Die Bestellung eines ständigen Vernehmungsrichters im kanonischen Prozess

[Abstract fehlt

Cyclo19,31[D-Cys19]-uPA19-31 is a potent competitive antagonist of the interaction of urokinase-type plasminogen activator with its receptor (CD87)

Urokinase-type plasminogen activator (uPA) represents a central molecule in pericellular proteolysis and is implicated in a variety of physiological and pathophysiological processes such as tissue remodelling, wound healing, tumor invasion, and metastasis. uPA binds with high affinity to a specific cell surface receptor, uPAR (CD87), via a well defined sequence within the N-terminal region of uPA (uPA(19-31)). This interaction directs the proteolytic activity of uPA to the cell surface which represents an important step in tumor cell proliferation, invasion, and metastasis. Due to its fundamental role in these processes, the uPA/uPAR-system has emerged as a novel target for tumor therapy. Previously, we have identified a synthetic, cyclic, uPA-derived peptide, cyclo(19,31)uPA(19-31), as a lead structure for the development of low molecular weight uPA-analogues, capable of blocking uPA/uPAR-interaction {[}Burgle et al., Biol. Chem. 378 (1997), 231-237]. We now searched for peptide variants of cyclo(19,31)uPA(19-31) with elevated affinities for uPAR binding. Among other tasks, we performed a systematic D-amino acid scan of quPA(19-31), in which each of the 13 L-amino acids was individually substituted by the corresponding D-amino acid. This led to the identification of cyclo(19,31) {[}D-Cys(19)]-uPA(19-31) as a potent inhibitor of uPA/uPAR-interaction, displaying only a 20 to 40-fold lower binding capacity as compared to the naturally occurring uPAR-ligands uPA and its amino-terminal fragment. Cyclo(19,31)[D-Cys(19)]-uPA(19-31) not only blocks binding of uPA to uPAR but is also capable of efficiently displacing uPAR-bound uPA from the cell surface and to inhibit uPA-mediated, tumor cell-associated plasminogen activation and fibrin degradation. Thus, cyclo(19,31)[D-Cys(19)]-uPA(19-31) represents a promising therapeutic agent to significantly affect the tumor-associated uPA/uPAR-system

Colour measurement of colostrum for estimation of colostral IgG and colostrum composition in dairy cows

Instruments for on-farm determination of colostrum quality such as refractometers and densimeters are increasingly used in dairy farms. The colour of colostrum is also supposed to reflect its quality. A paler or mature milk-like colour is associated with a lower colostrum value in terms of its general composition compared with a more yellowish and darker colour. The objective of this study was to investigate the relationships between colour measurement of colostrum using the CIELAB colour space (CIE L*=from white to black, a*=from red to green, b*=from yellow to blue, chroma value G=visual perceived colourfulness) and its composition. Dairy cow colostrum samples (n=117) obtained at 4·7±1·5h after parturition were analysed for immunoglobulin G (IgG) by ELISA and for fat, protein and lactose by infrared spectroscopy. For colour measurements, a calibrated spectrophotometer was used. At a cut-off value of 50mg IgG/ml, colour measurement had a sensitivity of 50·0%, a specificity of 49·5%, and a negative predictive value of 87·9%. Colostral IgG concentration was not correlated with the chroma value G, but with relative lightness L*. While milk fat content showed a relationship to the parameters L*, a*, b* and G from the colour measurement, milk protein content was not correlated with a*, but with L*, b*, and G. Lactose concentration in colostrum showed only a relationship with b* and G. In conclusion, parameters of the colour measurement showed clear relationships to colostral IgG, fat, protein and lactose concentration in dairy cows. Implementation of colour measuring devices in automatic milking systems and milking parlours might be a potential instrument to access colostrum quality as well as detecting abnormal mil

Stereotactic Body Radiation Therapy for Primary and Metastatic Liver Tumors

AbstractOBJECTIVES: The full potential of stereotactic body radiation therapy (SBRT), in the treatment of unresectable intrahepatic malignancies, has yet to be realized as our experience is still limited. Thus, we evaluated SBRT outcomes for primary and metastatic liver tumors, with the goal of identifying factors that may aid in optimization of therapy. METHODS: From2005 to 2010, 62 patients with 106 primary and metastatic liver tumors were treated with SBRT to a median biologic effective dose (BED) of 100 Gy (42.6-180). The majority of patients received either three (47%) or five fractions (48%). Median gross tumor volume (GTV) was 8.8 cm3 (0.2-222.4). RESULTS: With a median followup of 18 months (0.46-46.8), freedom from local progression (FFLP) was observed in 97 of 106 treated tumors, with 1- and 2-year FFLP rates of 93% and 82%. Median overall survival (OS) for all patients was 25.2 months, with 1- and 2-year OS of 81%and 52%. Neither BED nor GTV significantly predicted for FFLP. Local failure was associated with a higher risk of death [hazard ratio (HR) = 5.1, P = .0007]. One Child-Pugh Class B patient developed radiationinduced liver disease. There were no other significant toxicities. CONCLUSIONS: SBRT provides excellent local control for both primary and metastatic liver lesions with minimal toxicity. Future studies should focus on appropriate selection of patients and on careful assessment of liver function to maximize both the safety and efficacy of treatment

Effects of a Cognitive Training With and Without Additional Physical Activity in Healthy Older Adults: A Follow-Up 1 Year After a Randomized Controlled Trial

Background: Combining cognitive training (CT) with physical activity (CPT) has been suggested to be most effective in maintaining cognition in healthy older adults, but data are scarce and inconsistent regarding long-term effects (follow-up; FU) and predictors of success.Objective: To investigate the 1-year FU effects of CPT versus CT and CPT plus counseling (CPT+C), and to identify predictors for CPT success at FU.Setting and Participants: We included 55 healthy older participants in the data analyses; 18 participants (CPT group) were used for the predictor analysis.Interventions: In a randomized controlled trial, participants conducted a CT, CPT, or CPT+C for 7 weeks.Outcome Measures: Overall cognition, verbal, figural, and working memory, verbal fluency, attention, planning, and visuo-construction.Results: While within-group comparisons showed cognitive improvements for all types of training, only one significant interaction Group × Time favoring CPT in comparison to CPT+C was found for overall cognition and verbal long-term memory. The most consistent predictor for CPT success (in verbal short-term memory, verbal fluency, attention) was an initial low baseline performance. Lower education predicted working memory gains. Higher levels of insulin-like growth factor 1 (IGF-1) and lower levels of brain-derived neurotrophic factor at baseline (BDNF) predicted alternating letter verbal fluency gains.Discussion: Within-group comparisons indicate that all used training types are helpful to maintain cognition. The fact that cognitive and sociodemographic data as well as nerve growth factors predict long-term benefits of CPT contributes to the understanding of the mechanisms underlying training success and may ultimately help to adapt training to individual profiles.Clinical Trial Registration: WHO ICTRP (http://apps.who.int/trialsearch/), identifier DRKS00005194

Stability and Fluctuations in Complex Ecological Systems

From 08-12 August, 2022, 32 individuals participated in a workshop, Stability and Fluctuations in Complex Ecological Systems, at the Lorentz Center, located in Leiden, The Netherlands. An interdisciplinary dialogue between ecologists, mathematicians, and physicists provided a foundation of important problems to consider over the next 5-10 years. This paper outlines eight areas including (1) improving our understanding of the effect of scale, both temporal and spatial, for both deterministic and stochastic problems; (2) clarifying the different terminologies and definitions used in different scientific fields; (3) developing a comprehensive set of data analysis techniques arising from different fields but which can be used together to improve our understanding of existing data sets; (4) having theoreticians/computational scientists collaborate closely with empirical ecologists to determine what new data should be collected; (5) improving our knowledge of how to protect and/or restore ecosystems; (6) incorporating socio-economic effects into models of ecosystems; (7) improving our understanding of the role of deterministic and stochastic fluctuations; (8) studying the current state of biodiversity at the functional level, taxa level and genome level.Comment: 22 page