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Background: Due to the steadily increasing number of cancer patients worldwide the early diagnosis and treatment of cancer is a major field of research. The diagnosis of cancer is mostly performed by an experienced pathologist via the visual inspection of histo-pathological stained tissue sections. To save valuable time, low quality cryosections are frequently analyzed with diagnostic accuracies that are below those of high quality embedded tissue sections. Thus, alternative means have to be found that enable for fast and accurate diagnosis as the basis of following clinical decision making.
Methods: In this contribution we will show that the combination of the three label-free non-linear imaging modalities CARS (coherent anti-Stokes Raman-scattering), TPEF (two-photon excited autofluorescence) and SHG (second harmonic generation) yields information that can be translated into computational hematoxylin and eosin (HE) images by multivariate statistics. Thereby, a computational HE stain is generated resulting in pseudo-HE overview images that allow for identification of suspicious regions. The latter are analyzed further by Raman-spectroscopy retrieving the tissue’s molecular fingerprint.
Results: The results suggest that the combination of non-linear multimodal imaging and Raman-spectroscopy possesses the potential as a precise and fast tool in routine histopathology.
Conclusions: As the key advantage, both optical methods are non-invasive enabling for further pathological investigations of the same tissue section, e.g. a direct comparison with the current pathological gold-standard.
The gut microbiome is significantly altered in inflammatory bowel diseases, but the basis of these changes is not well understood. We have combined metagenomic and metatranscriptomic profiling of the gut microbiome to assess modifications to both bacterial community structure and transcriptional activity in a mouse model of colitis. By using transcriptomic analysis of colonic tissue and luminal RNA derived from the host, we have also characterised how host transcription relates to the microbial transcriptional response in inflammation. In colitis, increased abundance and transcription of diverse microbial gene families involved in responses to nutrient deprivation, antimicrobial peptide production and oxidative stress support an adaptation of multiple commensal genera to withstand a diverse set of environmental stressors in the inflammatory environment. These data are supported by a transcriptional signature of activated macrophages and granulocytes in the gut lumen during colitis, a signature that includes the transcription of the key antimicrobial genes S100a8 and S100a9 (calprotectin). Genes involved in microbial resistance to oxidative stress, including Dps/ferritin, Fe-dependent peroxidase and glutathione S-transferase were identified as changing to a greater extent at the level of transcription than would be predicted by DNA abundance changes, implicating a role for increased oxygen tension and/or host-derived reactive oxygen species in driving transcriptional changes in commensal microbes.