Evaluating the impact of handling and logger attachment on foraging parameters and physiology in southern rockhopper penguins

Logger technology has revolutionised our knowledge of the behaviour and physiology of free-living animals but handling and logger attachments may have negative effects on the behaviour of the animals and their welfare. We studied southern rockhopper penguin ( Eudyptes chrysocome ) females during the guard stage in three consecutive breeding seasons (2008/09−2010/11) to evaluate the effects of handling and logger attachment on foraging trip duration, dive behaviour and physiological parameters. Smaller dive loggers (TDRs) were used in 2010/11 for comparison to larger GPS data loggers used in all three seasons and we included two categories of control birds: handled controls and PIT control birds that were previously marked with passive integrative transponders (PITs), but which had not been handled during this study. Increased foraging trip duration was only observed in GPS birds during 2010/11, the breeding season in which we also found GPS birds foraging further away from the colony and travelling longer distances. Compared to previous breeding seasons, 2010/11 may have been a period with less favourable environmental conditions, which would enhance the impact of logger attachments. A comparison between GPS and TDR birds showed a significant difference in dive depth frequencies with birds carrying larger GPS data loggers diving shallower. Mean and maximum dive depths were similar between GPS and TDR birds. We measured little impact of logger attachments on physiological parameters (corticosterone, protein, triglyceride levels and leucocyte counts). Overall, handling and short-term logger attachments (1-3 days) showed limited impact on the behaviour and physiology of the birds but care must be taken with the size of data loggers on diving seabirds. Increased drag may alter their diving behaviour substantially, thus constraining them in their ability to catch prey. Results obtained in this study indicate that data recorded may also not represent their normal dive behaviour

Conditional generative adversarial network for 3D rigid-body motion correction in MRI

© 2019 International Society for Magnetic Resonance in Medicine Purpose: Subject motion in MRI remains an unsolved problem; motion during image acquisition may cause blurring and artifacts that severely degrade image quality. In this work, we approach motion correction as an image-to-image translation problem, which refers to the approach of training a deep neural network to predict an image in 1 domain from an image in another domain. Specifically, the purpose of this work was to develop and train a conditional generative adversarial network to predict artifact-free brain images from motion-corrupted data. Methods: An open source MRI data set comprising T2*-weighted, FLASH magnitude, and phase brain images for 53 patients was used to generate complex image data for motion simulation. To simulate rigid motion, rotations and translations were applied to the image data based on randomly generated motion profiles. A conditional generative adversarial network, comprising a generator and discriminator networks, was trained using the motion-corrupted and corresponding ground truth (original) images as training pairs. Results: The images predicted by the conditional generative adversarial network have improved image quality compared to the motion-corrupted images. The mean absolute error between the motion-corrupted and ground-truth images of the test set was 16.4% of the image mean value, whereas the mean absolute error between the conditional generative adversarial network-predicted and ground-truth images was 10.8% The network output also demonstrated improved peak SNR and structural similarity index for all test-set images. Conclusion: The images predicted by the conditional generative adversarial network have quantitatively and qualitatively improved image quality compared to the motion-corrupted images

A high vascular count and overexpression of vascular endothelial growth factor are associated with unfavourable prognosis in operated small cell lung carcinoma

It has been widely demonstrated that neo-angiogenesis and its mediators (i.e, vascular endothelial growth factor), represent useful indicators of poor prognosis in non small cell lung carcinoma. In order to veri whether neovascularization and vascular endothelial growth factor may be considered useful markers of clinical outcome also in the small cell lung cancer subgroup, we retrospectively investigated a series of 75 patients with small cell lung carcinoma treated by surgery between 1980 and 1990, Immunohistochemically-detected microvessels and vascular endothelial growth factor expressing cells were significantly associated with poor prognosis, as well as with nodal status and pathological stage, In fact, patients whose tumours had vascular count and vascular endothelial growth factor expression higher than median value of the entire series (59 vessels per 0.74 mm(2) and 50% of positive cells, respectively). showed a shorter overall and disease-free survival (P=0.001, P=0.001; P=0.008. P=0.03). Moreover, the presence of hilar and/or mediastinal nodal metastasis and advanced stage significantly affected overall and disease-free interval (P=0.00009, P=0.00001; P=0.0001, P=0.00001). At multivariate analysis, only vascular endothelial growth factor expression retained its influence on overall survival (P=0,001), suggesting that angiogenic phenomenon may have an important role in the clinical behaviour of this lung cancer subgroup. (C) 2002 Cancer Research UK