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Plasmacytoid dendritic cells (pDCs) are the most potent type I interferon-producing cells and play an important role in antiviral immunity. Tumor-infiltrating pDCs were shown to be predominantly pro-tumorigenic, with reduced ability to produce interferon alpha (IFNα) and confirmed capacity to prime regulatory T cells (Tregs) by the ICOS/ICOS-L pathway. Because a significant number of HNSCCs are induced by human papillomaviruses and show markedly different immune profiles than non-virally induced tumors, we compared the phenotype and functional capacity of HNSCC-infiltrating pDCs to the HPV status of the tumor. We observed a reduced capacity of pDCs to produce IFNα upon toll-like receptor activation in HPV-negative samples and a rather uncompromised functionality in HPV-associated tumors. Additionally, supernatants from non-virally induced but not HPV-associated tumor cell suspensions significantly inhibited IFNα production by peripheral blood-derived pDCs. We identified IL-10 and TNFα as the soluble pDC-suppressive factors with the highest variability between HPV-negative and HPV-positive tumor-derived supernatants. Additionally, we observed a positive correlation of tumor-infiltrating pDCs with Tregs in HPV-negative samples but not in virally induced tumors. Overall, our study indicates that the immunosuppressive cytokine milieu rich in IL-10 and TNFα in HPV-negative but not in HPV-positive HNSCC significantly affects the functional capacity of tumor-infiltrating pDCs, and such dysfunctional pDCs may further support the immunosuppressive tumor microenvironment by promoting the expansion of Tregs in the tumor tissue.Sustained exposure to pro-inflammatory cytokines in the leptomeninges is thought to play a major role in the pathogenetic mechanisms leading to cortical pathology in multiple sclerosis (MS). Although the molecular mechanisms underlying neurodegeneration in the grey matter remain unclear, several lines of evidence suggest a prominent role for tumour necrosis factor (TNF). Using cortical grey matter tissue blocks from post-mortem brains from 28 secondary progressive MS subjects and ten non-neurological controls, we describe an increase in expression of multiple steps in the TNF/TNF receptor 1 signaling pathway leading to necroptosis, including the key proteins TNFR1, FADD, RIPK1, RIPK3 and MLKL. Activation of this pathway was indicated by the phosphorylation of RIPK3 and MLKL and the formation of protein oligomers characteristic of necrosomes. In contrast, caspase-8 dependent apoptotic signaling was decreased. Upregulation of necroptotic signaling occurred predominantly in macroneurons in cortical layers II-IIIt is amenable to therapeutic intervention at several points in the signaling pathway.

Use claims data to assess healthcare resource utilization (HCRU) and cost for patients with ulcerative colitis (UC) who had surgery and patients who did not.

UC patients from a German health insurance were included between 01/01/2010-31/12/2017. Patients with proctocolectomy or colectomy between 01/07/2010 and 31/12/2014 were identified, and surgery date was set as index. For patients with IPAA, the last surgery in the 6 months was taken as index. Non-surgery patients received random index. After propensity score matching, UC-related HCRU and cost were observed for three years post-index.

Of 21,392 UC patients, 85 underwent surgery and 2655 did not. After matching, 76 were included in the surgery group and 114 in the non-surgery group. Matched cohorts did not differ in baseline characteristics and mortality rates where high in both groups (21.1% and 29.0%, respectively). The percentage of patients with at least one hospitalization in the follow-up period was higher in the surgery (53.9%) compared to the non-surgery group (25.4%, p<0.001). In contrast, the number of outpatient prescriptions of UC-related drugs in the non-surgery group (11.2) was almost twice as large as in the surgery group (5.8, p<0.001). Hospitalization cost was 4.6 times higher in the surgery (1955.5€) than in the non-surgery group (419.6€, p<0.001). Medication cost was three times higher in the non-surgery group (6519€) compared to the surgery group (2151.7€, p<0.001).

Based on hospitalizations, outpatient visits, and medical treatment, results show a considerable patient burden in UC from surgery complications or disease exacerbation in case of colectomy.

Based on hospitalizations, outpatient visits, and medical treatment, results show a considerable patient burden in UC from surgery complications or disease exacerbation in case of colectomy.

The susceptibility of CT imaging to metallic objects gives rise to strong streak artefacts and skewed information about the attenuation medium around the metallic implants. This metal-induced artefact in CT images leads to inaccurate attenuation correction in PET/CT imaging. This study investigates the potential of deep learning-based metal artefact reduction (MAR) in quantitative PET/CT imaging.

Deep learning-based metal artefact reduction approaches were implemented in the image (DLI-MAR) and projection (DLP-MAR) domains. The proposed algorithms were quantitatively compared to the normalized MAR (NMAR) method using simulated and clinical studies. Eighty metal-free CT images were employed for simulation of metal artefact as well as training and evaluation of the aforementioned MAR approaches. Thirty

F-FDG PET/CT images affected by the presence of metallic implants were retrospectively employed for clinical assessment of the MAR techniques.

The evaluation of MAR techniques on the simulation dataset detenuation and scatter correction in PET/CT imaging. • Deep learning-based MAR in the image (DLI-MAR) domain outperformed its counterpart implemented in the projection (DLP-MAR) domain. The DLI-MAR approach minimized the adverse impact of metal artefacts on whole-body PET images through generating accurate attenuation maps from corrupted CT images.

• The presence of metallic objects, such as dental implants, gives rise to severe photon starvation, beam hardening and scattering, thus leading to adverse artefacts in reconstructed CT images. • The aim of this work is to develop and evaluate a deep learning-based MAR to improve CT-based attenuation and scatter correction in PET/CT imaging. • Deep learning-based MAR in the image (DLI-MAR) domain outperformed its counterpart implemented in the projection (DLP-MAR) domain. AZD1656 The DLI-MAR approach minimized the adverse impact of metal artefacts on whole-body PET images through generating accurate attenuation maps from corrupted CT images.