Brain morphometric studies often incorporate comparative hemispheric asymmetry analyses of segmented brain structures. In this work, we present evidence that common user guided structural segmentation techniques exhibit strong left-right asymmetric biases and thus fundamentally influence any left-right asymmetry analyses. In this study, MRI scans from ten pediatric subjects were employed for studying segmentations of amygdala, globus pallidus, putamen, caudate, and lateral ventricle. Additionally, two pediatric and three adult scans were used for studying hippocampus segmentation. Segmentations of the sub-cortical structures were performed by skilled raters using standard manual and semi-automated methods. The left-right mirrored versions of each image were included in the data and segmented in a random order to assess potential left-right asymmetric bias. Using shape analysis we further assessed whether the asymmetric bias is consistent across subjects and raters with the focus on the hippocampus. The user guided segmentation techniques on the sub-cortical structures exhibited left-right asymmetric volume bias with the hippocampus displaying the most significant asymmetry values (p≪0.01). The hippocampal shape analysis revealed the bias to be strongest on the lateral side of the body and medial side of the head and tail. The origin of this asymmetric bias is considered to be based in laterality of visual perception; therefore segmentations with any degree of user interaction contain an asymmetric bias. The aim of our study is to raise awareness in the neuroimaging community regarding the presence of the asymmetric bias and its influence on any left-right hemispheric analyses. We also recommend reexamining previous research results in the light of this new finding.

The pharmacokinetics of cefquinome were studied in healthy and Pasteurella multocida-infected rabbits after a single intramuscular (IM) injection at 2 mg/kg of its sulfate salt. Twelve female New Zealand white rabbits (2.0-2.5 kg) were used; six of them served as controls, and the other six had been infected with P. multocida; the experiments were conducted 1-2 days after nasal inoculation of P. multocida when rabbits showed the signs of respiratory infection. Plasma concentrations of cefquinome were determined using high-performance liquid chromatography. The values of elimination half-life, area under the curve, area under the first moment curve, and mean residence time were significantly lower in infected rabbits (0.48 hr, 4.54 hr*μg/ml, 3.63 hr* hr*μg/ml and 0.8 hr, respectively) than healthy rabbits (0.72 hr, 9.11 hr*μg/ml, 9.85 hr* hr*μg/ml and 1.1 hr, respectively), whereas total body clearance was significantly higher in infected than healthy rabbits. Therefore, P. multocida infection caused significant changes in some of the pharmacokinetic parameters of cefquinome in rabbits. These pharmacokinetic changes may affect dose regimen when used in P. multocida-infected rabbits.

Background: Thin endometrium could be a major contributing factor in decreasing pregnancy rates with in-vitro fertilization. Several treatments have been studied in patients with thin endometrium, like hormonal therapy by GnRH-agonist and estrogen. Additionally, vasoactive measures like aspirin, a mix of pentoxifylline, vitamin E, l-arginine, sildenafil, and intrauterine infusion of a growth factor such as G-CSF, and the recent application of regenerative medicine were reported in previous trials. Main body of the abstract: We discuss here a new modality for thin endometrium treatment using platelet-rich plasma (PRP) administered as an intrauterine infusion. The purpose of this review is to evaluate the effectiveness of PRP in cases of infertility. All relevant articles addressing the use of PRP, published from January 2000 to September 2018, were reviewed and analyzed. The studies published on the PRP treatment model for thin endometrium in the gynecology field were mainly case series, pilot studies, or case reports. Conclusion: In the current review, we found that the local administration of PRP is significantly effective in increasing pregnancy rates of infertile women with thin endometrium < 6 mm.

Medical image denoising is the main step in medical diagnosis, which removes the noise without affecting relevant features of the image. There are many algorithms that can be used to reduce the noise such as: threshold and the sparse representation. The K-SVD is one of the most popular sparse representation algorithms, which is depend on Orthogonal Matching Pursuit (OMP) and Discrete Cosine Transform (DCT) dictionary. In this paper, an algorithm for image denoising was designed to develop K-SVD by using Regularized Orthogonal Matching Pursuit (ROMP) over log Gabor wavelet adaptive dictionary. To evaluate the performance of the proposed techniques, the results were compared with the results of DCT and Gabor wavelet dictionary. The numerical results show that the performance of our algorithm is more efficient in medical image denoising. KeywordsSparse representation (SR), K-SVD, log-Gabor wavelet dictionary, regularized orthogonal matching pursuit and orthogonal matching pursuit.

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