Lessons Learned: Can a Principled Mechanism for Improving Health Equity be Integrated into a Budgetary Process?

Health equity is the social justice lens that public health institutions across the United States have increasingly embraced as a mandate, however there are few jurisdictions addressing how to prioritize funding toward that end. The practical translation of a social justice concept necessitates the creation of a budgetary tool and an implementation process that identifies those with the highest levels of health disparity and social disadvantage. Using the San Francisco Department of Public Health (SFDPH) as its central case, this paper argues that for health delivery systems to be socially just and to achieve health equity, these systems must not only establish the principle that health equity is important, they must prioritize their funding to achieve it. The broad public health mission to protect and promote the health of all will create ethical and methodological challenges when it comes to prioritizing one group’s needs over others. This paper addresses the first steps toward creating a budget prioritization method that is feasible for managers to administer while also being transparent to the public, summarizes lessons learned, and discusses ethical dilemmas that jurisdictions will face when implementing health equity into a budgetary process

Multicultural Student Center: Measuring a Transformative Campus Experience

This poster will illustrate the student engaged experience utilized by Kansas State University for its Multicultural Student Center. It will delineate the campus community partnership and the empowerment process initiated by the multicultural student organizations that led to the preliminary building design and fundraising strategies by the University. It will also address how multiple communities in a university can engage in a creative, collaborative process that not only fosters inclusion but also student learning. Ultimately, it shows how student collaboration with University Administration can result in both intended and unexpected outcomes for all involved, especially impacts for beyond stated expectations

Non-adiabatic pressure loss boundary condition for modelling turbocharger turbine pulsating flow

This paper presents a simplified methodology of pulse flow turbine modelling, as an alternative over the meanline integrated methodology outlined in previous work, in order to make its application to engine cycle simulation codes much more straight forward. This is enabled through the development of a bespoke non-adiabatic pressure loss boundary to represent the turbine rotor. In this paper, turbocharger turbine pulse flow performance predictions are presented along with a comparison of computation duration against the previously established integrated meanline method. Plots of prediction deviation indicate that the mass flow rate and actual power predictions from both methods are highly comparable and are reasonably close to experimental data. However, the new boundary condition required significantly lower computational time and rotor geometrical inputs. In addition, the pressure wave propagation in this simplified unsteady turbine model at different pulse frequencies has also been found to be in agreement with data from the literature, thereby supporting the confidence in its ability to simulate the wave action encountered in turbine pulse flow operation

Expression of a barley cystatin gene in maize enhances resistance against phytophagous mites by altering their cysteine-proteases

Phytocystatins are inhibitors of cysteine-proteases from plants putatively involved in plant defence based on their capability of inhibit heterologous enzymes. We have previously characterised the whole cystatin gene family members from barley (HvCPI-1 to HvCPI-13). The aim of this study was to assess the effects of barley cystatins on two phytophagous spider mites, Tetranychus urticae and Brevipalpus chilensis. The determination of proteolytic activity profile in both mite species showed the presence of the cysteine-proteases, putative targets of cystatins, among other enzymatic activities. All barley cystatins, except HvCPI-1 and HvCPI-7, inhibited in vitro mite cathepsin L- and/or cathepsin B-like activities, HvCPI-6 being the strongest inhibitor for both mite species. Transgenic maize plants expressing HvCPI-6 protein were generated and the functional integrity of the cystatin transgene was confirmed by in vitro inhibitory effect observed against T. urticae and B. chilensis protein extracts. Feeding experiments impaired on transgenic lines performed with T. urticae impaired mite development and reproductive performance. Besides, a significant reduction of cathepsin L-like and/or cathepsin B-like activities was observed when the spider mite fed on maize plants expressing HvCPI-6 cystatin. These findings reveal the potential of barley cystatins as acaricide proteins to protect plants against two important mite pests

A Critical Inter-Subunit Interaction for the Transmission of the Allosteric Signal in the Agrobacterium Tumefaciens ADP-Glucose Pyrophosphorylase

ADP-glucose pyrophosphorylase is a key regulatory enzyme involved in starch and glycogen synthesis in plants and bacteria, respectively. It has been hypothesized that inter-subunit communications are important for the allosteric effect in this enzyme. However, no specific interactions have been identified as part of the regulatory signal. The enzyme from Agrobacterium tumefaciens is a homotetramer allosterically regulated by fructose 6-phosphate and pyruvate. Three pairs of distinct subunit-subunit interfaces are present. Here we focus on an interface that features two symmetrical interactions between Arg11 and Asp141 from one subunit with residues Asp141 and Arg11 of the neighbor subunit, respectively. Previously, scanning mutagenesis showed that a mutation at the Arg11 position disrupted the activation of the enzyme. Considering the distance of these residues from the allosteric and catalytic sites, we hypothesized that the interaction between Arg11 and Asp141 is critical for allosteric signaling rather than effector binding. To prove our hypothesis, we mutated those two sites (D141A, D141E, D141N, D141R, R11D, and R11K) and performed kinetic and binding analysis. Mutations that altered the charge affected the regulation the most. To prove that the interaction per se (rather than the presence of specific residues) is critical, we partially rescued the R11D protein by introducing a second mutation (R11D/D141R). This could not restore the activator effect on kcat, but it did rescue the effect on substrate affinity. Our results indicate the critical functional role of Arg11 and Asp141 to relay the allosteric signal in this subunit interface

Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

BfpI, BfpJ, and BfpK Minor Pilins Are Important for the Function and Biogenesis of Bundle-Forming Pili Expressed by Enteropathogenic Escherichia coli

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Methodology for evaluating thermal track buckling in dual gauge tracks with continuous welded rail

In the National Spanish railway network, two types of track gauge with continuous welded rails are currently in use: the Iberian wide gauge (1668 mm) and the standard gauge (1435 mm). In order to improve links and freight traffic between different lines and with the rest of Europe, a dual gauge track with three rails was developed. This solution modifies the classical track configuration, so it is necessary to develop new methodologies and studies to understand its behavior. Among other loads applied on a continuous welded rail track, a considerable rise in temperature induces compressive stresses in the three rails that can lead to lateral track buckling. Moreover, on dual gauge tracks, the addition of the third rail increases the axial compression, which may lead to track instability. For this reason, a three-dimensional continuous welded rail model is developed in this study to be used for dual gauge track buckling analysis on straight tracks subjected to temperature load. The continuous welded rail dual gauge track model consists of beam, solid and spring elements, in which a non-linear behaviour of the ballast is considered. The results obtained may be used to predict the buckling capacity of the continuous welded rail on dual gauge tracks with respect to different parameters such as lateral resist-ance, lateral imperfections, sleeper spacing or torsional stiffness.Villalba Sanchis, I.; Insa Franco, R.; Salvador Zuriaga, P.; Martínez Fernández, P. (2017). Methodology for evaluating thermal track buckling in dual gauge tracks with continuous welded rail. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. 231(3):269-279. doi:10.1177/0954409715626957S269279231