Action research and democracy

This contribution explores the relationship between research and learning democracy. Action research is seen as being compatible with the orientation of educational and social work research towards social justice and democracy. Nevertheless, the history of action research is characterized by a tension between democracy and social engineering. In the social-engineering approach, action research is conceptualized as a process of innovation aimed at a specific Bildungsideal. In a democratic approach action research is seen as research based on cooperation between research and practice. However, the notion of democratic action research as opposed to social engineering action research needs to be theorized. So called democratic action research involving the implementation by the researcher of democracy as a model and as a preset goal, reduces cooperation and participation into instruments to reach this goal, and becomes a type of social engineering in itself. We argue that the relationship between action research and democracy is in the acknowledgment of the political dimension of participation: ‘a democratic relationship in which both sides exercise power and shared control over decision-making as well as interpretation’. This implies an open research design and methodology able to understand democracy as a learning process and an ongoing experiment

A dynamic network approach for the study of human phenotypes

The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have; (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities; (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases; and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.Comment: 28 pages (double space), 6 figure

Light dark matter in the NMSSM: upper bounds on direct detection cross sections

In the Next-to-Minimal Supersymmetric Standard Model, a bino-like LSP can be as light as a few GeV and satisfy WMAP constraints on the dark matter relic density in the presence of a light CP-odd Higgs scalar. We study upper bounds on the direct detection cross sections for such a light LSP in the mass range 2-20 GeV in the NMSSM, respecting all constraints from B-physics and LEP. The OPAL constraints on e^+ e^- -> \chi^0_1 \chi^0_i (i > 1) play an important role and are discussed in some detail. The resulting upper bounds on the spin-independent and spin-dependent nucleon cross sections are ~ 10^{-42} cm^{-2} and ~ 4\times 10^{-40} cm^{-2}, respectively. Hence the upper bound on the spin-independent cross section is below the DAMA and CoGeNT regions, but could be compatible with the two events observed by CDMS-II.Comment: 17 pages, 3 figure

The pediatric glucocorticoid toxicity index

Objectives: To develop a Pediatric glucocorticoid toxicity index (pGTI), a standardized, weighted clinical outcome assessment that measures change in glucocorticoid (GC) toxicity over time. Methods: Fourteen physician experts from 7 subspecialties participated. The physician experts represented multiple subspecialties in which GCs play a major role in the treatment of inflammatory disease: nephrology, rheumatology, oncology, endocrinology, genetics, psychiatry, and maternal-fetal medicine. Nine investigators were from Canada, Europe, or New Zealand, and 5 were from the United States. Group consensus methods and multi-criteria decision analysis were used. The pGTI is an aggregate assessment of GC toxicities that are common, important, and dynamic. These toxicities are organized into health domains graded as minor, moderate, or major and are weighted according to severity. The relative weights were derived by group consensus and multi-criteria decision analysis using the 1000MindsTM software platform. Two quantitative scores comprise the overall toxicity profile derived from pGTI data: (1) the Cumulative Worsening Score; and (2) the Aggregate Improvement Score. The pGTI also includes a qualitative, unweighted record of GC side-effects known as the Damage Checklist, which documents less common toxicities that, although potentially severe, are unlikely to change with varying GC dosing. Results: One hundred and seven (107) toxicity items were included in the pGTI and thirty-two (32) in the Damage Checklist. To assess the degree to which the pGTI corresponds to expert clinical judgement, the investigators ranked 15 cases by clinical judgement from highest to lowest GC toxicity. Expert rankings were then compared to case ranking by the pGTI, yielding excellent agreement (weighted kappa 0.86). The pGTI was migrated to a digital environment following its development and initial validation. The digital platform is designed to ensure ease-of-use in the clinic, rigor in application, and accuracy of scoring. Clinic staff enter vital signs, laboratory results, and medication changes relevant to pGTI scoring. Clinicians record findings for GC myopathy, skin toxicity, mood dysfunction, and infection. The pGTI algorithms then apply the weights to these raw data and calculate scores. Embedded logic accounts for the impact of age- and sex-related reference ranges on several health domains: blood pressure, lipid metabolism, and bone mineral density. Other algorithms account for anticipated changes in the height Z-scores used in the growth domain, thereby addressing a concern unique to GC toxicity in children. The Damage Checklist ensures comprehensive measurement of GC toxicity but does not contribute to pGTI scoring, because the scored domains emphasize manifestations of GC toxicity that are likely to change over the course of a trial. Conclusions: We describe the development and initial evaluation of a weighted, composite toxicity index for the assessment of morbidity related to GC use in children and adolescents. Developing the pGTI digital platform was essential for performing the nuanced calculations necessary to ensure rigor, accuracy, and ease-of-use in both clinic and research settings

Efficacy and safety of indacaterol 150 μg once-daily in COPD: a double-blind, randomised, 12-week study

<p>Abstract</p> <p>Background</p> <p>Indacaterol is a novel, once-daily (o.d.) inhaled, long-acting <it>β</it>₂-agonist in development for chronic obstructive pulmonary disease (COPD). This 12-week, double-blind study compared the efficacy, safety, and tolerability of indacaterol to that of placebo in patients with moderate-to-severe COPD.</p> <p>Methods</p> <p>Efficacy variables included 24-h trough FEV₁(mean of 23 h 10 min and 23 h 45 min post-dose) at Week 12 (primary endpoint) and after Day 1, and the percentage of COPD days with poor control (i.e., worsening symptoms). Safety was assessed by adverse events (AEs), mean serum potassium and blood glucose, QTc (Fridericia), and vital signs.</p> <p>Results</p> <p>Patients were randomised (n = 416, mean age 63 years) to receive either indacaterol 150 <it>μ</it>g o.d. (n = 211) or placebo (n = 205) via a single-dose dry-powder inhaler; 87.5% completed the study. Trough FEV₁(LSM ± SEM) at Week 12 was 1.48 ± 0.018 L for indacaterol and 1.35 ± 0.019 L for placebo, a clinically relevant difference of 130 ± 24 mL (p < 0.001). Trough FEV₁after one dose was significantly higher with indacaterol than placebo (p < 0.001). Indacaterol demonstrated significantly higher peak FEV₁than placebo, both on Day 1 and at Week 12, with indacaterol-placebo differences (LSM ± SEM) of 190 ± 28 (p < 0.001) and 160 ± 28 mL (p < 0.001), respectively. Standardised AUC measurements for FEV₁(between 5 min and 4 h, 5 min and 1 h, and 1 and 4 h post-dose) at Week 12 were all significantly greater with indacaterol than placebo (p < 0.001), with LSM (± SEM) differences of 170 ± 24, 180 ± 24, and 170 ± 24 mL, respectively. Indacaterol significantly reduced the percentage of days of poor control versus placebo by 22.5% (p < 0.001) and was also associated with significantly reduced use of rescue medication (p < 0.001). The overall rates of AEs were comparable between the groups (indacaterol 49.3%, placebo 46.8%), with the most common AEs being COPD worsening (indacaterol 8.5%, placebo 12.2%) and cough (indacaterol 6.2%, placebo 7.3%). One patient died in the placebo group. Serum potassium and blood glucose levels did not differ significantly between the two groups, and no patient had QTc >500 ms.</p> <p>Conclusions</p> <p>Indacaterol 150 <it>μ</it>g o.d. provided clinically significant and sustained bronchodilation, reduced rescue medication use, and had a safety and tolerability profile similar to placebo.</p> <p>Trial registration</p> <p>NCT00624286</p

Effective Dark Matter Model: Relic density, CDMS II, Fermi LAT and LHC

The Cryogenic Dark Matter Search recently announced the observation of two signal events with a 77% confidence level. Although statistically inconclusive, it is nevertheless suggestive. In this work we present a model-independent analysis on the implication of a positive signal in dark matter scattering off nuclei. Assuming the interaction between (scalar, fermion or vector) dark matter and the standard model induced by unknown new physics at the scale $\Lambda$, we examine various dimension-6 tree-level induced operators and constrain them using the current experimental data, e.g. the WMAP data of the relic abundance, CDMS II direct detection of the spin-independent scattering, and indirect detection data (Fermi LAT cosmic gamma-ray), etc. Finally, the LHC reach is also explored

Effectiveness of social media sentiment analysis tools with the support of emoticon/emoji

Organizations are increasingly interested in using microblogging platforms, such as Twitter, to get rapid feedback in several domains using sentiment analysis algorithms to rate, for example, whether a target audience is happy or unhappy. However, posts on microblogging platforms can differ from the source material used to train the sentiment analysis tools. For example, emojis and emoticons are increasingly employed in social media to clarify, enhance, or sometimes reverse the sentiment of a post but can be stripped out of a piece of text before it is processed. Responding to this interest, many sentiment analysis algorithms are being made available as web services, but as details of the algorithms used are not always published on the website, comparisons between web services and how well they deal with the peculiarities of microblogging posts can be difficult. To address this, a prototype web application was developed to compare the performance of nine tweet-related sentiment analysis web services and, through targeted hypotheses, to study the effect of emojis and emoticons on polarity classification. Twelve specific research test sets were created with the application, labelled by volunteers, and tested against the analysis web services with evaluation provided by two- and three-class accuracy measures. Distinct differences were found in how the web services used emoticons and emojis in assigning a positive or negative sentiment value to a tweet, with some services seeming to ignore their presence. It was found in general that web services classified polarity sensitive tweets significantly less accurately than tweets where the sentiment of the emoji/emoticon supported the sentiment of the text

Fungal iron availability during deep seated candidiasis is defined by a complex interplay involving systemic and local events

Peer reviewedPublisher PD

Bacteremic community-acquired pneumonia due to Klebsiella pneumoniae: Clinical and microbiological characteristics in Taiwan, 2001-2008

<p>Abstract</p> <p>Background</p> <p><it>Klebsiella pneumoniae </it>is the major cause of community-acquired pyogenic infections in Taiwan. This retrospective study evaluated the clinical and microbiological characteristics of bacteremic community-acquired pneumonia due to <it>K. pneumoniae </it>in Taiwanese adults.</p> <p>Methods</p> <p>The clinical characteristics of bacteremic community-acquired pneumonia (CAP) in adults due to <it>K. pneumoniae </it>were compared to those of adults with bacteremic CAP due to <it>Streptococcus pneumoniae </it>at a tertiary medical center in Taiwan from 2001-2008. Risk factors for mortality of bacteremic CAP due to <it>K. pneumoniae </it>were analyzed. All clinical isolates of <it>K. pneumoniae </it>were examined for capsular serotypes, hypermucoviscosity phenotype, aerobactin and <it>rmpA </it>gene.</p> <p>Results</p> <p><it>K. pneumoniae </it>was the dominant cause of bacteremic CAP and was associated with a more fulminant course and a worse prognosis than bacteremic CAP due to <it>Streptococcus pneumoniae</it>. Initial presentation with septic shock and respiratory failure were independent risk factors for both early and total mortality. Serotype K1 and K2 comprised around half of all isolates. There were no significant differences in the clinical characteristics of patients with bacteremic CAP due to K1/K2 and non-K1/K2 isolates. Hypermucoviscosity phenotype as well as the aerobactin and <it>rmpA </it>genes were highly prevalent in the <it>K. pneumoniae </it>isolates.</p> <p>Conclusions</p> <p><it>K. pneumoniae </it>continued to be the dominant cause of bacteremic CAP in Taiwanese adults during 2001-2008. Initial presentation with septic shock and respiratory failure were independent risk factors for both early and total mortality from <it>K. pneumoniae </it>bacteremic CAP. Serotypes K1/K2 comprised around half of all isolates, but did not predispose patients to a poor clinical outcome. Physicians should be aware of the poor prognosis of any patient with bacteremic <it>K. pneumoniae </it>CAP and monitor these patients more closely.</p