Femur Specific Polyaffine Model to Regularize the Log-Domain Demons Registration

Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.

Post-translational signal peptide cleavage controls differential epitope recognition in the QP-rich domain of recombinant Theileria parva PIM

The presence of the schizont stage of the obligate intracellular parasites Theileria parva or T. annulata in the cytoplasm of an infected leukocyte results in host cell transformation via a mechanism that has not yet been elucidated. Proteins, secreted by the schizont, or expressed on its surface, are of interest as they can interact with host cell molecules that regulate host cell proliferation and/or survival. The major schizont surface protein is the polymorphic immunodominant molecule, PIM, which contains a large glutamine- and proline-rich domain (QP-rd) that protrudes into the host cell cytoplasm. Analyzing QP-rd generated by in vitro transcription/translation, we found that the signal peptide was efficiently cleaved post-translationally upon addition of T cell lysate or canine pancreatic microsomes, whereas signal peptide cleavage of a control protein only occurred cotranslationally and in the presence of microsomal membranes. The QP-rd of PIM migrated anomalously in SDS-PAGE and removal of the 19 amino acids corresponding to the predicted signal peptide caused a decrease in apparent molecular mass of 24kDa. The molecule was analyzed using monoclonal antibodies that recognize a set of previously defined PIM epitopes. Depending on the presence or the absence of the signal peptide, two conformational states could be demonstrated that are differentially recognized, with N-terminal epitopes becoming readily accessible upon signal peptide removal, and C-terminal epitopes becoming masked. Similar observations were made when the QP-rd of PIM was expressed in bacteria. Our observations could also be of relevance to other schizont proteins. A recent analysis of the proteomes of T. parva and T. annulata revealed the presence of a large family of potentially secreted proteins, characterized by the presence of large stretches of amino acids that are also particularly rich in QP-residues.

Electrical neuroimaging in the time domain

A publication entitled “A default mode of brain function” initiated a new way of looking at functional imaging data. In this PET study the authors discussed the often-observed consistent decrease of brain activation in a variety of tasks as compared with the baseline. They suggested that this deactivation is due to a task-induced suspension of a default mode of brain function that is active during rest, i.e. that there exists intrinsic well-organized brain activity during rest in several distinct brain regions. This suggestion led to a large number of imaging studies on the resting state of the brain and to the conclusion that the study of this intrinsic activity is crucial for understanding how the brain works. The fact that the brain is active during rest has been well known from a variety of EEG recordings for a very long time. Different states of the brain in the sleep–wake continuum are characterized by typical patterns of spontaneous oscillations in different frequency ranges and in different brain regions. Best studied are the evolving states during the different sleep stages, but characteristic EEG oscillation patterns have also been well described during awake periods (see Chapter 1 for details). A highly recommended comprehensive review on the brain's default state defined by oscillatory electrical brain activities is provided in the recent book by György Buzsaki, showing how these states can be measured by electrophysiological procedures at the global brain level as well as at the local cellular level.