Novel Defect Structures in Nematic Liquid Crystal Shells

We use double-emulsion drops to experimentally investigate the defect structures of spherical shells of nematic liquid crystals. We uncover a rich scenario of coexisting defect structures dictated by the unavoidable finite thickness of even the thinnest shell and by the thickness variation around the sphere. These structures are characterized by a varying number of disclination lines and pairs of surface point defects on the inner and outer surfaces of the nematic shell. In the limit of very thick shells the defect structure ultimately merges with that of a bulk nematic liquid crystal drop

Colloidal Assembly Route for Responsive Colloidosomes with Tunable

We present a robust and straightforward approach for fabricating a novel colloidosome system where colloidal particles are assembled to form colloidal shells on the surface of stimuli-responsive microgel scaffolds. We demonstrate that the structural properties of the colloidal shells can be controlled through the colloidal particle size and modulus, and the state of supporting microgel particles. This technique offers a new way to engineer colloidosomes, enabling fine control over their permeability over a wide range of length scales. Colloidosomes are hollow capsules whose shell is composed of closely packed uniform colloidal particles. 1-4 Like their liposome or polymersome counterparts, colloidosomes can encapsulate materials whose release rate is set by the properties of the shell. The inherent rigidity of the colloidosome shell offers mechanical advantages by comparison to the soft, self-assembled shell of liposomes or polymersomes. Moreover, the permeability of colloidosomes for encapsulated species, which is critically dependent on the size of the interstitial pores between the particles in the shell

Crash landing of Vibrio cholerae by MSHA pili-assisted braking and anchoring in a viscoelastic environment

Mannose-sensitive hemagglutinin (MSHA) pili and flagellum are critical for the surface attachment of Vibrio cholerae, the first step of V. cholerae colonization on host surfaces. However, the cell landing mechanism remains largely unknown, particularly in viscoelastic environments such as the mucus layers of intestines. Here, combining the cysteine-substitution-based labeling method with single-cell tracking techniques, we quantitatively characterized the landing of V. cholerae by directly observing both pili and flagellum of cells in a viscoelastic non-Newtonian solution consisting of 2% Luria-Bertani and 1% methylcellulose (LB+MC). The results show that MSHA pili are evenly distributed along the cell length and can stick to surfaces at any point along the filament. With such properties, MSHA pili are observed to act as a brake and anchor during cell landing which includes three phases: running, lingering, and attaching. Importantly, loss of MSHA pili results in a more dramatic increase in mean path length in LB+MC than in 2% LB only or in 20% Ficoll solutions, indicating that the role of MSHA pili during cell landing is more apparent in viscoelastic non-Newtonian fluids than viscous Newtonian ones. Our work provides a detailed picture of the landing dynamics of V. cholerae under viscoelastic conditions, which can provide insights into ways to better control V. cholerae infections in a real mucus-like environment

Multiparameter mechanical and morphometric screening of cells.

We introduce a label-free method to rapidly phenotype and classify cells purely based on physical properties. We extract 15 biophysical parameters from cells as they deform in a microfluidic stretching flow field via high-speed microscopy and apply machine-learning approaches to discriminate different cell types and states. When employing the full 15 dimensional dataset, the technique robustly classifies individual cells based on their pluripotency, with accuracy above 95%. Rheological and morphological properties of cells while deforming were critical for this classification. We also show the application of this method in accurate classifying cells based on their viability, drug screening and detecting populations of malignant cells in mixed samples. We show that some of the extracted parameters are not linearly independent, and in fact we reach maximum classification accuracy by using only a subset of parameters. However, the informative subsets could vary depending on cell types in the sample. This work shows the utility of an assay purely based on intrinsic biophysical properties of cells to identify changes in cell state. In addition to a label-free alternative to flow cytometry in certain applications, this work, also can provide novel intracellular metrics that would not be feasible with labeled approaches (i.e. flow cytometry)