6,197 research outputs found

    Understanding the Chemistry of Acetohydroxamic Acid (AHA) in the Presence of Fe(III) in the Context of an Advanced PUREX Process

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    Since the 1950s, the majority of operating commercial nuclear fuel reprocessing plants, including those in the UK, France, Russia and Japan, have used the well-proven hydrometallurgical PUREX (plutonium uranium extraction) process, or a variant PUREXbased process to chemically separate uranium (U) and plutonium (Pu) from used nuclear fuel. However, enhancements to PUREX are needed for future fuel cycles to improve its proliferation resistance, its capability to handle higher burnup fuels and to minimize its waste arisings. A key objective within the development of an Advanced PUREX process is the effective control of the actinides U, neptunium (Np) and Pu within a single cycle flowsheet. Simple hydroxamic acids such as acetohydroxamic acid (AHA) have the ability to strip Pu(IV) and Np(IV) from tri-butyl phosphate into nitric acid and have thus been identified as suitable reagents for this purpose. Utilising this in an Advanced PUREX process will ultimately allow for the generation of a co-processed Pu/Np product and a high purity U product, addressing some of the shortcomings of traditional PUREX. There are however a few key knowledge gaps that must be addressed before AHA can be implemented in such a process. Firstly, it is known that simple hydroxamic acids hydrolyse to hydroxylamine (NH2OH) and the parent carboxylic acid in acidic media, the former product being known to react autocatalytically / explosively with nitric acid which is ubiquitous in reprocessing flowsheets. Whether the reaction mechanism or product distribution changes when the AHA is complexed to a metal ion is unclear. Additionally, observations that Pu(IV) is reduced to Pu(III) during complex hydrolysis have opened up the possibility of their use as replacements for U(IV)/N2H4 or NH2OH in advanced PUREX processes, but whether the reducing agent is the hydroxamate itself, or NH2OH, is still in question. To answer these questions, Fe(III) has been used as a non-active analogue to Pu(IV) and Np(IV), as it exhibits analogous complexation with AHA and whilst thermodynamically possible, redox chemistry mechanistically analogous to that of Pu(IV) is thought to be kinetically hindered at high hydrogen ion concentrations to the point where it can be ignored on the timescales of AHA hydrolysis. However, initial studies by Raman spectroscopy showed identical AHA hydrolysis products in the absence and presence of initial Fe(III), but with differing final yields. Further quantification techniques were then explored including a titrimetric method for hydroxylamine, UV-Vis spectroscopy for nitrous acid and Fe(II), and ion chromatography (IC) for multiple species, all of which suggested redox chemistry akin to Pu(IV). A library of data to describe these systems has been gathered utilising a single column ion chromatography system to measure a number of key ions over time in nitric acid solutions of varying temperatures and initial Fe(III) and AHA concentrations. These key species include the acetate ion (CH3COO- ) and protonated hydroxylamine (NH3OH+) from the hydrolysis of AHA, and the reduced form of the metal ion, Fe(II), which has been not previously been seen during hydrolysis of the Fe(III)-AHA complex. Our analysis therefore shows that the current definition of Fe(III) as a non-oxidizing metal ion with regards to AHA needs revising. Using CH3COOingrowth as a direct measure of AHA loss and assuming redox chemistry of Fe(III) mechanistically analogous to Pu(IV), these studies have additionally been combined with kinetic modelling in the software platform gPROMS (General PROcess Modelling System), and have thus provided key insights into the nature of the reducing agent in these systems

    The organisation and function of the gut microbiota in cystic fibrosis

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    People with cystic fibrosis (pwCF) suffer from a range of gastrointestinal manifestations of disease, which has increased in prevalence as respiratory outcomes improve and life expectancy raises. This translates to the occurrence of daily GI symptoms for many pwCF, which is a top research priority to alleviate. The gut microbiota is altered in CF and has been shown to associate with intestinal abnormalities, therefore offers a potential avenue of therapeutic intervention by its modulation. This thesis investigated relationships between the microbiota and associated functions, intestinal outcomes, and cystic fibrosis transmembrane regulator (CFTR) modulator usage. Initially, relationships between altered intestinal function and physiology in CF were revealed with microbiota, by combining 16S rRNA gene sequencing data with magnetic resonance imaging (MRI) results and clinical metadata across pwCF and healthy controls. Significant differences in diversity and composition were observed between groups, which further associated with clinical factors and markers of intestinal function. To understand how microbiota function might be compromised in CF, a sensitive method to profile and quantify faecal short-chain fatty acids (SCFAs) using gas chromatography-mass spectrometry (GC-MS) was validated. This was subsequently used to demonstrate that overall SCFA compositional differences persist between healthy controls pwCF receiving Tezacaftor/Ivacaftor CFTR modulator therapy, further extending to microbiota compositional differences, which were also not significantly altered by treatment. Finally, microbiota composition and function were assessed across pwCF receiving more efficacious Elexacaftor/Tezacaftor/Ivacaftor (ETI) therapy. Subtle differences were observed following extended ETI administration, yet microbiota and SCFA compositions remained significantly different from controls. Interestingly, there were no differences across the most abundant SCFAs, indicating possible functional redundancy in the CF microbiota. Overall, the results obtained in this thesis advocate for further investigation of microbiota function through more sophisticated metagenomic and untargeted metabolomic approaches, to unravel the complex relationships between the microbiota, gastrointestinal (GI) manifestations, and patient symptoms in CF

    Activating Methane and Other Small Molecules: Computational study of Zeolites and Actinides

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    Exploring the catalytic properties and reactivity of actinide complexes towards activation of small molecules is important as human activities have led to the increased distribution of these species in nature. Toward this end, it is important to have a computational protocol for studying these species, in this thesis we provide details on the performance of multiconfigurational pair-density functional theory (MC-PDFT) in actinide chemistry. MC-PDFT and Kohn-Sham Density Functional Theory (KS-DFT) perform well for these species with indications that the former can be used for species with even greater static electron correlation effect. In addition, we study the activity of organometallic trans-uranium complexes towards the electrocatalytic reduction of water. We conclude that, with a guided choice of ligand, neptunium complexes can provide similar reactivity when compared to organometallic uranium complexes.Conversion of methane to methanol has been a major focus of research interest over the years. This is largely due to the abundance of natural gas, of which methane is the major constituent. Copper-exchanged zeolites have been shown to be able to kinetically trap activated methane as strongly-bound methoxy groups, preventing over-oxidation to CO2, CO and HCOOH. In this stepwise process, there are three cycles; an initial activation step to form the copper oxo active site, methane C-H activation and lastly simultaneous desorption of methanol and re -activation of the active site.. We provide detailed description of the pathway for the formation of over oxidation products. It is observed that to ensure high selectivity to methanol and prevent further hydrogen atom abstraction by extra-framework species, the methyl group must be stabilized from the copper-oxo active sites. There is a temperature gradient between the steps in the methane-to-methanol conversion cycle which is an impediment to industrial adoption of this approach for methane-to-methanol conversion. To mitigate this, we have investigated the impact of heterometallic extra-framework motifs on the temperature gradients of each step. Using periodic DFT, we provide detailed descriptions of the mechanistic pathways for each of the three steps. We were subsequently able to design motif(s) with great methane C-H activities as well as the abilities to be formed and regenerated at nearly the same temperatures. We found [Cu-O-Ag] and [Cu-O-Pd] to be potential candidates for isothermal or near-isothermal operations of the methane-to-methanol conversion cycle. Finally, we provide insights to the changes in optical spectra of activated copper-exchanged zeolites, gaining an understanding of the evolution of these systems on a molecular level will provide opportunities to achieve improved reactivity

    Machine Learning Model for Repurposing Drugs to Target Viral Diseases

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    With recent events, such as the Covid-19 pandemic, it is increasingly important to develop strategies to combat viral diseases. Due to technological advancements, computer-aided drug design and machine learning (ML)-based hit identification strategies have gained popularity. Applying these techniques to identify novel scaffolds and/or repurpose existing therapeutics for viral diseases is a promising approach. As an avenue to improve existing classification models for antiviral applications, this thesis aimed to make improvements to non-binding data selection within these models. We created a classification model using molecular fingerprints to assess the performance of machine learning predictions when the model is trained using randomly selected and rationally selected non-binding datasets. Our analyses revealed that machine learning predictions can be improved using a rational selection approach. We further used this approach and trained three machine learning models based on XGBoost, Random Forest, and Support Vector Machine to predict potential inhibitors for the SARS-CoV2 main protease (Mpro) enzyme. Probability-ranked hits from the combined model were further analyzed using classical structure-based methods. The binding modes and affinities of the hits were identified using AutoDock Vina, and molecular dynamics simulations-enabled MM-GBSA calculations. The top hits identified from this multi-step screening approach revealed potential candidates that show improved affinity and stability than existing non-covalent Mpro inhibitors. Thus, our approach and the model could be useful for screening large ligand libraries

    Crystal Structures of Metal Complexes

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    This reprint contains 11 papers published in a Special Issue of Molecules entitled "Crystal Structures of Metal Complexes". I will be very happy if readers will be interested in the crystal structures of metal complexes

    Dissecting structural and biochemical features of DNA methyltransferase 1

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    DNA methylation is an epigenetic modification found in every branch of life. An essential enzyme for the maintenance of DNA methylation patterns in mammals is DNA methyltransferase 1 (DNMT1). Its recruitment is regulated through its large N-terminus, which contains six annotated domains. Although most of these have been assigned a function, we are still lacking a holistic understanding of the enzyme's spatio-temporal regulation. Interestingly, a large segment of the N-terminus is devoid of any known domain and appears to be disordered in its sequence. Over the past years, such disordered sequences have increasingly gained attention, due to their role in forming biomolecular condensates through liquid-liquid phase separation (LLPS). These liquid compartments offer specific environmental conditions distinct from the surrounding that can enhance protein recruitment and function. In this work, we explore a potential role for the intrinsically disordered domain (IDR) in the recruitment of DNMT1. Taking an evolutionary approach, we uncover that structural features of the region that are key for IDR function are highly conserved. Moreover, we find conserved biochemical signatures compatible with a role in LLPS. Using a reconstitution assay and an opto-genetic approach in cells, we for the first time show that the DNMT1 IDR is capable of undergoing LLPS in vitro and in vivo. In addition, we define a novel region of interest (ROI) of about 120 amino acids in the IDR that appears to have been inserted in the ancestor of eutherian mammals. Although the ROI has a distinct biochemical signature, we find no effect on the LLPS behavior of the IDR. Therefore, we discuss other potential roles of the ROI related to DNA methylation, for example, imprinting. Finally, we lay the foundation for investigating a biological function of the IDR and establish a system for screening DNMT1 mutant phenotypes in mouse embryonic stem cells. Swift depletion of the endogenous protein is enabled by degron-mediated degradation, while our optimized construct design and efficient derivation strategy ensure the robust expression of the large transgenes. In combination with different methods for DNA methylation read-out, this system can now be used to study the role of the IDR and ROI in maintaining the steady-state level of DNA methylation against mechanisms of passive and active demethylation, but also for studying phenotypes affecting the efficiency of DNMT1 recruitment in the future

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    H-bonds in Crambin: Coherence in an alpha helix

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    We applied coherence analysis to molecular dynamics simulations of the plant protein crambin, a thionin storage protein found in Abyssinian cabbage. Coherence analysis was developed by engineers to identify linear interactions, without statistical assumptions. Coherence is greater than 0.9 between the displacement of oxygen and nitrogen atoms of H bonds in alpha helices for frequencies between 0.391 GHz and 5.08 GHz (corresponding reciprocally to times of 2.56 ns and 0.197 ns). These H bonds act much like a linear system. Unrelated atoms have uncorrelated motions and much smaller coherence, say 0.02. Groups of atoms (that form a layer of an alpha helix) were averaged and the coherence function of two groups was evaluated. Layers of the alpha helix form a linear system, suggesting that the harmonic analysis of classical molecular dynamics can successfully describe the allosteric interactions of the layers of an alpha helix.Comment: Version accepted by the journal ACS Omega, including Supplemental Information. PubMed Central (for the NIH) PMC1011662
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