Pharmacokinetics and bioavailability of doxycycline in fasted and nonfasted broiler chickens

The pharmacokinetics and the influence of food on the kinetic profile and bioavailability of doxycycline was studied after a single intravenous (i.v.) and oral dose of 10.0 mg/kg body weight in 7-week-old broiler chickens. Following i.v. administration the drug was rapidly distributed in the body with a distribution half-life of 0.21 ± 0.01 h. The elimination half-life of 6.78 ± 0.06 h was relatively long and resulted from both a low total body clearance of 0.139 ± 0.007 L/h·kg and a large volume of distribution of 1.36 ± 0.06 L/kg. After oral administration to fasted chickens, the absorption of doxycycline was quite fast and substantial as shown by the absorption half-life of 0.39 ± 0.03 h, the maximal plasma concentration of 4.47 ± 0.16 —g/mL and the time to reach the Cmax of 1.73 ± 0.06 h. The distribution and the final elimination of the drug were slower than after i.v. administration. The absolute bioavailability was 73.4 ± 2.5%. The presence of food in the intestinal tract reduced and extended the absorption (t1/2a = 1.23 ± 0.21 h; Cmax = 3.07 ± 0.23 µg/mL; tmax = 3.34 ± 0.21 h). The absolute bioavailability was reduced to 61.1% ± 4.4%

Comprehensive deep learning-based framework for automatic organs-at-risk segmentation in head-and-neck and pelvis for MR-guided radiation therapy planning

Introduction: The excellent soft-tissue contrast of magnetic resonance imaging (MRI) is appealing for delineation of organs-at-risk (OARs) as it is required for radiation therapy planning (RTP). In the last decade there has been an increasing interest in using deep-learning (DL) techniques to shorten the labor-intensive manual work and increase reproducibility. This paper focuses on the automatic segmentation of 27 head-and-neck and 10 male pelvis OARs with deep-learning methods based on T2-weighted MR images.Method: The proposed method uses 2D U-Nets for localization and 3D U-Net for segmentation of the various structures. The models were trained using public and private datasets and evaluated on private datasets only.Results and discussion: Evaluation with ground-truth contours demonstrated that the proposed method can accurately segment the majority of OARs and indicated similar or superior performance to state-of-the-art models. Furthermore, the auto-contours were visually rated by clinicians using Likert score and on average, 81% of them was found clinically acceptable

Mono-multi bipartite Ramsey numbers, designs, and matrices

AbstractEroh and Oellermann defined BRR(G1,G2) as the smallest N such that any edge coloring of the complete bipartite graph KN,N contains either a monochromatic G1 or a multicolored G2. We restate the problem of determining BRR(K1,λ,Kr,s) in matrix form and prove estimates and exact values for several choices of the parameters. Our general bound uses Füredi's result on fractional matchings of uniform hypergraphs and we show that it is sharp if certain block designs exist. We obtain two sharp results for the case r=s=2: we prove BRR(K1,λ,K2,2)=3λ-2 and that the smallest n for which any edge coloring of Kλ,n contains either a monochromatic K1,λ or a multicolored K2,2 is λ2

Classifier Independent Viewpoint Selection for 3-D Object Recognition

Abstract 3–D object recognition has been tackled by passive approaches in the past. This means that based on one image a decision for a certain class and pose must be made or the image must be rejected. This neglects the fact that some other views might exist, which allow for a more reliable classification. This situation especially arises if certain views of or between objects are ambiguous. In this paper we present a classifier independent approach to solve the problem of choosing optimals views (viewpoint selection) for 3–D object recognition. We formally define the selection of additional views as an optimization problem and we show how to use reinforcement learning for continuous viewpoint training and selection without user interaction. The main focus lies on the automatic configuration of the system, the classifier independent approach and the continuous representation of the 3–D space. The experimental results show that this approach is well suited to distinguish and recognize similar looking objects in 3–D by taking a minimum amount of views.

Edge disjoint monochromatic triangles in 2-colored graphs

AbstractLet N(n,k) be the minimum number of pairwise edge disjoint monochromatic complete graphs Kk in any 2-coloring of the edges of a Kn. Upper and lower bounds on N(n,k) will be given for k⩾3. For k=3, exact values will be given for n⩽11, and these will be used to give a lower bound for N(n,3)