Statistical methods for polyhedral shape classification with incomplete data - application to cryo-electron tomographic images

A certain type of bacterial inclusion, known as a bacterial microcompartment, was recently identified and imaged through cryo-electron tomography. A reconstructed 3D object from single-axis limited angle tilt-series cryo-electron tomography contains missing regions and this problem is known as the missing wedge problem. Due to missing regions on the reconstructed images, analyzing their 3D structures is a challenging problem. The existing methods overcome this problem by aligning and averaging several similar shaped objects. These schemes work well if the objects are symmetric and several objects with almost similar shapes and sizes are available. Since the bacterial inclusions studied here are not symmetric, are deformed, and show a wide range of shapes and sizes, the existing approaches are not appropriate. This research develops new statistical methods for analyzing geometric properties, such as volume, symmetry, aspect ratio, polyhedral structures etc., of these bacterial inclusions in presence of missing data. These methods work with deformed and non-symmetric varied shaped objects and do not necessitate multiple objects for handling the missing wedge problem. The developed methods and contributions include: (a) an improved method for manual image segmentation, (b) a new approach to 'complete' the segmented and reconstructed incomplete 3D images, (c) a polyhedral structural distance model to predict the polyhedral shapes of these microstructures, (d) a new shape descriptor for polyhedral shapes, named as polyhedron profile statistic, and (e) the Bayes classifier, linear discriminant analysis and support vector machine based classifiers for supervised incomplete polyhedral shape classification. Finally, the predicted 3D shapes for these bacterial microstructures belong to the Johnson solids family, and these shapes along with their other geometric properties are important for better understanding of their chemical and biological characteristics.

Stabilisation of dehydrated nanoemulsions using sugar - protein matrices

There are numerous review papers discussing liquid nanoemulsions and how they compare to other emulsion systems. Little research is available on dried nanoemulsions. The objectives of this research were to (i) study the effect of varying the continuous phase of nanoemulsions with different carbohydrate/protein ratios on subsequent emulsion stability, and (ii) compare the physicochemical properties, lactose crystallisation properties, microstructure, and lipid oxidation of spray dried nanoemulsions compared to spray dried conventional emulsions having different water and sugar contents. Nanoemulsions containing sunflower oil (10% w/w), β-casein (2.5–10% w/w) and lactose or trehalose (10–17.5%) were produced following optimisation of the continuous phase by maximising and minimising viscosity and glass transition temperature (Tg’) using mixture design software. Increasing levels of β-casein from caused a significant increase in viscosity, particle size, and nanoemulsion stability, while resulting in a decrease in Tg’. Powders were made from spray drying emulsions/nanoemulsions consisting of lactose or a 70:30 mixture of lactose:sucrose (23.9%), sodium caseinate (5.1%) and sunflower oil (11.5%) in water. Nanoemulsions, produced by microfluidisation (100 MPa), had higher stability and lower viscosity than control emulsions (homogenization at 17 MPa) with lower solvent extractable free fat in the resulting powder. Partial replacement of lactose with sucrose decreased Tg and delayed Tcr. DVS and PLM showed that in powdered nanoemulsions, lactose crystallises faster than in powdered conventional emulsions. Microstructure of both powders (CLSM and cryo-SEM) showed different FGS in powders and different structure post lactose crystallisation. Powdered nanoemulsions had lower pentanal and hexanal (indicators of lipid oxidation) after 24 months storage due to their lower free fat and porosity, measured using a validated GC HS-SPME method, This research has shown the effect of altering the continuous phase of nanoemulsions on microstructure of spray dried nanoemulsions, which affects physical properties, sugar crystallisation, and lipid oxidation.