Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

The regional economic impact of more graduates in the labour market: a “micro-to-macro” analysis for Scotland

This paper explores the system-wide impact of graduates on the regional economy. Graduates enjoy a significant wage premium, often interpreted as reflecting their greater productivity relative to non-graduates. If this is so there is a clear and direct supply-side impact of HEI activities on regional economies. We use an HEI-disaggregated computable general equilibrium model of Scotland to estimate the impact of the growing proportion of graduates in the Scottish labour force that is implied by the current participation rate and demographic change, taking the graduate wage premium in Scotland as an indicator of productivity enhancement. While the detailed results vary with alternative assumptions about the extent to which wage premia reflect productivity, they do suggest that the long-term supply-side impacts of HEIs provide a significant boost to regional GDP. Furthermore, the results suggest that the supply-side impacts of HEIs are likely to be more important than the expenditure impacts that are the focus of most HEI impact studies

Gender Differences in Publication Output: Towards an Unbiased Metric of Research Performance

We examined the publication records of a cohort of 168 life scientists in the field of ecology and evolutionary biology to assess gender differences in research performance. Clear discrepancies in publication rate between men and women appear very early in their careers and this has consequences for the subsequent citation of their work. We show that a recently proposed index designed to rank scientists fairly is in fact strongly biased against female researchers, and advocate a modified index to assess men and women on a more equitable basis

Residual susceptibility to measles among young adults in Victoria, Australia following a national targeted measles-mumps-rubella vaccination campaign

<p>Abstract</p> <p>Background</p> <p>Past measles immunisation policies in Australia have resulted in a cohort of young adults who have been inadequately vaccinated, but who also have low levels of naturally acquired immunity because immunisation programs have decreased the circulation of wild virus. A measles-mumps-rubella (MMR) immunisation campaign aimed at addressing this susceptibility to measles among young adults was conducted in Australia in 2001–2. By estimating age-specific immunity, we aimed to evaluate the success of this campaign in the state of Victoria.</p> <p>Methods</p> <p>We conducted serosurveys after the young adult MMR program at state and national levels to estimate immunity among young adults born between 1968–82. We compared results of the Victorian (state) surveys with the Victorian component of the national surveys and compared both surveys with surveys conducted before the campaign. We also reviewed all laboratory confirmed measles cases in Victoria between 2000–4.</p> <p>Results</p> <p>The Victorian state serosurveys indicated no significant change in immunity of the cohort following the young adult MMR campaign (83.9% immune pre and 85.5% immune post campaign) while the Victorian component of the national serosurvey indicated a significant decline in immunity (91.0% to 84.2%; p = 0.006). Both surveys indicated about 15% susceptibility to measles among young Victorian adults after the campaign. Measles outbreaks in Victoria between 2000–4 confirmed the susceptibility of young adults. Outbreaks involved a median of 2.5 cases with a median age of 24.5 years.</p> <p>Conclusion</p> <p>In Victoria, the young adult MMR program appears to have had no effect on residual susceptibility to measles among the 1968–82 birth cohort. Young adults in Victoria, as in other countries where past immunisation policies have left a residual susceptible cohort, represent a potential problem for the maintenance of measles elimination.</p

Comparison of hospital charge prediction models for gastric cancer patients: neural network vs. decision tree models

<p>Abstract</p> <p>Background</p> <p>In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients.</p> <p>Methods</p> <p>Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes.</p> <p>Results</p> <p>After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model.</p> <p>Conclusion</p> <p>ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.</p

Cutpoints for mild, moderate and severe pain in patients with osteoarthritis of the hip or knee ready for joint replacement surgery

<p>Abstract</p> <p>Background</p> <p>Cutpoints (CPs) for mild, moderate and severe pain are established and used primarily in cancer pain. In this study, we wanted to determine the optimal CPs for mild, moderate, and severe pain in joint replacement surgery candidates with osteoarthritis (OA) of the hip or knee, and to validate the different CPs.</p> <p>Methods</p> <p>Patients (n = 353) completed the Brief Pain Inventory (BPI), the WOMAC Arthritis Index, and the SF-36 health status measure. Optimal CPs for categorizing average pain with three severity levels were derived using multivariate analysis of variance, using different CP sets for average pain as the independent variable and seven interference items from the BPI as the dependent variable. To validate the CPs, we assessed if patients in the three pain severity groups differed in pain as assessed with WOMAC and SF-36, and if BPI average pain with the optimal CPs resulted in higher correlation with pain dimensions of the WOMAC and SF-36 than other CPs.</p> <p>Results</p> <p>The optimal CPs on the 0–10 point BPI scale were CP (4,6) among hip patients and CP (4,7) among knee patients. The resulting pain severity groups differed in pain, as assessed with other scales than those used to derive the CPs. The optimal CPs had the highest association of average pain with WOMAC pain scores.</p> <p>Conclusion</p> <p>CPs for pain severity differed somewhat for patients with OA of the hip and knee. The association of BPI average pain scores categorized according to the optimal CPs with WOMAC pain scores supports the validity of the derived optimal CPs.</p

SCAMP:standardised, concentrated, additional macronutrients, parenteral nutrition in very preterm infants: a phase IV randomised, controlled exploratory study of macronutrient intake, growth and other aspects of neonatal care

<p>Abstract</p> <p>Background</p> <p>Infants born <29 weeks gestation are at high risk of neurocognitive disability. Early postnatal growth failure, particularly head growth, is an important and potentially reversible risk factor for impaired neurodevelopmental outcome. Inadequate nutrition is a major factor in this postnatal growth failure, optimal protein and calorie (macronutrient) intakes are rarely achieved, especially in the first week. Infants <29 weeks are dependent on parenteral nutrition for the bulk of their nutrient needs for the first 2-3 weeks of life to allow gut adaptation to milk digestion. The prescription, formulation and administration of neonatal parenteral nutrition is critical to achieving optimal protein and calorie intake but has received little scientific evaluation. Current neonatal parenteral nutrition regimens often rely on individualised prescription to manage the labile, unpredictable biochemical and metabolic control characteristic of the early neonatal period. Individualised prescription frequently fails to translate into optimal macronutrient delivery. We have previously shown that a standardised, concentrated neonatal parenteral nutrition regimen can optimise macronutrient intake.</p> <p>Methods</p> <p>We propose a single centre, randomised controlled exploratory trial of two standardised, concentrated neonatal parenteral nutrition regimens comparing a standard macronutrient content (maximum protein 2.8 g/kg/day; lipid 2.8 g/kg/day, dextrose 10%) with a higher macronutrient content (maximum protein 3.8 g/kg/day; lipid 3.8 g/kg/day, dextrose 12%) over the first 28 days of life. 150 infants 24-28 completed weeks gestation and birthweight <1200 g will be recruited. The primary outcome will be head growth velocity in the first 28 days of life. Secondary outcomes will include a) auxological data between birth and 36 weeks corrected gestational age b) actual macronutrient intake in first 28 days c) biomarkers of biochemical and metabolic tolerance d) infection biomarkers and other intravascular line complications e) incidence of major complications of prematurity including mortality f) neurodevelopmental outcome at 2 years corrected gestational age</p> <p>Trial registration</p> <p>Current controlled trials: <a href="http://www.controlled-trials.com/ISRCTN76597892">ISRCTN76597892</a>; EudraCT Number: 2008-008899-14</p

Lower Respiratory Tract Infection Induced by a Genetically Modified Picornavirus in Its Natural Murine Host

Infections with the picornavirus, human rhinovirus (HRV), are a major cause of wheezing illnesses and asthma exacerbations. In developing a murine model of picornaviral airway infection, we noted the absence of murine rhinoviruses and that mice are not natural hosts for HRV. The picornavirus, mengovirus, induces lethal systemic infections in its natural murine hosts, but small genetic differences can profoundly affect picornaviral tropism and virulence. We demonstrate that inhalation of a genetically attenuated mengovirus, vMC0, induces lower respiratory tract infections in mice. After intranasal vMC0 inoculation, lung viral titers increased, peaking at 24 h postinoculation with viral shedding persisting for 5 days, whereas HRV-A01a lung viral titers decreased and were undetectable 24 h after intranasal inoculation. Inhalation of vMC0, but not vehicle or UV-inactivated vMC0, induced an acute respiratory illness, with body weight loss and lower airway inflammation, characterized by increased numbers of airway neutrophils and lymphocytes and elevated pulmonary expression of neutrophil chemoattractant CXCR2 ligands (CXCL1, CXCL2, CXCL5) and interleukin-17A. Mice inoculated with vMC0, compared with those inoculated with vehicle or UV-inactivated vMC0, exhibited increased pulmonary expression of interferon (IFN-α, IFN-β, IFN-λ), viral RNA sensors [toll-like receptor (TLR)3, TLR7, nucleotide-binding oligomerization domain containing 2 (NOD2)], and chemokines associated with HRV infection in humans (CXCL10, CCL2). Inhalation of vMC0, but not vehicle or UV-inactivated vMC0, was accompanied by increased airway fluid myeloperoxidase levels, an indicator of neutrophil activation, increased MUC5B gene expression, and lung edema, a sign of infection-related lung injury. Consistent with experimental HRV inoculations of nonallergic, nonasthmatic human subjects, there were no effects on airway hyperresponsiveness after inhalation of vMC0 by healthy mice. This novel murine model of picornaviral airway infection and inflammation should be useful for defining mechanisms of HRV pathogenesis in humans

Body composition in male elite athletes, comparison of bioelectrical impedance spectroscopy with dual energy X-ray absorptiometry

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to compare body composition results from bioelectrical spectroscopy (BIS) with results from dual energy X-ray absorptiometry (DXA) in a population of male elite athletes. Body composition was assessed using DXA (Lunar Prodigy, GE Lunar Corp., Madison, USA) and BIS (Hydra 4200, Xitron Technologies Inc, San Diego, California, USA) at the same occasion. Agreement between methods was assessed using paired t-tests and agreement-plots.</p> <p>Results</p> <p>Thirty-three male elite athletes (soccer and ice hockey) were included in the study. The results showed that BIS underestimates the proportion of fat mass by 4.6% points in the ice hockey players. In soccer players the BIS resulted in a lower mean fat mass by 1.1% points. Agreement between the methods at the individual level was highly variable.</p> <p>Conclusion</p> <p>Body composition results assessed by BIS in elite athletes should be interpreted with caution, especially in individual subjects. BIS may present values of fat mass that is either higher or lower than fat mass assessed by DXA, independent of true fat content of the individual.</p