[Antiqua- und Fraktur-Probe]

[Pankraz Lobinger]

Pilzige Fische und deren Behandlung (nach eigener Probe)

Von Chr. Felsberg

Herbert Hesse, John Gläser, Hans Meissner, Emmy Hainmüller, Clemens Kraus {[u.a.] nach der General-Probe zu Meistersinger, Frankfurt a. M.

Signatur des Originals: S 36/F04513

Hans Pfitzner, Bruno Walter, Karl Erb, Fritz Feinhals, Emmy Krüger, Friedrich Brodersen, {[N.N.], Gruppenbildnis, Anlass des Treffens: Probe zu Palestrina, München, 1917

Signatur des Originals: S 36/F05747

Hans Pfitzner, Bruno Walter, Karl Erb, Fritz Feinhals, Emmy Krüger, Friedrich Brodersen, {[N.N.], Gruppenbildnis, Anlass des Treffens: Probe zu Palestrina, München, 1917

Signatur des Originals: S 36/F05748

Philharmonischer Chor in Berlin (Dirigent: Prof. Siegfried Ochs). Probe in der Philharmonie

Signatur des Originals: S 36/F07792

Ausstellung "Das Theater im Freien", Frankfurt a. M. - Die Stadt des deutschen Handwerks in Verbindung mit dem Reichsbund der deutschen Freilicht- und Volksschauspiele E. V. : Die Probe im Park - Deutsches Ölgemälde aus der 2. Hälfte des 18. Jahrhunderts. Sammlung Niessen.

Signatur des Originals: S 36/F07992

Rudolf Brinkmann, Hermann Schramm, Erik Wirl, Enrico Caruso, Walter Schneider {[u.a.], Gruppenbildnis, nach der Probe von Ruggero Leoncavallo: I Pagliacci mit Enrico Caruso, 1909

Signatur des Originals: S 36/F07814

The role of self-efficacy in a low fat high fiber intervention to reduce breast cancer risk among African American women

Purpose. To determine if self-efficacy (SE) changes predicted total fat (TF) and total fiber (TFB) intake and the relationship between SE changes and the two dietary outcomes. ^ Design. This is a secondary analysis, utilizing baseline and first follow up (FFU) data from the NULIFE, a randomized trial. ^ Setting. Nutrition classes were taught in the Texas Medical Center in Houston, Texas. ^ Participants. 79 pre-menopausal, 25--45 year old African American women with an 85% response rate at FFU. ^ Method. Dietary intake was assessed with the Arizona Food Frequency Questionnaire and SE with the Self Efficacy for Dietary Change Questionnaire. Analysis was done using Stata version 9. Linear and logistic regression was used with adjustment for confounders. ^ Results. Linear regression analyses showed that SE changes for eating fruits and vegetables predicted total fiber intake in the control group for both the univariate (P = 0.001) and multivariate (P = 0.01) models while SE for eating fruits and vegetables at first follow-up predicted total fiber intake in the intervention for both models (P = 0.000). Logistic regression analyses of low fat SE changes and 30% or less for total fat intake, showed an adjusted OR of 0.22 (95% CI = 0.03, 1.48; P = 0.12) in the intervention group. The logistic regression analyses of SE changes in fruits and vegetables and 10g or more for total fiber intake, showed an adjusted OR of 6.25 (95% CI = 0.53, 72.78; P = 0.14) in the control group. ^ Conclusion. SE for eating fruits and vegetables at first follow-up predicted intervention groups' TFB intake and intervention women that increased their SE for eating a low fat diet were more likely to achieve the study goal of 30% or less calories from TF. SE changes for eating fruits and vegetables predicted the control's TFB intake and control women that increased their SE for eating fruits and vegetables were more likely to achieve the study goal of 10 g or more from TFB. Limitations are use of self-report measures, small sample size, and possible control group contamination.^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

Spectral reflectance library of selected biotic and abiotic coral reef features in Glovers Reef, Belize

Underwater spectral reflectance was measured for selected biotic and abiotic coral reef features of Glovers Reef, Belize from March 6 - 10, 2005. Spectral reflectance's of 63 different benthic types were obtained in-situ. An Ocean Optics USB2000 spectrometer was deployed in an custom made underwater housing with a 0.5 m fiber-optic probe mounted next to an artificial light source. Spectral readings were collected with the probe (bear fibre) about 5 cm from the target to ensure that the target would fill the field of view of the fiber optic (FOV diameter ~4.4 cm), as well as to reduce the attenuating effect of the intermediate water (Roelfsema et al., 2006). Spectral readings included for one target included: 1 reading of the covered spectral fibre to correct for instrument noise, 1 reading of spectralon panel mounted on divers wrist to measure incident ambient light, and 8 readings of the target. Spectral reflectance was calculated for each target by first subtracting the instrument noise reading from each other reading. The corrected target readings were then divided by the corrected spectralon reading resulting in spectral reflectance of each target reading. An average target spectral reflectance was calculated by averaging the eight individual spectral reflectance's of the target. If an individual target spectral reflectance was visual considered an outlier, it was not included in the average spectral reflectance calculation. See Roelfsema at al. (2006) for additional info on the methodology of underwater spectra collection.

Spectral reflectance library of selected biotic and abiotic coral reef features in Heron Reef

Underwater spectral reflectance was measured for selected biotic and abiotic coral reef features of Heron Reef from June 25-30, 2006. Spectral reflectance's of 105 different benthic types were obtained in-situ. An Ocean Optics USB2000 spectrometer was deployed in an custom made underwater housing with a 0.5 m fiber-optic probe mounted next to an artificial light source. Spectral readings were collected with the probe(bear fibre) about 5 cm from the target to ensure that the target would fill the field of view of the fiber optic (FOV diameter ~4.4 cm), as well as to reduce the attenuating effect of the intermediate water (Roelfsema et al., 2006). Spectral readings included for one target included: 1 reading of the covered spectral fibre to correct for instrument noise, 1 reading of spectralon panel mounted on divers wrist to measure incident ambient light, and 8 readings of the target. Spectral reflectance was calculated for each target by first subtracting the instrument noise reading from each other reading. The corrected target readings were then divided by the corrected spectralon reading resulting in spectral reflectance of each target reading. An average target spectral reflectance was calculated by averaging the eight individual spectral reflectance's of the target. If an individual target spectral reflectance was visual considered an outlier, it was not included in the average spectral reflectance calculation. See Roelfsema at al. (2006) for additional info on the methodology of underwater spectra collection.