 4.00 5.00 -3.0 450 136.1 16.58 7.20 vh (Porcine) - 0.16 [38] -9.9 1 0.35 0.15 7.35 Table 2 Gold nanoparticles characteristics. Hydrodynamic diameter (nm) Zeta potential (mV) Concentration in A-HA hydrogel (mg/mL) 50 − 34.5 5x10 − 4 100 - cITRATE − 32.7 5x10 − 4 100 - bpei 28.7 5x10 − 4 200 -31 5x10 − 4 Microscope : An Axio Observer.Z1 m (Carl Zeiss, DE) inverted optical microscope was used to create optical signatures or caustics that enabled the identification and tracking of gold nanoparticles in the viscous media. This was possible through an increase in the coherence of the light by closing the aperture of the condenser to its minimum (1 mm), adding a green interference filter (Olympus, JP, centred on 550 nm, 45 nm bandwidth) and adjusting the microscope for Köhler illumination; following the methodology described by Patterson and Whelan[ 26 ]. The microscope was also equipped with a stage-top incubation system (Incubator PM S1, Heating Insert P S1, Temp and CO 2 module S1, Carl Zeiss, DE), which was used to maintain the samples at 34˚C corresponding to the physiological mid-vitreous temperature, and is within the temperature range for characterising ocular endotamponades [ 29 ], [ 30 ]. Methods Agar-hyaluronic acid hydrogel synthesis : hydrogels were synthesised following the protocol described by Thakur et al.[ 14 ]. Three hydrogels with different viscosities were synthesised by adding different concentrations of agar and hyaluronic acid (high molecular weight) to 1X boiling phosphate buffer saline (PBS). For the high viscous (HV) hydrogel, hyaluronic acid was at a concentration of 5 mg/mL and agar at 4 mg/mL; for the medium viscous (MV) hydrogel, hyaluronic acid was at a concentration of 2.21 mg/mL and agar at 1.8 mg/mL; and for the low viscous (LV) hydrogel, hyaluronic acid was at a concentration of 0.7 mg/mL and agar at 0.95 mg/mL. The three solutions were magnetically stirred at 100˚C for 1 hour, after which the gels were cooled down at room temperature overnight before being characterized or used for NP tracking. Diffusion of gold nanoparticles in hydrogels : The diffusion coefficient of positively-charged 100 nm AuNP and 50 nm, 100 nm and 200 nm diameter negatively-charged AuNP were evaluated at 34°C. The samples were vortexed (with a Vortex-Fisherbrand® mixer) for 15 s and ultrasonicated (with a S-Series Heated Ultrasonic Bath Fisherbrand®) for 1 minute before aliquoting a volume of 50 µL onto a microscope slide (76x26 mm and 0.2 mm cavity depth). The samples were incubated on the microscope stage-top incubation system at 34°C for 10 minutes prior to being analysed under an inverted optical microscope, to ensure a consistent temperature throughout the sample. Videos were recorded using a x 40 objective and a monochromatic camera (Axiocam305, Carl Zeiss) with a spatial resolution of 0.086 µm 2 for one pixel and a temporal resolution of 40 fps. A total of 30 nanoparticles were tracked for each nanoparticle size in each of the hydrogels, in order to randomise the nanoparticle distribution across the hydrogels. For the preliminary quantitative analysis and investigation of the nanoparticle surface charge, six nanoparticles, randomly selected from the field of view, were tracked for each set of conditions and the mean value of diffusion coefficient calculated. The same process was repeated in deionized water as a control. Data analysis : An assumption of Brownian motion for a random walk of particles in a suspended fluid leads to the following definition of the diffusion coefficient ( D ): \(D= \frac{{k}_{b} T}{4d\pi nr}\) [ 1 ] In the equation k b is the Boltzmann constant, T is the temperature, d is the dimensionality (2D in this case), n is the viscosity of the diffusive media and r is the radius of the particle. This is known as the Stokes-Einstein relation because it combines Stokes’ Law and Einstein’s description of diffusion. Particle motion has been widely characterised by the mean squared displacement (MSD) of the particle and, considering a two-dimensional system, is expressed as [ 31 ], [ 32 ]: \(MSD=\frac{1}{N-n}{\sum _{i=0}^{N-n} \left(\right({x}_{i+n}-{x}_{i})}^{2}+{({y}_{i+n}-{y}_{i})}^{2})\) [ 2 ] Where x and y correspond to the particle coordinates for each i th step in n total frames and hence can be measured experimentally. Videos with a minimum of 50 frames and a maximum of 100 frames, depending on the speed of a particle and its motion perpendicular to the focal plane of the microscope, were recorded and analysed using the ImageJ software plugin TrackMate[ 33 ]. This provided information on the x and y positions of the nanoparticle for each frame. These coordinates provided the path of the NPs over time, from which values of their mean squared displacement (MSD) and experimental diffusion coefficient were determined, as there is a linear relation between the mean squared displacement and the diffusion coefficient (D), for Brownian motion, for a specific time lag ( \(\varDelta t):\) \(MSD= 2 d D \varDelta t\) [ 3 ] To better characterise the nanoparticle distribution through the hydrogels, the area containing the path of a nanoparticle was evaluated and compared to the values of their diffusion coefficient. The path of a nanoparticle through 50 frames was plotted and enclosed in the smallest possible convex hull or polygon, which was found using a geometric algorithm. Results and discussion Initial qualitative visualization of the agar-hyaluronic acid hydrogels, with the microscope set up to observe caustics, revealed a detailed heterogeneous nature of the synthetic hydrogels (Fig. 2 ). This was confirmed by analysis of nanoparticle motion, in which the nanoparticles were found to behave differently in different local environments within the hydrogels. NPs were found to diffuse faster in environments with a high-water content (aqueous phase) and slower when interacting with the agar (gel phase) (videos attached in supplementary information). To validate these qualitative findings, we performed a preliminary quantitative analysis by tracking six independent nanoparticles, using the label-free caustics optical technique, in low, medium and high viscosity solutions that were designed to represent the qualitatively characterized environments, identified from Fig. 2 and described above, i.e., an aqueous phase, gel phase and intermediate phase. The experimental diffusion coefficients of the nanoparticles in each local environment are plotted against the static bulk viscosity for each hydrogel (characterization in supplementary information) and compared to that of deionized water, which was used as a control, in Fig. 3 . To investigate the effect of nanoparticle surface charge on nanoparticle diffusion across the synthetic hydrogels, citrate-capped (negative) and branched polyethyleneimine (BPEI)-capped (positive) 100 nm diameter gold nanoparticles were tracked as described above using the caustic technique (Table 2 ). Considering that the presence of hyaluronic acid will give the hydrogels a partial negative charge, a difference in diffusion would be expected for differently charged nanoparticles [ 34 ]. However, the results in Fig. 3 show no definitive difference between the diffusion of positively (closed green symbols) and negatively (open red symbols) charged AuNPs across any of the gels. This was explained by the low zeta potential values of the hydrogels, characterizing these as neutral (Table 1 ), and the low nanoparticle concentration present in the hydrogels. More interestingly the values of diffusion coefficient were found to range from 10 − 12 to 10 − 15 m 2 /s for both, negatively and positively-charged 100 nm diameter AuNPs in the low and medium viscous hydrogels (Fig. 3 ). Deionized water was used as a control with a viscosity three orders of magnitude less than the hydrogel with lowest viscosity (approximately 0.001 Pa·s compared to 3 Pa·s). The medium and high viscosity hydrogels had viscosities one and two orders of magnitude higher than the low viscosity hydrogel, (i.e., approximately 40 and 400 Pa·s respectively). In the low and medium viscosity hydrogels, some of the tracked particles behaved in the same manner as those in the deionised water and their diffusion coefficients values were similar (approximately 10 − 12 m 2 /s). These nanoparticles had a random walk which led them away from the location at which they were first observed, as shown in the top inset in Fig. 3 . However, some particles moved randomly around a single location, essentially dancing on the spot (see bottom inset in Fig. 3 ); these nanoparticles had values for their diffusion coefficient of about 10 − 15 m 2 /s. This behaviour occurred in all three hydrogels with the diffusion coefficient decreasing in value with increasing viscosity, implying that the high viscosity inhibited the motion of the particles and constrained them from moving away from a given location. The observation that both of these types of behaviour, i.e. wandering away from a location and dancing on the spot, occurred the same in low and medium viscosity hydrogels implies that these hydrogels were heterogeneous with same zones that were largely aqueous solution and others that were largely gel, consisting of a polymeric matrix that inhibited nanoparticle motion. There is also evidence of nanoparticles diffusing in intermediate zones with properties that lie somewhere between those of the gel and aqueous solution, see middle inset in Fig. 3 , which shows a typical path of particles attempting to move away from a location but repeatedly returning to it. These different behaviours within the low and medium viscosity hydrogels were not observed in the high viscosity hydrogel which implied that it was a largely homogeneous gel. Following this preliminary investigation, a more detailed study was performed in which at least 30 randomly-selected nanoparticles were tracked in each sample with the aim of understanding the distribution of nanoparticle behavior in the hydrogels. Since the charge of the nanoparticles had been demonstrated to have no influence on their diffusion under these conditions, only citrate-capped gold nanoparticles with diameters of 50 nm, 100 nm and 200 nm were tested to investigate the effect of particle size on diffusion behavior in the hydrogels. These sizes were chosen because they are clinically relevant to back-of-the-eye drug delivery [ 35 ]. The values of the diffusion coefficient are shown in Figs. 4 to 6 as a function of the area of the convex hull enclosing its path for each tracked particle for the three hydrogels with low, medium and high viscosity. In each case a linear regression line was fitted to the data. The results confirm that the nanoparticles diffuse faster in gels with higher water content probably because there is less polymeric matrix (gel) to constrain their movement. Diffusion values in the high viscosity hydrogel were similar for all diameters of nanoparticles, with diffusion values in the range of 10 − 15 m 2 /s and lower, while the areas of the corresponding convex hulls were all in the range of 10 − 15 to 10 − 16 m 2 , suggesting that nanoparticle size did not affect nanoparticle diffusion in the hydrogel and that the motion of all nanoparticles was hindered by the polymeric matrix (red squares in Figs. 4 to 6 ). The values of correlation coefficient at this level of viscosity are in the range 0.9 to 0.65, decreasing with increasing particle diameter, implying that the correlation between speed and area enclosed by the path decreases with particle diameter. However, the behavior of the nanoparticles in the low and medium viscosity hydrogels was found to be size dependent, with the range of values for both diffusion coefficient and convex hull area remaining approximately constant but reducing in absolute value with increasing particle diameter which implies that larger particles move more slowly and cover a smaller area. The correlation between the diffusion coefficient and the area of the convex hulls is positive and close to one (0.94 to 0.99) for both the medium and low viscosity hydrogels. However, the distribution of the data points in the graphs (Figs. 4 to 6 ) for these hydrogels varies with particle diameter from an approximately uniform distribution for the 200 nm diameter particles to a bimodal distribution for the 100 nm and 50 nm diameter particles with a tendency for more data points at the higher end of the range, with diffusive values close to those in water. The bimodal distribution is perhaps more evident for the data from medium viscosity hydrogel (graph b) in Figs. 4 to 6 ). It is likely that the high viscosity hydrogel was relatively homogeneous with a uniform distribution of the polymeric matrix that inhibited the motion of all of nanoparticles; whereas the medium and low viscosity hydrogels were progressively less homogeneous with zones of low-density polymeric matrix that allowed relatively uninhibited motion and zones of high-density matrix that inhibited motion. An idealized structure of this nature would generate the bimodal distributions seen in Figs. 4 to 6 with the bimodality likely more pronounced in the medium viscosity hydrogel. The results demonstrated that label-free, real-time tracking of particles provides a powerful tool for characterizing the dynamics of nanoparticles interactions in heterogeneous polymeric hydrogels and to evaluate the degree to which nanoparticle size affects their behavior within the hydrogels. The resultant understanding should inform the development of nanoparticle- based drug delivery using in vitro models when combined with the findings of previous work reporting nanoparticle diffusion to be strongly affected by electrostatic and van der Waals forces, and controlled by the ionic strength of the media [ 36 ] as well as by the impact of the protein corona formation on the diffusion of nanoparticles [ 37 ]. Conclusions The heterogenous nature of agar-hyaluronic acid hydrogels, which have been previously validated as in vitro substitutes for vitreous humour, have been observed and quantified using a standard optical microscope set up to generate near-coherent light and reveal optical signatures known as caustics. The caustics generated by nanoparticles have been used in a label-free tracking technique to obtain experimental values of their diffusion coefficient in various local environments and for a range of particle diameters. It was found that the charge on the particles did not influence their diffusion through the hydrogels; however, both the diameter of the particles and the structure of the hydrogel affected the diffusion characteristics of the particles. NPs with diameters of 50, 100 and 200 nm moved progressively more slowly and within a smaller area. High viscosity hydrogels were observed to generate consistent behaviour of the nanoparticles implying a large homogeneous structure of polymeric matrix, or gel that uniformly inhibited particle motion, whereas medium and low viscosity hydrogels generated bimodal distributions of particle diffusion coefficients as functions of the area enclosed by the particle’s path suggesting a heterogeneous hydrogel with zones of low and high density polymeric matrix in which the particles move more or less freely, respectively. The results indicate that the single-particle label-free nanoparticle tracking technique is a powerful tool to characterise the diffusion and transport of nanoparticles in heterogeneous hydrogels that can be used as in vitro substitutes for vitreous humour. Hence, this technique has the potential to become an indispensable method in the development of pre-clinical models to optimise nanoparticle-based drug delivery systems for the treatment of retinal diseases, and to better characterise their pharmacokinetics profiles. These advances could help elucidate the variables that influence the diffusive behavior of nanoparticles leading to the optimization of drug delivery to the retina. Declarations Acknowledgements This work was supported by the Doctoral Network in Technologies for Healthy Aging; and the Engineering and Physical Sciences Research Council [grant numbers EP/R024839/1; EP/S012265/1]. Author contributions MLL performed data curation, analysis, and writing of first draft; VK advised on vitreous humour substitutes, EAP advised on data analysis and microscopy technique, JMC PI and grant holder. All authors contributed to manuscript edition and writing. Additional Information The authors declare no competing interests. Data Availability The datasets generated during and/or analysed during the current study are available in the [DataCat: The Research Data Catalogue] repository, [ https://doi.org/10.17638/datacat.liverpool.ac.uk%2F2603 ]. References M. Schmoker, ‘Time to Focus’, Principal Leadership , vol. 13, no. 3, pp. 18–21, 2012, Accessed: Jan. 14, 2024. [Online]. Available: https://www.fightforsight.org.uk/our-research/timetofocus/?gad_source=1&gclid=CjwKCAiAqY6tBhAtEiwAHeRopbFuAegQ_pW6sPvDRSMk-ArDwJ7mmt3chTaWST4jrJwcdxvAT3apchoCO6AQAvD_BwE R. R. A. 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Einstein, ‘Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen’, Ann Phys , vol. 322, no. 8, pp. 549–560, 1905, doi: 10.1002/ANDP.19053220806. J. Y. Tinevez et al. , ‘TrackMate: An open and extensible platform for single-particle tracking’, Methods , vol. 115, pp. 80–90, 2017, doi: 10.1016/j.ymeth.2016.09.016. F. Horkay, P. J. Basser, D. J. Londono, A. M. Hecht, and E. Geissler, ‘Ions in hyaluronic acid solutions’, Journal of Chemical Physics , vol. 131, no. 18, p. 184902, 2009, doi: 10.1063/1.3262308. R. Bisht, A. Mandal, J. K. Jaiswal, and I. D. Rupenthal, ‘Nanocarrier mediated retinal drug delivery: overcoming ocular barriers to treat posterior eye diseases’, Wiley Interdiscip Rev Nanomed Nanobiotechnol , vol. 10, no. 2, pp. 1–21, 2018, doi: 10.1002/wnan.1473. F. Giorgi et al. , ‘The influence of inter-particle forces on diffusion at the nanoscale’, Sci Rep , vol. 9, no. 1, pp. 1–6, 2019, doi: 10.1038/s41598-019-48754-5. S. Tavakoli et al. , ‘Diffusion and Protein Corona Formation of Lipid-Based Nanoparticles in the Vitreous Humor: Profiling and Pharmacokinetic Considerations’, Mol Pharm , vol. 18, no. 2, pp. 699–713, 2021, doi: 10.1021/acs.molpharmaceut.0c00411. S. Shafaie, V. Hutter, M. B. Brown, M. T. Cook, and D. Y. S. Chau, ‘Diffusion through the ex vivo vitreal body – Bovine, porcine, and ovine models are poor surrogates for the human vitreous’, Int J Pharm , vol. 550, no. 1–2, pp. 207–215, 2018, doi: 10.1016/j.ijpharm.2018.07.070. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3997364","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":277959433,"identity":"f70822ee-ef55-43a8-9299-01cc9ec55697","order_by":0,"name":"Moira Lorenzo Lopez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIie2RvwrCMBCHLxykS7FriqJPIKQURLEPYxc7CY66tQTi0hfwLRxdJaCL7u6uDrpVdLDWP1AhdnXINyRcwsfdLwEwGP4SEgOMu80avg+s58Z/K5z59KNgpVJcs1B+iiqlPRPylHEWScv2DtNl0HQQyCkD5euUznYl5ilnI4m27+22Q98VgG4KqqNV9qEAu1Do0E2kChcKoA6ggl8KueWDUaTR5aXgtUrBvMuAIq7JS6GPLvrB8izY4MyTiMpNiixE9lIe6eNvZgdynAQtx1kl5+TxYpZQ+2zS92KdU4LE77XiI78Vg8FgMJS5A+g6SrA7nAklAAAAAElFTkSuQmCC","orcid":"","institution":"University of Liverpool","correspondingAuthor":true,"prefix":"","firstName":"Moira","middleName":"Lorenzo","lastName":"Lopez","suffix":""},{"id":277959434,"identity":"fa5e3dd3-e05b-46a7-8e2d-afa0df47afa3","order_by":1,"name":"Victoria R. Kearns","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"R.","lastName":"Kearns","suffix":""},{"id":277959435,"identity":"8621d391-aacf-4d43-bf79-08eabbea9999","order_by":2,"name":"Eann A. Patterson","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Eann","middleName":"A.","lastName":"Patterson","suffix":""},{"id":277959436,"identity":"c2f92d67-4b27-4975-aede-9b5c5b1b5c09","order_by":3,"name":"Judith M. Curran","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Judith","middleName":"M.","lastName":"Curran","suffix":""}],"badges":[],"createdAt":"2024-02-28 17:30:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3997364/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3997364/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-68267-0","type":"published","date":"2024-07-29T15:58:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52409175,"identity":"4e3a96b3-cb96-447b-8f03-b8b725d07a1f","added_by":"auto","created_at":"2024-03-11 09:38:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2338479,"visible":true,"origin":"","legend":"\u003cp\u003eLabel-free visualization of nanoparticles through caustics optical microscopy technique. a) Optical signatures of 100 nm diameter gold nanoparticles in a 50% glycerol deionized water solution (v/v); b) Single 50 nm diameter gold nanoparticle in low viscous hydrogel; c) Single 100 nm diameter gold nanoparticle in medium viscous hydrogel and d) Single 200 nm diameter in deionized water. \u0026nbsp;Scale bar: 20 µm.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/cf4549b7fad5b0b0a8271a74.png"},{"id":52409174,"identity":"b77b7334-f1da-4141-8d78-3453df061dba","added_by":"auto","created_at":"2024-03-11 09:38:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2308741,"visible":true,"origin":"","legend":"\u003cp\u003eQualitative characterization of agar hyaluronic acid hydrogels visualized using the caustics optical technique (left) and normal bright field (right), images obtained from the same sample area, for each of the different viscous hydrogels, with a Zeiss inverted optical microscope. Scale bar: 20 µm.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/897a5ca7a40d3a9b84f0beea.png"},{"id":52409158,"identity":"46196450-51fc-4702-a2c6-90de6f6cdd67","added_by":"auto","created_at":"2024-03-11 09:38:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":482417,"visible":true,"origin":"","legend":"\u003cp\u003eDiffusion coefficient values of 100 nm diameter gold nanoparticles (AuNP) positively charged (green) and negatively charged (red) in deionized water (DIW= 0.001 Pa·s) and in the agar hyaluronic acid hydrogels: low viscous (LV= 1.4 Pa·s), medium viscous (MV= 10 Pa·s) and high viscous (HV= 180 Pa·s) at the physiological temperature of 34˚C. Showing the diffusion values for each hydrogel phase; aqueous phase (circles), intermediate phase (triangles), and gel phase (squares). Error bars correspond to ±1 standard deviation. Images represent the AuNP trails of motion in the three different hydrogel phases: aqueous, intermediate and gel (from top to bottom); in the three hydrogels: LV, MV, and HV (from top to bottom).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/018535bdd780eb0e9fa8d679.png"},{"id":52409173,"identity":"b59c5ee2-3df7-401d-bb31-e8d170a44d8f","added_by":"auto","created_at":"2024-03-11 09:38:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":491760,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the diffusion coefficient values of 50 nm diameter gold nanoparticles and the area of the convex hull of each nanoparticle trail of motion, in the a) low viscous (blue); b) medium viscous (orange); and c) high viscous(red) hydrogels.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/deb6fa3372f6110d4f79d00c.png"},{"id":52409144,"identity":"ffcd16c2-1df1-4a81-8d93-7f75420f4555","added_by":"auto","created_at":"2024-03-11 09:38:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":482278,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the diffusion coefficient values of 100 nm diameter gold nanoparticles and the area of the convex hull of each nanoparticle trail of motion, in the a) low viscous (blue); b) medium viscous (orange); and c) high viscous(red) hydrogels.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/6ab094c05879fa15c611c478.png"},{"id":52409167,"identity":"07e8ed4c-6567-4604-92c6-cd7569ce550e","added_by":"auto","created_at":"2024-03-11 09:38:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":490280,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the diffusion coefficient values of 200 nm diameter gold nanoparticles and the area of the convex hull of each nanoparticle trail of motion, in the a) low viscous (blue); b) medium viscous (orange); and c) high viscous(red) hydrogels.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/36aa132d370f114e94b2d619.png"},{"id":61793864,"identity":"1513740e-e4ea-4574-9fc3-8cb43ab1edd4","added_by":"auto","created_at":"2024-08-05 16:16:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7504016,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/41958741-e59f-413e-9296-9c6538273fb0.pdf"},{"id":52409164,"identity":"b94e3ef8-b410-4044-bcf7-7a013797b46d","added_by":"auto","created_at":"2024-03-11 09:38:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":70565,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-3997364/v1/56b8d2ddb2159c9e340a9895.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diffusion of Nanoparticles in Heterogeneous Hydrogels as Vitreous Humour Substitutes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eVision impairment creates an economic burden of \u0026pound;25\u0026nbsp;billion in the UK alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and diseases affecting the retina, such as macular degeneration (MD) and diabetic retinopathy (DR), affect more than 12\u0026nbsp;million people globally [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These numbers will grow as a result of an increase in life expectancy worldwide. Considering that current treatments for retinal diseases involve monthly or bimonthly intravitreal injections of anti-vascular endothelium growth factor (anti-VEGF) and corticoids, there is an urgent need to optimize drug delivery and increase the sustained efficacy of treatment in the retina [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] so that the patient\u0026rsquo;s quality of life can be increased and the economic burden on health care systems can be reduced.\u003c/p\u003e \u003cp\u003eNumerous advancements have been noted in ocular drug delivery systems with the goal of optimising intraocular drug delivery[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among these, the conjugation of first-line approved drugs with functionalized nanoparticles (NPs) has the potential to increase bioavailability in the posterior chamber, increase the concentration in the retinal cell layer, and minimize side effects by decreasing the number of intravitreal injections[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To optimize the drug delivery profile of these NP-drug conjugates, experimental models are required to characterize the diffusion of nanoparticle delivery systems across the vitreous humour (VH).\u003c/p\u003e \u003cp\u003eThe well-characterized drawbacks of \u003cem\u003ein vivo\u003c/em\u003e animal testing, such as ethical concerns and poor representation of human models make the use of small animals, to test retinal-targeted drugs, inadequate and a waste of resources [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The utilization of cadaveric eyes for \u003cem\u003eex vivo\u003c/em\u003e analysis presents issues of stability once the vitreous humour is detached from the retina for analysis, at the same time, the cadaveric nature will affect the stability of the biomechanical and biochemical properties, affecting the accuracy, and replicability of the results [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The development of a pre-clinical \u003cem\u003ein vitro\u003c/em\u003e model of the eye reduces the need for living or cadaveric donors, could improve the stability of the vitreous-like biomechanical properties, could increase the replicability of the results, and could lower the economic cost of screening novel therapeutics.\u003c/p\u003e \u003cp\u003eThe first biological barrier that a NP-drug conjugate faces following intravitreal injection is the vitreous humour, hence significant effort has been made to replicate its biomechanical properties to evaluate pharmacokinetics, to optimize dosage and to formulate the design of novel therapeutics as well as to characterize the real concentration that reaches the targeted retinal cell layer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Despite this effort, there is still no clear understanding of nanoparticle diffusion and distribution through the vitreous humour for back-of-the-eye \u003cem\u003ein vitro\u003c/em\u003e pre-clinical models [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn 2020, Thakur et al., validated previously studied agar-hyaluronic acid hydrogels as vitreous humour substitutes for \u003cem\u003ein vitro\u003c/em\u003e drug delivery screening [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The authors evaluated the rheological properties of the hydrogels and compared them to bovine-extracted vitreous humour, the data showed that the hydrogel with the lowest viscosity (LV) was the closest to mimicking the biomechanical properties of bovine vitreous humour [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, for polystyrene nanoparticles that had been fluorescently tagged, their data suggested that the rate of diffusion in low and medium viscosity synthetic hydrogels was the same as that in vitreous humour.\u003c/p\u003e \u003cp\u003eHowever, nanoparticle-labelling has several limitations; including photobleaching and the requirement for meticulous sample preparation, which translates into time-consuming and expensive practices[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In particular, when used for \u003cem\u003ein vitro\u003c/em\u003e purposes, we need to take into consideration that some dyes exhibit cytotoxicity due to the production of free radicals after excitation or phototoxicity induced by the laser or light beams used to detect them, affecting the overall aim of the test [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Moreover, a recent study has stated that the use of different labelling methods will have a direct impact on the diffusive behavior of particles, creating a large burden on the standardization, accuracy, and replicability of \u003cem\u003ein vitro\u003c/em\u003e models, where the results are dependent on the nature of the fluorescent dye [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSingle-particle tracking has emerged as a potential tool to better understand particle diffusion and interactions with hydrogels and other soft matter systems [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This is mainly due to the possibility of tracking nanoparticles in real-time in the media of interest, as opposed to other high-resolution (nanoscale) techniques, such as electronic microscopy [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Recently, Foreman and Tran-Ba used this technique to analyze nanoparticle diffusive behavior in polymer solutions, revealing the size-dependent and steric-dependent behavior of carboxylic fluorescently modified nanoparticles and quantum dots[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, this label-based technique can affect the physicochemical-surface properties of nanoparticles, impacting their dynamics and distribution through the hydrogels. Considering the previously highlighted disadvantages of fluorescence microscopy, and the clinical motivations of our experimental design, we have used a label-free, single-particle tracking technique that enables the visualization and localization of nanoparticles in real-time. This technique exploits the naturally-occurring optical phenomenon of caustics and applies it in a standard, inverted optical microscope, by increasing the coherence of the source of light [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The optical phenomenon of caustics generates optical signatures several orders of magnitude larger than the particle\u0026rsquo;s actual size (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), thus allowing the nanoparticles to be visualized and tracked without fluorescent dye, in a fast and cost-effective manner [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], see for example Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this study, we analysed the effects of nanoparticle surface charge and size on the diffusion through agar-hyaluronic acid hydrogels, which have been previously validated as \u003cem\u003ein vitro\u003c/em\u003e vitreous humour substitutes. Gold nanoparticles were used to validate the experimental technique, as these nanoparticles have been widely studied and characterized in the literature [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The motion of the particles through the hydrogels was characterized with the label-free technique in an inverted optical microscope. The results revealed the heterogeneous nature of the hydrogels, which contained regions of low and medium viscosity, thus affecting nanoparticle diffusion and distribution. As the NPs exhibit different degrees of diffusion depending on their location within the hydrogel, it is inappropriate to characterize their diffusion in a hydrogel by a single arbitrary value. This paper shows the potential of this label-free technique for nanoparticle tracking in complex heterogeneous polymeric hydrogels.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eMaterials\u003c/h2\u003e\n \u003cp\u003e\u003cspan type=\"Underline\" name=\"Emphasis\"\u003eGold nanoparticles\u003c/span\u003e: 50 nm (-34.5 mV), 100 nm (-32.7 mV) and 200 nm diameter (-31 mV) spherical citrate-capped gold nanoparticles (AuNPs) were purchased from BBI Solutions (Crumlin, UK), and 100 nm diameter (28.7 mV) branched polyethylenimine (BPEI) capped AuNPs were obtained from NanoComposix. These nanoparticle stock solutions were diluted in ultra-pure deionized water to obtain the desired constant concentration of 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e mg/mL when added to the hydrogels, see Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Agar-hyaluronic acid hydrogels characterization. Agar and hyaluronic acid concentrations were determined as by Thakur et al. Viscosity and rheological analysis were performed at 34˚C via in-house characterization.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"691\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.901306240928882%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003c/strong\u003e\u003cstrong\u003eydrogel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.320754716981131%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003egar (mg/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.400580551523948%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003c/strong\u003e\u003cstrong\u003eyaluronic acid (mg/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.41654571843251%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003cstrong\u003eeta potential (mV)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.851959361393323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003es\u003c/strong\u003e\u003cstrong\u003etatic viscosity (Pa\u0026middot;\u003c/strong\u003e\u003cstrong\u003es)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.57910014513788%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eG\u0026rsquo; (P\u003c/strong\u003e\u003cstrong\u003ea)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.57910014513788%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eG\u0026rsquo;\u0026rsquo; (P\u003c/strong\u003e\u003cstrong\u003ea)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.950653120464441%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.901306240928882%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLV A-HA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.320754716981131%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.400580551523948%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.41654571843251%\" valign=\"top\"\u003e\n \u003cp\u003e- 6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.44847605224964%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.982583454281568%\" valign=\"top\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.57910014513788%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.950653120464441%\" valign=\"top\"\u003e\n \u003cp\u003e7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.901306240928882%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMV A-HA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.320754716981131%\" valign=\"top\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.400580551523948%\" valign=\"top\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.41654571843251%\" valign=\"top\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.44847605224964%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.982583454281568%\" valign=\"top\"\u003e\n \u003cp\u003e6.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.57910014513788%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.950653120464441%\" valign=\"top\"\u003e\n \u003cp\u003e7.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.901306240928882%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHV A-HA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.320754716981131%\" valign=\"top\"\u003e\n \u003cp\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.400580551523948%\" valign=\"top\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.41654571843251%\" valign=\"top\"\u003e\n \u003cp\u003e-3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.44847605224964%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.982583454281568%\" valign=\"top\"\u003e\n \u003cp\u003e136.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.57910014513788%\" valign=\"top\"\u003e\n \u003cp\u003e16.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.950653120464441%\" valign=\"top\"\u003e\n \u003cp\u003e7.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.901306240928882%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003evh (Porcine)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.320754716981131%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.400580551523948%\" valign=\"top\"\u003e\n \u003cp\u003e0.16 [38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.41654571843251%\" valign=\"top\"\u003e\n \u003cp\u003e-9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.44847605224964%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.982583454281568%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.57910014513788%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.950653120464441%\" valign=\"top\"\u003e\n \u003cp\u003e7.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eGold nanoparticles characteristics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHydrodynamic diameter (nm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eZeta potential (mV)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConcentration in A-HA hydrogel (mg/mL)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100 - cITRATE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;32.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100 - bpei\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cspan type=\"Underline\" name=\"Emphasis\"\u003eMicroscope\u003c/span\u003e: An Axio Observer.Z1 m (Carl Zeiss, DE) inverted optical microscope was used to create optical signatures or caustics that enabled the identification and tracking of gold nanoparticles in the viscous media. This was possible through an increase in the coherence of the light by closing the aperture of the condenser to its minimum (1 mm), adding a green interference filter (Olympus, JP, centred on 550 nm, 45 nm bandwidth) and adjusting the microscope for K\u0026ouml;hler illumination; following the methodology described by Patterson and Whelan[\u003cspan\u003e26\u003c/span\u003e]. The microscope was also equipped with a stage-top incubation system (Incubator PM S1, Heating Insert P S1, Temp and CO\u003csub\u003e2\u003c/sub\u003e module S1, Carl Zeiss, DE), which was used to maintain the samples at 34˚C corresponding to the physiological mid-vitreous temperature, and is within the temperature range for characterising ocular endotamponades [\u003cspan\u003e29\u003c/span\u003e], [\u003cspan\u003e30\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003eMethods\u003c/h2\u003e\n \u003cp\u003e\u003cspan type=\"Underline\" name=\"Emphasis\"\u003eAgar-hyaluronic acid hydrogel synthesis\u003c/span\u003e: hydrogels were synthesised following the protocol described by Thakur et al.[\u003cspan\u003e14\u003c/span\u003e]. Three hydrogels with different viscosities were synthesised by adding different concentrations of agar and hyaluronic acid (high molecular weight) to 1X boiling phosphate buffer saline (PBS). For the high viscous (HV) hydrogel, hyaluronic acid was at a concentration of 5 mg/mL and agar at 4 mg/mL; for the medium viscous (MV) hydrogel, hyaluronic acid was at a concentration of 2.21 mg/mL and agar at 1.8 mg/mL; and for the low viscous (LV) hydrogel, hyaluronic acid was at a concentration of 0.7 mg/mL and agar at 0.95 mg/mL. The three solutions were magnetically stirred at 100˚C for 1 hour, after which the gels were cooled down at room temperature overnight before being characterized or used for NP tracking.\u003c/p\u003e\n \u003cp\u003e\u003cspan type=\"Underline\" name=\"Emphasis\"\u003eDiffusion of gold nanoparticles in hydrogels\u003c/span\u003e: The diffusion coefficient of positively-charged 100 nm AuNP and 50 nm, 100 nm and 200 nm diameter negatively-charged AuNP were evaluated at 34\u0026deg;C. The samples were vortexed (with a Vortex-Fisherbrand\u0026reg; mixer) for 15 s and ultrasonicated (with a S-Series Heated Ultrasonic Bath Fisherbrand\u0026reg;) for 1 minute before aliquoting a volume of 50 \u0026micro;L onto a microscope slide (76x26 mm and 0.2 mm cavity depth). The samples were incubated on the microscope stage-top incubation system at 34\u0026deg;C for 10 minutes prior to being analysed under an inverted optical microscope, to ensure a consistent temperature throughout the sample. Videos were recorded using a x 40 objective and a monochromatic camera (Axiocam305, Carl Zeiss) with a spatial resolution of 0.086 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e for one pixel and a temporal resolution of 40 fps. A total of 30 nanoparticles were tracked for each nanoparticle size in each of the hydrogels, in order to randomise the nanoparticle distribution across the hydrogels. For the preliminary quantitative analysis and investigation of the nanoparticle surface charge, six nanoparticles, randomly selected from the field of view, were tracked for each set of conditions and the mean value of diffusion coefficient calculated. The same process was repeated in deionized water as a control.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003e\u003cspan type=\"Underline\" name=\"Emphasis\"\u003eData analysis\u003c/span\u003e:\u003c/h2\u003e\n \u003cp\u003eAn assumption of Brownian motion for a random walk of particles in a suspended fluid leads to the following definition of the diffusion coefficient (\u003cem\u003eD\u003c/em\u003e):\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(D= \\frac{{k}_{b} T}{4d\\pi nr}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e [\u003cspan\u003e1\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eIn the equation \u003cem\u003ek\u003c/em\u003e\u003csub\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sub\u003e is the Boltzmann constant, \u003cem\u003eT\u003c/em\u003e is the temperature, \u003cem\u003ed\u003c/em\u003e is the dimensionality (2D in this case), \u003cem\u003en\u003c/em\u003e is the viscosity of the diffusive media and \u003cem\u003er\u003c/em\u003e is the radius of the particle. This is known as the Stokes-Einstein relation because it combines Stokes\u0026rsquo; Law and Einstein\u0026rsquo;s description of diffusion. Particle motion has been widely characterised by the mean squared displacement (MSD) of the particle and, considering a two-dimensional system, is expressed as [\u003cspan\u003e31\u003c/span\u003e], [\u003cspan\u003e32\u003c/span\u003e]:\u003c/p\u003e\u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(MSD=\\frac{1}{N-n}{\\sum _{i=0}^{N-n} \\left(\\right({x}_{i+n}-{x}_{i})}^{2}+{({y}_{i+n}-{y}_{i})}^{2})\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e [\u003cspan\u003e2\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eWhere \u003cem\u003ex\u003c/em\u003e and \u003cem\u003ey\u003c/em\u003e correspond to the particle coordinates for each \u003cem\u003ei\u003c/em\u003e\u003csup\u003e\u003cem\u003eth\u003c/em\u003e\u003c/sup\u003e step in \u003cem\u003en\u003c/em\u003e total frames and hence can be measured experimentally.\u003c/p\u003e\u003cp\u003eVideos with a minimum of 50 frames and a maximum of 100 frames, depending on the speed of a particle and its motion perpendicular to the focal plane of the microscope, were recorded and analysed using the ImageJ software plugin TrackMate[\u003cspan\u003e33\u003c/span\u003e]. This provided information on the \u003cem\u003ex\u003c/em\u003e and \u003cem\u003ey\u003c/em\u003e positions of the nanoparticle for each frame. These coordinates provided the path of the NPs over time, from which values of their mean squared displacement (MSD) and experimental diffusion coefficient were determined, as there is a linear relation between the mean squared displacement and the diffusion coefficient (D), for Brownian motion, for a specific time lag (\u003cspan\u003e\u003cspan\u003e\\(\\varDelta t):\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cdiv\u003e\u003cp\u003e\u003cspan\u003e\u0026nbsp;\u003cspan\u003e\\(MSD= 2 d D \\varDelta t\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e [\u003cspan\u003e3\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003cp\u003eTo better characterise the nanoparticle distribution through the hydrogels, the area containing the path of a nanoparticle was evaluated and compared to the values of their diffusion coefficient. The path of a nanoparticle through 50 frames was plotted and enclosed in the smallest possible convex hull or polygon, which was found using a geometric algorithm.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cp\u003eInitial qualitative visualization of the agar-hyaluronic acid hydrogels, with the microscope set up to observe caustics, revealed a detailed heterogeneous nature of the synthetic hydrogels (Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e). This was confirmed by analysis of nanoparticle motion, in which the nanoparticles were found to behave differently in different local environments within the hydrogels. NPs were found to diffuse faster in environments with a high-water content (aqueous phase) and slower when interacting with the agar (gel phase) (videos attached in supplementary information).\u003c/p\u003e\n\u003cp\u003eTo validate these qualitative findings, we performed a preliminary quantitative analysis by tracking six independent nanoparticles, using the label-free caustics optical technique, in low, medium and high viscosity solutions that were designed to represent the qualitatively characterized environments, identified from Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e and described above, i.e., an aqueous phase, gel phase and intermediate phase. The experimental diffusion coefficients of the nanoparticles in each local environment are plotted against the static bulk viscosity for each hydrogel (characterization in supplementary information) and compared to that of deionized water, which was used as a control, in Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e. To investigate the effect of nanoparticle surface charge on nanoparticle diffusion across the synthetic hydrogels, citrate-capped (negative) and branched polyethyleneimine (BPEI)-capped (positive) 100 nm diameter gold nanoparticles were tracked as described above using the caustic technique (Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eConsidering that the presence of hyaluronic acid will give the hydrogels a partial negative charge, a difference in diffusion would be expected for differently charged nanoparticles [\u003cspan\u003e34\u003c/span\u003e]. However, the results in Fig. \u003cspan\u003e3\u003c/span\u003e show no definitive difference between the diffusion of positively (closed green symbols) and negatively (open red symbols) charged AuNPs across any of the gels. This was explained by the low zeta potential values of the hydrogels, characterizing these as neutral (Table \u003cspan\u003e1\u003c/span\u003e), and the low nanoparticle concentration present in the hydrogels. More interestingly the values of diffusion coefficient were found to range from 10\u003csup\u003e\u0026minus;\u0026thinsp;12\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e m\u003csup\u003e2\u003c/sup\u003e/s for both, negatively and positively-charged 100 nm diameter AuNPs in the low and medium viscous hydrogels (Fig. \u003cspan\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv\u003eDeionized water was used as a control with a viscosity three orders of magnitude less than the hydrogel with lowest viscosity (approximately 0.001 Pa\u0026middot;s compared to 3 Pa\u0026middot;s). The medium and high viscosity hydrogels had viscosities one and two orders of magnitude higher than the low viscosity hydrogel, (i.e., approximately 40 and 400 Pa\u0026middot;s respectively). In the low and medium viscosity hydrogels, some of the tracked particles behaved in the same manner as those in the deionised water and their diffusion coefficients values were similar (approximately 10\u003csup\u003e\u0026minus;\u0026thinsp;12\u003c/sup\u003e m\u003csup\u003e2\u003c/sup\u003e/s). These nanoparticles had a random walk which led them away from the location at which they were first observed, as shown in the top inset in Fig. \u003cspan\u003e3\u003c/span\u003e. However, some particles moved randomly around a single location, essentially dancing on the spot (see bottom inset in Fig. \u003cspan\u003e3\u003c/span\u003e); these nanoparticles had values for their diffusion coefficient of about 10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e m\u003csup\u003e2\u003c/sup\u003e/s. This behaviour occurred in all three hydrogels with the diffusion coefficient decreasing in value with increasing viscosity, implying that the high viscosity inhibited the motion of the particles and constrained them from moving away from a given location. The observation that both of these types of behaviour, i.e. wandering away from a location and dancing on the spot, occurred the same in low and medium viscosity hydrogels implies that these hydrogels were heterogeneous with same zones that were largely aqueous solution and others that were largely gel, consisting of a polymeric matrix that inhibited nanoparticle motion. There is also evidence of nanoparticles diffusing in intermediate zones with properties that lie somewhere between those of the gel and aqueous solution, see middle inset in Fig. \u003cspan\u003e3\u003c/span\u003e, which shows a typical path of particles attempting to move away from a location but repeatedly returning to it. These different behaviours within the low and medium viscosity hydrogels were not observed in the high viscosity hydrogel which implied that it was a largely homogeneous gel.\u003c/div\u003e\n\u003cp\u003eFollowing this preliminary investigation, a more detailed study was performed in which at least 30 randomly-selected nanoparticles were tracked in each sample with the aim of understanding the distribution of nanoparticle behavior in the hydrogels. Since the charge of the nanoparticles had been demonstrated to have no influence on their diffusion under these conditions, only citrate-capped gold nanoparticles with diameters of 50 nm, 100 nm and 200 nm were tested to investigate the effect of particle size on diffusion behavior in the hydrogels. These sizes were chosen because they are clinically relevant to back-of-the-eye drug delivery [\u003cspan\u003e35\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThe values of the diffusion coefficient are shown in Figs.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e to \u003cspan\u003e6\u003c/span\u003e as a function of the area of the convex hull enclosing its path for each tracked particle for the three hydrogels with low, medium and high viscosity. In each case a linear regression line was fitted to the data. The results confirm that the nanoparticles diffuse faster in gels with higher water content probably because there is less polymeric matrix (gel) to constrain their movement.\u003c/p\u003e\n\u003cp\u003eDiffusion values in the high viscosity hydrogel were similar for all diameters of nanoparticles, with diffusion values in the range of 10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e m\u003csup\u003e2\u003c/sup\u003e/s and lower, while the areas of the corresponding convex hulls were all in the range of 10\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e m\u003csup\u003e2\u003c/sup\u003e, suggesting that nanoparticle size did not affect nanoparticle diffusion in the hydrogel and that the motion of all nanoparticles was hindered by the polymeric matrix (red squares in Figs.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e to \u003cspan\u003e6\u003c/span\u003e). The values of correlation coefficient at this level of viscosity are in the range 0.9 to 0.65, decreasing with increasing particle diameter, implying that the correlation between speed and area enclosed by the path decreases with particle diameter.\u003c/p\u003e\n\u003cp\u003eHowever, the behavior of the nanoparticles in the low and medium viscosity hydrogels was found to be size dependent, with the range of values for both diffusion coefficient and convex hull area remaining approximately constant but reducing in absolute value with increasing particle diameter which implies that larger particles move more slowly and cover a smaller area. The correlation between the diffusion coefficient and the area of the convex hulls is positive and close to one (0.94 to 0.99) for both the medium and low viscosity hydrogels. However, the distribution of the data points in the graphs (Figs.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e to \u003cspan\u003e6\u003c/span\u003e) for these hydrogels varies with particle diameter from an approximately uniform distribution for the 200 nm diameter particles to a bimodal distribution for the 100 nm and 50 nm diameter particles with a tendency for more data points at the higher end of the range, with diffusive values close to those in water. The bimodal distribution is perhaps more evident for the data from medium viscosity hydrogel (graph b) in Figs.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e to \u003cspan\u003e6\u003c/span\u003e). It is likely that the high viscosity hydrogel was relatively homogeneous with a uniform distribution of the polymeric matrix that inhibited the motion of all of nanoparticles; whereas the medium and low viscosity hydrogels were progressively less homogeneous with zones of low-density polymeric matrix that allowed relatively uninhibited motion and zones of high-density matrix that inhibited motion. An idealized structure of this nature would generate the bimodal distributions seen in Figs.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e to \u003cspan\u003e6\u003c/span\u003e with the bimodality likely more pronounced in the medium viscosity hydrogel.\u003c/p\u003e\n\u003cp\u003eThe results demonstrated that label-free, real-time tracking of particles provides a powerful tool for characterizing the dynamics of nanoparticles interactions in heterogeneous polymeric hydrogels and to evaluate the degree to which nanoparticle size affects their behavior within the hydrogels. The resultant understanding should inform the development of nanoparticle- based drug delivery using \u003cem\u003ein vitro\u003c/em\u003e models when combined with the findings of previous work reporting nanoparticle diffusion to be strongly affected by electrostatic and van der Waals forces, and controlled by the ionic strength of the media [\u003cspan\u003e36\u003c/span\u003e] as well as by the impact of the protein corona formation on the diffusion of nanoparticles [\u003cspan\u003e37\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe heterogenous nature of agar-hyaluronic acid hydrogels, which have been previously validated as \u003cem\u003ein vitro\u003c/em\u003e substitutes for vitreous humour, have been observed and quantified using a standard optical microscope set up to generate near-coherent light and reveal optical signatures known as caustics. The caustics generated by nanoparticles have been used in a label-free tracking technique to obtain experimental values of their diffusion coefficient in various local environments and for a range of particle diameters. It was found that the charge on the particles did not influence their diffusion through the hydrogels; however, both the diameter of the particles and the structure of the hydrogel affected the diffusion characteristics of the particles. NPs with diameters of 50, 100 and 200 nm moved progressively more slowly and within a smaller area. High viscosity hydrogels were observed to generate consistent behaviour of the nanoparticles implying a large homogeneous structure of polymeric matrix, or gel that uniformly inhibited particle motion, whereas medium and low viscosity hydrogels generated bimodal distributions of particle diffusion coefficients as functions of the area enclosed by the particle\u0026rsquo;s path suggesting a heterogeneous hydrogel with zones of low and high density polymeric matrix in which the particles move more or less freely, respectively.\u003c/p\u003e \u003cp\u003eThe results indicate that the single-particle label-free nanoparticle tracking technique is a powerful tool to characterise the diffusion and transport of nanoparticles in heterogeneous hydrogels that can be used as \u003cem\u003ein vitro\u003c/em\u003e substitutes for vitreous humour. Hence, this technique has the potential to become an indispensable method in the development of pre-clinical models to optimise nanoparticle-based drug delivery systems for the treatment of retinal diseases, and to better characterise their pharmacokinetics profiles. These advances could help elucidate the variables that influence the diffusive behavior of nanoparticles leading to the optimization of drug delivery to the retina.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Doctoral Network in Technologies for Healthy Aging; and the Engineering and Physical Sciences Research Council [grant numbers EP/R024839/1; EP/S012265/1].\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eMLL performed data curation, analysis, and writing of first draft; VK advised on vitreous humour substitutes, EAP advised on data analysis and microscopy technique, JMC PI and grant holder. All authors contributed to manuscript edition and writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available in the [DataCat: The Research Data Catalogue] repository, [ https://doi.org/10.17638/datacat.liverpool.ac.uk%2F2603 ].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eM. Schmoker, \u0026lsquo;Time to Focus\u0026rsquo;, \u003cem\u003ePrincipal Leadership\u003c/em\u003e, vol. 13, no. 3, pp. 18\u0026ndash;21, 2012, Accessed: Jan. 14, 2024. [Online]. 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T. Cook, and D. Y. S. Chau, \u0026lsquo;Diffusion through the ex vivo vitreal body \u0026ndash; Bovine, porcine, and ovine models are poor surrogates for the human vitreous\u0026rsquo;, \u003cem\u003eInt J Pharm\u003c/em\u003e, vol. 550, no. 1\u0026ndash;2, pp. 207\u0026ndash;215, 2018, doi: 10.1016/j.ijpharm.2018.07.070.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"retinal diseases, in vitro models, hydrogels, nanomedicine, drug delivery, label-free tracking","lastPublishedDoi":"10.21203/rs.3.rs-3997364/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3997364/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNanomedicine has the potential to increase the biostability of drugs to treat retinal diseases, improving their performance and decreasing the required number of intravitreal injections. However, accurate pharmacokinetic studies of these nanoparticle-drug conjugates, nanoparticle motion across the vitreous humour and interaction with the retinal cell layers still need to be investigated.\u003c/p\u003e \u003cp\u003eExisting nanoparticle tracking techniques require fluorescent labels, which can impact cytotoxicity, nanoparticles\u0026rsquo; motion, protein interactions, and cell internalization. In this study, a real-time label-free tracking technology, for single nanoparticles in an optical microscope based on the optical phenomena of caustics, was used to characterise the diffusion of nanoparticles in agar-hyaluronic acid hydrogels, previously validated as vitreous humour substitutes for \u003cem\u003ein vitro\u003c/em\u003e models.\u003c/p\u003e \u003cp\u003eThe results demonstrated that the diffusion of nanoparticles through these hydrogels was heterogeneous and that nanoparticle size had an important role in nanoparticle distribution across and within \u003cem\u003ein vitro\u003c/em\u003e vitreous substitutes. These findings suggest that nanoparticle diameter is a critical parameter for designing novel therapeutics for retinal diseases. Moreover, nanoparticle charge did not affect nanoparticle diffusion or distribution in these synthetic hydrogels. The use of caustics in optical microscopy has been demonstrated to be a reproducible, inexpensive technique for screening novel therapeutics in eye \u003cem\u003ein vitro\u003c/em\u003e models.\u003c/p\u003e","manuscriptTitle":"Diffusion of Nanoparticles in Heterogeneous Hydrogels as Vitreous Humour Substitutes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 09:36:20","doi":"10.21203/rs.3.rs-3997364/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-14T05:45:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-10T23:45:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-10T15:52:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-30T22:41:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-30T03:00:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"614c1c1c-f43a-40eb-ab73-50cbe6f91517","date":"2024-04-29T17:24:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10126f8e-b8f3-45b2-bf71-3826e7ea30f8","date":"2024-04-28T14:27:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"886ab60c-41a1-4802-8f3f-1c1ffbc1a441","date":"2024-04-27T23:15:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2ebc5369-715a-4295-aa9c-6165d2349645","date":"2024-04-27T17:42:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80225593-dd93-4993-8ca0-5c292c584534","date":"2024-04-27T17:41:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-22T15:47:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-13T03:16:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83d9b14d-b7f4-4f3b-8174-9a766b98b5df","date":"2024-03-13T01:40:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4c38a4a3-0b3c-4c2b-b561-bdde0e6ae8e2","date":"2024-03-12T11:02:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-12T09:45:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-12T09:39:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-07T15:02:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-07T14:54:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-02-28T17:24:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1bed3b67-7dae-4715-abb3-5537763b049e","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:07:51+00:00","versionOfRecord":{"articleIdentity":"rs-3997364","link":"https://doi.org/10.1038/s41598-024-68267-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-07-29 15:58:22","publishedOnDateReadable":"July 29th, 2024"},"versionCreatedAt":"2024-03-11 09:36:20","video":"","vorDoi":"10.1038/s41598-024-68267-0","vorDoiUrl":"https://doi.org/10.1038/s41598-024-68267-0","workflowStages":[]},"version":"v1","identity":"rs-3997364","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3997364","identity":"rs-3997364","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}