Paediatric procedural sedation using ketamine in a UK emergency department: a 7 year review of practice.

Ketamine is growing in popularity for procedural sedation in the paediatric population, yet safety concerns remain. We performed a retrospective review of practice and outcomes of paediatric ketamine sedation using the World SIVA International Sedation Task Force reporting tool.Accepted manuscript, with set statement, 12 month embargo

Multi-omics bioactivity profile-based chemical grouping and read-across:a case study with Daphnia magna and azo dyes

Grouping/read-across is widely used for predicting the toxicity of data-poor target substance(s) using data-rich source substance(s). While the chemical industry and the regulators recognise its benefits, registration dossiers are often rejected due to weak analogue/category justifications based largely on the structural similarity of source and target substances. Here we demonstrate how multi-omics measurements can improve confidence in grouping via a statistical assessment of the similarity of molecular effects. Six azo dyes provided a pool of potential source substances to predict long-term toxicity to aquatic invertebrates (Daphnia magna) for the dye Disperse Yellow 3 (DY3) as the target substance. First, we assessed the structural similarities of the dyes, generating a grouping hypothesis with DY3 and two Sudan dyes within one group. Daphnia magna were exposed acutely to equi-effective doses of all seven dyes (each at 3 doses and 3 time points), transcriptomics and metabolomics data were generated from 760 samples. Multi-omics bioactivity profile-based grouping uniquely revealed that Sudan 1 (S1) is the most suitable analogue for read-across to DY3. Mapping ToxPrint structural fingerprints of the dyes onto the bioactivity profile-based grouping indicated an aromatic alcohol moiety could be responsible for this bioactivity similarity. The long-term reproductive toxicity to aquatic invertebrates of DY3 was predicted from S1 (21-day NOEC, 40 µg/L). This prediction was confirmed experimentally by measuring the toxicity of DY3 in D. magna. While limitations of this ‘omics approach are identified, the study illustrates an effective statistical approach for building chemical groups

Multi-omics analysis of diabetic heart disease in the db/db model reveals potential targets for treatment by a longevity-associated gene

Characterisation of animal models of diabetic cardiomyopathy may help unravel new molecular targets for therapy. Long-living individuals are protected from the adverse influence of diabetes on the heart, and the transfer of a longevity-associated variant (LAV) of the human BPIFB4 gene protects cardiac function in the db/db mouse model. This study aimed to determine the effect of LAV-BPIFB4 therapy on the metabolic phenotype (ultra-high-performance liquid chromatography-mass spectrometry, UHPLC-MS) and cardiac transcriptome (next-generation RNAseq) in db/db mice. UHPLC-MS showed that 493 cardiac metabolites were differentially modulated in diabetic compared with non-diabetic mice, mainly related to lipid metabolism. Moreover, only 3 out of 63 metabolites influenced by LAV-BPIFB4 therapy in diabetic hearts showed a reversion from the diabetic towards the non-diabetic phenotype. RNAseq showed 60 genes were differentially expressed in hearts of diabetic and non-diabetic mice. The contrast between LAV-BPIFB4- and vehicle-treated diabetic hearts revealed eight genes differentially expressed, mainly associated with mitochondrial and metabolic function. Bioinformatic analysis indicated that LAV-BPIFB4 re-programmed the heart transcriptome and metabolome rather than reverting it to a non-diabetic phenotype. Beside illustrating global metabolic and expressional changes in diabetic heart, our findings pinpoint subtle changes in mitochondrial-related proteins and lipid metabolism that could contribute to LAV-BPIFB4-induced cardio-protection in a murine model of type-2 diabetes

Quantum entanglement using trapped atomic spins

We propose an implementation for quantum logic and computing using trapped atomic spins of two different species, interacting via direct magnetic spin-spin interaction. In this scheme, the spins (electronic or nuclear) of distantly spaced trapped neutral atoms serve as the qubit arrays for quantum information processing and storage, and the controlled interaction between two spins, as required for universal quantum computing, is implemented in a three step process that involves state swapping with a movable auxiliary spin.Comment: minor revisions with an updated discussion on adibatic tranportation of trapped qubit, 5 pages, 3 figs, resubmitted to PR

Species-Specific Variations in the Metabolomic Profiles of Acropora hyacinthus and Acropora millepora Mask Acute Temperature Stress Effects in Adult Coral Colonies

Coral reefs are suffering unprecedented declines in health state on a global scale. Some have suggested that human assisted evolution or assisted gene flow may now be necessary to effectively restore reefs and pre-condition them for future climate change. An understanding of the key metabolic processes in corals, including under stressed conditions, would greatly facilitate the effective application of such interventions. To date, however, there has been little research on corals at this level, particularly regarding studies of the metabolome of Scleractinian corals. Here, the metabolomic profiles [measured using 1H nuclear magnetic resonance spectroscopy (1H NMR) and ultra-high-performance liquid chromatography-mass spectrometry (LC-MS)] of two dominant reef building corals, Acropora hyacinthus and A. millepora, from two distinct geographical locations (Australia and Singapore) were characterized. We assessed how an acute temperature stress (an increase of 3.25°C ± 0.28 from ambient control levels over 8 days), shifted the corals’ baseline metabolomic profiles. Regardless of the profiling method utilized, metabolomic signatures of coral colonies were significantly distinct between coral species, a result supporting previous work. However, this strong species-specific metabolomic signature appeared to mask any changes resulting from the acute heat stress. On closer examination, we were able to discriminate between control and temperature stressed groups using a partial least squares discriminant analysis classification model (PLSDA). However, in all cases “late” components needed to be selected (i.e., 7 and 8 instead of 1 and 2), suggesting any treatment effect was small, relative to other sources of variation. This highlights the importance of pre-characterizing the coral colony metabolomes, and of factoring that knowledge into any experimental design that seeks to understand the apparently subtle metabolic effects of acute heat stress on adult corals. Further research is therefore needed to decouple these apparent individual and species-level metabolomic responses to climate change in corals.NER

Rapid identification of human muscle disease with fibre optic Raman spectroscopy

The diagnosis of muscle disorders (“myopathies”) can be challenging and new biomarkers of disease are required to enhance clinical practice and research. Despite advances in areas such as imaging and genomic medicine, muscle biopsy remains an important but time-consuming investigation. Raman spectroscopy is a vibrational spectroscopy application that could provide a rapid analysis of muscle tissue, as it requires no sample preparation and is simple to perform. Here, we investigated the feasibility of using a miniaturised, portable fibre optic Raman system for the rapid identification of muscle disease. Samples were assessed from 27 patients with a final clinico-pathological diagnosis of a myopathy and 17 patients in whom investigations and clinical follow-up excluded myopathy. Multivariate classification techniques achieved accuracies ranging between 71–77%. To explore the potential of Raman spectroscopy to identify different myopathies, patients were subdivided into mitochondrial and non-mitochondrial myopathy groups. Classification accuracies were between 74–89%. Observed spectral changes were related to changes in protein structure. These data indicate fibre optic Raman spectroscopy is a promising technique for the rapid identification of muscle disease that could provide real time diagnostic information. The application of fibre optic Raman technology raises the prospect of in vivo bedside testing for muscle diseases which would significantly streamline the diagnostic pathway of these disorders

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus

Background: In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state. Methods: An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D. Results: A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D. Conclusions: Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes

The characterisation of microsatellite markers reveals tetraploidy in the Greater Water Parsnip, Sium latifolium (Apiaceae).

BACKGROUND: The Greater Water Parsnip, Sium latifolium (Apiaceae), is a marginal aquatic perennial currently endangered in England and consequently the focus of a number of conservation translocation projects. Microsatellite markers were developed for S. latifolium to facilitate comparison of genetic diversity and composition between natural and introduced populations. RESULTS: We selected 65 S. latifolium microsatellite (MiSeq) sequences and designed primer pairs for these. Primer sets were tested in 32 individuals. We found 15 polymorphic loci that amplified consistently. For the selected 15 loci, the number of alleles per locus ranged from 8 to 17. For all loci, S. latifolium individuals displayed up to four alleles indicating polyploidy in this species. CONCLUSIONS: These are the first microsatellite loci developed for S. latifolium and each individual displayed 1-4 alleles per locus, suggesting polyploidy in this species. These markers provide a valuable resource in evaluating the population genetic composition of this endangered species and thus will be useful for guiding conservation and future translocations of the species

Markov clustering versus affinity propagation for the partitioning of protein interaction graphs

<p>Abstract</p> <p>Background</p> <p>Genome scale data on protein interactions are generally represented as large networks, or graphs, where hundreds or thousands of proteins are linked to one another. Since proteins tend to function in groups, or complexes, an important goal has been to reliably identify protein complexes from these graphs. This task is commonly executed using clustering procedures, which aim at detecting densely connected regions within the interaction graphs. There exists a wealth of clustering algorithms, some of which have been applied to this problem. One of the most successful clustering procedures in this context has been the Markov Cluster algorithm (MCL), which was recently shown to outperform a number of other procedures, some of which were specifically designed for partitioning protein interactions graphs. A novel promising clustering procedure termed Affinity Propagation (AP) was recently shown to be particularly effective, and much faster than other methods for a variety of problems, but has not yet been applied to partition protein interaction graphs.</p> <p>Results</p> <p>In this work we compare the performance of the Affinity Propagation (AP) and Markov Clustering (MCL) procedures. To this end we derive an unweighted network of protein-protein interactions from a set of 408 protein complexes from <it>S. cervisiae </it>hand curated in-house, and evaluate the performance of the two clustering algorithms in recalling the annotated complexes. In doing so the parameter space of each algorithm is sampled in order to select optimal values for these parameters, and the robustness of the algorithms is assessed by quantifying the level of complex recall as interactions are randomly added or removed to the network to simulate noise. To evaluate the performance on a weighted protein interaction graph, we also apply the two algorithms to the consolidated protein interaction network of <it>S. cerevisiae</it>, derived from genome scale purification experiments and to versions of this network in which varying proportions of the links have been randomly shuffled.</p> <p>Conclusion</p> <p>Our analysis shows that the MCL procedure is significantly more tolerant to noise and behaves more robustly than the AP algorithm. The advantage of MCL over AP is dramatic for unweighted protein interaction graphs, as AP displays severe convergence problems on the majority of the unweighted graph versions that we tested, whereas MCL continues to identify meaningful clusters, albeit fewer of them, as the level of noise in the graph increases. MCL thus remains the method of choice for identifying protein complexes from binary interaction networks.</p