Identification of novel esterase-active enzymes from hot environments by use of the host bacterium Thermus thermophilus

Functional metagenomic screening strategies, which are independent of known sequence information, can lead to the identification of truly novel genes and enzymes. Since E. coli has been used exhaustively for this purpose as a host, it is important to establish alternative expression hosts and to use them for functional metagenomic screening for new enzymes. In this study we show that Thermus thermophilus HB27 is an excellent screening host and can be used as an alternative provider of truly novel biocatalysts. In a previous study we constructed the mutant strain BL03 that was no longer able to grow on defined minimal medium supplemented with tributyrin as the sole carbon source and could be used as a host to screen for metagenomic DNA fragments that could complement growth on tributyrin. Several thousand single fosmid clones from thermophilic metagenomic libraries from heated compost and hot spring water samples were subjected to a comparative screening for esterase activity in both T. thermophilus strain BL03 and E. coli EPI300. We scored a greater number of active clones in the thermophilic bacterium than in the mesophilic E. coli. From all clones functionally screened in E. coli, only two thermostable α/β-fold hydrolase enzymes with high amino acid sequence similarity to already characterized enzymes were identifiable. In contrast, five further fosmids were found that conferred lipolytic activities in T. thermophilus. Four open reading frames (ORFs) were found which did not share significant similarity to known esterase enzymes. Two of the genes were expressed in both hosts and the novel thermophilic esterases, which based on their primary structures could not be assigned to known esterase or lipase families, were purified and preliminarily characterized. Our work underscores the benefit of using additional screening hosts other than E. coli for the identification of novel biocatalysts with industrial relevance

Zur Quantifizierung wiedervereinigungsinduzierter Kosten und Transfers in der gesetzlichen Rentenversicherung

Finanzielle Engpässe in der Gesetzlichen Rentenversicherung motivieren wiederholt Diskussionen um eine wiedervereinigungsbedingte Sonderlast. Deren Höhe wird in dieser Studie mittels Daten des VDR und des SOEP anhand ausgewählter Konzepte bestimmt. Im Vorfeld der Analyse werden die Begriffe Kosten und Transfers konzeptionell voneinander abgegrenzt und die verbreitete Annahme ihrer Synonymie widerlegt. Die betriebswirtschaftlichen Kosten der Wiedervereinigung für die Rentenversicherung lagen sachzielorientiert für den Zeitraum 1992 bis 1998 zwischen 18,6 und 20,8 Mrd. €. Gemessen an den Beitragseinnahmen entspricht dies einem Anteil am Beitragssatz von weniger als einem halben Prozentpunkt. Demgegenüber ergab sich periodenorientiert für 1992 bis 2003 ein Transfer in Höhe von 107,8 Mrd. € innerhalb des Finanzverbundes zu den ostdeutschen Versicherungsträgern. Migrationsbereinigt, das heißt unter Berücksichtigung der Wanderungsbewegungen zwischen den alten und neuen Bundesländern, reduziert sich dieser Transfer auf 89,5 Mrd. €. Für das Jahr 2004 zeigt eine Mikrosimulation, dass die Verwendung unterschiedlicher Berechnungsbasen in Ost und West zu einem Transferverlust in Höhe von 186 € für einen westdeutschen Standardrentner gegenüber einem Transfergewinn in Höhe von 236 € für einen ostdeutschen Standardrentner führt

Content Representations kohärent gedacht

Für die fachgerechte Planung, Durchführung oder Reflexion von Physikunterricht ist eine solide Wissensbasis unerlässlich. Wichtiger als die einzelnen Wissensfacetten ist jedoch deren kohärente Vernetzung. Kohärenzbildung kann durch Dozierende unterstützt werden, gleichzeitig obliegt die eigentliche Wissensvernetzung den Studierenden selbst. Die Methode der Content Representation (CoRe; tabellarische Darstellung von kontextspezifischem Wissen) kann die Ausprägung sowie den Grad der Vernetzung von im Studium entwickelten Wissensfacetten abbilden und zur Evaluation von Kohärenzbildung verwendet werden. Umgekehrt bietet die Methode Potential zur Kohärenzbildung selbst, welches als neue Sichtweise im Beitrag diskutiert wird. (DIPF/Orig.)A solid knowledge base is essential for the professional planning, teaching, or reflecting of physics lessons. However, more important than the individual knowledge facets are their coherent interconnection. Building coherence can be supported by lecturers, but the creation of knowledge connectivity is the responsibility of the students themselves. The method of content representation (CoRe; tabular representation of context-specific knowledge) can represent the development and the degree of interconnectedness of knowledge facets developed in teacher training programs and can be used to evaluate coherence-building. Conversely, the method offers potential for coherence-building itself, which is discussed as a new perspective in the article. (DIPF/Orig.

Enhancing writing analytics in science education research with machine learning and natural language processing—Formative assessment of science and non-science preservice teachers’ written reflections

IntroductionScience educators use writing assignments to assess competencies and facilitate learning processes such as conceptual understanding or reflective thinking. Writing assignments are typically scored with holistic, summative coding rubrics. This, however, is not very responsive to the more fine-grained features of text composition and represented knowledge in texts, which might be more relevant for adaptive guidance and writing-to-learn interventions. In this study we examine potentials of machine learning (ML) in combination with natural language processing (NLP) to provide means for analytic, formative assessment of written reflections in science teacher education.MethodsML and NLP are used to filter higher-level reasoning sentences in physics and non-physics teachers’ written reflections on a standardized teaching vignette. We particularly probe to what extent a previously trained ML model can facilitate the filtering, and to what extent further fine-tuning of the previously trained ML model can enhance performance. The filtered sentences are then clustered with ML and NLP to identify themes and represented knowledge in the teachers’ written reflections.ResultsResults indicate that ML and NLP can be used to filter higher-level reasoning elements in physics and non-physics preservice teachers’ written reflections. Furthermore, the applied clustering approach yields specific topics in the written reflections that indicate quality differences in physics and non-physics preservice teachers’ texts.DiscussionOverall, we argue that ML and NLP can enhance writing analytics in science education. For example, previously trained ML models can be utilized in further research to filter higher-level reasoning sentences, and thus provide science education researchers efficient mean to answer derived research questions

Nanocrystalline SnO2:F Thin Films for Liquid Petroleum Gas Sensors

This paper reports the improvement in the sensing performance of nanocrystalline SnO2-based liquid petroleum gas (LPG) sensors by doping with fluorine (F). Un-doped and F-doped tin oxide films were prepared on glass substrates by the dip-coating technique using a layer-by-layer deposition cycle (alternating between dip-coating a thin layer followed by a drying in air after each new layer). The results showed that this technique is superior to the conventional technique for both improving the film thickness uniformity and film transparency. The effect of F concentration on the structural, surface morphological and LPG sensing properties of the SnO2 films was investigated. Atomic Force Microscopy (AFM) and X-ray diffraction pattern measurements showed that the obtained thin films are nanocrystalline SnO2 with nanoscale-textured surfaces. Gas sensing characteristics (sensor response and response/recovery time) of the SnO2:F sensors based on a planar interdigital structure were investigated at different operating temperatures and at different LPG concentrations. The addition of fluorine to SnO2 was found to be advantageous for efficient detection of LPG gases, e.g., F-doped sensors are more stable at a low operating temperature (300 °C) with higher sensor response and faster response/recovery time, compared to un-doped sensor materials. The sensors based on SnO2:F films could detect LPG even at a low level of 25% LEL, showing the possibility of using this transparent material for LPG leak detection

Negative symptoms in neuroleptic-naïve patients with first-episode psychosis correlate with QEEG parameters

INTRODUCTION: While several studies have shown an association of QEEG band power with negative symptoms in patients with schizophrenia, this has not yet been investigated in a sample with neuroleptic-naïve first-episode patients (NNFE) up to now. From literature we hypothesized delta (0.5-4Hz) and theta (4-8Hz) power to be augmented and alpha (8-12Hz) power to be decreased with increased negative symptoms in NNFE. MATERIALS AND METHODS: The sample consisted of 27 NNFE. Psychopathology was rated with the Scale for the Assessment of Negative Symptoms (SANS). EEG was recorded from 21 electrodes according to the 10/20 system. Spectral analysis was performed on mean power of 8 electrodes in seven frequency bands after artefact removal. Linear regressions were calculated with log transformed power as dependent and psychopathology as independent variable. We controlled for medication, drugs, age, sex, education and day time of EEG recording. RESULTS: A positive correlation of SANS global score with power in delta and theta frequency bands could be confirmed in NNFE. In the alpha1 (8-10Hz) band we found no significant correlation with negative symptoms and in the alpha2 (10-12Hz) band there was a positive correlation with SANS (p=0.069). Beta1 (12-15Hz) power also correlated positively with SANS. DISCUSSION: The present results confirm the correlation of negative symptoms with power of slow frequency bands. In addition to previous studies in chronic schizophrenia patients, the effect was shown in NNFE, which is compatible with augmented slow wave power being a marker for negative symptoms in psychosis