Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

Increased ventral striatal volume in college-aged binge drinkers

BACKGROUND Binge drinking is a serious public health issue associated with cognitive, physiological, and anatomical differences from healthy individuals. No studies, however, have reported subcortical grey matter differences in this population. To address this, we compared the grey matter volumes of college-age binge drinkers and healthy controls, focusing on the ventral striatum, hippocampus and amygdala. METHOD T1-weighted images of 19 binge drinkers and 19 healthy volunteers were analyzed using voxel-based morphometry. Structural data were also covaried with Alcohol Use Disorders Identification Test (AUDIT) scores. Cluster-extent threshold and small volume corrections were both used to analyze imaging data. RESULTS Binge drinkers had significantly larger ventral striatal grey matter volumes compared to controls. There were no between group differences in hippocampal or amygdalar volume. Ventral striatal, amygdalar, and hippocampal volumes were also negatively related to AUDIT scores across groups. CONCLUSIONS Our findings stand in contrast to the lower ventral striatal volume previously observed in more severe forms of alcohol use disorders, suggesting that college-age binge drinkers may represent a distinct population from those groups. These findings may instead represent early sequelae, compensatory effects of repeated binge and withdrawal, or an endophenotypic risk factor

Beta defensin-2 is reduced in central but not in distal airways of smoker COPD patients

Background: Altered pulmonary defenses in chronic obstructive pulmonary disease (COPD) may promote distal airways bacterial colonization. The expression/activation of Toll Like receptors (TLR) and beta 2 defensin (HBD2) release by epithelial cells crucially affect pulmonary defence mechanisms. Methods: The epithelial expression of TLR4 and of HBD2 was assessed in surgical specimens from current smokers COPD (s-COPD; n = 17), ex-smokers COPD (ex-s-COPD; n = 8), smokers without COPD (S; n = 12), and from non-smoker non-COPD subjects (C; n = 13). Results: In distal airways, s-COPD highly expressed TLR4 and HBD2. In central airways, S and s-COPD showed increased TLR4 expression. Lower HBD2 expression was observed in central airways of s-COPD when compared to S and to ex-s-COPD. s-COPD had a reduced HBD2 gene expression as demonstrated by real-time PCR on micro-dissected bronchial epithelial cells. Furthermore, HBD2 expression positively correlated with FEV1/FVC ratio and inversely correlated with the cigarette smoke exposure. In a bronchial epithelial cell line (16 HBE) IL-1β significantly induced the HBD2 mRNA expression and cigarette smoke extracts significantly counteracted this IL-1 mediated effect reducing both the activation of NFkB pathway and the interaction between NFkB and HBD2 promoter. Conclusions: This study provides new insights on the possible mechanisms involved in the alteration of innate immunity mechanisms in COPD. © 2012 Pace et al

The validity of using ICD-9 codes and pharmacy records to identify patients with chronic obstructive pulmonary disease

Background: Administrative data is often used to identify patients with chronic obstructive pulmonary disease (COPD), yet the validity of this approach is unclear. We sought to develop a predictive model utilizing administrative data to accurately identify patients with COPD. Methods: Sequential logistic regression models were constructed using 9573 patients with postbronchodilator spirometry at two Veterans Affairs medical centers (2003-2007). COPD was defined as: 1) FEV1/FVC <0.70, and 2) FEV1/FVC < lower limits of normal. Model inputs included age, outpatient or inpatient COPD-related ICD-9 codes, and the number of metered does inhalers (MDI) prescribed over the one year prior to and one year post spirometry. Model performance was assessed using standard criteria. Results: 4564 of 9573 patients (47.7%) had an FEV1/FVC < 0.70. The presence of ≥1 outpatient COPD visit had a sensitivity of 76% and specificity of 67%; the AUC was 0.75 (95% CI 0.74-0.76). Adding the use of albuterol MDI increased the AUC of this model to 0.76 (95% CI 0.75-0.77) while the addition of ipratropium bromide MDI increased the AUC to 0.77 (95% CI 0.76-0.78). The best performing model included: ≥6 albuterol MDI, ≥3 ipratropium MDI, ≥1 outpatient ICD-9 code, ≥1 inpatient ICD-9 code, and age, achieving an AUC of 0.79 (95% CI 0.78-0.80). Conclusion: Commonly used definitions of COPD in observational studies misclassify the majority of patients as having COPD. Using multiple diagnostic codes in combination with pharmacy data improves the ability to accurately identify patients with COPD.Department of Veterans Affairs, Health Services Research and Development (DHA), American Lung Association (CI- 51755-N) awarded to DHA, the American Thoracic Society Fellow Career Development AwardPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84155/1/Cooke - ICD9 validity in COPD.pd