Higher sociability leads to lower reproductive success in female kangaroos: Sociability and fitness in kangaroos

In social mammals, social integration is generally assumed to improve females’ reproductive success. Most species demonstrating this relationship exhibit complex forms of social bonds and interactions. However, female eastern grey kangaroos (Macropus giganteus) exhibit differentiated social relationships, yet do not appear to cooperate directly. It is unclear what the fitness consequences of such sociability could be in species that do not exhibit obvious forms of cooperation. Using 4 years of life history, spatial and social data from a wild population of approximately 200 individually recognizable female eastern grey kangaroos, we tested whether higher levels of sociability are associated with greater reproductive success. Contrary to expectations, we found that the size of a female’s social network, her numbers of preferential associations with other females and her group sizes all negatively influenced her reproductive success. These factors influenced the survival of dependent young that had left the pouch rather than those that were still in the pouch. We also show that primiparous females (first-time breeders) were less likely to have surviving young. Our findings suggest that social bonds are not always beneficial for reproductive success in group-living species, and that female kangaroos may experience trade-offs between successfully rearing young and maintaining affiliative relationships

Higher sociability leads to lower reproductive success in female kangaroos

In social mammals, social integration is generally assumed to improve females' reproductive success. Most species demonstrating this relationship exhibit complex forms of social bonds and interactions. However, female eastern grey kangaroos (Macropus giganteus) exhibit differentiated social relationships, yet do not appear to cooperate directly. It is unclear what the fitness consequences of such sociability could be in species that do not exhibit obvious forms of cooperation. Using 4 years of life history, spatial and social data from a wild population of approximately 200 individually recognizable female eastern grey kangaroos, we tested whether higher levels of sociability are associated with greater reproductive success. Contrary to expectations, we found that the size of a female's social network, her numbers of preferential associations with other females and her group sizes all negatively influenced her reproductive success. These factors influenced the survival of dependent young that had left the pouch rather than those that were still in the pouch. We also show that primiparous females (first-time breeders) were less likely to have surviving young. Our findings suggest that social bonds are not always beneficial for reproductive success in group-living species, and that female kangaroos may experience trade-offs between successfully rearing young and maintaining affiliative relationships

Impact of CO₂-enriched combustion air on micro-gas turbine performance for carbon capture

Power generation is one of the largest anthropogenic greenhouse gas emission sources; although it is now reducing in carbon intensity due to switching from coal to gas, this is only part of a bridging solution that will require the utilization of carbon capture technologies. Gas turbines, such as those at the UK Carbon Capture Storage Research Centre's Pilot-scale Advanced CO2 Capture Technology (UKCCSRC PACT) National Core Facility, have high exhaust gas mass flow rates with relatively low CO2 concentrations; therefore solvent-based post-combustion capture is energy intensive. Exhaust gas recirculation (EGR) can increase CO2 levels, reducing the capture energy penalty. The aim of this paper is to simulate EGR through enrichment of the combustion air with CO2 to assess changes to turbine performance and potential impacts on complete generation and capture systems. The oxidising air was enhanced with CO2, up to 6.29%vol dry, impacting mechanical performance, reducing both engine speed by over 400 revolutions per minute and compression temperatures. Furthermore, it affected complete combustion, seen in changes to CO and unburned hydrocarbon emissions. This impacted on turbine efficiency, which increased specific fuel consumption (by 2.9%). CO2 enhancement could therefore result in significant efficiency gains for the capture plant

Diagnosis and aetiology of congenital muscular dystrophy: we are halfway there

OBJECTIVES: To evaluate the diagnostic outcomes in a large cohort of congenital muscular dystrophy (CMD) patients using traditional and Next Generation Sequencing (NGS) technologies. METHODS: 123 CMD patients were investigated using the traditional approaches of histology, immunohistochemical analysis of muscle biopsy and candidate gene sequencing. Undiagnosed patients available for further testing were investigated using NGS. RESULTS: Muscle biopsy and immunohistochemical analysis found deficiencies of laminin α2, α-dystroglycan or collagen VI in 50% of patients. Candidate gene sequencing and chromosomal microarray established a genetic diagnosis in 32% (39/123). Of 85 patients presenting in the last 20 years, 28 of 51 who lacked a confirmed genetic diagnosis (55%) consented to NGS studies, leading to confirmed diagnoses in a further 11 patients. Using the combination of approaches, a confirmed genetic diagnosis was achieved in 51% (43/85). The diagnoses within the cohort were heterogeneous. 45/59 probands with confirmed or probable diagnoses had variants in genes known to cause CMD (76%), and 11/59 (19%) had variants in genes associated with congenital myopathies, reflecting overlapping features of these conditions. One patient had a congenital myasthenic syndrome and two had microdeletions. Within the cohort, five patients had variants in novel (PIGY and GMPPB) or recently published genes (GFPT1 and MICU1) and seven had variants in TTN or RYR1; large genes that are technically difficult to Sanger sequence. INTERPRETATION: These data support NGS as a first-line tool for genetic evaluation of patients with a clinical phenotype suggestive of CMD, with muscle biopsy reserved as a second-tier investigation. This article is protected by copyright. All rights reserved

Are we under-utilizing the talents of primary care personnel? A job analytic examination

BACKGROUND: Primary care staffing decisions are often made unsystematically, potentially leading to increased costs, dissatisfaction, turnover, and reduced quality of care. This article aims to (1) catalogue the domain of primary care tasks, (2) explore the complexity associated with these tasks, and (3) examine how tasks performed by different job titles differ in function and complexity, using Functional Job Analysis to develop a new tool for making evidence-based staffing decisions. METHODS: Seventy-seven primary care personnel from six US Department of Veterans Affairs (VA) Medical Centers, representing six job titles, participated in two-day focus groups to generate 243 unique task statements describing the content of VA primary care. Certified job analysts rated tasks on ten dimensions representing task complexity, skills, autonomy, and error consequence. Two hundred and twenty-four primary care personnel from the same clinics then completed a survey indicating whether they performed each task. Tasks were catalogued using an adaptation of an existing classification scheme; complexity differences were tested via analysis of variance. RESULTS: Objective one: Task statements were categorized into four functions: service delivery (65%), administrative duties (15%), logistic support (9%), and workforce management (11%). Objective two: Consistent with expectations, 80% of tasks received ratings at or below the mid-scale value on all ten scales. Objective three: Service delivery and workforce management tasks received higher ratings on eight of ten scales (multiple functional complexity dimensions, autonomy, human error consequence) than administrative and logistic support tasks. Similarly, tasks performed by more highly trained job titles received higher ratings on six of ten scales than tasks performed by lower trained job titles. Contrary to expectations, the distribution of tasks across functions did not significantly vary by job title. CONCLUSION: Primary care personnel are not being utilized to the extent of their training; most personnel perform many tasks that could reasonably be performed by personnel with less training. Primary care clinics should use evidence-based information to optimize job-person fit, adjusting clinic staff mix and allocation of work across staff to enhance efficiency and effectiveness

Knowledge transfer & exchange through social networks: building foundations for a community of practice within tobacco control

BACKGROUND: Health services and population health innovations advance when knowledge transfer and exchange (KTE) occurs among researchers, practitioners, policy-makers and consumers using high-quality evidence. However, few KTE models have been evaluated in practice. Communities of practice (CoP) – voluntary, self-organizing, and focused groups of individuals and organizations – may provide one option. This paper outlines an approach to lay the foundation for a CoP within the area of Web-assisted tobacco interventions (WATI). The objectives of the study were to provide a data-driven foundation to inform decisions about organizing a CoP within the geographically diverse, multi-disciplinary WATI group using evaluation and social network methodologies. METHODS: A single-group design was employed using a survey of expectations, knowledge, and interpersonal WATI-related relationships administered prior to a meeting of the WATI group followed by a 3-week post-meeting Web survey to assess short-term impact on learning and networking outcomes. RESULTS: Twenty-three of 27 WATI attendees (85%) from diverse disciplinary and practice backgrounds completed the baseline survey, with 21 (91%) of those participants completing the three-week follow-up. Participants had modest expectations of the meeting at baseline. A social network map produced from the data illustrated a centralized, yet sparse network comprising of interdisciplinary teams with little trans-sectoral collaboration. Three-week follow-up survey results showed that participants had made new network connections and had actively engaged in KTE activities with WATI members outside their original network. CONCLUSION: Data illustrating both the shape and size of the WATI network as well as member's interests and commitment to KTE, when shared and used to frame action steps, can positively influence the motivation to collaborate and create communities of practice. Guiding KTE planning through blending data and theory can create more informed transdisciplinary and trans-sectoral collaboration environments

Shared component modelling as an alternative to assess geographical variations in medical practice: gender inequalities in hospital admissions for chronic diseases

<p>Abstract</p> <p>Background</p> <p>Small area analysis is the most prevalent methodological approach in the study of unwarranted and systematic variation in medical practice at geographical level. Several of its limitations drive researchers to use disease mapping methods -deemed as a valuable alternative. This work aims at exploring these techniques using - as a case of study- the gender differences in rates of hospitalization in elderly patients with chronic diseases.</p> <p>Methods</p> <p>Design and study setting: An empirical study of 538,358 hospitalizations affecting individuals aged over 75, who were admitted due to a chronic condition in 2006, were used to compare Small Area Analysis (SAVA), the Besag-York-Mollie (BYM) modelling and the Shared Component Modelling (SCM). Main endpoint: Gender spatial variation was measured, as follows: SAVA estimated gender-specific utilization ratio; BYM estimated the fraction of variance attributable to spatial correlation in each gender; and, SCM estimated the fraction of variance shared by the two genders, and those specific for each one.</p> <p>Results</p> <p>Hospitalization rates due to chronic diseases in the elderly were higher in men (median per area 21.4 per 100 inhabitants, interquartile range: 17.6 to 25.0) than in women (median per area 13.7 per 100, interquartile range: 10.8 to 16.6). Whereas Utilization Ratios showed a similar geographical pattern of variation in both genders, BYM found a high fraction of variation attributable to spatial correlation in both men (71%, CI95%: 50 to 94) and women (62%, CI95%: 45 to 77). In turn, SCM showed that the geographical admission pattern was mainly shared, with just 6% (CI95%: 4 to 8) of variation specific to the women component.</p> <p>Conclusions</p> <p>Whereas SAVA and BYM focused on the magnitude of variation and on allocating where variability cannot be due to chance, SCM signalled discrepant areas where latent factors would differently affect men and women.</p

The Professional Solution to the College Bubble

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Internet-based public debate of CCS: lessons from online focus groups in Poland and Spain

This paper makes three contributions to the developing literature on public opinion and understanding of CCS. The first is a discussion of online focus groups as a deliberative method in experimental and perhaps consultative contexts. The second is the role of anchoring and associative reasoning in the development of public opinion of CCS, illustrated through the coincidental timing of the investigation with the Fukushima nuclear accident. The third is a discussion of managing public-facing energy messaging in an age of public access to online information. Two multi-day, online focus groups or "dialogue boards" were held, one in Poland and one in Spain, with participants drawn from regions with active CCS development potential. The nature of the groups led to participants being subject to wider social influence through discussion of the topic off-line. They were also able to research and present evidence on the topic to the group, deepening debate and allowing the emergence of 'experts'. The study illustrates and affirms the importance of trust in message source, the difficulties of challenging pre-existing concerns and opinion and the challenge potentially posed by access to conflicting online information

A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

<p>Abstract</p> <p>Background</p> <p>The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes), for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties.</p> <p>Results</p> <p>The main patterns discovered by the classification methods are as follows: (a) the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b) the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO) annotations; (c) GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d) interaction with the XRCC5 (Ku80) protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e) DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related.</p> <p>Conclusions</p> <p>The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.</p