The Effect of Diethylstilbestrol on the Digestibility of Dry Matter and Nitrogen and on Nitrogen Retention in Lambs

Although the usefulness of orally administered diethylstilbestrol (stilbestrol) in increasing weight gains and feed efficiency of fattening cattle has been established, little is known concerning the mechanism by which it exerts its beneficial effect. Two possible modes of action may exist. First, the stilbestrol may have some effect on the rumen microorganisms which might cause an increased digestion of feed in the rumen. Brooks et al. (1954) have shown that stilbestrol increased the digestibility of cellulose in the artificial rumen. They also obtained increased cellulose and protein digestion in sheep when stilbestrol was fed. However the levels fed the sheep were considerably above the mg. per lamb per day reported to be effective with lambs (Hale et al. 1955). Sykes et al. (1956) reported an increase in crude fiber digestibility and a decrease in protein digestibility with lactating cows when stilbestrol was fed. Digestibility of the dry matter of the ration tended to be improved but the differences were not statistically significant. Erwin et al. (1956) reported stilbestroI had no effect on digestibility of dry matter, crude fiber, crude protein or ether extract with steers. Secondly, the orally fed stilbestrol may exert some action on the metabolism of the animal\u27s tissue which is thought to occur when the stilbestrol is implanted (Clegg and Cole, 19 54). It has been shown that implanted stilbestrol increased nitrogen retention but had no effect on ration digestibility (Jordan 1953: Whitehair et al. 1953). Bell et al. (1955) found that orally fed stilbestrol increased nitrogen retention in lambs. Presumably this action is brought about by the absorbed stilbestrol acting similar to that on the implanted stilbestrol. The objectives of this report were to study the effects of different levels of stilbestrol upon the digestibility of dry matter and crude protein and on nitrogen retention with wether lambs

An Integrated Framework For Histological Image Data Analytics

Introduction/ Background Automated image analysis enables the mining of rich information from digitized histological slides. A major challenge is the complexity and large size of the images. Whole-slide images contain a multitude of different structures, like sections, regions of different tissue types and the contained cells. To make sense of these struc- tures, often multiple analysis solutions must be com- bined. A common example is the initial identification of regions-of-interest and the subsequent evaluation of cellular structures with respect to these regions.   Aims There is no general standard for representing image analysis data. Different analysis solutions may represent analysis data as either XML or JSON documents, spread- sheets or images. When combining multiple analysis solutions, the inconsistent data representation makes it necessary to convert information between different formats and to match related entities. This complicates data analytics considerably. To overcome this problem, we describe an integrated framework for histological image data analytics.   Methods The framework represents image analysis data in an open relational  data model. Image  regions and cel- lular structures are represented as individual entitieswith properties and mutual relations. The framework incorporates multiple image analysis solutions for identifying image regions or cellular structures with machine-learning methods. The solutions are executed sequentially and populate the data model with more and more information from the image. Every step can take advantage of data generated in previous steps in order to target image processing operations to specific regions, or in order to reuse previously computed image features.   Results The relational data model greatly simplifies data ana- lytics in histological images. Region-specific statistics about cellular structures, or heat-maps of their spatial distribution can simply be computed by database queries. Furthermore, the relational data model en- ables the efficient management of the huge amounts of data generated by histological image analysis. We demonstrate the generic applicability of the framework by three example applications for the region-specific analysis of nuclear positivity, steatosis and inflammation in whole-slide images.

Together We Rise: Reaching Inclusivity for Student Excellence

This presentation outlines the BIONIC (Believe It Or Not I Care) Program at Mattoon High School. For the past 10 years, Dr. Larson and a team of counseling interns have partnered with Mattoon High School to implement BIONIC (Believe It Or Not I Care), a school-wide peer mentoring program

Enhanced light extraction from InGaN/GaN quantum wells with silver gratings

We demonstrate that an extraction enhancement by a factor of 2.8 can be obtained for a GaN quantum well structure using metallic nanostructures, compared to a flat semiconductor. The InGaN/GaN quantum well is inserted into a dielectric waveguide, naturally formed in the structure, and a silver grating is deposited on the surface and covered with a polymer film. The polymer layer greatly improves the extraction compared to a single metallic grating. The comparison of the experiments with simulations gives strong indications on the key role of weakly guided modes in the polymer layer diffracted by the grating.Peer reviewe

Automated quantification of steatosis: agreement with stereological point counting

Background: Steatosis is routinely assessed histologically in clinical practice and research. Automated image analysis can reduce the effort of quantifying steatosis. Since reproducibility is essential for practical use, we have evaluated different analysis methods in terms of their agreement with stereological point counting (SPC) performed by a hepatologist. Methods: The evaluation was based on a large and representative data set of 970 histological images from human patients with different liver diseases. Three of the evaluated methods were built on previously published approaches. One method incorporated a new approach to improve the robustness to image variability. Results: The new method showed the strongest agreement with the expert. At 20× resolution, it reproduced steatosis area fractions with a mean absolute error of 0.011 for absent or mild steatosis and 0.036 for moderate or severe steatosis. At 10× resolution, it was more accurate than and twice as fast as all other methods at 20× resolution. When compared with SPC performed by two additional human observers, its error was substantially lower than one and only slightly above the other observer. Conclusions: The results suggest that the new method can be a suitable automated replacement for SPC. Before further improvements can be verified, it is necessary to thoroughly assess the variability of SPC between human observers

Plasma Electronics

Contains reports on nine research projects.U. S. Air Force under Air Force Contract AF 19(604)-7400National Science Foundation under Grant G-9330U.S.Navy(Office of Naval Research)under Contract Nonr-1841(78)U. S. ArmyLincoln Laboratory, Purchase Order DDL B-00337U. S. Nav

Plasma Dynamics

Contains reports on two research projects.National Science Foundation under Grant G-9330WADD Contract AF33(616)-7624 with Flight Accessories Laboratory, Wright-Patterson Air Force Base, OhioAtomic Energy Commission under Contract AT(30-1)-1842Air Force Command and Control Development Division under Contract AF19(604)-599

Plasma Electronics

Contains research objectives and reports on twelve research projects.National Science Foundation under Grant G-9330U. S. Navy (Office of Naval Research) under Contract Nonr-1841(78)U. S. NavyLincoln Laboratory, Purchase Order DDL B-00306U. S. ArmyU. S. Air Force under Air Force Contract AF19(604)-740