Towards the Understanding and Development of Single Atom Alloy Catalysts from First Principles

Many industrial heterogeneous catalysts often use precious metals such as Pt and Pd thanks to their ability to catalyse a vast array of chemical reactions with exceptional activity. Unfortunately, the excellent reactivity of these metals results in poor selectivity, high susceptibility to poisoning and catalyst deactivation. One strategy that has been fruitful in overcoming these shortcomings is to alloy the catalytically active metals with those that are more selective, for example the coinage metals. A special class of these bimetallic surfaces may be formed by doping the inert host metal with a sufficiently low concentration of the catalytically active metal such that these dopant atoms isolate as individual, atomic dispersed ensembles in the surface layer of the host metal; such a material is known as a Single Atom Alloy (SAA). In this thesis, we use a dual-scale theoretical approach to develop a fundamental understanding of SAAs and their behaviour in catalytic systems. On the atomistic level, we make use of density functional theory (DFT) to investigate the electronic structure of SAAs, evaluating their thermodynamic stability and quantifying their surface interactions with various chemical species. Combining data acquired from DFT with kinetic Monte Carlo (KMC) simulation, we perform dynamic studies on length scales that are more relevant to real catalysis, allowing for the prediction of catalytic metrics. In particular, we show that the surface chemical heterogeneity of a SAAs results in novel catalytic properties, arising from combined weak adsorption and low activation energies for several bond dissociation reactions; that Pt/Cu SAAs can perform low temperature C-H bond without carbon deposition; and that SAAs offer strong resistivity to catalytic poisoning. Our findings will facilitate the discovery of new alloy catalysts that exhibit novel catalytic behaviour that can be fine-tuned in terms of activity, selectivity and stability

AGE-modified basement membrane cooperates with Endo180 to promote epithelial cell invasiveness and decrease prostate cancer survival

Biomechanical strain imposed by age-related thickening of the basal lamina and augmented tissue stiffness in the prostate gland coincides with increased cancer risk. Here we hypothesized that the structural alterations in the basal lamina associated with age can induce mechanotransduction pathways in prostate epithelial cells (PECs) to promote invasiveness and cancer progression. To demonstrate this, we developed a 3D model of PEC acini in which thickening and stiffening of basal lamina matrix was induced by advanced glycation end-product (AGE)-dependent non-enzymatic crosslinking of its major components, collagen IV and laminin. We used this model to demonstrate that antibody targeted blockade of CTLD2, the second of eight C-type lectin-like domains in Endo180 (CD280, CLEC13E, KIAA0709, MRC2, TEM9, uPARAP) that can recognize glycosylated collagens, reversed actinomyosin-based contractility [myosin-light chain-2 (MLC2) phosphorylation], loss of cell polarity, loss of cell–cell junctions, luminal infiltration and basal invasion induced by AGE-modified basal lamina matrix in PEC acini. Our in vitro results were concordant with luminal occlusion of acini in the prostate glands of adult Endo180ΔEx2–6/ΔEx2–6 mice, with constitutively exposed CTLD2 and decreased survival of men with early (non-invasive) prostate cancer with high epithelial Endo180 expression and levels of AGE. These findings indicate that AGE-dependent modification of the basal lamina induces invasive behaviour in non-transformed PECs via a molecular mechanism linked to cancer progression. This study provides a rationale for targeting CTLD2 in Endo180 in prostate cancer and other pathologies in which increased basal lamina thickness and tissue stiffness are driving factors

Understanding the yeast host cell response to recombinant membrane protein production

Membrane proteins are drug targets for a wide range of diseases. Having access to appropriate samples for further research underpins the pharmaceutical industry's strategy for developing new drugs. This is typically achieved by synthesizing a protein of interest in host cells that can be cultured on a large scale, allowing the isolation of the pure protein in quantities much higher than those found in the protein's native source. Yeast is a popular host as it is a eukaryote with similar synthetic machinery to that of the native human source cells of many proteins of interest, while also being quick, easy and cheap to grow and process. Even in these cells, the production of human membrane proteins can be plagued by low functional yields; we wish to understand why. We have identified molecular mechanisms and culture parameters underpinning high yields and have consolidated our findings to engineer improved yeast host strains. By relieving the bottlenecks to recombinant membrane protein production in yeast, we aim to contribute to the drug discovery pipeline, while providing insight into translational processes

The M3 muscarinic receptor Is required for optimal adaptive immunity to Helminth and bacterial infection

Innate immunity is regulated by cholinergic signalling through nicotinic acetylcholine receptors. We show here that signalling through the M3 muscarinic acetylcholine receptor (M3R) plays an important role in adaptive immunity to both Nippostrongylus brasiliensis and Salmonella enterica serovar Typhimurium, as M3R-/- mice were impaired in their ability to resolve infection with either pathogen. CD4 T cell activation and cytokine production were reduced in M3R-/- mice. Immunity to secondary infection with N. brasiliensis was severely impaired, with reduced cytokine responses in M3R-/- mice accompanied by lower numbers of mucus-producing goblet cells and alternatively activated macrophages in the lungs. Ex vivo lymphocyte stimulation of cells from intact BALB/c mice infected with N. brasiliensis and S. typhimurium with muscarinic agonists resulted in enhanced production of IL-13 and IFN-γ respectively, which was blocked by an M3R-selective antagonist. Our data therefore indicate that cholinergic signalling via the M3R is essential for optimal Th1 and Th2 adaptive immunity to infection

Improving pregnancy outcomes in humans through studies in sheep

Experimental studies that are relevant to human pregnancy rely on the selection of appropriate animal models as an important element in experimental design. Consideration of the strengths and weaknesses of any animal model of human disease is fundamental to effective and meaningful translation of preclinical research. Studies in sheep have made significant contributions to our understanding of the normal and abnormal development of the fetus. As a model of human pregnancy, studies in sheep have enabled scientists and clinicians to answer questions about the etiology and treatment of poor maternal, placental, and fetal health and to provide an evidence base for translation of interventions to the clinic. The aim of this review is to highlight the advances in perinatal human medicine that have been achieved following translation of research using the pregnant sheep and fetus

Generation and transmission of interlineage recombinants in the SARS-CoV-2 pandemic.

We present evidence for multiple independent origins of recombinant SARS-CoV-2 viruses sampled from late 2020 and early 2021 in the United Kingdom. Their genomes carry single-nucleotide polymorphisms and deletions that are characteristic of the B.1.1.7 variant of concern but lack the full complement of lineage-defining mutations. Instead, the remainder of their genomes share contiguous genetic variation with non-B.1.1.7 viruses circulating in the same geographic area at the same time as the recombinants. In four instances, there was evidence for onward transmission of a recombinant-origin virus, including one transmission cluster of 45 sequenced cases over the course of 2 months. The inferred genomic locations of recombination breakpoints suggest that every community-transmitted recombinant virus inherited its spike region from a B.1.1.7 parental virus, consistent with a transmission advantage for B.1.1.7's set of mutations.The COG-UK Consortium is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) (MC_PC_19027), and Genome Research Limited, operating as the Wellcome Sanger Institute. O.G.P. was supported by the Oxford Martin School. J.T.M., R.M.C., N.J.L., and A.R. acknowledge the support of the Wellcome Trust (Collaborators Award 206298/Z/17/Z – ARTIC network). D.L.R. acknowledges the support of the MRC (MC_UU_12014/12) and the Wellcome Trust (220977/Z/20/Z). E.S. and A.R. are supported by the European Research Council (grant agreement no. 725422 – ReservoirDOCS). T.R.C. and N.J.L. acknowledge the support of the MRC, which provided the funding for the MRC CLIMB infrastructure used to analyze, store, and share the UK sequencing dataset (MR/L015080/1 and MR/T030062/1). The samples sequenced in Wales were sequenced partly using funding provided by the Welsh Government

A foundation model for atomistic materials chemistry

Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations of ab initio quality on unprecedented time and length scales. However, they are currently limited by: (i) the significant computational and human effort that must go into development and validation of potentials for each particular system of interest; and (ii) a general lack of transferability from one chemical system to the next. Here, using the state-of-the-art MACE architecture we introduce a single general-purpose ML model, trained on a public database of 150k inorganic crystals, that is capable of running stable molecular dynamics on molecules and materials. We demonstrate the power of the MACE-MP-0 model - and its qualitative and at times quantitative accuracy - on a diverse set problems in the physical sciences, including the properties of solids, liquids, gases, chemical reactions, interfaces and even the dynamics of a small protein. The model can be applied out of the box and as a starting or "foundation model" for any atomistic system of interest and is thus a step towards democratising the revolution of ML force fields by lowering the barriers to entry.Comment: 119 pages, 63 figures, 37MB PD

Natural and Vaccine-Mediated Immunity to Salmonella Typhimurium is Impaired by the Helminth Nippostrongylus brasiliensis

The impact of exposure to multiple pathogens concurrently or consecutively on immune function is unclear. Here, immune responses induced by combinations of the bacterium Salmonella Typhimurium (STm) and the helminth Nippostrongylus brasiliensis (Nb), which causes a murine hookworm infection and an experimental porin protein vaccine against STm, were examined. Mice infected with both STm and Nb induced similar numbers of Th1 and Th2 lymphocytes compared with singly infected mice, as determined by flow cytometry, although lower levels of secreted Th2, but not Th1 cytokines were detected by ELISA after re-stimulation of splenocytes. Furthermore, the density of FoxP3+ T cells in the T zone of co-infected mice was lower compared to mice that only received Nb, but was greater than those that received STm. This reflected the intermediate levels of IL-10 detected from splenocytes. Co-infection compromised clearance of both pathogens, with worms still detectable in mice weeks after they were cleared in the control group. Despite altered control of bacterial and helminth colonization in co-infected mice, robust extrafollicular Th1 and Th2-reflecting immunoglobulin-switching profiles were detected, with IgG2a, IgG1 and IgE plasma cells all detected in parallel. Whilst extrafollicular antibody responses were maintained in the first weeks after co-infection, the GC response was less than that in mice infected with Nb only. Nb infection resulted in some abrogation of the longer-term development of anti-STm IgG responses. This suggested that prior Nb infection may modulate the induction of protective antibody responses to vaccination. To assess this we immunized mice with porins, which confer protection in an antibody-dependent manner, before challenging with STm. Mice that had resolved a Nb infection prior to immunization induced less anti-porin IgG and had compromised protection against infection. These findings demonstrate that co-infection can radically alter the development of protective immunity during natural infection and in response to immunization

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships