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The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain. Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Background. In June 2000, the hospital-acquired Clostridium difficile (CD) infection rate in our hospital (University of Pittsburgh Medical Center–Presbyterian, Pittsburgh, PA) increased to 10.4 infections per 1000 hospital discharges (HDs); the annual rate increased from 2.7 infections per 1000 HDs to 7.2 infections per 1000 HDs and was accompanied by an increase in the frequency of severe outcomes. Forty-seven (51%) of 92 HA CD isolates in 2001 were identified as the “epidemic BI strain.” A comprehensive CD infection control “bundle” was implemented to control the outbreak of CD infection. Methods. The CD infection control bundle consisted of education, increased and early case finding, expanded infection-control measures, development of a CD infection management team, and antimicrobial management. Process measures, antimicrobial usage, and hospital-acquired CD infection rates were analyzed, and CD isolates were typed. Results. The rates of compliance with hand hygiene and isolation were 75% and 68%, respectively. The CD management team evaluated a mean of 31 patients per month (11% were evaluated for moderate or severe disease). Use of antimicrobial therapy associated with increased CD infection risk decreased by 41% during the period 2003–2005 (P < .001). The aggregate rate of CD infection during the period 2001–2006 decreased to 4.8 infections per 1000 HDs (odds ratio, 2.2; 95% confidence interval, 1.4–3.1; P < .001) and by 2006, was 3.0 infections per 1000 HDs, a rate reduction of 71% (odds ratio, 3.5; 95% confidence interval, 2.3–5.4; P < .001). During the period 2000–2001, the proportion of severe CD cases peaked at 9.4% (37 of 393 CD infections were severe); the rate decreased to 3.1% in 2002 and further decreased to 1.0% in 2006—a 78% overall reduction (odds ratio, 20.3; 95% confidence interval, 2.8–148.2; P < .001). In 2005, 13% of CD isolates were type BI (20% were hospital acquired), which represented a significant reduction from 2001 (P < .001). Conclusions. The outbreak of CD infection with the BI strain in our hospital was controlled after implementing a CD infection control \"bundle.\" Early identification, coupled with appropriate control measures, reduces the rate of CD infection and the frequency of adverse events.

Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial intelligence with rich microbiome datasets can offer an improved understanding of the microbiome’s role in human health. To gain actionable insights it is essential to consider both the predictive power and the transparency of the models by providing explanations for the predictions. We combine the collection of leg skin microbiome samples from two healthy cohorts of women with the application of an explainable artificial intelligence (EAI) approach that provides accurate predictions of phenotypes with explanations. The explanations are expressed in terms of variations in the relative abundance of key microbes that drive the predictions. We predict skin hydration, subject's age, pre/post-menopausal status and smoking status from the leg skin microbiome. The changes in microbial composition linked to skin hydration can accelerate the development of personalized treatments for healthy skin, while those associated with age may offer insights into the skin aging process. The leg microbiome signatures associated with smoking and menopausal status are consistent with previous findings from oral/respiratory tract microbiomes and vaginal/gut microbiomes respectively. This suggests that easily accessible microbiome samples could be used to investigate health-related phenotypes, offering potential for non-invasive diagnosis and condition monitoring. Our EAI approach sets the stage for new work focused on understanding the complex relationships between microbial communities and phenotypes. Our approach can be applied to predict any condition from microbiome samples and has the potential to accelerate the development of microbiome-based personalized therapeutics and non-invasive diagnostics.

Gram-negative Enterobacteriaceae with resistance to carbapenem conferred by New Delhi metallo-β-lactamase 1 (NDM-1) are potentially a major global health problem. We investigated the prevalence of NDM-1, in multidrug-resistant Enterobacteriaceae in India, Pakistan, and the UK. Enterobacteriaceae isolates were studied from two major centres in India—Chennai (south India), Haryana (north India)—and those referred to the UK's national reference laboratory. Antibiotic susceptibilities were assessed, and the presence of the carbapenem resistance gene bla NDM-1 was established by PCR. Isolates were typed by pulsed-field gel electrophoresis of XbaI-restricted genomic DNA. Plasmids were analysed by S1 nuclease digestion and PCR typing. Case data for UK patients were reviewed for evidence of travel and recent admission to hospitals in India or Pakistan. We identified 44 isolates with NDM-1 in Chennai, 26 in Haryana, 37 in the UK, and 73 in other sites in India and Pakistan. NDM-1 was mostly found among Escherichia coli (36) and Klebsiella pneumoniae (111), which were highly resistant to all antibiotics except to tigecycline and colistin. K pneumoniae isolates from Haryana were clonal but NDM-1 producers from the UK and Chennai were clonally diverse. Most isolates carried the NDM-1 gene on plasmids: those from UK and Chennai were readily transferable whereas those from Haryana were not conjugative. Many of the UK NDM-1 positive patients had travelled to India or Pakistan within the past year, or had links with these countries. The potential of NDM-1 to be a worldwide public health problem is great, and co-ordinated international surveillance is needed. European Union, Wellcome Trust, and Wyeth.

Leading historians discuss the distinctive and internationally significant history of Scottish education The excellence of Scottish education is, as it is commonly understood, 'held to be absolute'. One of the key national 'myths' has emphasised the quality, distinctiveness and accessibility of educational institutions north of the Border. The 'democratic intellect', the 'lad o'pairts' and other aspects of the Scottish educational tradition have been identified as key elements of national identity. In this book, a range of authors consider the truth behind the 'myth', and between them tell the story of the development of Scottish education over a period lasting almost a millenium. From the medieval origins of the Scottish universities, to the development of parish schooling after the Reformation, to the reforms of the nineteenth century, to the radical extension of educational participation throughout the twentieth century, this book traces the emergence of the complex educational structure of today's Scotland out of all these legacies. Key FeaturesThe first multi-authored history of education in Scotland that covers the whole of its medieval and modern historyAn unrivalled group of historians and social scientists with extensive expertise in Scottish historySets new agendas for the future of historical research in Scotland

In England, influenza immunisation was first recommended to all pregnant women in 2009, and in response to a pertussis outbreak in 2012 the UK Department of Health introduced pertussis vaccination for all pregnant women. The aim of this study was to gain a contextualised understanding of factors influencing acceptance of vaccination during pregnancy in Hackney, a borough in north-east London, UK. Hackney was chosen because it has one of the lowest vaccination coverage rates in pregnancy in the UK. A purposive sampling method was used to recruit 40 pregnant and recently pregnant women from a wide range of backgrounds, and ten health-care professionals, from three general practices, two community antenatal clinics, nine parent-toddler groups, and four community centres. In-depth interviews and a focus group discussion with pregnant and recently pregnant women explored experiences of National Health Service health care during pregnancy and their views about vaccination in pregnancy. In-depth interviews with health-care workers explored their views about vaccination in pregnancy and how they discuss and provide vaccination. Interview and focus group data were analysed both inductively and deductively with a thematic analysis approach. The overarching themes relating to vaccine hesitancy identified from the interviews with pregnant and recently pregnant women were perceived risks associated with vaccination or the diseases they aim to prevent, trust in health-care workers and vaccination, and social influence. In addition to vaccine hesitancy, reasons for not being vaccinated, especially among women of lower socioeconomic status, included lack of access to vaccination or vaccination not having been recommended by a health-care worker. Overarching themes identified from the interviews with health-care workers were trust in vaccination, perceived importance of vaccination, responsibility of vaccine administration, perceived patient concerns, and interaction with patients. Reasons for vaccine hesitancy are complex. The findings of this study indicate that advice from friends, family, and the internet can greatly influence a pregnant woman's vaccination decisions. Hesitancy can be exacerbated because attitudes about vaccination and provision vary among health-care workers in Hackney. Also there are certain barriers to accessing vaccinations among patients of lower socioeconomic status. The results will help to inform contextualised policies aimed at increasing vaccination uptake and reducing inequality in access to vaccination during pregnancy in Hackney. National Institute for Health Research (NIHR) Health Protection Research Unit in Immunisation at the London School of Hygiene & Tropical Medicine (LSHTM) in partnership with Public Health England (PHE).

Background Methicillin-resistant Staphylococcus aureus (MRSA) bacteraemia is a serious infection resulting in 20–50 % 90-day mortality. The limitations of vancomycin, the current standard therapy for MRSA, make treatment difficult. The only other approved drug for treatment of MRSA bacteraemia, daptomycin, has not been shown to be superior to vancomycin. Surprisingly, there has been consistent in-vitro and in-vivo laboratory data demonstrating synergy between vancomycin or daptomycin and an anti-staphylococcal β-lactam antibiotic. There is also growing clinical data to support such combinations, including a recent pilot randomised controlled trial (RCT) that demonstrated a trend towards a reduction in the duration of bacteraemia in patients treated with vancomycin plus flucloxacillin compared to vancomycin alone. Our aim is to determine whether the addition of an anti-staphylococcal penicillin to standard therapy results in improved clinical outcomes in MRSA bacteraemia. Methods/Design We will perform an open-label, parallel-group, randomised (1:1) controlled trial at 29 sites in Australia, New Zealand, Singapore, and Israel. Adults (aged 18 years or older) with MRSA grown from at least one blood culture and able to be randomised within 72 hours of the index blood culture collection will be eligible for inclusion. Participants will be randomised to vancomycin or daptomycin (standard therapy) given intravenously or to standard therapy plus 7 days of an anti-staphylococcal β-lactam (flucloxacillin, cloxacillin, or cefazolin). The primary endpoint will be a composite outcome at 90 days of (1) all-cause mortality, (2) persistent bacteraemia at day 5 or beyond, (3) microbiological relapse, or (4) microbiological treatment failure. The recruitment target of 440 patients is based on an expected failure rate for the primary outcome of 30 % in the control arm and the ability to detect a clinically meaningful absolute decrease of 12.5 %, with a two-sided alpha of 0.05, a power of 80 %, and assuming 10 % of patients will not be evaluable for the primary endpoint. Discussion Key potential advantages of adding anti-staphylococcal β-lactams to standard therapy for MRSA bacteraemia include their safety profile, low cost, and wide availability. Trial registration ClinicalTrials.gov Identifier: NCT02365493 . Registered 24 February 2015.

INTRODUCTION This study aimed to identify cognitive tests that optimally relate to tau positron emission tomography (PET) signal in the inferior temporal cortex (ITC), a neocortical region associated with early tau accumulation in Alzheimer's disease (AD). METHODS We analyzed cross‐sectional data from the harvard aging brain study (HABS) (n = 128) and the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's (A4) study (n = 393). We used elastic net regression to identify the most robust cognitive correlates of tau PET signal in the ITC. Secondary analyses examined whether the cognitive correlates remained significantly associated with tau after adjusting for structural brain measures. RESULTS Episodic memory measures, including both total and “process” scores, were the most robust correlates of ITC tau across both cohorts. These cognitive test scores remained significant after accounting for structural brain measures. DISCUSSION These findings highlight the potential of specific episodic memory test scores to detect and monitor neuropathological changes associated with early AD. Highlights Machine learning identified cognitive correlates of early Alzheimer's disease tau burden. Both traditional and process scores predicted early tau burden. Episodic memory scores were among the strongest correlates. Cognitive scores remained significant after accounting for structural brain measures.