Der Einfluss der Kapazitätsgröße und -auslastung auf den Kostenverlauf ausgewählter Hilfskostenstellen von Molkereien - Abteilung Dampfversorgung

Die Kostenanalyse zur Bestimmung des Einflusses der Kapazitätsgröße und -auslastung auf den Kostenverlauf von Hilfskostenstellen (Hilfsabteilungen) erfolgt mit Hilfe von Modellkalkulationen. Eine spezielle Form der Teilkostenrechnung ermöglicht die Zurechnung der Kosten nach Kostenkategorien (jahresfix, tagesfix, ggf. chargenfix und mengenproportional) auf die entsprechenden Kostenträger (z. B. Kälte, Dampf) der jeweiligen Hilfskostenstelle. Durch computergestützte Simulationen können die Auswirkungen der verschiedenen Kosteneinflußfaktoren im einzelnen quantifiziert werden

Molecular identification of adenoviruses associated with respiratory infection in Egypt from 2003 to 2010.

BACKGROUND: Human adenoviruses of species B, C, and E (HAdV-B, -C, -E) are frequent causative agents of acute respiratory infections worldwide. As part of a surveillance program aimed at identifying the etiology of influenza-like illness (ILI) in Egypt, we characterized 105 adenovirus isolates from clinical samples collected between 2003 and 2010. METHODS: Identification of the isolates as HAdV was accomplished by an immunofluorescence assay (IFA) and confirmed by a set of species and type specific polymerase chain reactions (PCR). RESULTS: Of the 105 isolates, 42% were identified as belonging to HAdV-B, 60% as HAdV-C, and 1% as HAdV-E. We identified a total of six co-infections by PCR, of which five were HAdV-B/HAdV-C co-infections, and one was a co-infection of two HAdV-C types: HAdV-5/HAdV-6. Molecular typing by PCR enabled the identification of eight genotypes of human adenoviruses; HAdV-3 (n = 22), HAdV-7 (n = 14), HAdV-11 (n = 8), HAdV-1 (n = 22), HAdV-2 (20), HAdV-5 (n = 15), HAdV-6 (n = 3) and HAdV-4 (n = 1). The most abundant species in the characterized collection of isolates was HAdV-C, which is concordant with existing data for worldwide epidemiology of HAdV respiratory infections. CONCLUSIONS: We identified three species, HAdV-B, -C and -E, among patients with ILI over the course of 7 years in Egypt, with at least eight diverse types circulating

Oncoprotein DEK as a tissue and urinary biomarker for bladder cancer

<p>Abstract</p> <p>Background</p> <p>Bladder cancer is a significant healthcare problem in the United States of America with a high recurrence rate. Early detection of bladder cancer is essential for removing the tumor with preservation of the bladder, avoiding metastasis and hence improving prognosis and long-term survival. The objective of this study was to analyze the presence of DEK protein in voided urine of bladder cancer patients as a urine-based bladder cancer diagnostic test.</p> <p>Methods</p> <p>We examined the expression of DEK protein by western blot in 38 paired transitional cell carcinoma (TCC) bladder tumor tissues and adjacent normal tissue. The presence of DEK protein in voided urine was analyzed by western blot in 42 urine samples collected from patients with active TCC, other malignant urogenital disease and healthy individuals.</p> <p>Results</p> <p>The DEK protein is expressed in 33 of 38 bladder tumor tissues with no expression in adjacent normal tissue. Based on our sample size, DEK protein is expressed in 100% of tumors of low malignant potential, 92% of tumors of low grade and in 71% of tumors of high grade. Next, we analyzed 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals for DEK protein expression by western blot analysis. We are the first to show that the DEK protein is present in the urine of bladder cancer patients. Approximately 84% of TCC patient urine specimens were positive for urine DEK.</p> <p>Conclusion</p> <p>Based on our pilot study of 38 bladder tumor tissue and 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals; DEK protein is expressed in bladder tumor tissue and voided urine of bladder cancer patients. The presence of DEK protein in voided urine is potentially a suitable biomarker for bladder cancer and that the screening for the presence of DEK protein in urine can be explored as a noninvasive diagnostic test for bladder cancer.</p

Setting benchmarks for modelling gas–surface interactions using coherent control of rotational orientation states

A fundamental and predictive understanding of molecule-surface interactions is challenging to obtain. Here the authors report an experimental technique allowing direct measurement of the scattering matrix, which reports on the coherent evolution of quantum states of a molecule scattering from a surface

Are luminescent bacteria suitable for online detection and monitoring of toxic compounds in drinking water and its sources?

Biosensors based on luminescent bacteria may be valuable tools to monitor the chemical quality and safety of surface and drinking water. In this review, an overview is presented of the recombinant strains available that harbour the bacterial luciferase genes luxCDABE, and which may be used in an online biosensor for water quality monitoring. Many bacterial strains have been described for the detection of a broad range of toxicity parameters, including DNA damage, protein damage, membrane damage, oxidative stress, organic pollutants, and heavy metals. Most lux strains have sensitivities with detection limits ranging from milligrams per litre to micrograms per litre, usually with higher sensitivities in compound-specific strains. Although the sensitivity of lux strains can be enhanced by various molecular manipulations, most reported detection thresholds are still too high to detect levels of individual contaminants as they occur nowadays in European drinking waters. However, lux strains sensing specific toxic effects have the advantage of being able to respond to mixtures of contaminants inducing the same effect, and thus could be used as a sensor for the sum effect, including the effect of compounds that are as yet not identified by chemical analysis. An evaluation of the suitability of lux strains for monitoring surface and drinking water is therefore provided

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug—yohimbine, and an anti-anxiety drug—diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain–blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders—notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain