TY  - JOUR
A1  - Loda, Sophia
A1  - Krebs, Jonathan
A1  - Danhof, Sophia
A1  - Schreder, Martin
A1  - Solimando, Antonio G.
A1  - Strifler, Susanne
A1  - Rasche, Leo
A1  - Kortüm, Martin
A1  - Kerscher, Alexander
A1  - Knop, Stefan
A1  - Puppe, Frank
A1  - Einsele, Hermann
A1  - Bittrich, Max
T1  - Exploration of artificial intelligence use with ARIES in multiple myeloma research
JF  - Journal of Clinical Medicine
N2  - Background: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text. Methods: Our MM ontology consists of extensive MM-specific and hierarchically structured attributes and values. We implemented “A Rule-based Information Extraction System” (ARIES) that uses this ontology. We evaluated ARIES on 200 randomly selected medical reports of patients diagnosed with MM. Results: Our system achieved a high F1-Score of 0.92 on the evaluation dataset with a precision of 0.87 and recall of 0.98. Conclusions: Our rule-based IE system enables the comprehensive querying of medical reports. The IE accelerates the extraction of data and enables clinicians to faster generate RWE on hematological issues. RWE helps clinicians to make decisions in an evidence-based manner. Our tool easily accelerates the integration of research evidence into everyday clinical practice.
KW  - natural language processing
KW  - ontology
KW  - artificial intelligence
KW  - multiple myeloma
KW  - real world evidence
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-197231
SN  - 2077-0383
VL  - 8
IS  - 7
ER  - 
TY  - JOUR
A1  - Jahn, Daniel
A1  - Dorbath, Donata
A1  - Kircher, Stefan
A1  - Nier, Anika
A1  - Bergheim, Ina
A1  - Lenaerts, Kaatje
A1  - Hermanns, Heike M.
A1  - Geier, Andreas
T1  - Beneficial effects of vitamin D treatment in an obese mouse model of non-alcoholic steatohepatitis
JF  - Nutrients
N2  - Serum vitamin D levels negatively correlate with obesity and associated disorders such as non-alcoholic steatohepatitis (NASH). However, the mechanisms linking low vitamin D (VD) status to disease progression are not completely understood. In this study, we analyzed the effect of VD treatment on NASH in mice. C57BL6/J mice were fed a high-fat/high-sugar diet (HFSD) containing low amounts of VD for 16 weeks to induce obesity, NASH and liver fibrosis. The effects of preventive and interventional VD treatment were studied on the level of liver histology and hepatic/intestinal gene expression. Interestingly, preventive and to a lesser extent also interventional VD treatment resulted in improvements of liver histology. This included a significant decrease of steatosis, a trend towards lower non-alcoholic fatty liver disease (NAFLD) activity score and a slight non-significant decrease of fibrosis in the preventive treatment group. In line with these changes, preventive VD treatment reduced the hepatic expression of lipogenic, inflammatory and pro-fibrotic genes. Notably, these beneficial effects occurred in conjunction with a reduction of intestinal inflammation. Together, our observations suggest that timely initiation of VD supplementation (preventive vs. interventional) is a critical determinant of treatment outcome in NASH. In the applied animal model, the improvements of liver histology occurred in conjunction with reduced inflammation in the gut, suggesting a potential relevance of vitamin D as a therapeutic agent acting on the gut–liver axis.
KW  - vitamin D
KW  - obesity
KW  - NAFLD
KW  - NASH
KW  - inflammation
KW  - intestine
KW  - gut–liver axis
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-177222
VL  - 11
IS  - 1
ER  -