Regional differentiation of felid vertebral column evolution: a study of 3D shape trajectories

Recent advances in geometric morphometrics provide improved techniques for extraction of biological information from shape and have greatly contributed to the study of ecomorphology and morphological evolution. However, the vertebral column remains an under-studied structure due in part to a concentration on skull and limb research, but most importantly because of the difficulties in analysing the shape of a structure composed of multiple articulating discrete units (i.e. vertebrae). Here, we have applied a variety of geometric morphometric analyses to three-dimensional landmarks collected on 19 presacral vertebrae to investigate the influence of potential ecological and functional drivers, such as size, locomotion and prey size specialisation, on regional morphology of the vertebral column in the mammalian family Felidae. In particular, we have here provided a novel application of a method—phenotypic trajectory analysis (PTA)—that allows for shape analysis of a contiguous sequence of vertebrae as functionally linked osteological structures. Our results showed that ecological factors influence the shape of the vertebral column heterogeneously and that distinct vertebral sections may be under different selection pressures. While anterior presacral vertebrae may either have evolved under stronger phylogenetic constraints or are ecologically conservative, posterior presacral vertebrae, specifically in the post-T10 region, show significant differentiation among ecomorphs. Additionally, our PTA results demonstrated that functional vertebral regions differ among felid ecomorphs mainly in the relative covariation of vertebral shape variables (i.e. direction of trajectories, rather than in trajectory size) and, therefore, that ecological divergence among felid species is reflected by morphological changes in vertebral column shape

Molecular changes in the expression of human colonic nutrient transporters during the transition from normality to malignancy

Healthy colonocytes derive 60–70% of their energy supply from short-chain fatty acids, particularly butyrate. Butyrate has profound effects on differentiation, proliferation and apoptosis of colonic epithelial cells by regulating expression of various genes associated with these processes. We have previously shown that butyrate is transported across the luminal membrane of the colonic epithelium via a monocarboxylate transporter, MCT1. In this paper, using immunohistochemistry and in situ hybridisation histochemistry, we have determined the profile of MCT1 protein and mRNA expression along the crypt to surface axis of healthy human colonic tissue. There is a gradient of MCT1 protein expression in the apical membrane of the cells along the crypt-surface axis rising to a peak in the surface epithelial cells. MCT1 mRNA is expressed along the crypt-surface axis and is most abundant in cells lining the crypt. Analysis of healthy colonic tissues and carcinomas using immunohistochemistry and Western blotting revealed a significant decline in the expression of MCT1 protein during transition from normality to malignancy. This was reflected in a corresponding reduction in MCT1 mRNA expression, as measured by Northern analysis. Carcinoma samples displaying reduced levels of MCT1 were found to express the high affinity glucose transporter, GLUT1, suggesting that there is a switch from butyrate to glucose as an energy source in colonic epithelia during transition to malignancy. The expression levels of MCT1 in association with GLUT1 could potentially be used as determinants of the malignant state of colonic tissue

Solution Structure and Phylogenetics of Prod1, a Member of the Three-Finger Protein Superfamily Implicated in Salamander Limb Regeneration

Prod1 is a cell-surface molecule of the three-finger protein (TFP) superfamily involved in the specification of newt limb PD identity. The TFP superfamily is a highly diverse group of metazoan proteins that includes snake venom toxins, mammalian transmembrane receptors and miscellaneous signaling molecules..The available data suggest that Prod1, and thereby its role in encoding PD identity, is restricted to salamanders. The lack of comparable limb-regenerative capability in other adult vertebrates could be correlated with the absence of the Prod1 gene

Total Shoulder Arthroplasty

Shoulder arthroplasty has been the subject of marked advances over the last few years. Modern implants provide a wide range of options, including resurfacing of the humeral head, anatomic hemiarthroplasty, total shoulder arthroplasty, reverse shoulder arthroplasty and trauma-specific implants for fractures and nonunions. Most humeral components achieve successful long-term fixation without bone cement. Cemented all-polyethylene glenoid components remain the standard for anatomic total shoulder arthroplasty. The results of shoulder arthroplasty vary depending on the underlying diagnosis, the condition of the soft-tissues, and the type of reconstruction. Total shoulder arthroplasty seems to provide the best outcome for patients with osteoarthritis and inflammatory arthropathy. The outcome of hemiarthroplasty for proximal humerus fractures is somewhat unpredictable, though it seems to have improved with the use of fracture-specific designs, more attention to tuberosity repair, and the selective use of reverse arthroplasty, as well as a shift in indications towards internal fixation. Reverse shoulder arthroplasty has become extremely popular for patients with cuff-tear arthropathy, and its indications have been expanded to the field of revision surgery. Overall, shoulder arthroplasty is a very successful procedure with predictable pain relief and substantial improvements in motion and function

PFClust : a novel parameter free clustering algorithm

Background: We present the algorithm PFClust (Parameter Free Clustering), which is able automatically to cluster data and identify a suitable number of clusters to group them into without requiring any parameters to be specified by the user. The algorithm partitions a dataset into a number of clusters that share some common attributes, such as their minimum expectation value and variance of intra-cluster similarity. A set of n objects can be clustered into any number of clusters from one to n, and there are many different hierarchical and partitional, agglomerative and divisive, clustering methodologies available that can be used to do this. Nonetheless, automatically determining the number of clusters present in a dataset constitutes a significant challenge for clustering algorithms. Identifying a putative optimum number of clusters to group the objects into involves computing and evaluating a range of clusterings with different numbers of clusters. However, there is no agreed or unique definition of optimum in this context. Thus, we test PFClust on datasets for which an external gold standard of 'correct' cluster definitions exists, noting that this division into clusters may be suboptimal according to other reasonable criteria. PFClust is heuristic in the sense that it cannot be described in terms of optimising any single simply-expressed metric over the space of possible clusterings. Results: We validate PFClust firstly with reference to a number of synthetic datasets consisting of 2D vectors, showing that its clustering performance is at least equal to that of six other leading methodologies -- even though five of the other methods are told in advance how many clusters to use. We also demonstrate the ability of PFClust to classify the three dimensional structures of protein domains, using a set of folds taken from the structural bioinformatics database CATH. Conclusions: We show that PFClust is able to cluster the test datasets a little better, on average, than any of the other algorithms, and furthermore is able to do this without the need to specify any external parameters. Results on the synthetic datasets demonstrate that PFClust generates meaningful clusters, while our algorithm also shows excellent agreement with the correct assignments for a dataset extracted from the CATH part-manually curated classification of protein domain structures.Publisher PDFPeer reviewe