A New Approach to Analyzing Patterns of Collaboration in Co-authorship Networks - Mesoscopic Analysis and Interpretation

This paper focuses on methods to study patterns of collaboration in co-authorship networks at the mesoscopic level. We combine qualitative methods (participant interviews) with quantitative methods (network analysis) and demonstrate the application and value of our approach in a case study comparing three research fields in chemistry. A mesoscopic level of analysis means that in addition to the basic analytic unit of the individual researcher as node in a co-author network, we base our analysis on the observed modular structure of co-author networks. We interpret the clustering of authors into groups as bibliometric footprints of the basic collective units of knowledge production in a research specialty. We find two types of coauthor-linking patterns between author clusters that we interpret as representing two different forms of cooperative behavior, transfer-type connections due to career migrations or one-off services rendered, and stronger, dedicated inter-group collaboration. Hence the generic coauthor network of a research specialty can be understood as the overlay of two distinct types of cooperative networks between groups of authors publishing in a research specialty. We show how our analytic approach exposes field specific differences in the social organization of research.Comment: An earlier version of the paper was presented at ISSI 2009, 14-17 July, Rio de Janeiro, Brazil. Revised version accepted on 2 April 2010 for publication in Scientometrics. Removed part on node-role connectivity profile analysis after finding error in calculation and deciding to postpone analysis

Multi-level evidence of an allelic hierarchy of USH2A variants in hearing, auditory processing and speech/language outcomes.

Language development builds upon a complex network of interacting subservient systems. It therefore follows that variations in, and subclinical disruptions of, these systems may have secondary effects on emergent language. In this paper, we consider the relationship between genetic variants, hearing, auditory processing and language development. We employ whole genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. These investigations indicate that USH2A variants are associated with altered low-frequency sound perception which, in turn, increases the risk of developmental language disorder. We further show that Ush2a heterozygote mice have low-level hearing impairments, persistent higher-order acoustic processing deficits and altered vocalizations. These findings provide new insights into the complexity of genetic mechanisms serving language development and disorders and the relationships between developmental auditory and neural systems

Motives and comprehension in a public goods game with induced emotions

This study analyses the sensitivity of public goods contributions through the lens of psychological motives. We report the results of a public goods experiment in which subjects were induced with the motives of care and anger through autobiographical recall. Subjects' preferences, beliefs, and perceptions under each motive are compared with those of subjects experiencing a neutral autobiographical recall control condition. We find, but only for those subjects with the highest comprehension of the game, that care elicits significantly higher contributions than anger, with the control treatment in between. This positive influence of the care motive on unconditional giving is accounted for partly by preferences for giving and partly by the beliefs concerning greater contributions by others. Anger also affects attention to own and other's payoffs (using mouse tracking) and perceptions of the game's incentive structure (cooperative or competitive)

Medroxyprogesterone Acetate Alters Mycobacterium Bovis BCG-Induced Cytokine Production in Peripheral Blood Mononuclear Cells of Contraceptive Users

Most individuals latently infected with Mycobacterium tuberculosis (M.tb) contain the infection by a balance of effector and regulatory immune responses. This balance can be influenced by steroid hormones such as glucocorticoids. The widely used contraceptive medroxyprogesterone acetate (MPA) possesses glucocorticoid activity. We investigated the effect of this hormone on immune responses to BCG in household contacts of active TB patients. Multiplex bead array analysis revealed that MPA demonstrated both glucocorticoid and progestogenic properties at saturating and pharmacological concentrations in peripheral blood mononuclear cells (PBMCs) and suppressed antigen specific cytokine production. Furthermore we showed that PBMCs from women using MPA produced significantly lower levels of IL-1α, IL-12p40, IL-10, IL-13 and G-CSF in response to BCG which corresponded with lower numbers of circulating monocytes observed in these women. Our research study is the first to show that MPA impacts on infections outside the genital tract due to a systemic effect on immune function. Therefore MPA use could alter susceptibility to TB, TB disease severity as well as change the efficacy of new BCG-based vaccines, especially prime-boost vaccine strategies which may be administered to adult or adolescent women in the future

Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models

Purpose To investigate the robustness of pharmacokinetic modelling of DCE-MRI brain tumour data and to ascertain reliable perfusion parameters through a model selection process and a stability test. Methods DCE-MRI data of 14 patients with primary brain tumours were analysed using the Tofts model (TM), the extended Tofts model (ETM), the shutter speed model (SSM) and the extended shutter speed model (ESSM). A no-effect model (NEM) was implemented to assess overfitting of data by the other models. For each lesion, the Akaike Information Criteria (AIC) was used to build a 3D model selection map. The variability of each pharmacokinetic parameter extracted from this map was assessed with a noise propagation procedure, resulting in voxel-wise distributions of the coefficient of variation (CV). Results The model selection map over all patients showed NEM had the best fit in 35.5% of voxels, followed by ETM (32%), TM (28.2%), SSM (4.3%) and ESSM (<0.1%). In analysing the reliability of Ktrans, when considering regions with a CV<20%, ≈25% of voxels were found to be stable across all patients. The remaining 75% of voxels were considered unreliable. Conclusions The majority of studies quantifying DCE-MRI data in brain tumours only consider a single model and whole-tumour statistics for the output parameters. Appropriate model selection, considering tissue biology and its effects on blood brain barrier permeability and exchange conditions, together with an analysis on the reliability and stability of the calculated parameters, is critical in processing robust brain tumour DCE-MRI data

Comparison of gene expression profiles in core biopsies and corresponding surgical breast cancer samples

INTRODUCTION: Gene expression profiling has been successfully used to classify breast cancer into clinically distinct subtypes, and to predict the risk of recurrence and treatment response. The aim of this study was to investigate whether the gene expression profile (GEP) detected in a core biopsy (CB) is representative for the entire tumor, since CB is an important tool in breast cancer diagnosis. Moreover, we investigated whether performing CBs prior to the surgical excision could influence the GEP of the respective tumor. METHODS: We quantified the RNA expression of 60 relevant genes by quantitative real-time PCR in paired CBs and surgical specimens from 22 untreated primary breast cancer patients. Subsequently, expression data were compared with independent GEPs obtained from tumors of 317 patients without preceding CB. RESULTS: In 82% of the cases the GEP detected in the CB correlated very well with the corresponding profile in the surgical sample (r(s )≥ 0.95, p < 0.001). Gene-by-gene analysis revealed four genes significantly elevated in the surgical sample compared to the CB; these comprised genes mainly involved in inflammation and the wound repair process as well as in tumor invasion and metastasis. CONCLUSION: A GEP detected in a CB are representative for the entire tumor and is, therefore, of clinical relevance. The observed alterations of individual genes after performance of CB deserve attention since they might impact the clinical interpretation with respect to prognosis and therapy prediction of the GEP as detected in the surgical specimen following CB performance

Gradients and Modulation of K+ Channels Optimize Temporal Accuracy in Networks of Auditory Neurons

Accurate timing of action potentials is required for neurons in auditory brainstem nuclei to encode the frequency and phase of incoming sound stimuli. Many such neurons express “high threshold” Kv3-family channels that are required for firing at high rates (>∼200 Hz). Kv3 channels are expressed in gradients along the medial-lateral tonotopic axis of the nuclei. Numerical simulations of auditory brainstem neurons were used to calculate the input-output relations of ensembles of 1–50 neurons, stimulated at rates between 100–1500 Hz. Individual neurons with different levels of potassium currents differ in their ability to follow specific rates of stimulation but all perform poorly when the stimulus rate is greater than the maximal firing rate of the neurons. The temporal accuracy of the combined synaptic output of an ensemble is, however, enhanced by the presence of gradients in Kv3 channel levels over that measured when neurons express uniform levels of channels. Surprisingly, at high rates of stimulation, temporal accuracy is also enhanced by the occurrence of random spontaneous activity, such as is normally observed in the absence of sound stimulation. For any pattern of stimulation, however, greatest accuracy is observed when, in the presence of spontaneous activity, the levels of potassium conductance in all of the neurons is adjusted to that found in the subset of neurons that respond better than their neighbors. This optimization of response by adjusting the K+ conductance occurs for stimulus patterns containing either single and or multiple frequencies in the phase-locking range. The findings suggest that gradients of channel expression are required for normal auditory processing and that changes in levels of potassium currents across the nuclei, by mechanisms such as protein phosphorylation and rapid changes in channel synthesis, adapt the nuclei to the ongoing auditory environment

Self-prioritization and perceptual matching: The effects of temporal construal.

Recent research has revealed that self-referential processing enhances perceptual judgments - the so-called self-prioritization effect. The extent and origin of this effect remains unknown, however. Noting the multifaceted nature of the self, here we hypothesized that temporal influences on self-construal (i.e., past/future-self continuity) may serve as an important determinant of stimulus prioritization. Specifically, as representations of the self increase in abstraction as a function of temporal distance (i.e., distance from now), self-prioritization may only emerge when stimuli are associated with the current self. The results of three experiments supported this prediction. Self-relevance only enhanced performance in a standard perceptual-matching task when stimuli (i.e., geometric shapes) were connected with the current self; representations of the self in the future (Expts. 1 & 2) and past (Expt. 3) failed to facilitate decision making. To identify the processes underlying task performance, data were interrogated using a hierarchical drift diffusion model (HDDM) approach. Results of these analyses revealed that self-prioritization was underpinned by a stimulus bias (i.e., rate of information uptake). Collectively, these findings elucidate when and how self-relevance influences decisional processing

Evidence-based guidelines for the pharmacological treatment of postmenopausal osteoporosis: a consensus document by the Belgian Bone Club

Several drugs are available for the management of postmenopausal osteoporosis. This may, in daily practice, confuse the clinician. This manuscript offers an evidence-based update of previous treatment guidelines, with a critical assessment of the currently available efficacy data on all new chemical entities which were granted a marketing authorization. Osteoporosis is widely recognized as a major public health concern. The availability of new therapeutic agents makes clinical decision-making in osteoporosis more complex. Nation-specific guidelines are needed to take into consideration the specificities of each and every health care environment. The present manuscript is the result of a National Consensus, based on a systematic review and a critical appraisal of the currently available literature. It offers an evidence-based update of previous treatment guidelines, with the aim of providing clinicians with an unbiased assessment of osteoporosis treatment effect

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior