@article{HaederSchaeubleGehlenetal.2023,
  author    = {H{\"a}der, Antje and Sch{\"a}uble, Sascha and Gehlen, Jan and Thielemann, Nadja and Buerfent, Benedikt C. and Sch{\"u}ller, Vitalia and Hess, Timo and Wolf, Thomas and Schr{\"o}der, Julia and Weber, Michael and H{\"u}nniger, Kerstin and L{\"o}ffler, J{\"u}rgen and Vylkova, Slavena and Panagiotou, Gianni and Schumacher, Johannes and Kurzai, Oliver},
  title     = {Pathogen-specific innate immune response patterns are distinctly affected by genetic diversity},
  series = {Nature Communications},
  volume    = {14},
  journal   = {Nature Communications},
  doi       = {10.1038/s41467-023-38994-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357441},
  year      = {2023},
  abstract  = {Innate immune responses vary by pathogen and host genetics. We analyze quantitative trait loci (eQTLs) and transcriptomes of monocytes from 215 individuals stimulated by fungal, Gram-negative or Gram-positive bacterial pathogens. We identify conserved monocyte responses to bacterial pathogens and a distinct antifungal response. These include 745 response eQTLs (reQTLs) and corresponding genes with pathogen-specific effects, which we find first in samples of male donors and subsequently confirm for selected reQTLs in females. reQTLs affect predominantly upregulated genes that regulate immune response via e.g., NOD-like, C-type lectin, Toll-like and complement receptor-signaling pathways. Hence, reQTLs provide a functional explanation for individual differences in innate response patterns. Our identified reQTLs are also associated with cancer, autoimmunity, inflammatory and infectious diseases as shown by external genome-wide association studies. Thus, reQTLs help to explain interindividual variation in immune response to infection and provide candidate genes for variants associated with a range of diseases.},
  language  = {en}
}
@article{AlZabenMedyukhinaDietrichetal.2019,
  author    = {Al-Zaben, Naim and Medyukhina, Anna and Dietrich, Stefanie and Marolda, Alessandra and H{\"u}nniger, Kerstin and Kurzai, Oliver and Figge, Marc Thilo},
  title     = {Automated tracking of label-free cells with enhanced recognition of whole tracks},
  series = {Scientific Reports},
  volume    = {9},
  journal   = {Scientific Reports},
  doi       = {10.1038/s41598-019-39725-x},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-221093},
  year      = {2019},
  abstract  = {Migration and interactions of immune cells are routinely studied by time-lapse microscopy of in vitro migration and confrontation assays. To objectively quantify the dynamic behavior of cells, software tools for automated cell tracking can be applied. However, many existing tracking algorithms recognize only rather short fragments of a whole cell track and rely on cell staining to enhance cell segmentation. While our previously developed segmentation approach enables tracking of label-free cells, it still suffers from frequently recognizing only short track fragments. In this study, we identify sources of track fragmentation and provide solutions to obtain longer cell tracks. This is achieved by improving the detection of low-contrast cells and by optimizing the value of the gap size parameter, which defines the number of missing cell positions between track fragments that is accepted for still connecting them into one track. We find that the enhanced track recognition increases the average length of cell tracks up to 2.2-fold. Recognizing cell tracks as a whole will enable studying and quantifying more complex patterns of cell behavior, e.g. switches in migration mode or dependence of the phagocytosis efficiency on the number and type of preceding interactions. Such quantitative analyses will improve our understanding of how immune cells interact and function in health and disease.},
  language  = {en}
}