Tamar Louise Greaves

The measurement of intracellular reactive oxygen species (ROS) levels provides critical insights into cell health and pathophysiology. Here, we present a semi-quantitative, plate reader-based protocol using CellROX Green that can be used for the real-time measurement of general ROS levels of viable suspension mammalian cells. With menadione being the oxidative stress inducer, a cell concentration of 100,000 cells per well, a CellROX Green concentration of 10 µM, and a CellROX Green incubation time of 1 h was shown to provide the most accurate measurement of intracellular ROS levels in viable human monocyte leukemia (THP-1) cells. Unlike plate reader protocols using other general ROS-sensitive fluorogenic probes, this plate reader protocol eliminates the washing step of the unbound probe prior to measuring fluorescence, making it more suitable for suspension cells. Using the presented protocol, the fluorescence of up to 96 samples can be measured in under 1 min, making it ideal for rapid screening applications where moderate to large differences in oxidative stress levels are to be measured.

In aqueous solutions proline and ethylene glycol act independently where ethylene glycol can permeate cells but proline cannot.

Linear and non-linear machine learning models predicted T_m and ΔH_f of 182 protic salts, achieving R² as high as 0.82. Experimental cross-validation demonstrated the acceptable predictive ability of linear models for both T_m and ΔH_f.

Protic ionic liquids (PILs) are a class of ionic liquids that have an available proton for hydrogen bonding, offering unique physicochemical properties with applications in various fields, such as catalysis, energy storage, and separation processes. Despite their potential, the crystal structures of PILs remain underexplored due to their innate preference for amorphous phases, even as solids. This study investigates the crystal structures and phase behavior of a series of 24 alkylammonium-based PILs (with melting points up to 425 K) using synchrotron x-ray powder diffraction. Of these, 18 were able to be crystallized, and full crystal structures were obtained for 5. Our results reveal that the PILs investigated can be broadly divided into two groups, those with hydrogen-bonded networks dominating and those with a lamellar structure, separated into hydrophobic and hydrophilic regions. For both groups, the bonding dominant in the crystalline phase is similar to that of the liquid state. We discuss the challenges in crystallizing PILs and the approaches that can be used, laying the groundwork for further exploration of their structures.

Deep eutectic solvents are an exciting class of designer solvents that are increasingly gaining popularity. Deep eutectic solvents based on amino acids are particularly interesting for biomedical applications due to their potential low toxicity. However, very few have been reported to date, and only one of these has been comprehensively studied, made from a combination of proline and glycerol. Here, we report for the first time a systematic investigation into amino acid-based deep eutectic solvents, with a particular focus on the structural features of amino acids that promote eutectic formation and their influence on viscosity, refractive index, surface tension and thermal behavior. Of the 22 amino acids (and related compounds) examined, only 3 (lysine, arginine and, as previously reported, proline) formed stable homogenous liquids in combination with glycerol or ethylene glycol. For these mixtures, it was found that the second component (glycerol or ethylene glycol) had a much more significant influence on the physical properties than the identity of the amino acid. Most significantly, it was found that far fewer amino acids readily formed deep eutectic solvents than has been generally assumed. This is the first work to systematically characterize deep eutectic solvents based on amino acids and, as such, paves the way for future biomedical applications of these solvents.

Protein-nanoparticle interactions and the resulting corona formation play crucial roles in the behavior and functionality of nanoparticles in biological environments. In this study, we present a comprehensive analysis of protein corona formation with superfolder green fluorescent protein (sfGFP) and bovine serum albumin in silica nanoparticle dispersions using small-angle X-ray scattering (SAXS) and dynamic light scattering (DLS). For the first time, we subtracted the scattering of individual proteins in solution and individual nanoparticles from the protein-nanoparticle complexes. This approach effectively isolated the contributions of specific components within the corona. Our form factor analysis revealed consistent core-shell sphere thicknesses but varied attractive interaction strengths of the nanoparticle complexes, influenced by the protein corona and the surface properties of silica and aminated silica nanoparticles. Interestingly, fractal analysis of nanoparticles showed a transition from surface to mass fractals for sfGFP samples at high protein:nanoparticle molar ratios of over 264,000:1. DLS analysis highlighted aggregation behaviors, including the increasing size of protein-nanoparticle complexes and significant aggregation of both free proteins and complexes at ∼264,000 molar ratio. Large polydispersity and heterogeneous protein aggregation were observed at these high molar ratios. Both SAXS and DLS revealed transitions and changes in protein-nanoparticle interactions at molar ratios of 4000 to 44,000, consistent with corona formation, while pronounced aggregation was observed at a molar ratio of ∼264,000. These findings advance our understanding of the structural complexities in protein-nanoparticle association and suggest further avenues for refining characterization techniques in protein corona research.

Fluctuation scattering techniques (also known as x-ray cross-correlation analysis techniques) aim to extract 3D structural information from scanning diffraction experiments via statistical analysis methods, typically based on correlating diffracted intensities [ 1]. There are opportunities to study the nanostructure of disordered and polycrystalline materials, nanoparticle assemblies [ 2] and to image viruses and nanoparticles [ 3]. These methods use similar microfocus or nanofocus beam conditions to ptychography and spectroscopic mapping techniques and represent a route to add new capabilities to existing spectromicroscopy beamlines. A key challenge for fluctuation scattering methods is interpreting the results in terms of real space structure [ 1]. Here we present different approaches for interpreting fluctuation scattering results in real-space. As shown in Fig. 1, for disordered samples it is possible to extract the pair-angle distribution (PADF) function which is higher order form of the well-known pair-distribution function [ 4, 5]. We explain how the PADF can reveal 3D nanostructural information in highly disordered materials and show examples from thermotropic and lyotropic liquid crystals [ 6]. For polycrystalline materials we show how, depending on beam size and domain size, we can gain insights into the microtexture (orientation distribution of the grains) or the structure of the unit cell [ 7]. We also present an algorithm that can extract crystallographic structure factors to provide a route to structure determination via correlation analysis [ 8]. There is significant potential to grow these capabilities in a way that is complimentary to existing imaging and mapping techniques, and which may allow access to nanostructural information that is otherwise inaccessible. Figure 1 Diffraction data is collected with a scanning focused beam (top). The measurements contain either speckled coherent diffraction or spotty textured rings. These are analysed statistically to produce angular intensity correlation functions (left), which are converted into real-space to obtain the PADF (right). Common combinations of three and four atoms produce peaks in the PADF, allowing the identification of local nanostructure.