The biased apelin receptor agonist, MM07, reverses Sugen/hypoxia-induced pulmonary arterial hypertension as effectively as the endothelin antagonist macitentan.

Introduction: 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. Methods: Male Sprague-Dawley rats were randomised and treated with either normoxia/saline, or Sugen/hypoxia (SuHx) to induce an established model of PAH, before subsequent treatment with either saline, macitentan (30 mg/kg), or MM07 (10 mg/kg). Rats were then anaesthetised and catheterised for haemodynamic measurements, and tissues collected for histopathological assessment. Results: The SuHx/saline group presented with significant increases in right ventricular hypertrophy, right ventricular systolic pressure, and muscularization of pulmonary arteries compared to normoxic/saline controls. Critically, MM07 was as at least as effective as macitentan in significantly reversing detrimental structural and haemodynamic changes after 4 weeks of treatment. Discussion: These results support the development of G protein-biased apelin receptor agonists with improved pharmacokinetic profiles for use in human disease.

Alpha 2 agonists for sedation to produce better outcomes from critical illness (A2B Trial): protocol for a multicentre phase 3 pragmatic clinical and cost-effectiveness randomised trial in the UK.

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. METHODS AND ANALYSIS: Adult ICU patients within 48 hours of starting MV, expected to require at least 24 hours further MV, are randomised in an open-label three arm trial to receive propofol (usual care) or clonidine or dexmedetomidine as primary sedative, plus analgesia according to local practice. Exclusions include patients with primary brain injury; postcardiac arrest; other neurological conditions; or bradycardia. Unless clinically contraindicated, sedation is titrated using weight-based dosing guidance to achieve a Richmond-Agitation-Sedation score of -2 or greater as early as considered safe by clinicians. The primary outcome is time to successful extubation. Secondary ICU outcomes include delirium and coma incidence/duration, sedation quality, predefined adverse events, mortality and ICU length of stay. Post-ICU outcomes include mortality, anxiety and depression, post-traumatic stress, cognitive function and health-related quality of life at 6-month follow-up. A process evaluation and health economic evaluation are embedded in the trial.The analytic framework uses a hierarchical approach to maximise efficiency and control type I error. Stage 1 tests whether each alpha2-agonist is superior to propofol. If either/both interventions are superior, stages 2 and 3 testing explores which alpha2-agonist is more effective. To detect a mean difference of 2 days in MV duration, we aim to recruit 1437 patients (479 per group) in 40-50 UK ICUs. ETHICS AND DISSEMINATION: The Scotland A REC approved the trial (18/SS/0085). We use a surrogate decision-maker or deferred consent model consistent with UK law. Dissemination will be via publications, presentations and updated guidelines. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT03653832.

Regulation of blood-brain barrier integrity by microbiome-associated methylamines and cognition by trimethylamine N-oxide.

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. In contrast, the TMAO precursor trimethylamine (TMA) impaired BBB function and disrupted tight junction integrity. Moreover, we show that long-term exposure to TMAO protects murine cognitive function from inflammatory challenge, acting to limit astrocyte and microglial reactivity in a brain region-specific manner. CONCLUSION: Our findings demonstrate the mechanisms through which microbiome-associated methylamines directly interact with the mammalian BBB, with consequences for cerebrovascular and cognitive function. Video abstract.

G392E neuroserpin causing the dementia FENIB is secreted from cells but is not synaptotoxic.

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. Most investigations have concentrated on analysis of intracellular mechanisms such as endoplasmic reticulum (ER) stress, ER-associated protein degradation (ERAD) and oxidative stress. We have generated a HEK-293 cell model of FENIB by overexpressing G392E-mutant neuroserpin and in this study we examine trafficking and toxicity of this polymerogenic variant. We observed that a small fraction of mutant neuroserpin is secreted via the ER-to-Golgi pathway, and that this release can be pharmacologically regulated. Overexpression of the mutant form of neuroserpin did not stimulate cell death in the HEK-293 cell model. Finally, when treating primary hippocampal neurons with G392E neuroserpin polymers, we did not detect cytotoxicity or synaptotoxicity. Altogether, we report here that a polymerogenic mutant form of neuroserpin is secreted from cells but is not toxic in the extracellular milieu.

Structure-based identification of dual ligands at the A2AR and PDE10A with anti-proliferative effects in lung cancer cell-lines.

Enhanced/prolonged cAMP signalling has been suggested as a suppressor of cancer proliferation. Interestingly, two key modulators that elevate cAMP, the A2A receptor (A2AR) 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 A2AR whilst also inhibiting PDE10A, could be a novel anti-proliferative approach. Using ligand- and structure-based modelling combined with MD simulations (which identified Val84 displacement as a novel conformational descriptor of A2AR activation), a series of known PDE10A inhibitors were shown to dock to the orthosteric site of the A2AR. Subsequent in-vitro analysis confirmed that these compounds bind to the A2AR and exhibit dual-activity at both the A2AR and PDE10A. Furthermore, many of the compounds exhibited promising anti-proliferative effects upon NSCLC cell-lines, which directly correlated with the expression of both PDE10A and the A2AR. Thus, we propose a structure-based methodology, which has been validated in in-vitro binding and functional assays, and demonstrated a promising therapeutic value.

Multiple-testing correction in metabolome-wide association studies.

BACKGROUND: The search for statistically significant relationships between molecular markers and outcomes is challenging when dealing with high-dimensional, noisy and collinear multivariate omics data, such as metabolomic profiles. Permutation procedures allow for the estimation of adjusted significance levels without assuming independence among metabolomic variables. Nevertheless, the complex non-normal structure of metabolic profiles and outcomes may bias the permutation results leading to overly conservative threshold estimates i.e. lower than those from a Bonferroni or Sidak correction. METHODS: Within a univariate permutation procedure we employ parametric simulation methods based on the multivariate (log-)Normal distribution to obtain adjusted significance levels which are consistent across different outcomes while effectively controlling the type I error rate. Next, we derive an alternative closed-form expression for the estimation of the number of non-redundant metabolic variates based on the spectral decomposition of their correlation matrix. The performance of the method is tested for different model parametrizations and across a wide range of correlation levels of the variates using synthetic and real data sets. RESULTS: Both the permutation-based formulation and the more practical closed form expression are found to give an effective indication of the number of independent metabolic effects exhibited by the system, while guaranteeing that the derived adjusted threshold is stable across outcome measures with diverse properties.

Metabolomics: The Stethoscope for the Twenty-First Century.

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. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.

Extraction and Integration of Genetic Networks from Short-Profile Omic Data Sets.

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. These molecular or sub-molecular features are generally non-Gaussian and their covariance reveals patterns of correlations that reflect the system nature of the cell biochemistry and biology. Here, we introduce two similarity measures, the Mahalanobis cosine and the hybrid Mahalanobis cosine, that enforce information from the empirical covariance matrix of omics data from high-throughput screening and that can be used to quantify similarities between the profiled features of different mutants. We evaluate the performance of these similarity measures in the task of inferring and integrating genetic networks from short-profile ionomics/metabolomics data through an analysis of experimental data sets related to the ionome and the metabolome of the model organism S. cerevisiae. The study of the resulting ionome-metabolome Saccharomyces cerevisiae multilayer genetic network, which encodes multiple omic-specific levels of correlations between genes, shows that the proposed measures can provide an alternative description of relations between biological processes when compared to the commonly used Pearson's correlation coefficient and have the potential to guide the construction of novel hypotheses on the function of uncharacterised genes.

Consequences of Lipid Remodeling of Adipocyte Membranes Being Functionally Distinct from Lipid Storage in Obesity.

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. Phospholipids (PLs) contribute to a variety of cellular processes including maintaining organelle functionality, providing an optimized environment for membrane-associated proteins, and acting as pools for metabolites (e.g. choline for one-carbon metabolism and for methylation of DNA). We have conducted a comprehensive lipidomic study of white adipose tissue in mice which become obese either through genetic modification (ob/ob), diet (high fat diet), or a combination of the two, using both solid phase extraction and ion mobility to increase coverage of the lipidome. Composition changes in seven classes of lipids (free fatty acids, diglycerides, TGs, phosphatidylcholines, lyso-phosphatidylcholines, phosphatidylethanolamines, and phosphatidylserines) correlated with perturbations in one-carbon metabolism and transcriptional changes in adipose tissue. We demonstrate that changes in TGs that dominate the overall lipid composition of white adipose tissue are distinct from diet-induced alterations of PLs, the predominant components of the cell membranes. PLs correlate better with transcriptional and one-carbon metabolism changes within the cell, suggesting that the compositional changes that occur in cell membranes during adipocyte expansion have far-reaching functional consequences. Data are available at MetaboLights under the submission number: MTBLS1775.

Metabolic Fingerprinting Links Oncogenic PIK3CA with Enhanced Arachidonic Acid-Derived Eicosanoids.

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. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA-induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction. VIDEO ABSTRACT.

Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

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. We show that the performance of support vector machines is competitive with that of deep learning methods. Additionally, using a series of numerical experiments, we question the relevance of area under the receiver operating characteristic curve as a metric in virtual screening. We further suggest that area under the precision-recall curve should be used in conjunction with the receiver operating characteristic curve. Our numerical experiments also highlight challenges in estimating the uncertainty in model performance via scaffold-split nested cross validation.

The G Protein Biased Small Molecule Apelin Agonist CMF-019 is Disease Modifying in Endothelial Cell Apoptosis In Vitro and Induces Vasodilatation Without Desensitisation In Vivo.

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 ß-arrestin (∼400 fold), may be more suitable. This study demonstrates that in addition to being a positive inotrope, CMF-019 caused dose-dependent vasodilatation in vivo (50 nmol 4.16 ± 1.18 mmHg, **p < 0.01; 500 nmol 6.62 ± 1.85 mmHg, **p < 0.01), without receptor desensitization. Furthermore, CMF-019 rescues human pulmonary artery endothelial cells from apoptosis induced by tumor necrosis factor α and cycloheximide (5.66 ± 0.97%, **p < 0.01) by approximately 50% of that observable with rhVEGF (11.59 ± 1.85%, **p < 0.01), suggesting it has disease-modifying potential in vitro. CMF-019 displays remarkable bias at the apelin receptor for a small molecule and importantly recapitulates all aspects of the cardiovascular responses to the endogenous ligand, [Pyr1]apelin-13, in vivo. Additionally, it is able to protect human pulmonary artery endothelial cells from apoptosis, suggesting that the beneficial effects observed with apelin agonists extend beyond hemodynamic alleviation and address disease etiology itself. These findings support CMF-019 as a G protein biased small molecule apelin agonist in vitro and in vivo that could form the basis for the design of novel therapeutic agents in chronic diseases, such as, pulmonary arterial hypertension.

Apelin peptides linked to anti-serum albumin domain antibodies retain affinity in vitro and are efficacious receptor agonists in vivo.

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 (pKi  = 9.39 ± 0.09) bound with similar high affinity as the endogenous peptides [Pyr1 ]apelin-13 (pKi  = 8.83 ± 0.06) and apelin-17 (pKi  = 9.57 ± 0.08). [Pyr1 ]apelin-13 was tenfold more potent in the cAMP (pD2  = 9.52 ± 0.05) compared to the ß-arrestin (pD2  = 8.53 ± 0.03) assay, whereas apelin-17 (pD2  = 10.31 ± 0.28; pD2  = 10.15 ± 0.13, respectively) and MM202-AlbudAb (pD2  = 9.15 ± 0.12; pD2  = 9.26 ± 0.03, respectively) were equipotent in both assays, with MM202-AlbudAb tenfold less potent than apelin-17. MM202-AlbudAb bound to immobilised human serum albumin with high affinity (pKD  = 9.02). In anaesthetised, male Sprague Dawley rats, MM202-AlbudAb (5 nmol, n = 15) significantly reduced left ventricular systolic pressure by 6.61 ± 1.46 mm Hg and systolic arterial pressure by 14.12 ± 3.35 mm Hg and significantly increased cardiac contractility by 533 ± 170 mm Hg/s, cardiac output by 1277 ± 190 RVU/min, stroke volume by 3.09 ± 0.47 RVU and heart rate by 4.64 ± 2.24 bpm. This study demonstrates that conjugating an apelin mimetic peptide to the AlbudAb structure retains receptor and in vivo activity and may be a new strategy for development of apelin peptides as therapeutic agents.

Exercise and Executive Function during Follicular and Luteal Menstrual Cycle Phases.

PURPOSE: A single bout of aerobic or resistance exercise improves executive function. We sought to determine whether menstrual cycle variations in ovarian hormone concentrations differentially influence the expression and/or magnitude of a postexercise executive benefit. METHODS: Eumenorrheic female participants completed 20-min single bouts of aerobic exercise (via cycle ergometer) at a moderate intensity (i.e., 80% of estimated lactate threshold) during the early follicular and midluteal phases of their menstrual cycle. Pre- and postexercise executive function was examined via antisaccades-an executive task requiring a saccade mirror-symmetrical to a visual stimulus. Antisaccades are an ideal tool for examining postexercise executive changes because the task is mediated via the same frontoparietal networks as modified following single-bout and chronic exercise. RESULTS: Antisaccade reaction times decreased from the pre- to postexercise assessments by an average of 22 ms (P = 0.003), and this benefit was independent of changes in directional errors or end point accuracy (P's > 0.26). In other words, participants did not decrease their postexercise reaction times at the cost of increased planning times or execution errors. Most notably, the postexercise antisaccade benefit did not vary in magnitude across follicular or luteal phases (P = 0.33) and a two one-sided test statistic (i.e., equivalence testing) provided support for the null hypothesis (P = 0.008). CONCLUSIONS: A postexercise executive benefit is independent of hormonal variations in the menstrual cycle. Further, our results evince that the phase of a female participant's menstrual cycle should not be a limiting factor in determining their inclusion in exercise neuroscience research.

A Bone Morphogenetic Protein (BMP)-derived Peptide Based on the Type I Receptor-binding Site Modifies Cell-type Dependent BMP Signalling.

Bone morphogenetic proteins (BMPs) are multifunctional cytokines of the transforming growth factor ß (TGFß) 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. Although showing no baseline activity, P3 significantly enhanced BMP9-induced Smad1/5 phosphorylation as well as ID1, BMPR2, HEY1 and HEY2 gene expression in pulmonary artery endothelial cells (hPAECs), and this activity is dependent on its alpha helix propensity. However, in human dermal microvascular endothelial cells, P3 did not affect BMP9-induced Smad1/5 phosphorylation, but potently inhibited ALK3-dependent BMP4-induced Smad1/5 phosphorylation and gene expression. In C2C12 mouse myoblast cells, P3 had no effect on BMP9-induced osteogenic signalling, which is primarily mediated by ALK2. Interestingly, a previously published peptide from the knuckle region of BMP9 was found to inhibit BMP4-induced Smad1/5 phosphorylation. Together, our data identify a BMP9-derived peptide that can selectively enhance ALK1-mediated BMP9 signalling in hPAECs and modulate BMP9 and BMP4 signalling in a cell type-specific manner.

International Union of Basic and Clinical Pharmacology. CVII. Structure and Pharmacology of the Apelin Receptor with a Recommendation that Elabela/Toddler Is a Second Endogenous Peptide Ligand.

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 [Pyr1]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. Recently, a second endogenous ligand has been identified and called Elabela/Toddler, a 54-amino acid peptide originally identified in the genomes of fish and humans but misclassified as noncoding. This precursor is also able to be cleaved to shorter sequences (32, 21, and 11 amino acids), and all are able to activate the apelin receptor and are blocked by apelin receptor antagonists. This review summarizes the pharmacology of these ligands and the apelin receptor, highlights the emerging physiologic and pathophysiological roles in a number of diseases, and recommends that Elabela/Toddler is a second endogenous peptide ligand of the apelin receptor protein.

The structural basis for membrane assembly of immunoreceptor signalling complexes.

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. Based on > 15 µs of explicitly solvated, atomic-resolution sampling, we explore molecular aspects of immunoreceptor complex stability in different functionally relevant states. A novel alchemical approach is used to simulate the cytoplasmic CD3ε tail at different depths within lipid bilayer models, revealing that the conformation and cytoplasmic exposure of ITAMs are highly sensitive to local enrichment by different lipid species and to phosphorylation. Furthermore, simulations of the TCR and DAP12 TM domains in various states of oligomerisation suggest that, during the early stages of assembly, stable membrane insertion is facilitated by the interfacial lipid/solvent environment and/or partial ionisation of charged residues. Collectively, our results indicate that the architecture and mechanisms of signal transduction in immunoreceptor complexes are tightly regulated by interactions with the microenvironment.

The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets.

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.org/project/nPYc/, source is available at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation can be found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials at https://github.com/phenomecentre/nPYc-toolbox-tutorials.

Colocalization Features for Classification of Tumors Using Desorption Electrospray Ionization Mass Spectrometry Imaging.

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. Furthermore, intensity-related batch effects can introduce biases in the statistical models. Here we introduce a method based on ion colocalization features that allows the classification of whole tissue specimens using MSI data, which naturally preserves the spatial information associated the with the mass spectra and is less sensitive to possible batch effects. Finally, we propose data visualization strategies for the inspection of the derived networks, which can be used to assess whether the correlation differences are related to coexpression/suppression or disjoint spatial localization patterns and can suggest hypotheses based on the underlying mechanisms associated with the different classes of analyzed samples.

Continuous prospectively navigated multi-echo GRE for improved BOLD imaging of the kidneys.

The objective of this study is to develop improved methods for renal blood oxygenation level dependent (BOLD) imaging. T2* mapping of the kidneys, or renal BOLD imaging, may depict renal oxygen levels and may be valuable as a noninvasive means of following the progression of renal disease. Current renal BOLD data is limited by imaging in a single breath hold, which results in low resolution and low signal-to-noise ratio (SNR). We compare a new free-breathing renal BOLD method with conventional breath-hold BOLD (BH-BOLD). A multi-echo GRE sequence with continuous prospective respiratory navigation and real-time feedback was developed that allows high resolution and high SNR renal BOLD imaging with constant sequence repetition time (TR) during free-breathing BOLD (FB-BOLD). The sequence was evaluated in 10 normal volunteers and compared with conventional BH-BOLD. Scan time for the FB-BOLD sequence was approximately three minutes, compared with 15 seconds for the BH-BOLD sequence. SNR of source images and residual error of T2* fitting were compared between the two methods. The FB-BOLD sequence produced motion-free T2* maps of the kidneys with SNR 1.9 times higher than BH-BOLD images. Residual error of T2* fitting was consistently lower in the right kidney with FB-BOLD (30% less than BH-BOLD) but higher in the left kidney (80% more than BH-BOLD), likely related to placement of the navigator on the right hemidiaphragm. A free-breathing prospectively navigated renal BOLD sequence allows flexible tradeoff between scan time, resolution, and SNR.