Multiple Particle Tracking Research Articles

High-fidelity predictions of diffusion in the brain microenvironment

Multiple-particle tracking (MPT) is a microscopy technique capable of simultaneously tracking hundreds to thousands of nanoparticles in a biological sample and has been used extensively to characterize biological microenvironments, including the brain extracellular space (ECS). Machine learning techniques have been applied to MPT data sets to predict the diffusion mode of nanoparticle trajectories as well as more complex biological variables, such as biological age. In this study, we develop a machine learning pipeline to predict and investigate changes to the brain ECS due to injury using supervised classification and feature importance calculations. We first validate the pipeline on three related but distinct MPT data sets from the living brain ECS—age differences, region differences, and enzymatic degradation of ECS structure. We predict three ages with 86% accuracy, three regions with 90% accuracy, and healthy versus enzyme-treated tissue with 69% accuracy. Since injury across groups is normally compared with traditional statistical approaches, we first used linear mixed effects models to compare features between healthy control conditions and injury induced by two different oxygen glucose deprivation (1) exposure times. We then used machine learning to predict injury state using MPT features. We show that the pipeline predicts between the healthy control, 0.5 h OGD treatment, and 1.5 h OGD treatment with 59% accuracy in the cortex and 66% in the striatum, and identifies nonlinear relationships between trajectory features that were not evident from traditional linear models. Our work demonstrates that machine learning applied to MPT data is effective across multiple experimental conditions and can find unique biologically relevant features of nanoparticle diffusion.

Human Mesofluidic Intestinal Model for Studying Transport of Drug Carriers and Bacteria Through a Live Mucosal Barrier.

The intestinal mucosal barrier forms a critical interface between lumen contents such as bacteria, drugs, and drug carriers and the underlying tissue. Current in vitro intestinal models, while recapitulating certain aspects of this barrier, generally present challenges with respect to imaging transport across mucus and uptake into enterocytes. A human mesofluidic small intestinal chip was designed to enable facile visualization of a mucosal interface created by growing primary human intestinal cells on a vertical hydrogel wall separating channels representing the intestinal lumen and circulatory flow. Type I collagen, fortified via cross-linking to prevent deformation and leaking during culture, was identified as a suitable gel wall material for supporting primary organoid-derived human duodenal epithelial cell attachment and monolayer formation. Addition of DAPT and PGE2 to culture medium paired with air-liquid interface culture increased the thickness of the mucus layer on epithelium grown within the device for 5 days from approximately 5 mm to 50 μm, making the model suitable for revealing intriguing features of interactions between luminal contents and the mucus barrier using live cell imaging. Time-lapse imaging of nanoparticle diffusion within mucus revealed a zone adjacent to the epithelium largely devoid of nanoparticles up to 4.5 hr after introduction to the lumen channel, as well as pockets of dimly lectin-stained mucus within which particles freely diffused, and apparent clumping of particles by mucus components. Multiple particle tracking conducted on the intact mucus layer in the chip revealed significant size-dependent differences in measured diffusion coefficients. E. coli introduced to the lumen channel were freely mobile within the mucus layer and appeared to intermittently contact the epithelial surface over 30 minute periods of culture. Mucus shedding into the lumen and turnover of mucus components within cells were visualized. Taken together, this system represents a powerful tool for visualization of interactions between luminal contents and an intact live mucosal barrier.

Ab initio uncertainty quantification in scattering analysis of microscopy.

Estimating parameters from data is a fundamental problem in physics, customarily done by minimizing a loss function between a model and observed statistics. In scattering-based analysis, it is common to work in the reciprocal space. Researchers often employ their domain expertise to select a specific range of wave vectors for analysis, a choice that can vary depending on the specific case. We introduce another paradigm that defines a probabilistic generative model from the beginning of data processing and propagates the uncertainty for parameter estimation, termed the ab initio uncertainty quantification (AIUQ). As an illustrative example, we demonstrate this approach with differential dynamic microscopy (DDM) that extracts dynamical information through minimizing a loss function for the squared differences of the Fourier-transformed intensities, at a selected range of wave vectors. We first show that the conventional way of estimation in DDM is equivalent to fitting a temporal variogram in the reciprocal space using a latent factor model as the generative model. Then we derive the maximum marginal likelihood estimator, which optimally weighs the information at all wave vectors, therefore eliminating the need to select the range of wave vectors. Furthermore, we substantially reduce the computational cost of computing the likelihood function without approximation, by utilizing the generalized Schur algorithm for Toeplitz covariances. Simulated studies of a wide range of dynamical systems validate that the AIUQ method improves estimation accuracy and enables model selection with automated analysis. The utility of AIUQ is also demonstrated by three distinct sets of experiments: first in an isotropic Newtonian fluid, pushing limits of optically dense systems compared to multiple particle tracking; next in a system undergoing a sol-gel transition, automating the determination of gelling points and critical exponent; and lastly, in discerning anisotropic diffusive behavior of colloids in a liquid crystal. These studies demonstrate that the new approach does not require manually selecting the wave vector range and enables automated analysis.

Cell-Material Interactions in Covalent Adaptable Thioester Hydrogels.

Covalent adaptable networks (CANs) are polymeric networks with cross-links that can break and reform in response to external stimuli, including pH, shear, and temperature, making them potential materials for use as injectable cell delivery vehicles. In the native niche, cells rearrange the extracellular matrix (ECM) to undergo basic functions including migration, spreading, and proliferation. Bond rearrangement enables these hydrogels to mimic viscoelastic properties of the native ECM which promote migration and delivery from the material to the native tissue. In this work, we characterize thioester CANs to inform their design as effective cell delivery vehicles. Using bulk rheology, we characterize the rearrangement of these networks when they are subjected to strain, which mimics the strain applied by a syringe, and using multiple particle tracking microrheology (MPT) we measure cell-mediated remodeling of the pericellular region. Thioester networks are formed by photopolymerizing 8-arm poly(ethylene glycol) (PEG)-thiol and PEG-thioester norbornene. Bulk rheology measures scaffold properties during low and high strain and demonstrates that thioester scaffolds can recover rheological properties after high strain is applied. We then 3D encapsulated human mesenchymal stem cells (hMSCs) in thioester scaffolds. Using MPT, we characterize degradation in the pericellular region. Encapsulated hMSCs degrade these scaffolds within ≈4 days post-encapsulation. We hypothesize that this degradation is mainly due to cytoskeletal tension that cells apply to the matrix, causing adaptable thioester bonds to rearrange, leading to degradation. To verify this, we inhibited cytoskeletal tension using blebbistatin, a myosin-II inhibitor. Blebbistatin-treated cells can degrade these networks only by secreting enzymes including esterases. Esterases hydrolyze thioester bonds, which generate free thiols, leading to bond exchange. Around treated cells, we measure a decrease in the extent of pericellular degradation. We also compare cell area, eccentricity, and speed of untreated and treated cells. Inhibiting cytoskeletal tension results in significantly smaller cell area, more rounded cells, and lower cell speeds when compared to untreated cells. Overall, this work shows that cytoskeletal tension plays a major role in hMSC-mediated degradation of thioester networks. Cytoskeletal tension is also important for the spreading and motility of hMSCs in these networks. This work informs the design of thioester scaffolds for tissue regeneration and cell delivery.

A Rheological Study on the Effect of Tethering Pro- and Anti-Inflammatory Cytokines into Hydrogels on Human Mesenchymal Stem Cell Migration, Degradation, and Morphology.

Polymer-peptide hydrogels are being designed as implantable materials that deliver human mesenchymal stem cells (hMSCs) to treat wounds. Most wounds can progress through the healing process without intervention. During the normal healing process, cytokines are released from the wound to create a concentration gradient, which causes directed cell migration from the native niche to the wound site. Our work takes inspiration from this process and uniformly tethers cytokines into the scaffold to measure changes in cell-mediated degradation and motility. This is the first step in designing cytokine concentration gradients into the material to direct cell migration. We measure changes in rheological properties, encapsulated cell-mediated pericellular degradation and migration in a hydrogel scaffold with covalently tethered cytokines, either tumor necrosis factor-α (TNF-α) or transforming growth factor-β (TGF-β). TNF-α is expressed in early stages of wound healing causing an inflammatory response. TGF-β is released in later stages of wound healing causing an anti-inflammatory response in the surrounding tissue. Both cytokines cause directed cell migration. We measure no statistically significant difference in modulus or the critical relaxation exponent when tethering either cytokine in the polymeric network without encapsulated hMSCs. This indicates that the scaffold structure and rheology is unchanged by the addition of tethered cytokines. Increases in hMSC motility, morphology and cell-mediated degradation are measured using a combination of multiple particle tracking microrheology (MPT) and live-cell imaging in hydrogels with tethered cytokines. We measure that tethering TNF-α into the hydrogel increases cellular remodeling on earlier days postencapsulation and tethering TGF-β into the scaffold increases cellular remodeling on later days. We measure tethering either TGF-β or TNF-α enhances cell stretching and, subsequently, migration. This work provides rheological characterization that can be used to design new materials that present chemical cues in the pericellular region to direct cell migration.

Multi-detector fusion and Bayesian smoothing for tracking viral and chromatin structures

Automatic tracking of viral and intracellular structures displayed as spots with varying sizes in fluorescence microscopy images is an important task to quantify cellular processes. We propose a novel probabilistic tracking approach for multiple particle tracking based on multi-detector and multi-scale data fusion as well as Bayesian smoothing. The approach integrates results from multiple detectors using a novel intensity-based covariance intersection method which takes into account information about the image intensities, positions, and uncertainties. The method ensures a consistent estimate of multiple fused particle detections and does not require an optimization step. Our probabilistic tracking approach performs data fusion of detections from classical and deep learning methods as well as exploits single-scale and multi-scale detections. In addition, we use Bayesian smoothing to fuse information of predictions from both past and future time points. We evaluated our approach using image data of the Particle Tracking Challenge and achieved state-of-the-art results or outperformed previous methods. Our method was also assessed on challenging live cell fluorescence microscopy image data of viral and cellular proteins expressed in hepatitis C virus-infected cells and chromatin structures in non-infected cells, acquired at different spatial–temporal resolutions. We found that the proposed approach outperforms existing methods.

Effect of beta glucan coating on controlled release, bioaccessibility, and absorption of β-carotene from loaded liposomes.

Recently, the use of biopolymers as coating material to stabilise phospholipid-based nanocarriers has increased. One such class of biopolymers is the dietary fibre beta-glucan (βG). In this study, we developed and characterized beta-carotene (βC) loaded βG coated nanoliposomes (GNLs) to investigate the effect of βG coating on the stability, controlled release, bioaccessibility, diffusion and subsequent absorption of the lipophilic active agent. The size, charge (Z-potential), and FTIR spectra were measured to determine the physicochemical stability of GNLs. βG coating reduced the bioaccessibility, provided prolonged release and improved the antioxidant activity of the nanoliposomes. Multiple particle tracking (MPT) data suggested that βC-GNLs were less diffusive in porcine intestinal mucus (PIM). Additionally, the microviscosity of the PIM treated with GNLs was observed to be higher (0.04744 ± 0.00865 Pa s) than the PIM incubated with uncoated NLs (0.015 ± 0.0004 Pa s). An Ex vivo experiment was performed on mouse jejunum to measure the absorption of beta-carotene from coated (βC-GNLs) and uncoated nanoliposomes (βC-NLs). Data showed that after 2 hours, 27.7 ± 1.3 ng mL-1 of βC encapsulated in GNLs and 61.54 ± 3 ng mL-1 of the βC encapsulated in uncoated NLs was absorbed by mouse intestinal mucosa. These results highlight that coating with βG stabilise NLs during gastrointestinal digestion and provides more sustained release of βC from nanoliposomes.

Multiple Particle Tracking: A Method for Probing Biologically Relevant Mobility of Bacterial Extracellular Vesicles.

Bacterial extracellular vesicles (bEVs) are produced by both Gram-negative and Gram-positive bacteria. These biological nanoparticles transport small molecules, nucleic acids, and proteins, enabling communication with both bacterial and mammalian cells. bEVs can evade and disrupt biological barriers, and their lipid membranes protect their cargo from degradation, facilitating long-distance communication in vivo. Furthermore, bacteria are easily manipulated and easily cultured. These combined factors make bEVs an ideal candidate for drug delivery applications. Thus, the study of how bEVs interact with biological barriers is interesting from both a signaling and drug delivery perspective. Here we describe methods for tracking bEV motion in biological matrices ex vivo. We outline methods for growth, isolation, quantification, and labeling, as well as techniques for tracking bEV motion ex vivo and quantifying these data. The methods described here are relevant to bEV communication with host cells as well as drug delivery applications using bEVs.

Deep learning-based multiple particle tracking in complex system

This paper presents an innovative approach for multiple particle tracking within complex systems, utilizing convolutional neural networks in conjunction with multi-output models. Accurate particle tracking is a critical prerequisite for unraveling the dynamic behaviors of particles in a myriad of research domains, encompassing colloidal particles, biological cells, and molecular dynamics. Different from conventional methodologies, our approach combines data preprocessing, multilayer perceptron model training, and multi-output model integration to yield precise and efficient particle tracking results. The significance of this research lies in the adaptability and versatility of the trained models, which are designed to surmount challenges, including crowded and noisy environments. This work represents a substantial step forward in particle tracking methodologies, providing a robust and efficient alternative to conventional methods, promising more profound investigations into particle dynamics within complex systems, and contributing to a deeper understanding of the microscale world.

Herb-Nanoparticle Hybrid System for Improved Oral Delivery Efficiency to Alleviate Breast Cancer Lung Metastasis.

Metastasis is a complex process involving multiple factors and stages, in which tumor cells and the tumor microenvironment (TME) play significant roles. A combination of orally bioavailable therapeutic agents that target both tumor cells and TME is conducive to prevent or impede the progression of metastasis, especially when undetectable. However, sequentially overcoming intestinal barriers, ensuring biodistribution in tumors and metastatic tissues, and enhancing therapeutic effects required for efficient therapy remain challenging. Inspired by the unique chemical features of natural herbs, we propose an oral herb-nanoparticle hybrid system (HNS) formed through the self-binding of Platycodon grandiflorum-Curcuma zedoaria (HG), a herb pair/group used in clinical practice to treat breast cancer metastasis, to lipid-polymer nanoparticles (LPNs) loaded with silibinin. The molecular structure responsible for HG association with LPNs was assessed using surface-enhanced Raman spectroscopy for HNS surface chemistry characterization. Moreover, the molecular class of HG was identified using UPLC-Orbitrap-MS/MS to further confirm the surface binding. Mucus diffusion and in vivo biodistribution were evaluated using in vitro multiple-particle tracking and environment-responsive fluorescence probe in 4T1 tumor-bearing mice, respectively. The alleviation of breast cancer metastasis was assessed in 4T1 tumor-bearing mice, and the underlying mechanism was investigated. The HNS reduced particle-mucus interactions by altering hydrophilicity and surface characteristics compared to LPNs. The epithelium transportation of HNS and absorption through Peyer's patch in mice were improved, promoting their biodistribution in the lung and tumor tissues. Furthermore, the HNS alleviated lung metastasis by inducing cell apoptosis and regulating the expression of MMP-9 and TGF-β1, which altered the TME in 4T1 tumor-bearing mice. HNS provides an appealing system with multi-component binding of herbal medicine to facilitate both oral nanoparticle delivery efficiency and the alleviation of lung metastasis. This strategy may potentially help improve treatment for patients with breast cancer.

Nanoparticle transport in biomimetic polymer‐linked emulsions

AbstractThe ability of nanoparticles to penetrate and transport through soft tissues is essential to delivering therapeutics to treat diseases or signaling agents for advanced imaging and sensing. Nanoparticle transport in biological systems, however, is challenging to predict and control due to the physicochemical complexity of tissues and biological fluids. Here, we demonstrate that nanoparticles suspended in a novel class of soft matter—polymer‐linked emulsions (PLEs)—exhibit characteristics essential for mimicking transport in biological systems, including subdiffusive dynamics, non‐Gaussian displacement distributions, and decoupling of dynamics from material viscoelasticity. Using multiple particle tracking, we identify the physical mechanisms underlying this behavior, which we attribute to a coupling of nanoparticle dynamics to fluctuations in the local network of polymer‐linked droplets. Our findings demonstrate the potential of PLEs to serve as fully synthetic mimics of biological transport.

CellTool: An Open-Source Software Combining Bio-Image Analysis and Mathematical Modeling for the Study of DNA Repair Dynamics

Elucidating the dynamics of DNA repair proteins is essential to understanding the mechanisms that preserve genomic stability and prevent carcinogenesis. However, the measurement and modeling of protein dynamics at DNA lesions via currently available image analysis tools is cumbersome. Therefore, we developed CellTool—a stand-alone open-source software with a graphical user interface for the analysis of time-lapse microscopy images. It combines data management, image processing, mathematical modeling, and graphical presentation of data in a single package. Multiple image filters, segmentation, and particle tracking algorithms, combined with direct visualization of the obtained results, make CellTool an ideal application for the comprehensive analysis of DNA repair protein dynamics. This software enables the fitting of obtained kinetic data to predefined or custom mathematical models. Importantly, CellTool provides a platform for easy implementation of custom image analysis packages written in a variety of programing languages. Using CellTool, we demonstrate that the ALKB homolog 2 (ALKBH2) demethylase is excluded from DNA damage sites despite recruitment of its putative interaction partner proliferating cell nuclear antigen (PCNA). Further, CellTool facilitates the straightforward fluorescence recovery after photobleaching (FRAP) analysis of BRCA1 associated RING domain 1 (BARD1) exchange at complex DNA lesions. In summary, the software presented herein enables the time-efficient analysis of a wide range of time-lapse microscopy experiments through a user-friendly interface.

Physiological Concentrations of Calcium Interact with Alginate and Extracellular DNA in the Matrices of Pseudomonas aeruginosa Biofilms to Impede Phagocytosis by Neutrophils.

Biofilms are communities of interacting microbes embedded in a matrix of polymer, protein, and other materials. Biofilms develop distinct mechanical characteristics that depend on their predominant matrix components. These matrix components may be produced by microbes themselves or, for infections in vivo, incorporated from the host environment. Pseudomonas aeruginosa (P. aeruginosa) is a human pathogen that forms robust biofilms that extensively tolerate antibiotics and effectively evade clearance by the immune system. Two of the important bacterial-produced polymers in the matrices of P. aeruginosa biofilms are alginate and extracellular DNA (eDNA), both of which are anionic and therefore have the potential to interact electrostatically with cations. Many physiological sites of infection contain significant concentrations of the calcium ion (Ca2+). In this study, we investigate the structural and mechanical impacts of Ca2+ supplementation in alginate-dominated biofilms grown in vitro, and we evaluate the impact of targeted enzyme treatments on clearance by immune cells. We use multiple-particle tracking microrheology to evaluate the changes in biofilm viscoelasticity caused by treatment with alginate lyase or DNase I. For biofilms grown without Ca2+, we correlate a decrease in relative elasticity with increased phagocytic success. However, we find that growth with Ca2+ supplementation disrupts this correlation except in the case where both enzymes are applied. This suggests that the calcium cation may be impacting the microstructure of the biofilm in nontrivial ways. Indeed, confocal laser scanning fluorescence microscopy and scanning electron microscopy reveal unique Ca2+-dependent eDNA and alginate microstructures. Our results suggest that the presence of Ca2+ drives the formation of structurally and compositionally discrete microdomains within the biofilm through electrostatic interactions with the anionic matrix components eDNA and alginate. Further, we observe that these structures serve a protective function as the dissolution of both components is required to render biofilm bacteria vulnerable to phagocytosis by neutrophils.

Microrheological characterisation of Cyanoflan in human blood plasma

Naturally occurring polysaccharidic biopolymers released by marine cyanobacteria are of great interest for numerous biomedical applications, such as wound healing and drug delivery. Such polymers generally exhibit high molecular weight and an entangled structure that impact the rheology of biological fluids. However, biocompatibility tests focus not so much on rheological properties as on immune response. In the present study, the rheological behaviour of native blood plasma as a function of the concentration of a cyanobacterium biopolymer is investigated via multiple particle tracking microrheology, which measures the Brownian motion of probes embedded in a sample, and cryogenic scanning electron microscope microstructural characterisation. We use Cyanoflan as the biopolymer of choice, and profit from our knowledge of its chemical structure and its exciting potential for biotechnological applications. A sol–gel transition is identified using time-concentration superposition and the power-law behaviour of the incipient network's viscoelastic response is observed in a variety of microrheological data. Our results point to rheology-based principles for blood compatibility tests by facilitating the assignment of quantitative values to specific properties, as opposed to more heuristic approaches.

Broadly neutralizing antibodies consistently trap HIV-1 in fresh cervicovaginal mucus from select individuals.

In addition to direct neutralization and other classical effector functions, IgG possesses a little recognized and thus under-utilized effector function at mucosal surfaces: Fc-mucin bonds enable IgG to trap viruses in mucus. Due to the paucity of envelope glycoproteins that limits the number of IgG that can bind HIV, it remains poorly understood whether IgG-mucin interactions can effectively immobilize HIV in human cervicovaginal mucus (CVM). Here, we obtained 54 fresh, undiluted CVM specimens from 17 different women, and employed high-resolution multiple particle tracking to quantify the mobility of fluorescent HIV virus-like-particles in CVM treated with various HIV-specific IgG. We observed consistent and effective trapping of HIV by broadly neutralizing antibodies (VRC01, PGT121, and 2F5) in a subset of women. While trapping efficacy was not affected by the menstrual cycle, it was positively correlated with appreciable L. Crispatus populations in the microbiome, and negatively correlated with appreciable L. Iners or G. Vaginalis populations. Our work demonstrates for the first time that IgG-mucin crosslinking is capable of reinforcing the mucosal barrier against HIV, and motivates further investigation of passive immunization against vaginal transmission of STIs. STATEMENT OF SIGNIFICANCE: HIV transmission in women primarily occurs vaginally, yet the 3-way interactions between mucins and HIV virions mediated by HIV-binding antibodies in cervicovaginal mucus (CVM) is not well understood. While IgG-Fc possess weak affinity to mucins that trap virus/IgG complexes in mucus, the effectiveness against HIV remains unclear, due to the low number of virion-bound IgG. Here, we discovered that IgG can trap HIV consistently in CVM from select individuals regardless of their birth control status or menstrual cycle phase. IgG-mediated trapping of HIV was moderately associated with microbiome composition. These results suggest that IgG-mucin interactions could potentially reduce HIV transmission and highlight the importance of mucosal secretions in antibody-mediated prevention of HIV and other sexually transmitted infections.

Characterizing Phase Transitions of Microfibrillated Cellulose Induced by Anionic and Cationic Surfactants.

Rheological modifiers are used to tune rheology or induce phase transitions of products. Microfibrillated cellulose (MFC), a renewable material, has the potential to be used for rheological modification. However, the lack of studies on the evolution in rheological properties and structure during its phase transitions has prevented MFC from being added to consumer, fabric, and home care products. In this work, we characterize surface-oxidized MFC (OMFC), a negatively charged colloidal rod suspension. We measure the rheological properties and structure of OMFC during sol-gel phase transitions induced by either anionic or cationic surfactant using multiple particle tracking microrheology (MPT). MPT tracks the Brownian motion of fluorescent probe particles embedded in a sample, which is related to the sample's rheological properties. Using MPT, we measure that OMFC gelation evolution is dependent on the charge of the surfactant that induces the phase transition. OMFC gelation is gradual in anionic surfactant. In cationic surfactant, gelation is rapid followed by length scale-dependent colloidal fiber rearrangement. Initial OMFC concentration is directly related to how tightly associated the network is at the phase transition, with an increase in concentration resulting in a more tightly associated network with smaller pores. Bulk rheology measures that OMFC forms a stiffer structure but yields at lower strains in cationic surfactant than in anionic surfactant. This study characterizes the role of surfactant in inducing phase transitions, which can be used as a guide for designing future products.

Targeted micro-heterogeneity in bioinks allows for 3D printing of complex constructs with improved resolution and cell viability.

Three-dimensional bioprinting is an evolving versatile technique for biomedical applications. Ideal bioinks have complex micro-environment that mimic human tissue, allow for good printing quality and provide high cell viability after printing. Here we present two strategies for enhancing gelatin-based bioinks heterogeneity on a 1-100µm length scale resulting in superior printing quality and high cell viability. A thorough spatial and micro-mechanical characterization of swollen hydrogel heterogeneity was done using multiple particle tracking microrheology. When poly(vinyl alcohol) is added to homogeneous gelatin gels, viscous inclusions are formed due to micro-phase separation. This phenomenon leads to pronounced slip and superior printing quality of complex 3D constructs as well as high human hepatocellular carcinoma (HepG2) and normal human dermal fibroblast (NHDF) cell viability due to reduced shear damage during extrusion. Similar printability and cell viability results are obtained with gelatin/nanoclay composites. The formation of polymer/nanoclay clusters reduces the critical stress of gel fracture, which facilitates extrusion, thus enhancing printing quality and cell viability. Targeted introduction of micro-heterogeneities in bioinks through micro-phase separation is an effective technique for high resolution 3D printing of complex constructs with high cell viability. The size of the heterogeneities, however, has to be substantially smaller than the desired feature size in order to achieve good printing quality.

Development, validation and implementation of multiple radioactive particle tracking technique

Computer Automated Radioactive Particle Tracking (CARPT) technique has been successfully utilized to measure the velocity profiles and mixing parameters in different multiphase flow systems where a single radioactive tracer is used to track the tagged phase. However, many industrial processes use a wide range of particles with different physical properties where solid particles could vary in size, shape and density. For application in such systems, the capability of current single tracer CARPT can be advanced to track more than one particle simultaneously. Tracking multiple particles will thus enable to track the motion of particles of different size shape and density, determine segregation of particles and probing particle interactions. In this work, a newly developed Multiple Radioactive Particle Tracking technique (M-RPT) used to track two different radioactive tracers is demonstrated. The M-RPT electronics was developed that can differentiate between gamma counts obtained from the different radioactive tracers on the basis of their gamma energy peak. The M-RPT technique was validated by tracking two stationary and moving particles (Sc-46 and Co-60) simultaneously. Finally, M-RPT was successfully implemented to track two phases, solid and liquid, simultaneously in three phase slurry bubble column reactors.

PH-Mediated Mucus Penetration of Zwitterionic Polydopamine-Modified Silica Nanoparticles.

Zwitterionic polymers have emerged as promising trans-mucus nanocarriers due to their superior antifouling properties. However, for pH-sensitive zwitterionic polymers, the effect of the pH microenvironment on their trans-mucus fate remains unclear. In this work, we prepared a library of zwitterionic polydopamine-modified silica nanoparticles (SiNPs-PDA) with an isoelectric point of 5.6. Multiple-particle tracking showed that diffusion of SiNPs-PDA in mucus with a pH value of 5.6 was 3 times faster than that in mucus with pH value 3.0 or 7.0. Biophysical analysis found that the trans-mucus behavior of SiNPs-PDA was mediated by hydrophobic and electrostatic interactions and hydrogen bonding between mucin and the particles. Furthermore, the particle distribution in the stomach, intestine, and lung demonstrated the pH-mediated mucus penetration behavior of the SiNPs-PDA. This study reveals the pH-mediated mucus penetration behavior of zwitterionic nanomaterials, which provides rational design strategies for zwitterionic polymers as nanocarriers in various mucus microenvironments.

Change of network structure in agarose solution during gelation studied by multiple particle tracking and NMR measurements

The gelation mechanism of agarose solution on cooling has been successfully elucidated by measurements from macroscopic to microscopic scales using a dynamic rheometer, the multiple particle tracking with two different diameters and the pulsed-field-gradient stimulated echo (PGSTE) 1H NMR. The dynamic rheometer detected the gradual increase of G’ in the temperature range from 55 to 40 °C before the steep increase at the gelation temperature. The time-averaged mean square displacement (msd) obtained by multiple particle tracking for particles with diameter of 270 nm and 1000 nm revealed the generation of micro domains with the network structure obstructing particle diffusion. Further, the NMR measurements gave detailed information about the change of molecular mobility for agarose chains during the formation of the micro domains and the macroscopic overall network structure. These results suggest a gelation mechanism and gel network structure including the formation of micro domains in the temperature range from 55 to 40 °C and the connection among the micro domains by agarose aggregates to form the overall network structure at the gelation temperature.