IonFlow: a galaxy tool for the analysis of ionomics data sets.

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.com/wanchanglin/ionflow . It is designed as a pipeline that can process raw data to enable exploration and interpretation using multivariate statistical techniques and network-based algorithms, including principal components analysis, hierarchical clustering, relevance network extraction and analysis, and gene set enrichment analysis. RESULTS AND CONCLUSION: The pipeline is described and tested on two benchmark data sets of the haploid S. Cerevisiae ionome and of the human HeLa cell ionome

A new method for the reproducible generation of polymorphs: two forms of sulindac with very different solubilities

Polymorphism of drugs has been the subject of intense interest in the pharmaceutical industry for over forty years. Although identical in chemical composition, polymorphs differ in bioavailability, solubility, dissolution rate, chemical and physical stability, melting point, colour, filterability, density, flow properties, and many other properties. The difference in solubility is particularly important for pharmaceuticals, as it can affect drug efficacy, bioavailability and safety. Despite significant investment in processes to find all the possible polymorphs of active pharmaceutical ingredients (APIs), new polymorphs can suddenly appear without warning. Polymorphs tend to convert spontaneously from less stable to more stable forms, and, therefore, it is best to discover and characterize the stable form as early as possible. Ideally the most stable polymorph will be found while the drug candidate is still in the discovery process, so that this is the form used for subsequent testing. The most stable polymorph will be the least soluble and solubility may be a limiting factor in the efficacy of the API. Despite the huge importance of polymorphism in the properties of materials, however, there is no method that can produce all the stable polymorphs of a compound, or even one that can provide confidence that the most stable polymorph has been obtained. Here we describe a new method, `potentiometric cycling for polymorph creation (PC)2', which is able to generate the most stable polymorph in aqueous solution. This new method has been applied to sulindac, a non-steroidal anti-inflammatory drug, which also shows promise in anticancer treatment, producing two polymorphs of this API, including a new more stable one. By adjusting the conditions, this method is able to produce either polymorph exclusively.</jats:p

SPUTNIK: an R package for filtering of spatially related peaks in mass spectrometry imaging data

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: SPUTNIK is freely available online from CRAN repository and at https://github.com/paoloinglese/SPUTNIK. The package is distributed under the GNU General Public License version 3 and is accompanied by example files and data. Supplementary information: Supplementary data are available at Bioinformatics online

Full "Laplacianised" posterior naive Bayesian algorithm

BACKGROUND: In the last decade the standard Naive Bayes (SNB) algorithm has been widely employed in multi–class classification problems in cheminformatics. This popularity is mainly due to the fact that the algorithm is simple to implement and in many cases yields respectable classification results. Using clever heuristic arguments “anchored” by insightful cheminformatics knowledge, Xia et al. have simplified the SNB algorithm further and termed it the Laplacian Corrected Modified Naive Bayes (LCMNB) approach, which has been widely used in cheminformatics since its publication. In this note we mathematically illustrate the conditions under which Xia et al.’s simplification holds. It is our hope that this clarification could help Naive Bayes practitioners in deciding when it is appropriate to employ the LCMNB algorithm to classify large chemical datasets. RESULTS: A general formulation that subsumes the simplified Naive Bayes version is presented. Unlike the widely used NB method, the Standard Naive Bayes description presented in this work is discriminative (not generative) in nature, which may lead to possible further applications of the SNB method. CONCLUSIONS: Starting from a standard Naive Bayes (SNB) algorithm, we have derived mathematically the relationship between Xia et al.’s ingenious, but heuristic algorithm, and the SNB approach. We have also demonstrated the conditions under which Xia et al.’s crucial assumptions hold. We therefore hope that the new insight and recommendations provided can be found useful by the cheminformatics community

Propionate has protective and anti-inflammatory effects on the blood–brain barrier

Production of short-chain fatty acids (SCFAs) from dietary substrates by the gut microbiota is associated with health, with these metabolites influencing the host via the ‘gut–brain axis’. Micromolar quantities of microbially derived SCFAs are taken up from the gut and reach systemic circulation, where they can influence host gene expression through a variety of largely unknown mechanisms. The blood–brain barrier (BBB) is the major interface between the circulation and central nervous system, and is critically involved in the pathogenesis of neuroinflammatory disorders such as stroke and vascular dementia. We hypothesized exposure of the BBB to SCFAs influences barrier integrity and function. To test our hypothesis, we investigated the in vitro effects of a physiologically relevant concentration (1 μM) of propionate upon the human immortalised cerebromicrovascular endothelial cell line hCMEC/D3. Propionate is produced by the microbiota from dietary glucans, and is biologically active via the G protein coupled receptors FFAR2 and FFAR3. It is a highly potent FFAR2 agonist (agonist activity 3.99) and has close to optimal ligand efficiency (-ΔG=1.19 kcal mol-1 atom-1) for this receptor. Notably, FFAR3 is expressed on the vascular endothelium and a likely target for propionate in the BBB. After confirming the presence of FFAR3 on hCMEC/D3 cells, we undertook an unbiased transcriptomic analysis of confluent hCMEC/D3 monolayers treated or not for 24 h with 1 μM propionate, supported by in vitro validation of key findings and assessment of functional endothelial permeability barrier properties. Propionate treatment had a significant (PFDR < 0.1) effect on the expression of 1136 genes: 553 upregulated, 583 downregulated. Propionate inhibited several inflammation-associated pathways: namely, TLR-specific signalling, NFkappaB signalling, and cytosolic DNA-sensing. Functional validation of these findings confirmed the down-regulation of TLR signalling by propionate, achieved primarily through down-regulation of endothelial CD14 expression. Accordingly, propionate prevented LPS-induced increases in paracellular permeability to 70 kDa FITC-dextran and loss of transendothelial electrical resistance. Enrichr analysis indicated the activation by propionate of the NFE2L2 (NRF2)-driven protective response against oxidative stress. Confirming these data, propionate limited free reactive oxygen species induction by the mitochondrial respiratory inhibitor rotenone. Together, these data strongly suggest the SCFA propionate contributes to maintaining BBB integrity and protecting against inflammatory challenge by downregulating BBB responsiveness. In addition to its well-described effects on cholesterol metabolism, maintenance of propionate levels in the circulation may be an additional mechanism whereby a glucan-containing diet protects against neurovascular disease

Specular sets

We introduce the notion of specular sets which are subsets of groups called here specular and which form a natural generalization of free groups. These sets are an abstract generalization of the natural codings of linear involutions. We prove several results concerning the subgroups generated by return words and by maximal bifix codes in these sets.Comment: arXiv admin note: substantial text overlap with arXiv:1405.352

Cardiac action of the first G protein biased small molecule apelin agonist.

Apelin peptide analogues displaying bias towards G protein signalling pathways have beneficial cardiovascular actions compared with the native peptide in humans in vivo. Our aim was to determine whether small molecule agonists could retain G protein bias. We have identified a biased small molecule, CMF-019, and characterised it in vitro and in vivo. In competition radioligand binding experiments in heart homogenates, CMF-019 bound to the human, rat and mouse apelin receptor with high affinity (pKi=8.58±0.04, 8.49±0.04 and 8.71±0.06 respectively). In cell-based functional assays, whereas, CMF-019 showed similar potency for the Gαi pathway to the endogenous agonist [Pyr(1)]apelin-13 (pD2=10.00±0.13 vs 9.34±0.15), in β-arrestin and internalisation assays it was less potent (pD2=6.65±0.15 vs 8.65±0.10 and pD2=6.16±0.21 vs 9.28±0.10 respectively). Analysis of these data demonstrated a bias of ∼400 for the Gαi over the β-arrestin pathway and ∼6000 over receptor internalisation. CMF-019 was tested for in vivo activity using intravenous injections into anaesthetised male Sprague-Dawley rats fitted with a pressure-volume catheter in the left ventricle. CMF-019 caused a significant increase in cardiac contractility of 606±112mmHg/s (p<0.001) at 500nmol. CMF-019 is the first biased small molecule identified at the apelin receptor and increases cardiac contractility in vivo. We have demonstrated that Gαi over β-arrestin/internalisation bias can be retained in a non-peptide analogue and predict that such bias will have the therapeutic benefit following chronic use. CMF-019 is suitable as a tool compound and provides the basis for design of biased agonists with improved pharmacokinetics for treatment of cardiovascular conditions such as pulmonary arterial hypertension.British Heart Foundation [FS/14/59/31282]; Wellcome Trust [WT107715/Z/15/Z], Wellcome Trust Programme in Metabolic and Cardiovascular Disease [096822/Z/11/Z]; Medical Research Council [MRC MC PC 14116]; Pulmonary Hypertension Association UK; Cambridge Biomedical Research Centre Biomedical Resources Grant University of Cambridge [099156/Z/12/Z]; Engineering and Physical Sciences Research Council [EP/M506552/1]; Biomedical Health Research Centre, University of Leed

Target Fishing: A Single-Label or Multi-Label Problem?

According to Cobanoglu et al and Murphy, it is now widely acknowledged that the single target paradigm (one protein or target, one disease, one drug) that has been the dominant premise in drug development in the recent past is untenable. More often than not, a drug-like compound (ligand) can be promiscuous - that is, it can interact with more than one target protein. In recent years, in in silico target prediction methods the promiscuity issue has been approached computationally in different ways. In this study we confine attention to the so-called ligand-based target prediction machine learning approaches, commonly referred to as target-fishing. With a few exceptions, the target-fishing approaches that are currently ubiquitous in cheminformatics literature can be essentially viewed as single-label multi-classification schemes; these approaches inherently bank on the single target paradigm assumption that a ligand can home in on one specific target. In order to address the ligand promiscuity issue, one might be able to cast target-fishing as a multi-label multi-class classification problem. For illustrative and comparison purposes, single-label and multi-label Naive Bayes classification models (denoted here by SMM and MMM, respectively) for target-fishing were implemented. The models were constructed and tested on 65,587 compounds and 308 targets retrieved from the ChEMBL17 database. SMM and MMM performed differently: for 16,344 test compounds, the MMM model returned recall and precision values of 0.8058 and 0.6622, respectively; the corresponding recall and precision values yielded by the SMM model were 0.7805 and 0.7596, respectively. However, at a significance level of 0.05 and one degree of freedom McNemar test performed on the target prediction results returned by SMM and MMM for the 16,344 test ligands gave a chi-squared value of 15.656, in favour of the MMM approach

Validity of a novel computerized cognitive battery for mild cognitive impairment

BACKGROUND: The NeuroTrax Mindstreams computerized cognitive assessment system was designed for widespread clinical and research use in detecting mild cognitive impairment (MCI). However, the capability of Mindstreams tests to discriminate elderly with MCI from those who are cognitively healthy has yet to be evaluated. Moreover, the comparability between these tests and traditional neuropsychological tests in detecting MCI has not been examined. METHODS: A 2-center study was designed to assess discriminant validity of tests in the Mindstreams Mild Impairment Battery. Participants were 30 individuals diagnosed with MCI, 29 with mild Alzheimer's disease (AD), and 39 healthy elderly. Testing was with the Mindstreams battery and traditional neuropsychological tests. Receiver operating characteristic (ROC) analysis was used to examine the ability of Mindstreams and traditional measures to discriminate those with MCI from cognitively healthy elderly. Between-group comparisons were made (Mann-Whitney U test) between MCI and healthy elderly and between MCI and mild AD groups. RESULTS: Mindstreams outcome parameters across multiple cognitive domains significantly discriminated among MCI and healthy elderly with considerable effect sizes (p < 0.05). Measures of memory, executive function, visual spatial skills, and verbal fluency discriminated best, and discriminability was at least comparable to that of traditional neuropsychological tests in these domains. CONCLUSIONS: Mindstreams tests are effective in detecting MCI, providing a comprehensive profile of cognitive function. Further, the enhanced precision and ease of use of these computerized tests make the NeuroTrax system a valuable clinical tool in the identification of elderly at high risk for dementia