Antimicrobial Resistance and Universal Health Coverage

The WHO launched a Global Action Plan on antimicrobial resistance (AMR) in 2015. World leaders in the G7, G20 and the UN General Assembly have declared AMR to be a global crisis. World leaders have also adopted universal health coverage (UHC) as a key target under the sustainable development goals. This paper argues that neither initiative is likely to succeed in isolation from the other and that the policy goals should be to both provide access to appropriate antimicrobial treatment and reduce the risk of the emergence and spread of resistance by taking a systems approach. It focuses on outpatient treatment of human infections and identifies a number of interventions that would be needed to achieve these policy goals. It then shows how a strategy for achieving key attributes of a health system for UHC can take into account the need to address AMR as part of a UHC strategy in any country. It concludes with a list of recommended priority actions for integrating initiatives on AMR and UHC

Social Media in Educational Practice: Faculty Present and Future Use of Social Media in Teaching

This paper presents results from a questionnaire (n=333) designed to gain an understanding of instructor motivations and experience with social media use in educational practice. Data on overall use of social media, and instructors’ use of social media in classes are applied to assess factors leading to present and future use of social media in teaching, using a framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. Our findings show use in teaching is driven by factors associated with UTAUT’s Performance Expectancy construct, i.e., personal engagement with social media, and Moderating Condition of age, with older participants making greater use of social media in teaching. Other constructs associated with use are Habit (experience teaching online), Social Influence (colleagues using social media), Effort Expectancy (awareness of barriers, staying informed), Facilitating Conditions (institutional technology support) and Moderating Conditions (teaching at a two-year college)

Noise bias in weak lensing shape measurements

Weak lensing experiments are a powerful probe of cosmology through their measurement of the mass distribution of the universe. A challenge for this technique is to control systematic errors that occur when measuring the shapes of distant galaxies. In this paper we investigate noise bias, a systematic error that arises from second order noise terms in the shape measurement process. We first derive analytical expressions for the bias of general Maximum Likelihood Estimators (MLEs) in the presence of additive noise. We then find analytical expressions for a simplified toy model in which galaxies are modeled and fitted with a Gaussian with its size as a single free parameter. Even for this very simple case we find a significant effect. We also extend our analysis to a more realistic 6-parameter elliptical Gaussian model. We find that the noise bias is generically of the order of the inverse-squared signal-to-noise ratio (SNR) of the galaxies and is thus of the order of a percent for galaxies of SNR of 10, i.e. comparable to the weak lensing shear signal. This is nearly two orders of magnitude greater than the systematics requirements for future all-sky weak lensing surveys. We discuss possible ways to circumvent this effect, including a calibration method using simulations discussed in an associated paper.Comment: 8 pages, 3 figures, submitted to MNRA

Surfactant-free purification of membrane protein complexes from bacteria: application to the staphylococcal penicillin-binding protein complex PBP2/PBP2a

Surfactant-mediated removal of proteins from biomembranes invariably results in partial or complete loss of function and disassembly of multi-protein complexes. We determined the capacity of styrene-co-maleic acid (SMA) co-polymer to remove components of the cell division machinery from the membrane of drug-resistant staphylococcal cells. SMA-lipid nanoparticles solubilized FtsZ-PBP2-PBP2a complexes from intact cells, demonstrating the close physical proximity of these proteins within the lipid bilayer. Exposure of bacteria to (-)-epicatechin gallate, a polyphenolic agent that abolishes β-lactam resistance in staphylococci, disrupted the association between PBP2 and PBP2a. Thus, SMA purification provides a means to remove native integral membrane protein assemblages with minimal physical disruption and shows promise as a tool for the interrogation of molecular aspects of bacterial membrane protein structure and function

Learning in the wild:Predicting the formation of ties in ‘Ask’ subreddit communities using ERG models

The theoretical lenses, empirical measures and analytical tools associated with social network analysis comprise a wealth of knowledge that can be used to analyse networked learning. This has popularized the use of the social network analysis approach to understand and visualize structures and dynamics in online learning networks, particularly where data could be automatically gathered and analysed. Research in the field of social network learning analysis has (a) used social network visualizations as a feedback mechanism and an intervention to enhance online social learning activities (Bakharia & Dawson, 2011; Schreurs, Teplovs, Ferguson, de Laat, & Buckingham Shum, 2013), (b) investigated what variables predicted the formation of learning ties in networked learning processes (Cho, Gay, Davidson, & Ingraffea, 2007), (c) predicted learning outcomes in online environments (Russo & Koesten, 2005), and (d) studied the nature of the learning ties (de Laat, 2006). This paper expands the understanding of the variables predicting the formation of learning ties in online informal environments. Reddit, an online news sharing site that is commonly referred to as ‘the front page of the Internet’, has been chosen as the environment for our investigation because conversations on it emerge from the contributions of members, and it combines perspectives of experts and non-experts (Moore & Chuang, 2017) taking place in a plethora of subcultures (subreddits) occurring outside traditional settings. We study two subreddit communities, ‘AskStatistics’, and ‘AskSocialScience’, in which we believe that informal learning is likely to happen in Reddit, and which offer avenues for comparison both in terms of the communication dynamics and learning processes occurring between members. We gathered all the interactions amongst the users of these two subreddit communities for a 1-year period, from January 1st, 2015 until December 31st, 2015. Exponential Random Graph models (ERGm) were employed to determine the endogenous (network) and exogenous (node attributes) factors facilitating the networked ties amongst the users of these communities. We found evidence that Redditors’ networked ties arise from network dynamics (reciprocity and transitivity) and from the Redditors’ role as a moderator in the subreddit communities. These results shed light into the understanding of the variables predicting the formation of ties in informal networked learning environments, and more broadly contribute to the development of the field of social network learning analysis