How big does the effect of an intervention have to be? Application of two novel methods to determine the smallest worthwhile effect of a fall prevention programme: A study protocol

Introduction: This project concerns the identification of the smallest worthwhile effect (SWE) of exercise-based programmes to prevent falls in older people. The SWE is the smallest effect that justifies the costs, risks and inconveniences of an intervention and is used to inform the design and interpretation of systematic reviews and randomised clinical trials. Methods and analysis: This study will comprise two different methodological approaches: the benefitharm trade-off method and the discrete choice experiment to estimate the SWE of exercise interventions to prevent falls in older people. In the benefit-harm trade-off method, hypothetical scenarios with the benefits, costs, risks and inconveniences associated with the intervention will be presented to each participant. Then, assuming a treatment effect of certain magnitude, the participant will be asked if he or she would choose to have the intervention. The size of the hypothetical benefit will be varied up and down until it is possible to identify the SWE for which the participant would choose to have the intervention. In the discrete choice experiment, the same attributes (benefits, costs, risks and inconveniences) with varying levels will be presented as choice sets, and participants will be asked to choose between these choice sets. With this approach, we will determine the probability that a person will consider the effects of an intervention to be worthwhile, given the particular costs, risks and inconveniences. For each of the two approaches, participants will be interviewed in person and on different occasions. A subsample of the total cohort will participate in both interviews. Ethics and dissemination: This project has received Ethics Approval from the University of Sydney Human Ethics Committee (Protocol number: 14404). Findings will be disseminated through conference presentations, seminars and peer-reviewed scientific journals

Design of Experiments Methodology to Build a Multifactorial Statistical Model Describing the Metabolic Interactions of Alcohol Dehydrogenase Isozymes in the Ethanol Biosynthetic Pathway of the Yeast Saccharomyces cerevisiae

This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this recordMultifactorial approaches can quickly and efficiently model complex, interacting natural or engineered biological systems in a way that traditional one-factor-at-a-time experimentation can fail to do. We applied a Design of Experiments (DOE) approach to model ethanol biosynthesis in yeast, which is well-understood and genetically tractable, yet complex. Six alcohol dehydrogenase (ADH) isozymes catalyze ethanol synthesis, differing in their transcriptional and post-translational regulation, subcellular localization, and enzyme kinetics. We generated a combinatorial library of all ADH gene deletions and measured the impact of gene deletion(s) and environmental context on ethanol production of a subset of this library. The data were used to build a statistical model that described known behaviors of ADH isozymes and identified novel interactions. Importantly, the model described features of ADH metabolic behavior without explicit a priori knowledge. The method is therefore highly suited to understanding and optimizing metabolic pathways in less well-understood systems.We wish to thank Dr. Alex Johns for helpful discussions. S.R.B. would also like to thank Shell Biodomain for funding for this PhD research project

Rapid, Heuristic Discovery and Design of Promoter Collections in Non-Model Microbes for Industrial Applications

This is the author accepted manusript. The final version is available from American Chemical Society via the DOI in this recordAccession Codes: The sequence data for the four Geobacillus spp. used in this study have been submitted to the NCBI Sequence Read Archive and are available under the accession number PRJNA521450.Well-characterized promoter collections for synthetic biology applications are not always available in industrially relevant hosts. We developed a broadly applicable method for promoter identification in atypical microbial hosts that requires no a priori understanding of cis-regulatory element structure. This novel approach combines bioinformatic filtering with rapid empirical characterization to expand the promoter toolkit and uses machine learning to improve the understanding of the relationship between DNA sequence and function. Here, we apply the method in Geobacillus thermoglucosidasius, a thermophilic organism with high potential as a synthetic biology chassis for industrial applications. Bioinformatic screening of G. kaustophilus, G. stearothermophilus, G. thermodenitrificans, and G. thermoglucosidasius resulted in the identification of 636 100 bp putative promoters, encompassing the genome-wide design space and lacking known transcription factor binding sites. Eighty of these sequences were characterized in vivo, and activities covered a 2-log range of predictable expression levels. Seven sequences were shown to function consistently regardless of the downstream coding sequence. Partition modeling identified sequence positions upstream of the canonical -35 and -10 consensus motifs that were predicted to strongly influence regulatory activity in Geobacillus, and artificial neural network and partial least squares regression models were derived to assess if there were a simple, forward, quantitative method for in silico prediction of promoter function. However, the models were insufficiently general to predict pre hoc promoter activity in vivo, most probably as a result of the relatively small size of the training data set compared to the size of the modeled design space

Neutron studies of Na-ion battery materials

The relative vast abundance and more equitable global distribution of terrestrial sodium makes sodium-ion batteries (NIBs) potentially cheaper and more sustainable alternatives to commercial lithium-ion batteries (LIBs). However, the practical capacities and cycle lives of NIBs at present do not match those of LIBs and have therefore hindered their progress to commercialisation. The present drawback of NIB technology stems largely from the electrode materials and their associated Na+ion storage mechanisms. Increased understanding of the electrochemical storage mechanisms and kinetics is therefore vital for the development of current and novel materials to realise the commercial NIB. In contrast to x-ray techniques, the non-dependency of neutron scattering on the atomic number of elements (Z) can substantially increase the scattering contrast of small elements such as sodium and carbon, making neutron techniques powerful for the investigation of NIB electrode materials. Moreover, neutrons are far more penetrating which enables more complex sample environments including in situ and operando studies. Here, we introduce the theory of, and review the use of, neutron diffraction and quasi-elastic neutron scattering, to investigate the structural and dynamic properties of electrode and electrolyte materials for NIBs. To improve our understanding of the actual sodium storage mechanisms and identify intermediate stages during charge/discharge, ex situ, in situ, and operando neutron experiments are required. However, to date there are few studies where operando experiments are conducted during electrochemical cycling. This highlights an opportunity for research to elucidate the operating mechanisms within NIB materials that are under much debate at present

Neutron studies of Na-ion battery materials

The relative vast abundance and more equitable global distribution of terrestrial sodium makes sodium-ion batteries (NIBs) potentially cheaper and more sustainable alternatives to commercial lithium-ion batteries (LIBs). However, the practical capacities and cycle lives of NIBs at present do not match those of LIBs and have therefore hindered their progress to commercialisation. The present drawback of NIB technology stems largely from the electrode materials and their associated Na+ion storage mechanisms. Increased understanding of the electrochemical storage mechanisms and kinetics is therefore vital for the development of current and novel materials to realise the commercial NIB. In contrast to x-ray techniques, the non-dependency of neutron scattering on the atomic number of elements (Z) can substantially increase the scattering contrast of small elements such as sodium and carbon, making neutron techniques powerful for the investigation of NIB electrode materials. Moreover, neutrons are far more penetrating which enables more complex sample environments including in situ and operando studies. Here, we introduce the theory of, and review the use of, neutron diffraction and quasi-elastic neutron scattering, to investigate the structural and dynamic properties of electrode and electrolyte materials for NIBs. To improve our understanding of the actual sodium storage mechanisms and identify intermediate stages during charge/discharge, ex situ, in situ, and operando neutron experiments are required. However, to date there are few studies where operando experiments are conducted during electrochemical cycling. This highlights an opportunity for research to elucidate the operating mechanisms within NIB materials that are under much debate at present

Synthesis of customized petroleum-replica fuel molecules by targeted modification of free fatty acid pools in Escherichia coli.

This is the final version of the article. Available from National Academy of Sciences via the DOI in this record.Data deposition: The synthetic nucleotide sequences reported in this paper have been deposited in GenBank database (accession nos. JQ901708, JQ901709, and JQ901710).Biofuels are the most immediate, practical solution for mitigating dependence on fossil hydrocarbons, but current biofuels (alcohols and biodiesels) require significant downstream processing and are not fully compatible with modern, mass-market internal combustion engines. Rather, the ideal biofuels are structurally and chemically identical to the fossil fuels they seek to replace (i.e., aliphatic n- and iso-alkanes and -alkenes of various chain lengths). Here we report on production of such petroleum-replica hydrocarbons in Escherichia coli. The activity of the fatty acid (FA) reductase complex from Photorhabdus luminescens was coupled with aldehyde decarbonylase from Nostoc punctiforme to use free FAs as substrates for alkane biosynthesis. This combination of genes enabled rational alterations to hydrocarbon chain length (Cn) and the production of branched alkanes through upstream genetic and exogenous manipulations of the FA pool. Genetic components for targeted manipulation of the FA pool included expression of a thioesterase from Cinnamomum camphora (camphor) to alter alkane Cn and expression of the branched-chain α-keto acid dehydrogenase complex and β-keto acyl-acyl carrier protein synthase III from Bacillus subtilis to synthesize branched (iso-) alkanes. Rather than simply reconstituting existing metabolic routes to alkane production found in nature, these results demonstrate the ability to design and implement artificial molecular pathways for the production of renewable, industrially relevant fuel molecules.This work was supported by a grant from Shell Research Ltd. and a Biotechnology and Biological Sciences Research Council (BBSRC) Industry Interchange Partnership grant (to J.L.)

Developing a model for decision-making around antibiotic prescribing for patients with COVID-19 pneumonia in acute NHS hospitals during the first wave of the COVID-19 pandemic: Qualitative results from the Procalcitonin Evaluation of Antibiotic use in COVID-19 Hospitalised patients (PEACH Study)

\ua9 Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Objective To explore and model factors affecting antibiotic prescribing decision-making early in the pandemic. Design Semistructured qualitative interview study. Setting National Health Service (NHS) trusts/health boards in England and Wales. Participants Clinicians from NHS trusts/health boards in England and Wales. Method Individual semistructured interviews were conducted with clinicians in six NHS trusts/health boards in England and Wales as part of the Procalcitonin Evaluation of Antibiotic use in COVID-19 Hospitalised patients study, a wider study that included statistical analysis of procalcitonin (PCT) use in hospitals during the first wave of the pandemic. Thematic analysis was used to identify key factors influencing antibiotic prescribing decisions for patients with COVID-19 pneumonia during the first wave of the pandemic (March to May 2020), including how much influence PCT test results had on these decisions. Results During the first wave of the pandemic, recommendations to prescribe antibiotics for patients with COVID-19 pneumonia were based on concerns about secondary bacterial infections. However, as clinicians gained more experience with COVID-19, they reported increasing confidence in their ability to distinguish between symptoms and signs caused by SARS-CoV-2 viral infection alone, and secondary bacterial infections. Antibiotic prescribing decisions were influenced by factors such as clinician experience, confidence, senior support, situational factors and organisational influences. A decision-making model was developed. Conclusion This study provides insight into the decision-making process around antibiotic prescribing for patients with COVID-19 pneumonia during the first wave of the pandemic. The importance of clinician experience and of senior review of decisions as factors in optimising antibiotic stewardship is highlighted. In addition, situational and organisational factors were identified that could be optimised. The model presented in the study can be used as a tool to aid understanding of the complexity of the decision-making process around antibiotic prescribing and planning antimicrobial stewardship support in the context of a pandemic. Trial registration number ISRCTN66682918

Key reaction components affect the kinetics and performance robustness of cell-free protein synthesis reactions

This is the final version. Available on open access from Elsevier via the DOI in this recordData statement: All data are available both in Source Data files associated with this publication, and at https://doi.org/10.25405/data.ncl.17041931Cell-free protein synthesis (CFPS) reactions have grown in popularity with particular interest in applications such as gene construct prototyping, biosensor technologies and the production of proteins with novel chemistry. Work has frequently focussed on optimising CFPS protocols for improving protein yield, reducing cost, or developing streamlined production protocols. Here we describe a statistical Design of Experiments analysis of 20 components of a popular CFPS reaction buffer. We simultaneously identify factors and factor interactions that impact on protein yield, rate of reaction, lag time and reaction longevity. This systematic experimental approach enables the creation of a statistical model capturing multiple behaviours of CFPS reactions in response to components and their interactions. We show that a novel reaction buffer outperforms the reference reaction by 400% and importantly reduces failures in CFPS across batches of cell lysates, strains of E. coli, and in the synthesis of different proteins. Detailed and quantitative understanding of how reaction components affect kinetic responses and robustness is imperative for future deployment of cell-free technologies.Engineering and Physical Sciences Research Council (EPSRC

The yeast P5 type ATPase, Spf1, regulates manganese transport into the endoplasmic reticulum

The endoplasmic reticulum (ER) is a large, multifunctional and essential organelle. Despite intense research, the function of more than a third of ER proteins remains unknown even in the well-studied model organism Saccharomyces cerevisiae. One such protein is Spf1, which is a highly conserved, ER localized, putative P-type ATPase. Deletion of SPF1 causes a wide variety of phenotypes including severe ER stress suggesting that this protein is essential for the normal function of the ER. The closest homologue of Spf1 is the vacuolar P-type ATPase Ypk9 that influences Mn2+ homeostasis. However in vitro reconstitution assays with Spf1 have not yielded insight into its transport specificity. Here we took an in vivo approach to detect the direct and indirect effects of deleting SPF1. We found a specific reduction in the luminal concentration of Mn2+ in ∆spf1 cells and an increase following it’s overexpression. In agreement with the observed loss of luminal Mn2+ we could observe concurrent reduction in many Mn2+-related process in the ER lumen. Conversely, cytosolic Mn2+-dependent processes were increased. Together, these data support a role for Spf1p in Mn2+ transport in the cell. We also demonstrate that the human sequence homologue, ATP13A1, is a functionally conserved orthologue. Since ATP13A1 is highly expressed in developing neuronal tissues and in the brain, this should help in the study of Mn2+-dependent neurological disorders