Why do scientists migrate? A diffusion model

The article is intended to improve our understanding of the reasons underlying the intellectual migration of scientists from well-known cognitive domains to nascent scientific fields. To that purpose we present, first, a number of findings from the sociology of science that give different insights about this phenomenon. We then attempt to bring some of these insights together under the conceptual roof of an actor-based approach linking expected utility and diffusion theory. Intellectual migration is regarded as the rational choice of scientists who decide under uncertainty and on the base of a number of decision-making variables, which define probabilities, costs, and benefits of the migration.

Counsellor behaviours and patient language during brief motivational interventions: a sequential analysis of speech

AIMS: To investigate empirically the hypothesized relationship between counsellor motivational interviewing (MI) skills and patient change talk (CT) by analysing the articulation between counsellor behaviours and patient language during brief motivational interventions (BMI) addressing at-risk alcohol consumption. DESIGN: Sequential analysis of psycholinguistic codes obtained by two independent raters using the Motivational Interviewing Skill Code (MISC), version 2.0. SETTING: Secondary analysis of data from a randomized controlled trial evaluating the effectiveness of BMI in an emergency department. PARTICIPANTS: A total of 97 patients tape-recorded when receiving BMI. MEASUREMENTS: MISC variables were categorized into three counsellor behaviours (MI-consistent, MI-inconsistent and 'other') and three kinds of patient language (CT, counter-CT (CCT) and utterances not linked with the alcohol topic). Observed transition frequencies, conditional probabilities and significance levels based on odds ratios were computed using sequential analysis software. FINDINGS: MI-consistent behaviours were the only counsellor behaviours that were significantly more likely to be followed by patient CT. Those behaviours were significantly more likely to be followed by patient change exploration (CT and CCT) while MI-inconsistent behaviours and 'other' counsellor behaviours were significantly more likely to be followed by utterances not linked with the alcohol topic and significantly less likely to be followed by CT. MI-consistent behaviours were more likely after change exploration, whereas 'other' counsellor behaviours were more likely only after utterances not linked with the alcohol topic. CONCLUSIONS: Findings lend support to the hypothesized relationship between MI-consistent behaviours and CT, highlight the importance of patient influence on counsellor behaviour and emphasize the usefulness of MI techniques and spirit during brief interventions targeting change enhancement.

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient.Location Two study areas in the Alps of Switzerland.Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways - summing binary predictions, summing random draws of binomial trials and summing predicted probabilities - to obtain a final species count.Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches the summed binomial trials based on predicted probabilities and summed predicted probabilities - do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient.Main conclusions Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.

Modern statistical models for forensic fingerprint examinations : a critical review

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

Properties of ideal composite knots.

The shortest tube of constant diameter that can form a given knot represents the 'ideal' form of the knot. Ideal knots provide an irreducible representation of the knot, and they have some intriguing mathematical and physical features, including a direct correspondence with the time-averaged shapes of knotted DNA molecules in solution. Here we describe the properties of ideal forms of composite knots-knots obtained by the sequential tying of two or more independent knots (called factor knots) on the same string. We find that the writhe (related to the handedness of crossing points) of composite knots is the sum of that of the ideal forms of the factor knots. By comparing ideal composite knots with simulated configurations of knotted, thermally fluctuating DNA, we conclude that the additivity of writhe applies also to randomly distorted configurations of composite knots and their corresponding factor knots. We show that composite knots with several factor knots may possess distinct structural isomers that can be interconverted only by loosening the knot.

The subjectivist interpretation of probability and the problem of individualisation in forensic science

This paper presents and discusses further aspects of the subjectivist interpretation of probability (also known as the 'personalist' view of probabilities) as initiated in earlier forensic and legal literature. It shows that operational devices to elicit subjective probabilities - in particular the so-called scoring rules - provide additional arguments in support of the standpoint according to which categorical claims of forensic individualisation do not follow from a formal analysis under that view of probability theory.

Incidence of HIV-1 drug resistance among antiretroviral treatment-naive individuals starting modern therapy combinations.

BACKGROUND: Estimates of drug resistance incidence to modern first-line combination antiretroviral therapies against human immunodeficiency virus (HIV) type 1 are complicated by limited availability of genotypic drug resistance tests (GRTs) and uncertain timing of resistance emergence. METHODS: Five first-line combinations were studied (all paired with lamivudine or emtricitabine): efavirenz (EFV) plus zidovudine (AZT) (n = 524); EFV plus tenofovir (TDF) (n = 615); lopinavir (LPV) plus AZT (n = 573); LPV plus TDF (n = 301); and ritonavir-boosted atazanavir (ATZ/r) plus TDF (n = 250). Virological treatment outcomes were classified into 3 risk strata for emergence of resistance, based on whether undetectable HIV RNA levels were maintained during therapy and, if not, whether viral loads were >500 copies/mL during treatment. Probabilities for presence of resistance mutations were estimated from GRTs (n = 2876) according to risk stratum and therapy received at time of testing. On the basis of these data, events of resistance emergence were imputed for each individual and were assessed using survival analysis. Imputation was repeated 100 times, and results were summarized by median values (2.5th-97.5th percentile range). RESULTS: Six years after treatment initiation, EFV plus AZT showed the highest cumulative resistance incidence (16%) of all regimens (<11%). Confounder-adjusted Cox regression confirmed that first-line EFV plus AZT (reference) was associated with a higher median hazard for resistance emergence, compared with other treatments: EFV plus TDF (hazard ratio [HR], 0.57; range, 0.42-0.76), LPV plus AZT (HR, 0.63; range, 0.45-0.89), LPV plus TDF (HR, 0.55; range, 0.33-0.83), ATZ/r plus TDF (HR, 0.43; range, 0.17-0.83). Two-thirds of resistance events were associated with detectable HIV RNA level ≤500 copies/mL during treatment, and only one-third with virological failure (HIV RNA level, >500 copies/mL). CONCLUSIONS: The inclusion of TDF instead of AZT and ATZ/r was correlated with lower rates of resistance emergence, most likely because of improved tolerability and pharmacokinetics resulting from a once-daily dosage.

Rate of gene sequence evolution and species diversification in flowering plants: a re-evaluation

Barraclough and co-workers (in a paper published in 1996) observed that there was a significant positive correlation between the rate of evolution of the rbcL chloroplast gene within families of flowering plants and the number of species in those families. We tested three additional data sets of our own (based on both plastid and nuclear genes) and used methods designed specifically for the comparison of sister families (based on random speciation and extinction). We show that, over all sister groups, the correlation between the rate of gene evolution and an increased diversity is not always present. Despite tending towards a positive association, the observation of individual probabilities presents a U-shaped distribution of association (i.e. it can be either significantly positive or negative). We discuss the influence of both phylogenetic sampling and applied taxonomies on the results.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Combined impact of negative lifestyle factors on cardiovascular risk in children: a randomized prospective study.

PURPOSE: Negative lifestyle factors are known to be associated with increased cardiovascular risk (CVR) in children, but research on their combined impact on a general population of children is sparse. Therefore, we aimed to quantify the combined impact of easily assessable negative lifestyle factors on the CVR scores of randomly selected children after 4 years. METHODS: Of the 540 randomly selected 6- to 13-year-old children, 502 children participated in a baseline health assessment, and 64% were assessed again after 4 years. Measures included anthropometry, fasting blood samples, and a health assessment questionnaire. Participants scored one point for each negative lifestyle factor at baseline: overweight; physical inactivity; high media consumption; little outdoor time; skipping breakfast; and having a parent who has ever smoked, is inactive, or overweight. A CVR score at follow-up was constructed by averaging sex- and age-related z-scores of waist circumference, blood pressure, glucose, inverted high-density lipoprotein, and triglycerides. RESULTS: The age-, sex-, pubertal stage-, and social class-adjusted probabilities (95% confidence interval) for being in the highest CVR score tertile at follow-up for children who had at most one (n = 48), two (n = 64), three (n = 56), four (n = 41), or five or more (n = 14) risky lifestyle factors were 15.4% (8.9-25.3), 24.3% (17.4-32.8), 36.0% (28.6-44.2), 49.8% (38.6-61.0), and 63.5% (47.2-77.2), respectively. CONCLUSIONS: Even in childhood, an accumulation of negative lifestyle factors is associated with higher CVR scores after 4 years. These negative lifestyle factors are easy to assess in clinical practice and allow early detection and prevention of CVR in childhood.

Event-related potential analyses via single-subject topographic classification.

Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

FRAX® International Task Force of the 2010 Joint International Society for Clinical Densitometry & International Osteoporosis Foundation Position Development Conference.

Osteoporosis is a serious worldwide epidemic. FRAX® is a web-based tool developed by the Sheffield WHO Collaborating Center team, that integrates clinical risk factors and femoral neck BMD and calculates the 10 year fracture probability in order to help health care professionals identify patients who need treatment. However, only 31 countries have a FRAX® calculator. In the absence of a FRAX® model for a particular country, it has been suggested to use a surrogate country for which the epidemiology of osteoporosis most closely approximates the index country. More specific recommendations for clinicians in these countries are not available. In North America, concerns have also been raised regarding the assumptions used to construct the US ethnic specific FRAX® calculators with respect to the correction factors applied to derive fracture probabilities in Blacks, Asians and Hispanics in comparison to Whites. In addition, questions were raised about calculating fracture risk in other ethnic groups e.g., Native Americans and First Canadians. The International Society for Clinical Densitometry (ISCD) in conjunction with the International Osteoporosis Foundation (IOF) assembled an international panel of experts that ultimately developed joint Official Positions of the ISCD and IOF advising clinicians regarding FRAX® usage. As part of the process, the charge of the FRAX® International Task Force was to review and synthesize data regarding geographic and race/ethnic variability in hip fractures, non-hip osteoporotic fractures, and make recommendations about the use of FRAX® in ethnic groups and countries without a FRAX® calculator. This synthesis was presented to the expert panel and constitutes the data on which the subsequent Official Positions are predicated. A summary of the International Task Force composition and charge is presented here.

Explicit ruin formulas for models with dependence among risks

We show that a simple mixing idea allows one to establish a number of explicit formulas for ruin probabilities and related quantities in collective risk models with dependence among claim sizes and among claim inter-occurrence times. Examples include compound Poisson risk models with completely monotone marginal claim size distributions that are dependent according to Archimedean survival copulas as well as renewal risk models with dependent inter-occurrence times.

Reply to Budowle, Ge, Chakraborty and Gill-King: use of prior odds for missing persons identifications

Prior probabilities represent a core element of the Bayesian probabilistic approach to relatedness testing. This letter opinions on the commentary 'Use of prior odds for missing persons identifications' by Budowle et al. (2011), published recently in this journal. Contrary to Budowle et al. (2011), we argue that the concept of prior probabilities (i) is not endowed with the notion of objectivity, (ii) is not a case for computation and (iii) does not require new guidelines edited by the forensic DNA community - as long as probability is properly considered as an expression of personal belief. Please see related article: http://www.investigativegenetics.com/content/3/1/3

Dissection of the complex phenotype in cuticular mutants of Arabidopsis reveals a role of SERRATE as a mediator.

Mutations in LACERATA (LCR), FIDDLEHEAD (FDH), and BODYGUARD (BDG) cause a complex developmental syndrome that is consistent with an important role for these Arabidopsis genes in cuticle biogenesis. The genesis of their pleiotropic phenotypes is, however, poorly understood. We provide evidence that neither distorted depositions of cutin, nor deficiencies in the chemical composition of cuticular lipids, account for these features, instead suggesting that the mutants alleviate the functional disorder of the cuticle by reinforcing their defenses. To better understand how plants adapt to these mutations, we performed a genome-wide gene expression analysis. We found that apparent compensatory transcriptional responses in these mutants involve the induction of wax, cutin, cell wall, and defense genes. To gain greater insight into the mechanism by which cuticular mutations trigger this response in the plants, we performed an overlap meta-analysis, which is termed MASTA (MicroArray overlap Search Tool and Analysis), of differentially expressed genes. This suggested that different cell integrity pathways are recruited in cesA cellulose synthase and cuticular mutants. Using MASTA for an in silico suppressor/enhancer screen, we identified SERRATE (SE), which encodes a protein of RNA-processing multi-protein complexes, as a likely enhancer. In confirmation of this notion, the se lcr and se bdg double mutants eradicate severe leaf deformations as well as the organ fusions that are typical of lcr and bdg and other cuticular mutants. Also, lcr does not confer resistance to Botrytis cinerea in a se mutant background. We propose that there is a role for SERRATE-mediated RNA signaling in the cuticle integrity pathway.