The electronic structure of copper and nickel in the oxidation state qIII was studied for La Li Cu O , Cs KCuF , pronounced preedge peaks that monitor ligand-2p holes induced by covalency. These preedge peaks move to lower energies with increasing oxidation state of Cu and Ni as well as when going from nickelates to cuprates. q 1998 Elsevier Science B.V. All rights reserved.

Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text.

Durch Solvothermalsynthese in wasserfreier HF gelang es endlich erstmals, TiF4 aus (O2)2Ti7F30 in Form solcher Einkristalle darzustellen, die eine Strukturbestimmung ermöglichten. Die farblosen, transparenten Nadeln kristallisieren in der Raumgruppe Pnma–D 2h16 (Nr. 62) mit a = 2 281,1, b = 384,8, c = 956,8 pm, Z = 12. TiF4 bildet einen eigenen Strukturtyp, dessen charakteristisches Merkmal von einander isolierte, aus TiF6‐Oktaedern aufgebaute Säulen sind (Kolumnarstruktur).

No abstract

Erstmals wurden schwarze, metallisch glänzende Einkristalle von AgF2 durch Erhitzen des mikrokristallinen AgF2 dargestellt (Monel‐Autoklaven, T ≈ 400°C, HF/F2‐Gemisch, 4 d). Die röntgenographische Untersuchung (a = 556,8(1); = 583,1(1); c = 510,1(1) pm; Z = 4; Parameter siehe Text) bestätigt die aus Neutronenbeugungsuntersuchung ermittelte Raumgruppe Pbca – D 2h15 (Nr. 61) und ergibt Lageparameter, die mit den damals ermittelten Werten praktisch übereinstimmen. Der Madelunganteil der Gitterenergie, MAPLE, sowie Effektive Koordinationszahlen, ECoN, werden über Mittlere Fiktive Ionenradien, MEFIR, berechnet und diskutiert.

Erneut dargestellt, aber erstmals anhand von Einkristallen röntgenographisch untersucht wurden die Fluoride O 2+MF 6− (M = Sb, Ru, Pt, Au). Farbloses O 2+ und die rubinroten Verbindungen O 2+RuF 6− und O 2+PtF 6− kristallisieren isotyp in der Raumgruppe Ia3‐Th7 (Nr. 206) mit a = 1016(1) pm (Sb), a = 1002,6(9) pm (Ru) und a = 1003,6(9) pm (Pt), Z = 8. Gelbes O 2+AuF 6− kristallisiert trigonal‐rhomboedrisch in der Raumgruppe R3‐D326 (Nr. 148) mit a = 775,9(3) pm, c = 711,7(4) pm, Z = 3.

BackgroundFor selection and evaluation of potential biomarkers, inclusion of already published information is of utmost importance. In spite of significant advancements in text- and data-mining techniques, the vast knowledge space of biomarkers in biomedical text has remained unexplored. Existing named entity recognition approaches are not sufficiently selective for the retrieval of biomarker information from the literature. The purpose of this study was to identify textual features that enhance the effectiveness of biomarker information retrieval for different indication areas and diverse end user perspectives.MethodsA biomarker terminology was created and further organized into six concept classes. Performance of this terminology was optimized towards balanced selectivity and specificity. The information retrieval performance using the biomarker terminology was evaluated based on various combinations of the terminology's six classes. Further validation of these results was performed on two independent corpora representing two different neurodegenerative diseases.ResultsThe current state of the biomarker terminology contains 119 entity classes supported by 1890 different synonyms. The result of information retrieval shows improved retrieval rate of informative abstracts, which is achieved by including clinical management terms and evidence of gene/protein alterations (e.g. gene/protein expression status or certain polymorphisms) in combination with disease and gene name recognition. When additional filtering through other classes (e.g. diagnostic or prognostic methods) is applied, the typical high number of unspecific search results is significantly reduced. The evaluation results suggest that this approach enables the automated identification of biomarker information in the literature. A demo version of the search engine SCAIView, including the biomarker retrieval, is made available to the public through http://www.scaiview.com/scaiview-academia.html.ConclusionsThe approach presented in this paper demonstrates that using a dedicated biomarker terminology for automated analysis of the scientific literature maybe helpful as an aid to finding biomarker information in text. Successful extraction of candidate biomarkers information from published resources can be considered as the first step towards developing novel hypotheses. These hypotheses will be valuable for the early decision-making in the drug discovery and development process.

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