Induction of ovulation in rabbits by adding Lecirelin to the seminal dose: In vitro and in vivo effects of different excipients.

This study evaluates the effect of Lecirelin (Dalmarelin®, Fatro, Italy) diluted in different excipients (benzilic alcohol, benzoic acid and paraben) added to a seminal dose on LH concentrations, progesterone concentrations and ovarian status in rabbits. The in vitro effect on spermatozoa was also tested. A total of 100 multiparous female rabbits were divided into 5 groups, which at the moment of AI, received 0.2 mL (5 μg/dose) intramuscular (im) inoculation of Lecirelin (control) or the same Lecirelin dose administered intravaginally (iv) with the seminal dose alone (Lecirelin group) or with benzilic alcohol (Lecirelin BA group), benzoic acid (Lecirelin BAc group) or parabens (Lecirelin PA group) as an excipient. After 7 days, 10 rabbits per group were euthanized to analyze their ovarian status. In the control group, a high LH peak was detected 30 min post AI, while in the iv groups a slight increase in LH occurred after 120 min. The ovulation and fertility rate was similar in control and Lecirelin groups, while the lowest fertility rate was detected in the Lecirelin BA group. In a second experiment, the semen samples collected from male rabbits were diluted in TALP (control) or mixed with the 5 μg of Lecirelin solutions used in the first experiment. The highest percentage of capacitated sperm (68.3%) was recorded in the Lecirelin PA. The lowest percentages were observed in the Lecirelin BA and BAc groups. In conclusion, the iv administration of Lecirelin represents an alternative method for simplifying rabbit insemination procedures.

Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.