A quantitative analysis of the taxonomy of artistic styles

Classifying artists and their work as distinct art styles has been an important task of scholars in the field of art history. Due to its subjectivity, scholars often contradict one another. Our project investigated differences in aesthetic qualities of seven art styles through quantitative means. This was achieved with state-of-the-art deep-learning paradigms to generate new images resembling the style of an artist or entire era. We conducted psychological experiments to measure the behavior of subjects when viewing these new art images. Two different experiments were used: In an eye-tracking study, subjects viewed art-style-specific generated images. Eye movements were recorded and then compared between art styles. In a visual singleton search study, subjects had to locate a style-outlier image among three images of an alternative style. Reaction time and accuracy were measured and analyzed. These experiments show that there are measurable differences in behavior when viewing images of varying art styles. From these differences, we constructed hierarchical clusterings relating art styles based on the different behaviors of subjects viewing the samples. Our study reveals a novel perspective on the classification of artworks into stylistic eras and motivates future research in the domain of empirical aesthetics through quantitative means

Künstliche Intelligenz zur Studienindividualisierung. Der Ansatz von SIDDATA

Derzeit wird in unterschiedlichen Forschungszusammenhängen diskutiert, wie Studierende bei der Erreichung individueller Bildungsziele unterstützt werden können. Die Studienindividualisierung wird aktuell insbesondere im Zusammenhang mit der Fähigkeit zum eigenaktiven Studieren erörtert. Neben der Hochschulbildung bieten auch die Diskussion zum lebenslangen Lernen und zur weiteren Differenzierung von Lebensläufen wichtige Anknüpfungspunkte. Die Frage stellt sich jedoch, wie Studienindividualisierung trotz enger curricularer Strukturen ermöglicht werden kann und inwiefern hier auch eine technologische Unterstützung möglich ist. Diese Idee wird durch das BMBF-geförderte Projekt SIDDATA verfolgt. SIDDATA ist ein Studienassistenzsystem, das mit Hilfe von intelligenten und selbstlernenden Algorithmen adaptives und individuelles Studieren unterstützt. Im Fokus stehen KI-gestützte Module, die Studierenden dabei helfen, individuelle Interessen zu definieren und diese im Laufe ihres Studiums zu verfolgen. Dieser Beitrag beschäftigt sich mit dem Konzept des Moduls »Fachliche Interessen«, den darin verwendeten KI-Algorithmen, den ersten Erfahrungen mit Test und Einsatz dieses Moduls sowie mit den Potenzialen und Hindernissen für den Einsatz von KI zur Studienindividualisierung. Die Ergebnisse der ersten Testerfahrungen mit dem Modul bestätigen, dass der Einsatz von KI in dem digitalen Studienassistenten SIDDATA Möglichkeiten bietet, die Individualisierung im Studium zu fördern, und auf diese Weise einen Beitrag leistet, Potenziale der KI-gestützten Hochschulbildung zu entdecken und diese weiterzuentwickeln. (DIPF/Orig.)Self-regulated learning is an important aspect of lifelong and individual learning. In higher education however, the question arises how individualisation of study can be enabled despite narrow curricular structures and to what extent technological support is appropriate to achieve this aim. The idea of supporting an individualisation of study is being pursued by the BMBF-funded project SIDDATA. SIDDATA is a study assistance system that uses intelligent and self-learning algorithms to support adaptive and individualised studying. The focus is on AI-supported modulesthat help students define individual interests and pursuethemthroughout their studies. This paper deals with the idea behind the SIDDATA module »Specialised Interests«, the AI algorithms used, the first experiences with testing and using this module as well as with the potentials and obstacles higher education may have to face when using AI to strengthen individual study approaches for their students. The results of the first test experiences with the module confirm that the use of AI in the digital study assistant SIDDATA offers opportunities to promote individualisation in studies and in this way contributes to discovering potentials of AI-supported higher education and development. (DIPF/Orig.

Electrostatic Modifications of the Human Leukocyte Antigen-DR P9 Peptide-Binding Pocket and Susceptibility to Primary Sclerosing Cholangitis

The strongest genetic risk factors for primary sclerosing cholangitis (PSC) are found in the human leukocyte antigen (HLA) complex at chromosome 6p21. Genes in the HLA class II region encode molecules that present antigen to T lymphocytes. Polymorphisms in these genes are associated with most autoimmune diseases, most likely because they contribute to the specificity of immune responses. The aim of this study was to analyze the structure and electrostatic properties of the peptide-binding groove of HLA-DR in relation to PSC. Thus, four-digit resolution HLA-DRB1 genotyping was performed in 356 PSC patients and 366 healthy controls. Sequence information was used to assign which amino acids were encoded at all polymorphic positions. In stepwise logistic regressions, variations at residues 37 and 86 were independently associated with PSC (P = 1.2 × 10−32 and P = 1.8 × 10−22 in single-residue models, respectively). Three-dimensional modeling was performed to explore the effect of these key residues on the HLA-DR molecule. This analysis indicated that residue 37 was a major determinant of the electrostatic properties of pocket P9 of the peptide-binding groove. Asparagine at residue 37, which was associated with PSC, induced a positive charge in pocket P9. Tyrosine, which protected against PSC, induced a negative charge in this pocket. Consistent with the statistical observations, variation at residue 86 also indirectly influenced the electrostatic properties of this pocket. DRB1*13:01, which was PSC-associated, had a positive P9 pocket and DRB1*13:02, protective against PSC, had a negative P9 pocket. Conclusion: The results suggest that in patients with PSC, residues 37 and 86 of the HLA-DRβ chain critically influence the electrostatic properties of pocket P9 and thereby the range of peptides presented. (Hepatology 2011;53:1967-1976

The Evolution of Ecological Diversity in Acidobacteria

Acidobacteria occur in a large variety of ecosystems worldwide and are particularly abundant and highly diverse in soils. In spite of their diversity, only few species have been characterized to date which makes Acidobacteria one of the most poorly understood phyla among the domain Bacteria. We used a culture-independent niche modeling approach to elucidate ecological adaptations and their evolution for 4,154 operational taxonomic units (OTUs) of Acidobacteria across 150 different, comprehensively characterized grassland soils in Germany. Using the relative abundances of their 16S rRNA gene transcripts, the responses of active OTUs along gradients of 41 environmental variables were modeled using hierarchical logistic regression (HOF), which allowed to determine values for optimum activity for each variable (niche optima). By linking 16S rRNA transcripts to the phylogeny of full 16S rRNA gene sequences, we could trace the evolution of the different ecological adaptations during the diversification of Acidobacteria. This approach revealed a pronounced ecological diversification even among acidobacterial sister clades. Although the evolution of habitat adaptation was mainly cladogenic, it was disrupted by recurrent events of convergent evolution that resulted in frequent habitat switching within individual clades. Our findings indicate that the high diversity of soil acidobacterial communities is largely sustained by differential habitat adaptation even at the level of closely related species. A comparison of niche optima of individual OTUs with the phenotypic properties of their cultivated representatives showed that our niche modeling approach (1) correctly predicts those physiological properties that have been determined for cultivated species of Acidobacteria but (2) also provides ample information on ecological adaptations that cannot be inferred from standard taxonomic descriptions of bacterial isolates. These novel information on specific adaptations of not-yet-cultivated Acidobacteria can therefore guide future cultivation trials and likely will increase their cultivation success

Extended analysis of a genome-wide association study in primary sclerosing cholangitis detects multiple novel risk loci.

A limited number of genetic risk factors have been reported in primary sclerosing cholangitis (PSC). To discover further genetic susceptibility factors for PSC, we followed up on a second tier of single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS). We analyzed 45 SNPs in 1221 PSC cases and 3508 controls. The association results from the replication analysis and the original GWAS (715 PSC cases and 2962 controls) were combined in a meta-analysis comprising 1936 PSC cases and 6470 controls. We performed an analysis of bile microbial community composition in 39 PSC patients by 16S rRNA sequencing. Seventeen SNPs representing 12 distinct genetic loci achieved nominal significance (p(replication) <0.05) in the replication. The most robust novel association was detected at chromosome 1p36 (rs3748816; p(combined)=2.1 × 10(-8)) where the MMEL1 and TNFRSF14 genes represent potential disease genes. Eight additional novel loci showed suggestive evidence of association (p(repl) <0.05). FUT2 at chromosome 19q13 (rs602662; p(comb)=1.9 × 10(-6), rs281377; p(comb)=2.1 × 10(-6) and rs601338; p(comb)=2.7 × 10(-6)) is notable due to its implication in altered susceptibility to infectious agents. We found that FUT2 secretor status and genotype defined by rs601338 significantly influence biliary microbial community composition in PSC patients. We identify multiple new PSC risk loci by extended analysis of a PSC GWAS. FUT2 genotype needs to be taken into account when assessing the influence of microbiota on biliary pathology in PSC.Norwegian PSC Research Center German Ministry of Education and Research (BMBF) through the National Genome Research Network (NGFN) Integrated Research and Treatment Center - Transplantation 01EO0802 PopGen biobank NIH DK 8496

Mutational Characterization of the Bile Acid Receptor TGR5 in Primary Sclerosing Cholangitis

TGR5, the G protein-coupled bile acid receptor 1 (GPBAR1), has been linked to inflammatory pathways as well as bile homeostasis, and could therefore be involved in primary sclerosing cholangitis (PSC) a chronic inflammatory bile duct disease. We aimed to extensively investigate TGR5 sequence variation in PSC, as well as functionally characterize detected variants. Complete resequencing of TGR5 was performed in 267 PSC patients and 274 healthy controls. Six nonsynonymous mutations were identified in addition to 16 other novel single-nucleotide polymorphisms. To investigate the impact from the nonsynonymous variants on TGR5, we created a receptor model, and introduced mutated TGR5 constructs into human epithelial cell lines. By using confocal microscopy, flow cytometry and a cAMP-sensitive luciferase assay, five of the nonsynonymous mutations (W83R, V178M, A217P, S272G and Q296X) were found to reduce or abolish TGR5 function. Fine-mapping of the previously reported PSC and UC associated locus at chromosome 2q35 in large patient panels revealed an overall association between the TGR5 single-nucleotide polymorphism rs11554825 and PSC (odds ratio = 1.14, 95% confidence interval: 1.03-1.26, p = 0.010) and UC (odds ratio = 1.19, 95% confidence interval 1.11-1.27, p = 8.5 x 10(-7)), but strong linkage disequilibrium precluded demarcation of TGR5 from neighboring genes. Resequencing of TGR5 along with functional investigations of novel variants provided unique insight into an important candidate gene for several inflammatory and metabolic conditions. While significant TGR5 associations were detected in both UC and PSC, further studies are needed to conclusively define the role of TGR5 variation in these diseases

Novel serum and bile protein markers predict primary sclerosing cholangitis disease severity and prognosis

Background & Aims: Prognostic biomarkers are lacking in primary sclerosing cholangitis, hampering patient care and the development of therapy. We aimed to identify novel protein biomarkers of disease severity and prognosis in primary sclerosing cholangitis (PSC). Methods: Using a bead-based array targeting 63 proteins, we profiled a derivation panel of Norwegian endoscopic retrograde cholangiography bile samples (55 PSC, 20 disease controls) and a Finnish validation panel (34 PSC, 10 disease controls). Selected identified proteins were measured in serum from two Norwegian PSC cohorts (n = 167 [1992-2006] and n = 138 [2008-2012]), inflammatory bowel disease (n = 96) and healthy controls (n = 100). Results: In the bile derivation panel, the levels of 14 proteins were different between PSC patients and controls (p <0.05); all were confirmed in the validation panel. Twenty-four proteins in the bile derivation panel were significantly (p <0.05) different between PSC patients with mild compared to severe cholangiographic changes (modified Amsterdam criteria); this was replicated for 18 proteins in the validation panel. Interleukin (IL)-8, matrix metallopeptidase (MMP)9/lipocalin (LCN)2-complex, S100A8/9, S100A12 and tryptophan hydroxylase (TPH)2 in the bile were associated with both a PSC diagnosis and grade of cholangiographic changes. Stratifying PSC patients according to tertiles of serum IL-8, but not MMP9/LCN2 and S100A12, provided excellent discrimination for transplant-free survival both in the serum derivation and validation cohort. Furthermore, IL-8 was associated with transplant-free survival in multivariable analyses in both serum panels independently of age and disease duration, indicating an independent influence on PSC progression. However, the Enhanced Liver Fibrosis (ELF (R)) test and Mayo risk score proved to be stronger predictors of transplant-free survival. Conclusions: Based on assaying of biliary proteins, we have identified novel biliary and serum biomarkers as indicators of severity and prognosis in PSC. Lay summary: Prognostic biomarkers are lacking in primary sclerosing cholangitis, hampering patient care and the development of therapy. We have identified inflammatory proteins including calprotectin and IL-8 as important indicators of disease severity and prognosis in bile and serum from patients with primary sclerosing cholangitis. (C) 2017 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.Peer reviewe

Genetic association analysis identifies variants associated with disease progression in primary sclerosing cholangitis

Objective Primary sclerosing cholangitis (PSC) is a genetically complex, inflammatory bile duct disease of largely unknown aetiology often leading to liver transplantation or death. Little is known about the genetic contribution to the severity and progression of PSC. The aim of this study is to identify genetic variants associated with PSC disease progression and development of complications. Design We collected standardised PSC subphenotypes in a large cohort of 3402 patients with PSC. After quality control, we combined 130 422 single nucleotide polymorphisms of all patients-obtained using the Illumina immunochip-with their disease subphenotypes. Using logistic regression and Cox proportional hazards models, we identified genetic variants associated with binary and time-to-event PSC subphenotypes. Results We identified genetic variant rs853974 to be associated with liver transplant-free survival (p=6.07x10(-9)). Kaplan-Meier survival analysis showed a 50.9% (95% CI 41.5% to 59.5%) transplant-free survival for homozygous AA allele carriers of rs853974 compared with 72.8% (95% CI 69.6% to 75.7%) for GG carriers at 10 years after PSC diagnosis. For the candidate gene in the region, RSPO3, we demonstrated expression in key liver-resident effector cells, such as human and murine cholangiocytes and human hepatic stellate cells. Conclusion We present a large international PSC cohort, and report genetic loci associated with PSC disease progression. For liver transplant-free survival, we identified a genome-wide significant signal and demonstrated expression of the candidate gene RSPO3 in key liver-resident effector cells. This warrants further assessments of the role of this potential key PSC modifier gene.Peer reviewe

Artificial Intelligence in Personalized E-learning Environments

Digital study assistant systems are software implementations that aim at supporting students throughout their studying endeavor at higher education institutions. In order to do so, digital study assistant systems may rely on technologies from the domain of Artificial Intelligence to maximize their assistance utility. This thesis investigates the feasibility of deploying Artificial Intelligence (AI) algorithms within a digital study assistant system for self-determined learning. This thesis guides the reader through the development process of the SIDDATA digital study assistant system and its AI-driven features. By adhering to data availability constraints and data protection regulations, a general educational resource recommendation system in the form of an artificial neural network based on Google BERT was developed and integrated into the digital study assistant’s feature set. Through a subsequent investigation into the AI-driven feature usage through quantitative and qualitative means, we discover a high perceived potential for AI technologies to incentivize student self-determined learning. Technical and boundary conditional challenges will need to be overcome to realize this potential for all users in future studies