5 resultados para Biocrystallization
Resumo:
The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).
Resumo:
Biological nanopores provide optimum dimensions and an optimal environment to study early aggregation kinetics of charged polyaromatic molecules in the nano-confined regime. It is expected that probing early stages of nucleation will enable us to design a strategy for supramolecular assembly and biocrystallization processes. Specifically, we have studied translocation dynamics of coronene and perylene based salts, through the alpha-hemolysin (alpha-HL) protein nanopore. The characteristic blocking events in the time-series signal are a function of concentration and bias voltage. We argue that different blocking events arise due to different aggregation processes as captured by all atomistic molecular dynamics (MD) simulations. These confinement induced aggregations of polyaromatic chromophores during the different stages of translocation are correlated with the spatial symmetry and charge distribution of the molecules.
Resumo:
The investigation of the effect of micro impurity on crystal growth by optical microscopy has been validated. The results showed that the growth rate of a lysozyme crystal was affected even if the concentration of impurity of fluorescent-labeled lysozyme (abbreviation, F-lysozyme) was very small. Different concentrations of F-lysozyme had different effects on crystal growth rate. The growth rate decreased much more as F-lysozyme concentration increased. The density of incorporated F-lysozyme on different grown layers of a lysozyme crystal during crystal growth was obtained from the results of flat-bottomed etch pits density. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
Die Qualität ökologischer Produkte wird über den Prozess und nicht am Produkt selbst bestimmt. Die zunehmende Nachfrage nach ökologischen Produkten fordert Methoden, die den Prozess am Produkt zeigen (Authentizitätsprüfung). Eine Literaturstudie für die vorliegende Habilitationsschrift ergab, dass ganzheitliche Verfahren sich dazu besonders eignen. Zu solchen ganzheitlichen Verfahren gehört die Biokristallisation. Bei diesem Verfahren kristallisiert eine Mischung aus Probe und CuCl2 auf einer Glasplatte zu einem Bild, das sowohl visuell, als auch computergestützt ausgewertet werden kann. Es wurden zunächst alle Schritte im Labor dokumentiert und entsprechende Standardarbeitsanweisungen erstellt. Mit einem eigens entwickelten Computerprogramm werden die Bedingungen während der Probenaufbereitung und Kristallisation für jede Probe und jedes Bild erfasst. Mit einer Texturanalyse können auch die für diese Arbeiten erstellte große Menge an Bildern ausgewertet und die Ergebnisse statistisch bearbeitet werden. Damit ist es möglich das Verfahren und Methoden für Weizen- und Möhrenproben zu charakterisieren. Es wurden verschiedene Einflussgrößen untersucht. Das Verfahren ist besonders gegenüber Änderungen in der Probenvorbereitung (z.B. Vermahlung, Mischungsverhältnis) empfindlich. Es wurde sowohl die Methodenstreuung, als auch der Anteil einzelner Schritte an der Gesamtstreuung für Weizen-, Möhren- und Apfelproben ermittelt. Die Verdampfung und Kristallisation hat den größten Anteil an der Gesamtstreuung. Die Durchführung eines Laboreignungstests zeigte, dass die so dokumentierten und charakterisierten Methoden in anderen Laboratorien erfolgreich eingesetzt werden können. Das Verfahren wurde für die nominale Unterscheidung von Weizen-, Möhren- und Apfelproben aus unterschiedlichem Anbau und Verarbeitungsschritten eingesetzt. Weizen-, Möhren- und Apfelproben aus definiertem Anbau können signifikant unterschieden werden. Weizen-, Möhren- und Apfelproben vom Erzeuger (Markt) konnten im Paarvergleich (ökologisch, konventionell) teilweise signifikant getrennt werden. Das Verfahren ist auch für die Charakterisierung von verarbeiteten Proben einsetzbar. Es konnte der Einfluss von Saftherstellung, Erwärmung und Alterung signifikant gezeigt werden. Darüber hinaus lässt sich das Verfahren auf weitere Probenarten anwenden. Das Verfahren arbeitet ganzheitlich, d.h. es werden keine Einzelstoffe analytisch bestimmt, sondern als Ergebnis wird ein Bild erhalten. Die Textur- und Struktureigenschaften dieses Bildes können mit standardisierten Methoden ausgewertet werden.
Resumo:
Abstract Background All organisms living under aerobic atmosphere have powerful mechanisms that confer their macromolecules protection against oxygen reactive species. Microorganisms have developed biomolecule-protecting systems in response to starvation and/or oxidative stress, such as DNA biocrystallization with Dps (DNA-binding protein from starved cells). Dps is a protein that is produced in large amounts when the bacterial cell faces harm, which results in DNA protection. In this work, we evaluated the glycosylation in the Dps extracted from Salmonella enterica serovar Typhimurium. This Dps was purified from the crude extract as an 18-kDa protein, by means of affinity chromatography on an immobilized jacalin column. Results The N-terminal sequencing of the jacalin-bound protein revealed 100% identity with the Dps of S. enterica serovar Typhimurium. Methyl-alpha-galactopyranoside inhibited the binding of Dps to jacalin in an enzyme-linked lectin assay, suggesting that the carbohydrate recognition domain (CRD) of jacalin is involved in the interaction with Dps. Furthermore, monosaccharide compositional analysis showed that Dps contained mannose, glucose, and an unknown sugar residue. Finally, jacalin-binding Dps was detected in larger amounts during the bacterial earlier growth periods, whereas high detection of total Dps was verified throughout the bacterial growth period. Conclusion Taken together, these results indicate that Dps undergoes post-translational modifications in the pre- and early stationary phases of bacterial growth. There is also evidence that a small mannose-containing oligosaccharide is linked to this bacterial protein.