Subcutaneous Immunotherapy with a Depigmented Polymerized Birch Pollen Extract – A New Therapeutic Option for Patients with Atopic Dermatitis

Background: Birch pollen is an important outdoor allergen able to aggravate symptoms in atopic dermatitis (AD). Specific immunotherapy (SIT), an established procedure for allergic airway diseases, might also represent an attractive therapeutic option for the causal treatment of allergen-triggered cutaneous symptoms in these patients. Studies with house dust mite SIT have already shown beneficial effects in AD patients, whereas the safety and efficacy of SIT with birch pollen extract in AD patients have not been studied so far. The aim of this study was to evaluate for the first time the safety and efficacy of SIT with a depigmented polymerized birch pollen extract in AD patients. Methods: Fifty-five adult patients with moderate-to-severe AD and clinically relevant sensitization to birch pollen received SIT for 12 weeks. SIT was continued during birch pollen season. The assessment of safety, the total SCORAD value, and the Dermatology Life Quality Index (DLQI) were evaluated. Results: The median total SCORAD value was reduced by 34% (p < 0.001) during the course of treatment and the mean DLQI improved by 49% (p < 0.001) despite strong simultaneous birch pollen exposure. Eight patients (14.5%) developed systemic reactions and 19 patients (34.5%) developed local reactions which were of mild intensity in most cases. No patient discontinued the study prematurely due to adverse drug reactions. Coseasonal treatment was well tolerated. Conclusion: SIT with a depigmented polymerized birch pollen extract leads to significant improvement of the SCORAD value and the DLQI in patients suffering from moderate-to-severe AD sensitized to birch pollen.Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe