Microliter viscometry using a bright-field microscope: η-DDM

Self-Emulsifying Drug Delivery System Enhances Tissue Distribution of Cinnamaldehyde by Altering the Properties of the Mucus Layer

Oral delivery is considered the preferred route of administration due to its convenience and favorable compliance. However, this delivery often faces difficulties, such as poor solubility, limited absorption, and undesirable stability, especially for some volatile oils. The aim of this study was to develop self-emulsifying drug delivery systems (SEDDS) containing cinnamaldehyde (CA) to overcome these shortcomings. The CA-SEDDS were spherical and smooth with an average size of 14.96 ± 0.18 nm. Differential scanning calorimetry (DSC) and attenuated total reflection by Fourier transform infrared (ATR-FTIR) showed that CA has been successfully loaded into SEDDS. The accumulative release of CA-SEDDS (73.39%) was approximately 2.14-fold that of free CA when using simulated intestinal fluid as the release medium. A scanning electron microscope was used to observe the mucus network structure. Rheological tests found that CA-SEDDS can appropriately enhance the viscosity of the mucus system. We found from tissue distribution studies that CA was more widely distributed in various tissues in the CA-SEDDS group compared to the free CA group. The cinnamaldehyde and cinnamon acid also accumulated more in various tissues in the CA-SEDDS group than in the free CA group, especially in the kidney. These findings hinted that SEDDS exhibited lower irritation, good release, and penetration, which demonstrated great potential for utilizing CA. Our research supports the rational implications of SEDDS in delivering similar volatile substances by improving the solubility, mucus penetration, and stability, resulting in excellent clinical efficacy.

Particle-Based Microrheology As a Tool for Characterizing Protein-Based Materials

Microrheology based on video microscopy of embedded tracer particles has the potential to be used for high-throughput protein-based materials characterization. This potential is due to a number of characteristics of the techniques, including the suitability for measurement of low sample volumes, noninvasive and noncontact measurements, and the ability to set up a large number of samples for facile, sequential measurement. In addition to characterization of the bulk rheological properties of proteins in solution, for example, viscosity, microrheology can provide insight into the dynamics and self-assembly of protein-based materials as well as heterogeneities in the microenvironment being probed. Specifically, passive microrheology in the form of multiple particle tracking and differential dynamic microscopy holds promise for applications in high-throughput characterization because of the lack of user interaction required while making measurements. Herein, recent developments in the use of multiple particle tracking and differential dynamic microscopy are reviewed for protein characterization and their potential to be applied in a high-throughput, automatable setting.

In vitro and in vivo evaluation of cinnamaldehyde Microemulsion-Mucus interaction

The current investigation explores the possible mechanism of the microemulsion drug delivery system to improve the oral bioavailability of cinnamaldehyde (CA), an important food spice, from the perspective of the microemulsion-mucus system. The cinnamaldehyde microemulsion (CA-ME) was prepared by the water titration method combined with the pseudo-ternary phase diagram. The dynamic analysis was applied to detect the drug release in vitro. An intestinal mucosal injury test was conducted to evaluate the safety of CA-ME and drug absorption across the intestinal tract of rats was investigated through an Ussing chamber system. The rheology of blank mucus and drug-loaded mucus was investigated using a rheometer. The bioavailability of CA-ME in rats was evaluated through pharmacokinetic characteristics. The ratio of optimal prescription was Tween 80: 1,2-propanediol: vitamin E oil: CA: water = 24.3:4.8:5:7.5:58.4. The droplets were uniform in size and evenly dispersed. Rheological studies showed that the microemulsion-mucus system all exhibit pseudoplastic fluid behavior, and CA-ME increased the viscosity of the mucus to a certain extent. Compared with CA solution, CA-ME promoted the absorption of CA in various intestinal segments, especially the ileum. Pharmacokinetic experiments showed that the relative bioavailability of CA-ME was enhanced 2.5-fold higher than that of CA solution. ME as a carrier for lipophobic substances, may increase the viscosity of the intestine mucus system to obtain longer residue time and better absorption. PRACTICAL APPLICATIONS: In this study, in vitro absorption Ussing model was combined with rheological and pharmacokinetic analysis to systematically analyze the intestinal mucus mechanism of microemulsion to improve the oral bioavailability of cinnamic aldehyde. It laid the foundation for exploring the absorption and transport of drugs in the intestinal mucus barrier.

A small-volume microcapillary rheometer

We demonstrate a capillary device used to measure the shear rate-dependent viscosity of microliter scale volumes. Liquid samples are driven pneumatically through a microcapillary and partially fill a larger glass capillary. The glass capillary is mounted on an optical linear sensor to track the air-liquid meniscus in real time and trigger the reversal of flow direction by switching a pneumatic valve. Each transit provides a volumetric flow rate measurement, which is used with the pressure drop to determine viscosity as a function of shear rate. A given sample of at least 50 μL can be measured over at least 2 to 3 decades in shear rate, in the range of 10 to 10⁵ s^-1, and be essentially fully recovered. Validation by comparison to reference measurements is performed using samples of Newtonian and non-Newtonian fluid, with viscosity ranging from 1 to 100 mPa s. The range of operation and uncertainty arising from instrumentation, meniscus effects, and inertial effects are discussed. The performance of this rheometer is advantageous, especially for use and reuse of small volumes.

Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning

Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing for mechanical and biological properties in living hydrogels-for example, gel time of the hydrogel formulation and viability of the embedded organisms-can be challenging. In this study, a pipeline is developed to automate the characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli-formulated from within a 4D parameter space-are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between artificial intelligence (AI)-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 min, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties-at least over a finite range-while maintaining biological activity.

Uncertainty quantification and estimation in differential dynamic microscopy

Differential dynamic microscopy (DDM) is a form of video image analysis that combines the sensitivity of scattering and the direct visualization benefits of microscopy. DDM is broadly useful in determining dynamical properties including the intermediate scattering function for many spatiotemporally correlated systems. Despite its straightforward analysis, DDM has not been fully adopted as a routine characterization tool, largely due to computational cost and lack of algorithmic robustness. We present statistical analysis that quantifies the noise, reduces the computational order, and enhances the robustness of DDM analysis. We propagate the image noise through the Fourier analysis, which allows us to comprehensively study the bias in different estimators of model parameters, and we derive a different way to detect whether the bias is negligible. Furthermore, through use of Gaussian process regression (GPR), we find that predictive samples of the image structure function require only around 0.5%-5% of the Fourier transforms of the observed quantities. This vastly reduces computational cost, while preserving information of the quantities of interest, such as quantiles of the image scattering function, for subsequent analysis. The approach, which we call DDM with uncertainty quantification (DDM-UQ), is validated using both simulations and experiments with respect to accuracy and computational efficiency, as compared with conventional DDM and multiple particle tracking. Overall, we propose that DDM-UQ lays the foundation for important new applications of DDM, as well as to high-throughput characterization.

Particle sizing for flowing colloidal suspensions using flow-differential dynamic microscopy

Particle size is a key variable in understanding the behaviour of the particulate products that underpin much of our modern lives. Typically obtained from suspensions at rest, measuring the particle size under flowing conditions would enable advances for in-line testing during manufacture and high-throughput testing during development. However, samples are often turbid, multiply scattering light and preventing the direct use of common sizing techniques. Differential dynamic microscopy (DDM) is a powerful technique for analysing video microscopy of such samples, measuring diffusion and hence particle size without the need to resolve individual particles while free of substantial user input. However, when applying DDM to a flowing sample, diffusive dynamics are rapidly dominated by flow effects, preventing particle sizing. Here, we develop "flow-DDM", a novel analysis scheme that combines optimised imaging conditions, a drift-velocity correction and modelling of the impact of flow. Flow-DDM allows a decoupling of flow from diffusive motion that facilitates successful particle size measurements at flow speeds an order of magnitude higher than for DDM. We demonstrate the generality of the technique by applying flow-DDM to two separate microscopy methods and flow geometries.

Particle diffusion in extracellular hydrogels

Hyaluronic acid is an abundant polyelectrolyte in the human body that forms extracellular hydrogels in connective tissues. It is essential for regulating tissue biomechanics and cell-cell communication, yet hyaluronan overexpression is associated with pathological situations such as cancer and multiple sclerosis. Due to its enormous molecular weight (in the range of millions of Daltons), accumulation of hyaluronan hinders transport of macromolecules including nutrients and growth factors through tissues and also hampers drug delivery. However, the exact contribution of hyaluronan to tissue penetrability is poorly understood due to the complex structure and molecular composition of tissues. Here we reconstitute biomimetic hyaluronan gels and systematically investigate the effects of gel composition and crosslinking on the diffusion of microscopic tracer particles. We combine ensemble-averaged measurements via differential dynamic microscopy with single-particle tracking. We show that the particle diffusivity depends on the particle size relative to the network pore size and also on the stress relaxation dynamics of the network. We furthermore show that addition of collagen, the other major biopolymer in tissues, causes the emergence of caged particle dynamics. Our findings are useful for understanding macromolecular transport in tissues and for designing biomimetic extracellular matrix hydrogels for drug delivery and tissue regeneration.

Hyaluronan biopolymers release water upon pH-induced gelation

We measure the reorientation dynamics of water in hyaluronan solutions, and find that, upon pH-induced gelation, these biopolymers release water.

Experimental Evidence for a Cluster Glass Transition in Concentrated Lysozyme Solutions

Lysozyme is known to form equilibrium clusters at pH ≈ 7.8 and at low ionic strength as a result of a mixed potential. While this cluster formation and the related dynamic and static structure factors have been extensively investigated, its consequences on the macroscopic dynamic behavior expressed by the zero shear viscosity η₀ remain controversial. Here we present results from a systematic investigation of η₀ using two complementary passive microrheology techniques, dynamic light scattering based tracer microrheology, and multiple particle tracking using confocal microscopy. The combination of these techniques with a simple but effective evaporation approach allows for reaching concentrations close to and above the arrest transition in a controlled and gentle way. We find a strong increase of η₀ with increasing volume fraction ϕ with an apparent divergence at ϕ ≈ 0.35, and unambiguously demonstrate that this is due to the existence of an arrest transition where a cluster glass forms. These findings demonstrate the power of tracer microrheology to investigate complex fluids, where weak temporary bonds and limited sample volumes make measurements with classical rheology challenging.