Kinder und Jugendliche Fertilität Medikamente in der Schwangerschaft und Stillzeit Entbindung Impfungen des Neugeborenen Der*die ältere CED-Patient*in M. Crohn -Leitlinie AG 07 Ernährung Ernährung Ernährung als Krankheitsauslöser beim M. Crohn Ernährung als ein den Krankheitsverlauf modulierender Faktor Ernährung als therapeutischer Ansatz bei Patient*innen mit M. Crohn Ernährung zur Behandlung von Defiziten bzw. Mangelzuständen
Background Vaccination is a promising strategy to protect vulnerable groups like immunocompromised inflammatory bowel disease (IBD) patients from an infection with SARS-CoV-2. These patients may have lower immune responses. Little is known about the cellular and humoral immune response after a SARS-CoV-2 vaccination in IBD. Methods 28 patients with IBD and 27 age- and sex-matched healthy controls were recruited at Jena University Hospital. Blood samples were taken before, after the first and in a subgroup of 11 patients after second dose of a SARS-CoV-2 vaccination. Cellular immune response including IFN-γ and TNF-α response and antibody titers were analyzed. Results Overall, 71.4% of the IBD-patients and 85.2% of the controls showed levels of anti-SARS-CoV-2 antibodies above the cutoff of 33.8 BAU/ml (p=0.329) after the first dose. Even in the absence of SARS-CoV-2 antibodies, IBD patients showed significant T cell responses after first SARS-CoV-2 vaccination compared to healthy controls, which was not influenced by different immunosuppressive regimens. Associated with the vaccination, we could also detect a slight increase of the TNF production among SARS-CoV-2-reactive TH cells in HD and IBD patients. After the second dose of vaccination, in IBD patients a further increase of humoral immune response in all but one patient was observed. Conclusions Already after the first dose of a SARS-CoV-2 vaccination, cellular immune response in IBD patients is comparable to controls, indicating a similar efficacy. However, close monitoring of long-term immunity in these patients should be considered.
Ulcerative colitis (UC) is one of the main types of chronic inflammatory diseases that affect the bowel, but its pathogenesis is yet to be completely defined. Assessing the disease activity of UC is vital for developing a personalized treatment. Conventionally, the assessment of UC is performed by colonoscopy and histopathology. However, conventional methods fail to retain biomolecular information associated to the severity of UC and are solely based on morphological characteristics of the inflamed colon. Furthermore, assessing endoscopic disease severity is limited by the requirement for experienced human reviewers. Therefore, this work presents a nondestructive biospectroscopic technique, for example, Raman spectroscopy, for assessing endoscopic disease severity according to the four-level Mayo subscore. This contribution utilizes multidimensional Raman spectroscopic data to generate a predictive model for identifying colonic inflammation. The predictive modeling of the Raman spectroscopic data is performed using a one-dimensional deep convolutional neural network (1D-CNN). The classification results of 1D-CNN achieved a mean sensitivity of 78% and a mean specificity of 93% for the four Mayo endoscopic scores. Furthermore, the results of the 1D-CNN are interpreted by a first-order Taylor expansion, which extracts the Raman bands important for classification. Additionally, a regression model of the 1D-CNN model is constructed to study the extent of misclassification and border-line patients. The overall results of Raman spectroscopy with 1D-CNN as a classification and regression model show a good performance, and such a method can serve as a complementary method for UC analysis.
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