Variation in honey bee gut microbial diversity affected by ontogenetic stage, age and geographic location

Social honey bees, Apis mellifera, host a set of distinct microbiota, which is similar across the continents and various honey bee species. Some of these bacteria, such as lactobacilli, have been linked to immunity and defence against pathogens. Pathogen defence is crucial, particularly in larval stages, as many pathogens affect the brood. However, information on larval microbiota is conflicting. Seven developmental stages and drones were sampled from 3 colonies at each of the 4 geographic locations of A. mellifera carnica, and the samples were maintained separately for analysis. We analysed the variation and abundance of important bacterial groups and taxa in the collected bees. Major bacterial groups were evaluated over the entire life of honey bee individuals, where digestive tracts of same aged bees were sampled in the course of time. The results showed that the microbial tract of 6-day-old 5th instar larvae were nearly equally rich in total microbial counts per total digestive tract weight as foraging bees, showing a high percentage of various lactobacilli (Firmicutes) and Gilliamella apicola (Gammaproteobacteria 1). However, during pupation, microbial counts were significantly reduced but recovered quickly by 6 days post-emergence. Between emergence and day 6, imago reached the highest counts of Firmicutes and Gammaproteobacteria, which then gradually declined with bee age. Redundancy analysis conducted using denaturing gradient gel electrophoresis identified bacterial species that were characteristic of each developmental stage. The results suggest that 3-day 4th instar larvae contain low microbial counts that increase 2-fold by day 6 and then decrease during pupation. Microbial succession of the imago begins soon after emergence. We found that bacterial counts do not show only yearly cycles within a colony, but vary on the individual level. Sampling and pooling adult bees or 6th day larvae may lead to high errors and variability, as both of these stages may be undergoing dynamic succession

Empirical exploration of brilliance in health care: perceptions of health professionals

Objective. The aim of the present study was to develop a positive organisational scholarship in health care approach to health management, informed by health managers and health professionals’ experiences of brilliance in health care delivery. Methods. A sample of postgraduate students with professional and/or management experience within a health service was invited to share their experiences of brilliant health services via online discussions and a survey running on the SurveyMonkey platform. A lexical analysis of student contributions was conducted using the individual as the unit of analysis. Results. Using lexical analysis, the examination of themes in the concept map, the relationships between themes and the relationships between concepts identified ‘care’ as the most important concept in recognising brilliance in health care, followed by the concepts of ‘staff’ and ‘patient’. Conclusions. The research presents empirical material to support the emergence of an evidence-based health professional perspective of brilliance in health management. The findings support other studies that have drawn on both quantitative and qualitative materials to explore brilliance in health care. Pockets of brilliance have been previously identified as catalysts for changing health care systems. Both quality, seen as driven from the outside, and excellence, driven from within individuals, are necessary to produce brilliance

Empirical exploration of brilliance in health care : perceptions of health professionals

Objective The aim of the present study was to develop a positive organisational scholarship in health care approach to health management, informed by health managers and health professionals' experiences of brilliance in health care delivery. Methods A sample of postgraduate students with professional and/or management experience within a health service was invited to share their experiences of brilliant health services via online discussions and a survey running on the SurveyMonkey platform. A lexical analysis of student contributions was conducted using the individual as the unit of analysis. Results Using lexical analysis, the examination of themes in the concept map, the relationships between themes and the relationships between concepts identified 'care' as the most important concept in recognising brilliance in health care, followed by the concepts of 'staff' and 'patient'. Conclusions The research presents empirical material to support the emergence of an evidence-based health professional perspective of brilliance in health management. The findings support other studies that have drawn on both quantitative and qualitative materials to explore brilliance in health care. Pockets of brilliance have been previously identified as catalysts for changing health care systems. Both quality, seen as driven from the outside, and excellence, driven from within individuals, are necessary to produce brilliance. What is known about the topic? The quest for brilliance in health care is not easy but essential to reinvigorating and energising health professionals to pursue the highest possible standards of health care delivery. What does this paper add? Using an innovative methodology, the present study identified the key drivers that health care professionals believe are vital to moving in the direction of identifying brilliant performance. What are the implications for practitioners? This work presents evidence on the perceptions of leadership and management practices associated with brilliant health management. Lessons learned from exceptionally well-delivered services contain different templates for change than those dealing with failures, errors, misconduct and the resulting negativity

Guideline for the non-surgical management of hip and knee osteoarthritis

Introduction: Chronic disease is a major public health burden on Australian society. An increasing proportion of the population has risk factors for, or at least one, chronic disease, leading to increasing public health costs. Health service policy and delivery must not only address acute conditions, it must also effectively respond to the wide range of health and public service requirements of people with chronic illness.1,2 Strong primary health care policy is an important foundation for a successful national health delivery system and long term management of public health, and is linked to practical outcomes including lower mortality, decreased hospitalisation and improved health outcomes.1 National strategic health policy has recently given increased recognition to the importance of chronic disease management, with the Australian Federal Government endorsement of a number of initiatives for the prevention (or delay in onset), early detection and evidence based management of chronic disease, including osteoarthritis.1,3 Chronic musculoskeletal conditions, including arthritis, account for over 4% of the national disease burden in terms of disability adjusted life years. Over 6 million Australians (almost one-third of the population) are estimated to have a chronic musculoskeletal disease; chronic musculoskeletal disease represents the main cause of long term pain and physical disability. In Australia, osteoarthritis is self reported by more than 1.4 million people (7.3% of the population4) and is the tenth most commonly managed problem in general practice.5 This number is set to rise as the elderly population grows. Osteoarthritis exerts a significant burden on the individual and the community through reduction in quality of life, diminished employment capacity and an increase in health care costs. For further details, refer to the Evidence to support the National Action Plan for Osteoarthritis, Rheumatoid Arthritis and Osteoporosis: Opportunities to improve health-related quality of life and reduce the burden of disease and disability (2004).6As such, federal government health policy has identified arthritis as a National Health Priority Area and adopted a number of initiatives aimed at decreasing the burden of chronic disease and disability; raising awareness of preventive disease factors; providing access to evidence based knowledge; and improving the overall management of arthritis within the community.4 In 2002, all Australian health ministers designated arthritis and musculoskeletal conditions as Australia&rsquo;s seventh National Health Priority Area. In response, a National Action Plan was developed in 2004 by the National Arthritis and Musculoskeletal Conditions Advisory Group (NAMSCAG).6 The aim of this document was to provide a blueprint for national initiatives to improve the health related quality of life of people living with osteoarthritis, rheumatoid arthritis and osteoporosis; reduce the cost and prevalence of these conditions; and reduce the impact on individuals, their carers and their communities within Australia. The National Action Plan was developed to complement both the National Chronic Disease Strategy &ndash; which is broader &ndash; and the National Service Improvement Framework for Osteoarthritis, Rheumatoid Arthritis and Osteoporosis, in addition to other national and state/ territory structures.<br /

Boxplot of quantitative real-time PCR (qRT-PCR) data of the abundance of selected bacterial groups in pooled samples of total gastrointestinal tract of each honey bee ontogenetic stage.

<p>The Y axis shows log-transformed copies of the 16S rRNA gene per gram of honey bee gastrointestinal tract. Boxes show pooled data from 4 locations and 3 hives at each location. 1-, 3- and 6-day old larvae (L1, L3 and L6, respectively), white and black pupae (PW, PB), young bees, drones and flying bees (BY, DR and BF, respectively). The codes of the outliers refer to the location (Pos: Postrizin, Hos: Hostice, Ust: Ustrasice) and colony number (1, 2, 3).</p

Heatmap summarising the relative density of dominant denaturing electrophoresis bands of the 16S rRNA amplicon profiles of the total gastrointestinal tract contents of several honey bee ontogenetic stages.

<p>1-, 3- and 6-day old larvae (L1, L3 and L6, respectively), white and black pupae (PW, PB), young bees, drones and flying bees (BY, DR and BF, respectively) collected in 4 different locations (Dol, Postrizin, Ustrasice, Hostice). Samples are sorted by ontogenetic stage (A) and location (B). The colours refer to relative band strength according to the colour key.</p

Dynamics of selected bacterial groups in the total gastrointestinal tract during development and aging of a “single” honey bee.

<p>Data were obtained by collecting pooled samples of sister honey bees from the eggs of the same oviposition. Young bees were marked by paint shortly after emergence. Legend in the grey field provides a link to the first experiment EXP2 described here and shows at which approximate time points the samples for EXP1 were collected.</p

Biplot from redundancy analysis (RDA) explaining the distribution of honey bee ontogenetic stages according to major bacterial strain abundance.

<p>Test of interactions between factors location and ontogenetic stage: A, crude data considering absolute DGGE band intensities; B, centred and standardized data considering relative band intensities. Abbreviations: Gil, <i>Gilliamella apicola</i>; Sno, <i>Snodgrassella alvi</i>; Lac, <i>Lactobacillus</i> sp.; Rhi, <i>Rhizobiales</i> bacterium; Fri, <i>Frischella perrara</i>, UM, unknown multiple—probable DNA heterodimer. For further strain descriptions, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118707#pone.0118707.s005" target="_blank">S5 Fig.</a> Dotted shapes surrounding each ontogenetic stage were created as an aid in visualization. Eighteen bacterial strains occurring as major 16S rDNA DGGE bands were used for statistical analysis, while only selected strains are plotted as arrows. Same descriptions are for bands of the same sequence occurring at multiple locations of the line. Blue arrows show hypothetical developmental timeline. Its dotted part is ambiguous.</p