Hr. Statsgeolog

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Protective effect of bacterial lipopolysaccharides in the grapevine- Agrobacterium vitis interaction

Cell-associated lipopolysaccharides (LPS) were extracted by the phenol-chloroform-petroleum ether extraction method (PCP) from a nopaline strain of Agrobacterium vitis, purified by treatment with DNase/RNase, proteinase K and dialysis, characterized by polyacrylamide gel electrophoresis (SDS-PAGE), and bioassayed on grapevine shoot nodal segments. LPS preparation used for the experiments in planta was a mixture of rough-type LPS, obtained from precipitation with water after PCP-extraction, and some smooth- and rough-type LPS from the remaining phenol phase. Infiltration of an aqueous dispersion of the mixture in concentrations of 25-1000 µ g.ml-1 did not cause grapevine tissue necrosis, and callus formed within one month. When the LPS dispersions were infiltrated in the grapevine nodal segments, 24 h before challenge inoculation with A. vitis (5x102 cells per 5 µ l droplet), they prevented tumorgenesis and tissue necrosis; but, when the pathogen was inoculated at a higher concentration (5x105 cells per 5 CII droplet), these LS applications were active in protecting plant tissue from necrosis and did not prevent tumor induction. The potential role of LPS as candidate molecules in the protection of grapevine from A. vitis infection is discussed

Truncated glucagon-like peptide I, an insulin-releasing hormone from the distal gut

AbstractBy hydrophobic gel permeation and high pressure liquid chromatography we isolated from pig intestinal mucosa a peptide which corresponds to proglucagon 78–107 as suggested by chromatography and determination of its N-terminal sequence. Natural and synthetic proglucagon 78–107 dose dependently and potently increased insulin secretion from the isolated perfused pig pancreas. Proglucagon 78–107 also secreted by the small intestine may participate in the hormonal control of insulin secretion

Regional Impact of Retiring Whole Farms

Suppose the government adopted a program of returing marginal land on a whole farm basis. What would happen to the Corn Belt in 1965 if the major goal were to balance supply demand? Where would the nation stand in 1975

Identification and structural determination of the capsular polysaccharides from two Acinetobacter baumannii clinical isolates, MG1 and SMAL

The structures of the capsular polysaccharides (CPSs) of the two clinical isolates Acinetobacter baumannii SMAL and MG1 were elucidated. Hot phenol/water extractions of the dry biomasses, followed by enzymatic digestions and repeated ultracentrifugations led to the isolation of polysaccharides that were negative in Western blot analysis utilizing an anti-lipid A antibody, thus proving that they were not the LPS O-antigens but CPSs. Their structures were established on the basis of NMR spectroscopy and GC-MS analyses. The A. baumannii MG1 CPS consisted of a linear aminopolysaccharide with acyl substitution heterogeneity at the N-4 amino group of QuipN4N: 4)-alpha-D-GlcpNAc-(1 -> 4)-alpha-L-GalpNAcA-(1 -> 3)-beta-D-QuipNAc4NR-(1 -> R = -3-hydroxybutyrryl or acetyl. The repeating unit of the CPS produced by strain SMAL is a pentasaccharide, already reported for the O-antigen moiety from A. baumannii strain ATCC 17961: beta-D-GlcpNAc3NAcA-(1 down arrow 4) 6)-beta-D-Glcp-(1 -> 3)-beta-D-GalpNAc-(1 -> 3)-alpha-D-Galp-(1 -> 6)up arrow beta-D-GlcpNAc-(

Enriching Thermal Point Clouds of Buildings using Semantic 3D building Models

Thermal point clouds integrate thermal radiation and laser point clouds effectively. However, the semantic information for the interpretation of building thermal point clouds can hardly be precisely inferred. Transferring the semantics encapsulated in 3D building models at Level of Detail (LoD)3 has a potential to fill this gap. In this work, we propose a workflow enriching thermal point clouds with the geo-position and semantics of LoD3 building models, which utilizes features of both modalities: model point clouds are generated from LoD3 models, and thermal point clouds are co-registered by coarse-to-fine registration. The proposed method can automatically co-register the point clouds from different sources and enrich the thermal point cloud in facade-detailed semantics. The enriched thermal point cloud supports thermal analysis and can facilitate the development of currently scarce deep learning models operating directly on thermal point clouds

Analyzing the impact of semantic LoD3 building models on image-based vehicle localization

Numerous navigation applications rely on data from global navigation satellite systems (GNSS), even though their accuracy is compromised in urban areas, posing a significant challenge, particularly for precise autonomous car localization. Extensive research has focused on enhancing localization accuracy by integrating various sensor types to address this issue. This paper introduces a novel approach for car localization, leveraging image features that correspond with highly detailed semantic 3D building models. The core concept involves augmenting positioning accuracy by incorporating prior geometric and semantic knowledge into calculations. The work assesses outcomes using Level of Detail 2 (LoD2) and Level of Detail 3 (LoD3) models, analyzing whether facade-enriched models yield superior accuracy. This comprehensive analysis encompasses diverse methods, including off-the-shelf feature matching and deep learning, facilitating thorough discussion. Our experiments corroborate that LoD3 enables detecting up to 69% more features than using LoD2 models. We believe that this study will contribute to the research of enhancing positioning accuracy in GNSS-denied urban canyons. It also shows a practical application of under-explored LoD3 building models on map-based car positioning