Modulation of neurosteroid potentiation by protein kinases at synaptic- and extrasynaptic-type GABAA receptors.

GABAA receptors are important for inhibition in the CNS where neurosteroids and protein kinases are potent endogenous modulators. Acting individually, these can either enhance or depress receptor function, dependent upon the type of neurosteroid or kinase and the receptor subunit combination. However, in vivo, these modulators probably act in concert to fine-tune GABAA receptor activity and thus inhibition, although how this is achieved remains unclear. Therefore, we investigated the relationship between these modulators at synaptic-type α1β3γ2L and extrasynaptic-type α4β3δ GABAA receptors using electrophysiology. For α1β3γ2L, potentiation of GABA responses by tetrahydro-deoxycorticosterone was reduced after inhibiting protein kinase C, and enhanced following its activation, suggesting this kinase regulates neurosteroid modulation. In comparison, neurosteroid potentiation was reduced at α1β3(S408A,S409A)γ2L receptors, and unaltered by PKC inhibitors or activators, indicating that phosphorylation of β3 subunits is important for regulating neurosteroid activity. To determine whether extrasynaptic-type GABAA receptors were similarly modulated, α4β3δ and α4β3(S408A,S409A)δ receptors were investigated. Neurosteroid potentiation was reduced at both receptors by the kinase inhibitor staurosporine. By contrast, neurosteroid-mediated potentiation at α4(S443A)β3(S408A,S409A)δ receptors was unaffected by protein kinase inhibition, strongly suggesting that phosphorylation of α4 and β3 subunits is required for regulating neurosteroid activity at extrasynaptic receptors. Western blot analyses revealed that neurosteroids increased phosphorylation of β3(S408,S409) implying that a reciprocal pathway exists for neurosteroids to modulate phosphorylation of GABAA receptors. Overall, these findings provide important insight into the regulation of GABAA receptors in vivo, and into the mechanisms by which GABAergic inhibitory transmission may be simultaneously tuned by two endogenous neuromodulators

Modelling the healthcare costs of an opportunistic chlamydia screening programme.

OBJECTIVES: To estimate the average cost per screening offer, cost per testing episode and cost per chlamydia positive episode for an opportunistic chlamydia screening programme (including partner management), and to explore the uncertainty of parameter assumptions, based on the costs to the healthcare system. METHODS: A decision tree was constructed and parameterised using empirical data from a chlamydia screening pilot study and other sources. The model was run using baseline data from the pilot, and univariate and multivariate sensitivity analyses were conducted. RESULTS: The total estimated cost for offering screening over 12 months to 33,215 females aged 16-24 was 493,412 pounds . The average cost (with partner management) was 14.88 pounds per screening offer (90% credibility interval (CI) 10.34 to 18.56), 21.83 pounds per testing episode (90% CI 18.16 to 24.20), and 38.36 pounds per positive episode (90% CI 33.97 to 42.25). The proportion of individuals accepting screening, the clinician (general practitioner/nurse) time and their relative involvement in discussing screening, the test cost, the time to notify patients of their results, and the receptionist time recruiting patients had the greatest impact on the outcomes in both the univariate and multivariate sensitivity analyses. CONCLUSIONS: Results from this costing study may be used to inform resource allocation for current and future chlamydia screening programme implementation

Closely Related Tree Species Differentially Influence the Transfer of Carbon and Nitrogen from Leaf Litter Up the Aquatic Food Web

Decomposing leaf litter in streams provides habitat and nutrition for aquatic insects. Despite large differences in the nutritional qualities of litter among different plant species, their effects on aquatic insects are often difficult to detect. We evaluated how leaf litter of two dominant riparian species (Populus fremontii and P. angustifolia) influenced carbon and nitrogen assimilation by aquatic insect communities, quantifying assimilation rates using stable isotope tracers (13C, 15N). We tested the hypothesis that element fluxes from litter of different plant species better define aquatic insect community structure than insect relative abundances, which often fail. We found that (1) functional communities (defined by fluxes of carbon and nitrogen from leaf litter to insects) were different between leaf litter species, whereas more traditional insect communities (defined by relativized taxa abundances) were not different between leaf litter species, (2) insects assimilated N, but not C, at a higher rate from P. angustifolia litter compared to P. fremontii, even though P. angustifolia decomposes more slowly, and (3) the C:N ratio of material assimilated by aquatic insects was lower for P. angustifolia compared to P. fremontii, indicating higher nutritional quality, despite similar initial litter C:N ratios. These findings provide new evidence for the effects of terrestrial plant species on aquatic ecosystems via their direct influence on the transfer of elements up the food web. We demonstrate how isotopically labeled leaf litter can be used to assess the functioning of insect communities, uncovering patterns undetected by traditional approaches and improving our understanding of the association between food web structure and element cycling

Unmanned aerial systems (UAS) operators’ accuracy and confidence of decisions: Professional pilots or video game players?

Unmanned Aerial Systems (UAS) operations have outpaced current training regimes resulting in a shortage of qualified UAS pilots. Three potential UAS operator groups were explored for suitability (i.e. video game players [VGP]; private pilots; professional pilots) and examined to assess levels of accuracy, confidence and confidence-accuracy judgements (W-S C-A) during a simulated civilian cargo flight. Sixty participants made 21 decision tasks, which varied across three levels of danger/risk. Scales of Tolerance of Ambiguity, Decision Style and NEO-PIR were also completed. Professional pilots and VGPs exhibited the highest level of decision confidence, with VGPs maintaining a constant and positive W-S C-A relationship across decision danger/risk. As decision danger/risk increased, confidence, accuracy and W-S C-A decreased. Decision danger also had a role to play in the confidence expressed when choosing to intervene or rely on automation. Neuroticism was negatively related, and conscientiousness positively related, to confidence. Intolerance of ambiguity was negatively related to W-S C-A. All groups showed higher levels of decision confidence in decisions controlled by the UAS in comparison to decisions where the operator manually intervened. VGPs display less overconfidence in decision judgements. Findings support the idea that VGPs could be considered a resource in UAS operation

Ceramides: a new player in the inflammation-insulin resistance paradigm?

No abstract available

Predictive Entropy Search for Bayesian optimization with unknown constraints

Unknown constraints arise in many types of expensive black-box optimization problems. Several methods have been proposed recently for performing Bayesian optimization with constraints, based on the expected improvement (EI) heuristic. However, EI can lead to pathologies when used with constraints. For example, in the case of decoupled constraints---i.e., when one can independently evaluate the objective or the constraints---EI can encounter a pathology that prevents exploration. Additionally, computing EI requires a current best solution, which may not exist if none of the data collected so far satisfy the constraints. By contrast, information-based approaches do not suffer from these failure modes. In this paper, we present a new information-based method called Predictive Entropy Search with Constraints (PESC). We analyze the performance of PESC and show that it compares favorably to EI-based approaches on synthetic and benchmark problems, as well as several real-world examples. We demonstrate that PESC is an effective algorithm that provides a promising direction towards a unified solution for constrained Bayesian optimization.José Miguel Hernández-Lobato acknowledges support from the Rafael del Pino Foundation. Zoubin Ghahramani acknowledges support from Google Focused Research Award and EPSRC grant EP/I036575/1. Matthew W. Hoffman acknowledges support from EPSRC grant EP/J012300/1.This is the final published version. It first appeared at http://jmlr.org/proceedings/papers/v37/hernandez-lobatob15.html

Burnout in therapy radiographers in the United Kingdom

The 2007 UK National Radiotherapy Advisory Group (NRAG) report indicated the number and type of staff available is one of the ‘rate limiting’ steps in improving productivity in radiotherapy departments. Retaining well trained, satisfied staff, is key to meeting the objectives of the report; burnout is an important factor linked to satisfaction and attrition. Results of a survey measuring burnout in a sample of Radiation Therapists (Therapy Radiographers) are presented and considered against norms for the health sector and burnout in therapists from Canada and the US

A General Framework for Constrained Bayesian Optimization using Information-based Search

We present an information-theoretic framework for solving global black-box optimization problems that also have black-box constraints. Of particular interest to us is to efficiently solve problems with $\textit{decoupled}$ constraints, in which subsets of the objective and constraint functions may be evaluated independently. For example, when the objective is evaluated on a CPU and the constraints are evaluated independently on a GPU. These problems require an acquisition function that can be separated into the contributions of the individual function evaluations. We develop one such acquisition function and call it Predictive Entropy Search with Constraints (PESC). PESC is an approximation to the expected information gain criterion and it compares favorably to alternative approaches based on improvement in several synthetic and real-world problems. In addition to this, we consider problems with a mix of functions that are fast and slow to evaluate. These problems require balancing the amount of time spent in the meta-computation of PESC and in the actual evaluation of the target objective. We take a bounded rationality approach and develop a partial update for PESC which trades off accuracy against speed. We then propose a method for adaptively switching between the partial and full updates for PESC. This allows us to interpolate between versions of PESC that are efficient in terms of function evaluations and those that are efficient in terms of wall-clock time. Overall, we demonstrate that PESC is an effective algorithm that provides a promising direction towards a unified solution for constrained Bayesian optimization.Rafael del Pino Foundation, Google Focused Research Award, Engineering and Physical Sciences Research Council (Grant IDs: EP/I036575/1, EP/J012300/1

Disruption of a Proto-Planetary Disk by the Black Hole at the Milky Way Centre

Recently, an ionized cloud of gas was discovered plunging toward the supermassive black hole, SgrA*, at the centre of the Milky Way. The cloud is being tidally disrupted along its path to closest approach at ~3100 Schwarzschild radii from the black hole. Here, we show that the observed properties of this cloud of gas can naturally be produced by a proto-planetary disk surrounding a low-mass star, which was scattered from the observed ring of young stars orbiting SgrA*. As the young star approaches the black hole, its disk experiences both photo-evaporation and tidal disruption, producing a cloud. Our model implies that planets form in the Galactic centre, and that tidal debris from proto-planetary disks can flag low mass stars which are otherwise too faint to be detected.Comment: Accepted to Nature Communications; new Figure 4b provides predicted Br-gamma emission as a function of tim