Multi-axis fields boost SABRE hyperpolarization via new strategies

The inherently low signal-to-noise ratio of NMR and MRI is now being addressed by hyperpolarization methods. For example, iridium-based catalysts that reversibly bind both parahydrogen and ligands in solution can hyperpolarize protons (SABRE) or heteronuclei (X-SABRE) on a wide variety of ligands, using a complex interplay of spin dynamics and chemical exchange processes, with common signal enhancements between $10^3-10^4$. This does not approach obvious theoretical limits, and further enhancement would be valuable in many applications (such as imaging mM concentration species in vivo). Most SABRE/X-SABRE implementations require far lower fields (${\mu}T-mT$) than standard magnetic resonance (>1T), and this gives an additional degree of freedom: the ability to fully modulate fields in three dimensions. However, this has been underexplored because the standard simplifying theoretical assumptions in magnetic resonance need to be revisited. Here we take a different approach, an evolutionary strategy algorithm for numerical optimization, Multi-Axis Computer-aided HEteronuclear Transfer Enhancement for SABRE (MACHETE-SABRE). We find nonintuitive but highly efficient multi-axial pulse sequences which experimentally can produce a 10-fold improvement in polarization over continuous excitation. This approach optimizes polarization differently than traditional methods, thus gaining extra efficiency

Distance decay in delivery care utilisation associated with neonatal mortality. A case referent study in northern Vietnam

BACKGROUND: Efforts to reduce neonatal mortality are essential if the Millennium Development Goal (MDG) 4 is to be met. The impact of spatial dimensions of neonatal survival has not been thoroughly investigated even though access to good quality delivery care is considered to be one of the main priorities when trying to reduce neonatal mortality. This study examined the association between distance from the mother's home to the closest health facility and neonatal mortality, and investigated the influence of distance on patterns of perinatal health care utilisation. METHODS: A surveillance system of live births and neonatal deaths was set up in eight districts of Quang Ninh province, Vietnam, from July 2008 to December 2009. Case referent design including all neonatal deaths and randomly selected newborn referents from the same population. Interviews were performed with mothers of all subjects and GIS coordinates for mothers' homes and all health facilities in the study area were obtained. Straight-line distances were calculated using ArcGIS software. RESULTS: A total of 197 neonatal deaths and 11 708 births were registered and 686 referents selected. Health care utilisation prior to and at delivery varied with distance to the health facility. Mothers living farthest away (4th and 5th quintile, ≥1257 meters) from a health facility had an increased risk of neonatal mortality (OR 1.96, 95% CI 1.40 - 2.75, adjusted for maternal age at delivery and marital status). When stratified for socio-economic factors there was an increased risk for neonatal mortality for mothers with low education and from poor households who lived farther away from a health facility. Mothers who delivered at home had more than twice as long to a health facility compared to mothers who delivered at a health care facility. There was no difference in age at death when comparing neonates born at home or health facility deliveries (p = 0.56). CONCLUSION: Distance to the closest health facility was negatively associated with neonatal mortality risk. Health care utilisation in the prenatal period could partly explain this risk elevation since there was a distance decay in health system usage prior to and at delivery. The geographical dimension must be taken into consideration when planning interventions for improved neonatal survival, especially when targeting socio-economically disadvantaged groups

Bayesian Inference for Identifying Interaction Rules in Moving Animal Groups

The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of “universal” classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed

Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.Peer reviewe

Coordinated Regulation of Virulence during Systemic Infection of Salmonella enterica Serovar Typhimurium

To cause a systemic infection, Salmonella must respond to many environmental cues during mouse infection and express specific subsets of genes in a temporal and spatial manner, but the regulatory pathways are poorly established. To unravel how micro-environmental signals are processed and integrated into coordinated action, we constructed in-frame non-polar deletions of 83 regulators inferred to play a role in Salmonella enteriditis Typhimurium (STM) virulence and tested them in three virulence assays (intraperitoneal [i.p.], and intragastric [i.g.] infection in BALB/c mice, and persistence in 129X1/SvJ mice). Overall, 35 regulators were identified whose absence attenuated virulence in at least one assay, and of those, 14 regulators were required for systemic mouse infection, the most stringent virulence assay. As a first step towards understanding the interplay between a pathogen and its host from a systems biology standpoint, we focused on these 14 genes. Transcriptional profiles were obtained for deletions of each of these 14 regulators grown under four different environmental conditions. These results, as well as publicly available transcriptional profiles, were analyzed using both network inference and cluster analysis algorithms. The analysis predicts a regulatory network in which all 14 regulators control the same set of genes necessary for Salmonella to cause systemic infection. We tested the regulatory model by expressing a subset of the regulators in trans and monitoring transcription of 7 known virulence factors located within Salmonella pathogenicity island 2 (SPI-2). These experiments validated the regulatory model and showed that the response regulator SsrB and the MarR type regulator, SlyA, are the terminal regulators in a cascade that integrates multiple signals. Furthermore, experiments to demonstrate epistatic relationships showed that SsrB can replace SlyA and, in some cases, SlyA can replace SsrB for expression of SPI-2 encoded virulence factors

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)