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Background: Liver metastases are common in patients with breast cancer, and determining the factors associated with such metastases may improve both their early detection and treatment. Given that liver function protein level changes in these patients have not been determined, the aim of our study was to investigate liver function protein level changes over time, spanning 6 months before the detection of liver metastasis to 12 months after. Methods: We retrospectively studied 104 patients with hepatic metastasis from breast cancer who were treated at the Departments of Internal Medicine I and the Department of Obstetrics and Gynecology at the Medical University of Vienna between 1980 and 2019. Data were extracted from patient records. Results: Aspartate aminotransferase, alanine aminotransferase, gamma-glutamyltransferase, lactate dehydrogenase and alkaline phosphatase were significantly elevated when compared to normal range 6 months before the detection of liver metastases (p<0.001) Albumin was decreased (p<0.001). The values of aspartate aminotransferase, gamma-glutamyltransferase, and lactate dehydrogenase were significantly increased at the time of diagnosis compared to 6 months prior (p<0.001). Patient- and tumor-specific parameters had no influence on these liver function indicators. Elevated aspartate aminotransferase (p = 0.002) and reduced albumin (p = 0.002) levels at the time of diagnosis were associated with shorter overall survival. Conclusion: Liver function protein levels should be considered as potential indicators when screening for liver metastasis in patients with breast cancer. With the new treatment options available, it could lead to prolonged life. [ABSTRACT FROM AUTHOR]

The interaction between the T cell receptor and the major histocompatibility complex is one of the most important events in adaptive immunology. Although several different models for the activation process of the T cell via the T cell receptor have been proposed, it could not be shown that a structural mechanism, which discriminates between peptides of different immunogenicity levels, exists within the T cell receptor. In this study, we performed systematic molecular dynamics simulations of 172 closely related altered peptide ligands in the same T cell receptor/major histocompatibility complex system. Statistical evaluations yielded significant differences in the initial relaxation process between sets of peptides at four different immunogenicity levels. [ABSTRACT FROM AUTHOR]

Background: Bacteraemia is a frequent and severe condition with a high mortality rate. Despite profound knowledge about the pre-test probability of bacteraemia, blood culture analysis often results in low rates of pathogen detection and therefore increasing diagnostic costs. To improve the cost-effectiveness of blood culture sampling, we computed a risk prediction model based on highly standardizable variables, with the ultimate goal to identify via an automated decision support tool patients with very low risk for bacteraemia. Methods: In this retrospective hospital-wide cohort study evaluating 15,985 patients with suspected bacteraemia, 51 variables were assessed for their diagnostic potency. A derivation cohort (n = 14.699) was used for feature and model selection as well as for cut-off specification. Models were established using the A2DE classifier, a supervised Bayesian classifier. Two internally validated models were further evaluated by a validation cohort (n = 1,286). Results: The proportion of neutrophile leukocytes in differential blood count was the best individual variable to predict bacteraemia (ROC-AUC: 0.694). Applying the A2DE classifier, two models, model 1 (20 variables) and model 2 (10 variables) were established with an area under the receiver operating characteristic curve (ROC-AUC) of 0.767 and 0.759, respectively. In the validation cohort, ROC-AUCs of 0.800 and 0.786 were achieved. Using predefined cut-off points, 16% and 12% of patients were allocated to the low risk group with a negative predictive value of more than 98.8%. Conclusion: Applying the proposed models, more than ten percent of patients with suspected blood stream infection were identified having minimal risk for bacteraemia. Based on these data the application of this model as an automated decision support tool for physicians is conceivable leading to a potential increase in the cost-effectiveness of blood culture sampling. External prospective validation of the model's generalizability is needed for further appreciation of the usefulness of this tool. [ABSTRACT FROM AUTHOR]