Publications by authors named "Glen R"

The gut microbiota-brain axis has been associated with the pathogenesis of numerous disorders, but the mechanism(s) underlying these links are generally poorly understood. Accumulating evidence indicates the involvement of gut microbe-derived metabolites. Circulating levels of the gut microbe/host co-metabolite -cresol sulfate (pCS) correlate with cerebrovascular event risk in individuals with chronic kidney disease (CKD), but whether this relationship is mechanistic is unclear.

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Pulmonary arterial hypertension (PAH) is characterised by endothelial dysfunction and pathological vascular remodelling, resulting in the occlusion of pulmonary arteries and arterioles, right ventricular hypertrophy, and eventually fatal heart failure. Targeting the apelin receptor with the novel, G protein-biased peptide agonist, MM07, is hypothesised to reverse the developed symptoms of elevated right ventricular systolic pressure and right ventricular hypertrophy. Here, the effects of MM07 were compared with the clinical standard-of-care endothelin receptor antagonist macitentan.

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Introduction: Almost all patients receiving mechanical ventilation (MV) in intensive care units (ICUs) require analgesia and sedation. The most widely used sedative drug is propofol, but there is uncertainty whether alpha2-agonists are superior. The alpha 2 agonists for sedation to produce better outcomes from critical illness (A2B) trial aims to determine whether clonidine or dexmedetomidine (or both) are clinically and cost-effective in MV ICU patients compared with usual care.

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Article Synopsis
  • - The COVID Moonshot was a collaborative, open-science effort focused on finding a new drug to inhibit the SARS-CoV-2 main protease, which is crucial for the virus's survival.
  • - Researchers developed a novel noncovalent, nonpeptidic inhibitor that stands out from existing drugs targeting the same protease, employing advanced techniques like machine learning and high-throughput structural biology.
  • - Over 18,000 compound designs, 490 ligand-bound x-ray structures, and extensive assay data were generated and shared openly, creating a comprehensive and accessible knowledge base for future drug discovery efforts against coronaviruses.
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Background: Communication between the gut microbiota and the brain is primarily mediated via soluble microbe-derived metabolites, but the details of this pathway remain poorly defined. Methylamines produced by microbial metabolism of dietary choline and L-carnitine have received attention due to their proposed association with vascular disease, but their effects upon the cerebrovascular circulation have hitherto not been studied.

Results: Here, we use an integrated in vitro/in vivo approach to show that physiologically relevant concentrations of the dietary methylamine trimethylamine N-oxide (TMAO) enhanced blood-brain barrier (BBB) integrity and protected it from inflammatory insult, acting through the tight junction regulator annexin A1.

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Introduction: Inductively coupled plasma mass spectrometry (ICP-MS) experiments generate complex multi-dimensional data sets that require specialist data analysis tools.

Objective: Here we describe tools to facilitate analysis of the ionome composed of high-throughput elemental profiling data.

Methods: IonFlow is a Galaxy tool written in R for ionomics data analysis and is freely accessible at https://github.

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Familial encephalopathy with neuroserpin inclusion bodies (FENIB) is a progressive neurodegenerative disease caused by point mutations in the gene for neuroserpin, a serine protease inhibitor of the nervous system. Different mutations are known that are responsible for mutant neuroserpin polymerization and accumulation as inclusion bodies in many cortical and subcortical neurons, thereby leading to cell death, dementia and epilepsy. Many efforts have been undertaken to elucidate the molecular pathways responsible for neuronal death.

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Signaling through the apelin receptor is beneficial for a number of diseases including pulmonary arterial hypertension. The endogenous small peptides, apelin and elabela/toddler, are downregulated in pulmonary arterial hypertension but are not suitable for exogenous administration owing to a lack of bioavailability, proteolytic instability and susceptibility to renal clearance. CMF-019, a small molecule apelin agonist that displays strong bias towards G protein signaling over β-arrestin (∼400 fold), may be more suitable.

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Enhanced/prolonged cAMP signalling has been suggested as a suppressor of cancer proliferation. Interestingly, two key modulators that elevate cAMP, the A receptor (AR) and phosphodiesterase 10A (PDE10A), are differentially co-expressed in various types of non-small lung cancer (NSCLC) cell-lines. Thus, finding dual-target compounds, which are simultaneously agonists at the AR whilst also inhibiting PDE10A, could be a novel anti-proliferative approach.

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Article Synopsis
  • The text discusses the difficulties of finding significant relationships between molecular markers and outcomes in complex omics data, specifically metabolomic profiles, due to high dimensionality and noise.
  • It introduces a univariate permutation procedure that uses parametric simulation based on a multivariate (log-)Normal distribution to accurately estimate significance levels while controlling type I error rates.
  • The methods were tested with both synthetic and real data, showing that they effectively indicate the number of independent metabolic effects and maintain stability in significance thresholds across various outcomes.
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Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces.

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Mass spectrometry technologies are widely used in the fields of ionomics and metabolomics to simultaneously profile the intracellular concentrations of, e.g., amino acids or elements in genome-wide mutant libraries.

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Obesity is a complex disorder where the genome interacts with diet and environmental factors to ultimately influence body mass, composition, and shape. Numerous studies have investigated how bulk lipid metabolism of adipose tissue changes with obesity and, in particular, how the composition of triglycerides (TGs) changes with increased adipocyte expansion. However, reflecting the analytical challenge posed by examining non-TG lipids in extracts dominated by TGs, the glycerophospholipid composition of cell membranes has been seldom investigated.

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Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner.

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Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchmarked and validated. We reanalyze the data generated by a recently published large-scale comparison of machine learning models for bioactivity prediction and arrive at a somewhat different conclusion.

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Bone morphogenetic proteins (BMPs) are multifunctional cytokines of the transforming growth factor β (TGFβ) superfamily with potential therapeutic applications due to their broad biological functionality. Designing BMP mimetics with specific activity will contribute to the translational potential of BMP-based therapies. Here, we report a BMP9 peptide mimetic, P3, designed from the type I receptor binding site, which showed millimolar binding affinities for the type I receptor activin receptor like kinase 1 (ALK1), ALK2 and ALK3.

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The predicted protein encoded by the APJ gene discovered in 1993 was originally classified as a class A G protein-coupled orphan receptor but was subsequently paired with a novel peptide ligand, apelin-36 in 1998. Substantial research identified a family of shorter peptides activating the apelin receptor, including apelin-17, apelin-13, and [Pyr]apelin-13, with the latter peptide predominating in human plasma and cardiovascular system. A range of pharmacological tools have been developed, including radiolabeled ligands, analogs with improved plasma stability, peptides, and small molecules including biased agonists and antagonists, leading to the recommendation that the APJ gene be renamed APLNR and encode the apelin receptor protein.

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Immunoreceptors are TM complexes that consist of separate ligand-binding and signal-transducing modules. Mounting evidence suggests that interactions with the local environment may influence the architecture of these TM domains, which assemble via crucial sets of conserved ionisable residues, and also control the peripheral association of immunoreceptor tyrosine-based activation motifs (ITAMs) whose phosphorylation triggers cytoplasmic signalling cascades. We now report a molecular dynamics (MD) simulation study of the archetypal T cell receptor (TCR) and its cluster of differentiation 3 (CD3) signalling partners, along with the analogous DNAX-activation protein of 12 kDa (DAP12)/natural killer group 2C (NKG2C) complex.

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Summary: As large-scale metabolic phenotyping studies become increasingly common, the need for systemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysis has become increasingly important, both within a study, and to allow meaningful inter-study comparisons. The nPYc-Toolbox provides software for the import, pre-processing, QC and visualization of metabolic phenotyping datasets, either interactively, or in automated pipelines.

Availability And Implementation: The nPYc-Toolbox is implemented in Python, and is freely available from the Python package index https://pypi.

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Supervised modeling of mass spectrometry imaging (MSI) data is a crucial component for the detection of the distinct molecular characteristics of cancerous tissues. Currently, two types of supervised analyses are mainly used on MSI data: pixel-wise segmentation of sample images and whole-sample-based classification. A large number of mass spectra associated with each MSI sample can represent a challenge for designing models that simultaneously preserve the overall molecular content while capturing valuable information contained in the MSI data.

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The apelin receptor is a potential target in the treatment of heart failure and pulmonary arterial hypertension where levels of endogenous apelin peptides are reduced but significant receptor levels remain. Our aim was to characterise the pharmacology of a modified peptide agonist, MM202, designed to have high affinity for the apelin receptor and resistance to peptidase degradation and linked to an anti-serum albumin domain antibody (AlbudAb) to extend half-life in the blood. In competition, binding experiments in human heart MM202-AlbudAb (pK  = 9.

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Background And Purpose: Apelin is an endogenous vasodilatory and inotropic peptide that is down-regulated in human pulmonary arterial hypertension, although the density of the apelin receptor is not significantly attenuated. We hypothesised that a G protein-biased apelin analogue MM07, which is more stable than the endogenous apelin peptide, may be beneficial in this condition with the advantage of reduced β-arrestin-mediated receptor internalisation with chronic use.

Experimental Approach: Male Sprague-Dawley rats received either monocrotaline to induce pulmonary arterial hypertension or saline and then daily i.

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Background: Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools.

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Dimeric calpains constitute a promising therapeutic target for many diseases such as cardiovascular, neurodegenerative and ischaemic disease. The discovery of selective calpain inhibitors, however, has been extremely challenging. Previously, allosteric inhibitors of calpains, such as PD150606, which included a specific α-mercaptoacrylic acid sub-structure, were reported to bind to the penta-EF hand calcium binding domain, PEF(S) of calpain.

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Summary: SPUTNIK is an R package consisting of a series of tools to filter mass spectrometry imaging peaks characterized by a noisy or unlikely spatial distribution. SPUTNIK can produce mass spectrometry imaging datasets characterized by a smaller but more informative set of peaks, reduce the complexity of subsequent multi-variate analysis and increase the interpretability of the statistical results.

Availability And Implementation: SPUTNIK is freely available online from CRAN repository and at https://github.

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