University of Tübingen

About: University of Tübingen is a education organization based out in Tübingen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 40555 authors who have published 84108 publications receiving 3015320 citations. The organization is also known as: Eberhard Karls University & Eberhard-Karls-Universität Tübingen.

Encorafenib plus binimetinib versus vemurafenib or encorafenib in patients with BRAF-mutant melanoma (COLUMBUS): a multicentre, open-label, randomised phase 3 trial

Abstract: Summary Background Combined BRAF-MEK inhibitor therapy is the standard of care for BRAF V600 -mutant advanced melanoma. We investigated encorafenib, a BRAF inhibitor with unique target-binding properties, alone or in combination with the MEK inhibitor binimetinib, versus vemurafenib in patients with advanced BRAF V600 -mutant melanoma. Methods COLUMBUS was conducted as a two-part, randomised, open-label phase 3 study at 162 hospitals in 28 countries. Eligible patients were aged 18 years or older and had histologically confirmed locally advanced (American Joint Committee on Cancer [AJCC] stage IIIB, IIIC, or IV), unresectable or metastatic cutaneous melanoma, or unknown primary melanoma; a BRAF V600E or BRAF V600K mutation; an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1; and were treatment naive or had progressed on or after previous first-line immunotherapy. In part 1 of the study, patients were randomly assigned (1:1:1) via interactive response technology to receive either oral encorafenib 450 mg once daily plus oral binimetinib 45 mg twice daily (encorafenib plus binimetinib group), oral encorafenib 300 mg once daily (encorafenib group), or oral vemurafenib 960 mg twice daily (vemurafenib group). The primary endpoint was progression-free survival by blinded independent central review for encorafenib plus binimetinib versus vemurafenib. Efficacy analyses were by intention-to-treat. Safety was analysed in patients who received at least one dose of study drug and one postbaseline safety assessment. The results of part 2 will be published separately. This study is registered with ClinicalTrials.gov, number NCT01909453, and EudraCT, number 2013-001176-38. Findings Between Dec 30, 2013, and April 10, 2015, 577 of 1345 screened patients were randomly assigned to either the encorafenib plus binimetinib group (n=192), the encorafenib group (n=194), or the vemurafenib group (n=191). With a median follow-up of 16·6 months (95% CI 14·8–16·9), median progression-free survival was 14·9 months (95% CI 11·0–18·5) in the encorafenib plus binimetinib group and 7·3 months (5·6–8·2) in the vemurafenib group (hazard ratio [HR] 0·54, 95% CI 0·41–0·71; two-sided p Interpretation Encorafenib plus binimetinib and encorafenib monotherapy showed favourable efficacy compared with vemurafenib. Overall, encorafenib plus binimetinib appears to have an improved tolerability profile compared with encorafenib or vemurafenib. Encorafenib plus binimetinib could represent a new treatment option for patients with BRAF -mutant melanoma. Funding Array BioPharma, Novartis.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Dermcidin: a novel human antibiotic peptide secreted by sweat glands.

Abstract: Antimicrobial peptides are an important component of the innate response in many species. Here we describe the isolation of the gene Dermcidin, which encodes an antimicrobial peptide that has a broad spectrum of activity and no homology to other known antimicrobial peptides. This protein was specifically and constitutively expressed in the sweat glands, secreted into the sweat and transported to the epidermal surface. In sweat, a proteolytically processed 47–amino acid peptide was generated that showed antimicrobial activity in response to a variety of pathogenic microorganisms. The activity of the peptide was maintained over a broad pH range and in high salt concentrations that resembled the conditions in human sweat. This indicated that sweat plays a role in the regulation of human skin flora through the presence of an antimicrobial peptide. This peptide may help limit infection by potential pathogens in the first few hours following bacterial colonization.

From simple associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony

Abstract: Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency – as though these inferences were a reflexive response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuronlike elements represent a large body of systemic knowledge and perform a range of inferences with such speed? We describe a computational model that takes a step toward addressing the cognitive science challenge and resolving the artificial intelligence paradox. We show how a connectionist network can encode millions of facts and rules involving n-ary predicates and variables and perform a class of inferences in a few hundred milliseconds. Efficient reasoning requires the rapid representation and propagation of dynamic bindings. Our model (which we refer to as SHRUTI) achieves this by representing (1) dynamic bindings as the synchronous firing of appropriate nodes, (2) rules as interconnection patterns that direct the propagation of rhythmic activity, and (3) long-term facts as temporal pattern-matching subnetworks. The model is consistent with recent neurophysiological evidence that synchronous activity occurs in the brain and may play a representational role in neural information processing. The model also makes specific psychologically significant predictions about the nature of reflexive reasoning. It identifies constraints on the form of rules that may participate in such reasoning and relates the capacity of the working memory underlying reflexive reasoning to biological parameters such as the lowest frequency at which nodes can sustain synchronous oscillations and the coarseness of synchronization.