Multiangle Dynamic Light Scattering Research Articles

Pharmaceutical Applications and Advances with Zetasizer: An Essential Analytical Tool for Size and Zeta Potential Analysis

: Zetasizer is an advanced device that measures various properties of particles or molecules suspended in a liquid medium. It is extensively used for evaluating the size of nanoparticles, colloids, and biomolecular particles, and for determining particle charge. There are several analytical techniques by which the size, zeta potential, and molecular weight can be determined, like Dynamic Light Scattering (DLS) that measures the size of particles in dispersed systems, which can range from sub-nanometers to several micrometers in diameter. Electrophoretic Light Scattering (ELS) analyzes the mobility and charge of particles, also known as the zeta potential. Static Light Scattering (SLS) determines the molecular weight of particles in a solution. The Zetasizer is part of the Zetasizer Advance range of benchtop systems available for laboratory use. The Zetasizer Ultra model offers unique measurement capabilities, such as Multi-angle Dynamic Light Scattering (MADLS) and particle concentration. These features offer a deeper understanding of samples, making the Zetasizer a vital instrument in numerous scientific and industrial applications. In this review, we have discussed Zetasizer’s principles for the determination of particle size, zeta potential, and molecular weight, along with its qualification and applications in different formulations.

In-Depth Comparison of Adeno-Associated Virus Containing Fractions after CsCl Ultracentrifugation Gradient Separation.

Recombinant adeno-associated viruses (rAAVs) play a pivotal role in the treatment of genetic diseases. However, current production and purification processes yield AAV-based preparations that often contain unwanted empty, partially filled or damaged viral particles and impurities, including residual host cell DNA and proteins, plasmid DNA, and viral aggregates. To precisely understand the composition of AAV preparations, we systematically compared four different single-stranded AAV (ssAAV) and self-complementary (scAAV) fractions extracted from the CsCl ultracentrifugation gradient using established methods (transduction efficiency, analytical ultracentrifugation (AUC), quantitative and digital droplet PCR (qPCR and ddPCR), transmission electron microscopy (TEM) and enzyme-linked immunosorbent assay (ELISA)) alongside newer techniques (multiplex ddPCR, multi-angle light-scattering coupled to size-exclusion chromatography (SEC-MALS), multi-angle dynamic light scattering (MADLS), and high-throughput sequencing (HTS)). Suboptimal particle separation within the fractions resulted in unexpectedly similar infectivity levels. No single technique could simultaneously provide comprehensive insights in the presence of both bioactive particles and contaminants. Notably, multiplex ddPCR revealed distinct vector genome fragmentation patterns, differing between ssAAV and scAAV. This highlights the urgent need for innovative analytical and production approaches to optimize AAV vector production and enhance therapeutic outcomes.

In vitro and in vivo characterization of human serum albumin-based PEGylated nanoparticles for BDNF and NT3 codelivery

The utilization of neurotrophins in medicine shows significant potential for addressing neurodegenerative conditions, such as age-related macular degeneration (AMD). However, the therapeutic use of neurotrophins has been restricted due to their short half-life. Here, we aimed to synthesize PEGylated nanoparticles based on electrostatic-driven interactions between human serum albumin (HSA), a carrier for adsorption; neurotrophin-3 (NT3); and brain-derived neurotrophic factor (BDNF). Electrophoretic (ELS) and multi-angle dynamic light scattering (MADLS) revealed that the PEGylated HSA-NT3-BDNF nanoparticles ranged from 10 to 430 nm in diameter and exhibited a low polydispersity index (<0.4) and a zeta potential of −8 mV. Based on microscale thermophoresis (MST), the estimated dissociation constant (Kd) from the HSA molecule of BDNF was 1.6 μM, and the Kd of NT3 was 732 μM. The nanoparticles were nontoxic toward ARPE-19 and L-929 cells in vitro and efficiently delivered BDNF and NT3. Based on the biodistribution of neurotrophins after intravitreal injection into BALB/c mice, both nanoparticles were gradually released in the mouse vitreous body within 28 days. PEGylated HSA-NT3-BDNF nanoparticles stabilize neurotrophins and maintain this characteristic in vivo. Thus, given the simplicity of the system, the nanoparticles may enhance the treatment of a variety of neurological disorders in the future.

Mechanisms of Fibroblast Growth Factor 21 Adsorption on Macroion Layers: Molecular Dynamics Modeling and Kinetic Measurements.

Molecular dynamic modeling and various experimental techniques, including multi-angle dynamic light scattering (MADLS), streaming potential, optical waveguide light spectroscopy (OWLS), quartz crystal microbalance with dissipation (QCM), and atomic force microscopy (AFM), were applied to determine the basic physicochemical parameters of fibroblast growth factor 21 in electrolyte solutions. The protein size and shape, cross-section area, dependence of the nominal charge on pH, and isoelectric point of 5.3 were acquired. These data enabled the interpretation of the adsorption kinetics of FGF 21 on bare and macrocation-covered silica investigated by OWLS and QCM. It was confirmed that the protein molecules irreversibly adsorbed on the latter substrate, forming layers with controlled coverage up to 0.8 mg m-2, while their adsorption on bare silica was much smaller. The viability of two cell lines, CHO-K1 and L-929, on both bare and macrocation/FGF 21-covered substrates was also determined. It is postulated that the acquired results can serve as useful reference systems for designing complexes that can extend the half-life of FGF 21 in its active state.

Evaluation and Screening of Biopharmaceuticals using Multi-Angle Dynamic Light Scattering.

Biopharmaceuticals are large, complex and labile therapeutic molecules prone to instability due to various factors during manufacturing. To ensure their safety, quality and efficacy, a wide range of critical quality attributes (CQAs) such as product concentration, aggregation, particle size, purity and turbidity have to be met. Size exclusion chromatography (SEC) is the gold standard to measure protein aggregation and degradation. However, other techniques such as dynamic light scattering (DLS) are employed in tandem to measure the particle size distribution (PSD) and polydispersity of biopharmaceutical formulations. In this study, the application of multi-angle dynamic light scattering (MADLS) was evaluated for the determination of particle size, particle concentration and aggregation in 3 different protein modalities, namely bovine serum albumin (BSA) and two biopharmaceuticals including a monoclonal antibody (mAb) and an enzyme. The obtained calibration curve (R2 > 0.95) for the particle number concentration of the 3 proteins and the observed correlation between MADLS and SEC (R2 = 0.9938) for the analysis of aggregation in the enzyme can be employed as a 3-in-1 approach to assessing particle size, concentration and aggregation for the screening and development of products while also reducing the number of samples and experiments required for analysis prior to other orthogonal tests.

A precise nanoparticle quantification approach using microfluidics and single-particle tracking

Due to the limited available amounts of components, especially of low water-soluble drugs, formulation development is often impeded by a careful characterization. The use of small batch sizes might solve this problem but requires also adequate analytics. Concentration of nanoparticulate formulations lack straightforward evaluation techniques. In this work, a precise and straight-forward method is established to individually count nanoparticles. A microfluidic chip with known dimensions was used to visualize single particles flowing through the channel (single-particle tracking (SPT)). A sequence of 10,000 images was analyzed to determine the mean particle concentration. The proposed method is independent of the particular flow rate through the microfluidic chip as long as there is no particle overlap and a continuous exchange of particles. Monodisperse Rhodamine B labeled poly (methyl methacrylate) (PMMA) nanoparticles (267.03 ± 9.79 nm) were used as a model and reference particle system for the evaluation process of SPT allowing for a gravimetric determination based on density analysis using analytical ultracentrifugation (AUC) and gas pycnometry. The SPT method was evaluated and compared to other techniques used for concentration measurement. Both approaches (SPT and gravimetry) provide very similar and comparable results indicating the applicability of this novel quantification approach. In contrast, multi angle dynamic light scattering (MADLS) could not yield a precision as good as SPT (number density rel. standard deviation SD nSPT = 11.67%; SD nMADLS = 49.45%). Finally, the measured particle number concentrations can be realized in low concentration ranges (0.8249 μg mL−1 – 0.08249 μg mL−1) not accessible for MADLS (0.08249 mg mL−1 – 0.008249 mg mL−1) and gravimetric analysis.

Measuring particle concentration of multimodal synthetic reference materials and extracellular vesicles with orthogonal techniques: Who is up to the challenge?

The measurement of physicochemical properties of polydisperse complex biological samples, for example, extracellular vesicles, is critical to assess their quality, for example, resulting from their production and isolation methods. The community is gradually becoming aware of the need to combine multiple orthogonal techniques to perform a robust characterization of complex biological samples. Three pillars of critical quality attribute characterization of EVs are sizing, concentration measurement and phenotyping. The repeatable measurement of vesicle concentration is one of the key‐challenges that requires further efforts, in order to obtain comparable results by using different techniques and assure reproducibility. In this study, the performance of measuring the concentration of particles in the size range of 50–300 nm with complementary techniques is thoroughly investigated in a step‐by step approach of incremental complexity. The six applied techniques include multi‐angle dynamic light scattering (MADLS), asymmetric flow field flow fractionation coupled with multi‐angle light scattering (AF4‐MALS), centrifugal liquid sedimentation (CLS), nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), and high‐sensitivity nano flow cytometry (nFCM). To achieve comparability, monomodal samples and complex polystyrene mixtures were used as particles of metrological interest, in order to check the suitability of each technique in the size and concentration range of interest, and to develop reliable post‐processing data protocols for the analysis. Subsequent complexity was introduced by testing liposomes as validation of the developed approaches with a known sample of physicochemical properties closer to EVs. Finally, the vesicles in EV containing plasma samples were analysed with all the tested techniques. The results presented here aim to shed some light into the requirements for the complex characterization of biological samples, as this is a critical need for quality assurance by the EV and regulatory community. Such efforts go with the view to contribute to both, set‐up reproducible and reliable characterization protocols, and comply with the Minimal Information for Studies of Extracellular Vesicles (MISEV) requirements.

Nanoparticle number concentration measurements by multi-angle dynamic light scattering

We present the use of Multi-angle Dynamic Light Scattering (MADLS®) for the measurement of nanoparticle concentration. We describe the theory of the method and its application to nanoparticles made of gold, silica and polystyrene, with diameters ranging from 30 to 400 nm, and demonstrate some of the limitations with particles of sizes 500 nm and above. We evaluate the method accuracy, linearity and reproducibility, as well as the operational nanoparticle concentration and size range. We show that the concentration working range depends on the material’s optical properties, size and concentration. Here it is shown that the level of accuracy that can be expected for the concentration of particles is typically within 50% of the nominal value across a range of materials and sizes and, for some samples, within 20%. The repeatability of the measurements, in terms of relative standard deviation, is typically below 30%. A linearity of within 40% across a concentration range of 3·108 to 2·1011 mL−1 for concentration measurements was also demonstrated by using gold nanoparticles and gravimetric dilutions for method validation. Overall, we show that MADLS® is a rapid and straightforward method for the reproducible measurement of particle concentration, as well as size, requiring minimal sample preparation, without the need to calibrate using a pre-determined concentration series, and applicable to a broad range of materials. These features make it an ideal tool to support both development and quality control of particle materials for a broad range of applications.

Interlaboratory comparison of nanoparticle size measurements between NMIJ and NIST using two different types of dynamic light scattering instruments

The question of how to relate particle sizes measured using a fixed-angle dynamic light scattering (DLS) instrument with those measured using a multi-angle DLS instrument is addressed. A series of nearly monodisperse polystyrene latex (PSL) particles with nominal diameters of 100 nm, 70 nm, 50 nm, and 30 nm were measured using two different types of DLS instruments: one owned by the National Metrology Institute of Japan (NMIJ) of the multi-angle type and the other owned by the National Institute of Standards and Technology (NIST) of the fixed-angle type. The mean particle size of the PSL particles was measured using the multi-angle-type instrument at various scattering angles and at various concentrations of particle suspension. These data were used to establish the functional dependence of the measured particle size on the scattering angle and particle concentration through the least-squares fitting method. The established function was then used to predict the mean particle sizes that would have been obtained if the same scattering angle and particle concentrations as those used at NIST had been selected at NMIJ. The mean particle sizes obtained at NIST and at NMIJ agreed quite well for all four PSL particle samples after compensating for the angle and concentration differences. The result of this study clearly demonstrates that consideration for the dependence of measured particle sizes on the scattering angle and particle concentration is crucial in intra-method comparisons of mean particle sizes obtained using DLS.

Multi-angle dynamic light scattering analysis based on successive updating of the angular weighting

The angular weighting coefficient is key to accurate particle size distribution (PSD) measurement using multiangle dynamic light scattering (MDLS). However, determining the weighting coefficient is affected by the noise in the measured MDLS data. In this paper, a novel successive updating of the angular weighting (AWSU) method is proposed. By using information character weighting, the angular weighting coefficient and the character weighting matrix are updated once with each additional angle. The effect of autocorrelation function (ACF) denoising and information extraction is improved by using information character weighting step-by-step. The results for broad unimodal and closely-spaced bimodal PSDs demonstrate the effectiveness of this method. Compared with another routinely used inversion method, it is found that the increase in PSD information retrieved from MDLS depends not only on increasing the number of angles, but also on the calculation of the angular weightings. An accurate weighting algorithm can reduce the number of scattering angles required. Using the AWSU method for PSD recovery with 4 scattering angles can give better results than the usual method with 6 scattering angles. It is also found that the AWSU method not only improves the accuracy of the weightings, but it also contributes directly to the PSD recovery by reconstructing the ACF with the PSD obtained by the weighted inversion. The combination of these two contributions not only reduces the number of scattering angles needed, but also keeps the PSD recovery results from getting worse because of excessive scattering angles.

Bovine beta-casein micelles as delivery systems for hydrophobic flavonoids

The milk protein β-casein (β-CN) is an intrinsically unstructured amphiphilic protein that self-assembles into micelles. Naringenin is the main hydrophobic flavanone in grapefruit and has several beneficial biological effects: it exhibits, for example, antioxidant, anticancer and anti-inflammatory activity. This paper shows that naringenin can be encapsulated in β-CN micelles. Fluorescence spectroscopy, molecular docking modelling, dynamic light scattering (DLS), static light scattering (SLS) and isothermal titration calorimetry (ITC) were applied to characterize the effect of naringenin on the protein association behavior and properties of the resulting micelles. Naringenin binds to β-CN at both pH 7 and pH 2, promotes the formation of micelles with a well-defined size distribution and stabilizes the micelles. It was found that naringenin-containing β-CN micelles have a lower critical micelle concentration (CMC) and a larger aggregation number (Nagg) compared to pure β-CN micelles. SLS and multi-angle DLS results suggest considerable differences between the structures of pure β-CN micelles and naringenin-containing β-CN micelles. In the presence of naringenin spherical micelles were formed with a relatively loose core (“hollow sphere”), while the pure β-CN micelles are smaller and seem to be elliptic. Notably, by uptake of naringenin in the micelles, the concentration of naringenin in aqueous solution could be raised considerably. These findings lead to the conclusion that β-CN micelles are very promising as effective delivery nano-vehicles for hydrophobic bioactive compounds.

A regularization algorithm for estimating the multimodal size distribution of nanoparticles from multiangle dynamic light scattering

The multiangle dynamic light scattering (MDLS) technique provides more robust, reproducible, and accurate particle size distributions (PSDs) than single-angle dynamic light scattering. However, in MDLS, the determination of peak locations is difficult but significant, particularly for multimodal distributions. In this paper, a self-adaptive algorithm, the iterative recursion nonnegative Tikhonov–Phillips–Twomey (IRNNT-PT) algorithm, is proposed for the estimation of the PSD from MDLS measurements. This algorithm optimizes the weighting coefficients, distinguishes features of PSDs and chooses the optimal inversion method from two regularization algorithms self-adaptively. Numerical simulations and experimental results for unimodal and multimodal distributions are presented to demonstrate both the validity and noise immunity of the IRNNT-PT algorithm, and demonstrate that the proposed algorithm can be well applied to reconstruct PSDs from MDLS measurements.

Angular dependence of multiangle dynamic light scattering for particle size distribution inversion using a self-adapting regularization algorithm

The multiangle dynamic light scattering (MDLS) technique can better estimate particle size distributions (PSDs) than single-angle dynamic light scattering. However, determining the inversion range, angular weighting coefficients, and scattering angle combination is difficult but fundamental to the reconstruction for both unimodal and multimodal distributions. In this paper, we propose a self-adapting regularization method called the wavelet iterative recursion nonnegative Tikhonov–Phillips–Twomey (WIRNNT-PT) algorithm. This algorithm combines a wavelet multiscale strategy with an appropriate inversion method and could self-adaptively optimize several noteworthy issues containing the choices of the weighting coefficients, the inversion range and the optimal inversion method from two regularization algorithms for estimating the PSD from MDLS measurements. In addition, the angular dependence of the MDLS for estimating the PSDs of polymeric latexes is thoroughly analyzed. The dependence of the results on the number and range of measurement angles was analyzed in depth to identify the optimal scattering angle combination. Numerical simulations and experimental results for unimodal and multimodal distributions are presented to demonstrate both the validity of the WIRNNT-PT algorithm and the angular dependence of MDLS and show that the proposed algorithm with a six-angle analysis in the 30–130° range can be satisfactorily applied to retrieve PSDs from MDLS measurements.

Information-weighted constrained regularization for particle size distribution recovery in multiangle dynamic light scattering

In particle size measurement with dynamic light scattering (DLS), it is difficult to get an accurate recovery of a bimodal particle size distribution (PSD) with a peak position ratio less than ~2:1, especially when large particles (>350nm) are present. This is due to the inherent noise in the autocorrelation function (ACF) data and the scarce utilization of PSD information during the inversion process. In this paper, the PSD information distribution in the ACF data is investigated. It was found that the initial decay section of the ACF contains more information, especially for a bimodal PSD. Based on this, an information-weighted constrained regularization (IWCR) method is proposed in this paper and applied in multiangle DLS analysis for bimodal PSD recovery. By using larger (or smaller) coefficients for weighting the ACF data, more (or less) weight can then be given to the initial part of the ACF. In this way, the IWCR method can enhance utilization of the PSD information in the ACF data, and effectively weaken the effect of noise at large delay time on PSD recovery. Using this method, bimodal PSDs (with nominal diameters of 400:608 nm, 448:608 nm, 500:600 nm) were recovered successfully from simulated data and it appears that the IWCR method can improve the recovery resolution for closely spaced bimodal particles. Results of the PSD recovery from experimental DLS data confirm the performance of this method.

Weighting inversion of dynamic light scattering based on particle-size information distribution character

In particle sizing with dynamic light scattering (DLS) technique, the determination of particle size distribution (PSD), via inversing the autocorrelation function (ACF) of scattering light, is usually limited by the inherently low particle size information in ACF data and, the lack of targeted inversion on the noise restriction and the particle size information utilization. For the ACF data in DLS measurement, most of particle size information is centrally contained in the decay section and the larger noise is contained in the larger delay section. However, no consideration of the particle size information distribution in the ACF data for the routine inversion method increases the difficulty of the accurate PSD inversion, especially the broad and bimodal PSDs. Until now, it is still a difficult problem to obtain an accurate recovery of the broad and bimodal PSDs, specifically the bimodal PSD with a peak position ratio less than 2:1 and containing large particles (350 nm). In this paper, a character-weighted constrained regularization (CW-CR) method is proposed, in which, the particle size information distribution in the ACF as the base and the adjustment parameter as the exponent are used to weight the ACF. By using the weighting coefficients corresponding to the particle size information distribution along the delay time in ACF, the CW-CR method can enhance the utilization of the particle size information in ACF data, and effectively weaken the effect of noise at large delay time. With this method, the closely spaced bimodal PSD (with nominal diameters of m 350 nm:500 nm in simulation, m 300 nm:502 nm in experiment) is recovered successfully at a high noise level of 0.01. It shows that the CW-CR method, combined with the multiangle DLS (MDLS) measurement, can effectively make the best use of the particle size information hiding in the noisy ACF data, and improve the resolution of bimodal PSD as well as the capability of noise suppression. So it can make the advantages of MDLS more highlighted than the routine method in the recovery of the broad and bimodal PSDs.

基于Mie散射光强的多角度动态光散射复合角度加权方法

基于Mie散射光强的多角度动态光散射复合角度加权方法

双峰分布颗粒体系的多角度动态光散射数据反演

双峰分布颗粒体系的多角度动态光散射数据反演

基于多角度动态退偏振光散射的短碳纳管测量

基于多角度动态退偏振光散射的短碳纳管测量

A recursive regularization algorithm for estimating the particle size distribution from multiangle dynamic light scattering measurements

Conventional regularization methods have been widely used for estimating particle size distribution (PSD) in single-angle dynamic light scattering, but they could not be used directly in multiangle dynamic light scattering (MDLS) measurements for lack of accurate angular weighting coefficients, which greatly affects the PSD determination and none of the regularization methods perform well for both unimodal and multimodal distributions. In this paper, we propose a recursive regularization method—Recursion Nonnegative Tikhonov–Phillips–Twomey (RNNT-PT) algorithm for estimating the weighting coefficients and PSD from MDLS data. This is a self-adaptive algorithm which distinguishes characteristics of PSDs and chooses the optimal inversion method from Nonnegative Tikhonov (NNT) and Nonnegative Phillips–Twomey (NNPT) regularization algorithm efficiently and automatically. In simulations, the proposed algorithm was able to estimate the PSDs more accurately than the classical regularization methods and performed stably against random noise and adaptable to both unimodal and multimodal distributions. Furthermore, we found that the six-angle analysis in the 30–130° range is an optimal angle set for both unimodal and multimodal PSDs.

Effect of scattering angle error on particle size determination by multiangle dynamic light scattering.

Dynamic light scattering (DLS) is a popular method of particle size measurement. Multiangle dynamic light scattering (MDLS) collects DLS data at multiple angles and analyzes the data simultaneously to improve the particle size measurement. Using data from several scattering angles admits the possibility of introducing noise caused by scattering angle error in the measurement, which may have an impact on the performance of the MDLS technique. We investigate the effect of scattering angle noise on recovered particle size distributions (PSDs) using simulated and measured MDLS data and various levels of angular noise. Our results show that, for unimodal PSDs, those with small particle sizes are more strongly affected by the noise than are medium and large particle size systems. For bimodal PSDs, those containing small-sized particles are also more affected by the noise than the systems of larger particles. Furthermore, broad PSDs are more vulnerable to angular noise than narrow PSDs.