Enhancing the early student experience

This paper is concerned with identifying how the early student experience can be enhanced in order to improve levels of student retention and achievement. The early student experience is the focus of this project as the literature has consistently declared the first year to be the most critical in shaping persistence decisions. Programme managers of courses with high and low retention rates have been interviewed to identify activities that appear to be associated with good retention rates. The results show that there are similarities in the way programmes with high retention are run, with these features not being prevalent on programmes with low retention. Recommendations of activities that appear likely to enhance the early student experience are provided

Classification of protein domain movements using Dynamic Contact Graphs

A new method for the classification of domain movements in proteins is described and applied to 1822 pairs of structures from the Protein Data Bank that represent a domain movement in two-domain proteins. The method is based on changes in contacts between residues from the two domains in moving from one conformation to the other. We argue that there are five types of elemental contact changes and that these relate to five model domain movements called: ‘‘free’’, ‘‘openclosed’’, ‘‘anchored’’, ‘‘sliding-twist’’, and ‘‘see-saw.’’ A directed graph is introduced called the ‘‘Dynamic Contact Graph’’ which represents the contact changes in a domain movement. In many cases a graph, or part of a graph, provides a clear visual metaphor for the movement it represents and is a motif that can be easily recognised. The Dynamic Contact Graphs are often comprised of disconnected subgraphs indicating independent regions which may play different roles in the domain movement. The Dynamic Contact Graph for each domain movement is decomposed into elemental Dynamic Contact Graphs, those that represent elemental contact changes, allowing us to count the number of instances of each type of elemental contact change in the domain movement. This naturally leads to sixteen classes into which the 1822 domain movements are classified

Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome

Background: Glioblastoma (GBM) is the most common malignant brain cancer occurring in adults, and is associated with dismal outcome and few therapeutic options. GBM has been shown to predominantly disrupt three core pathways through somatic aberrations, rendering it ideal for precision medicine approaches. Methods: We describe a 35-year-old female patient with recurrent GBM following surgical removal of the primary tumour, adjuvant treatment with temozolomide and a 3-year disease-free period. Rapid whole-genome sequencing (WGS) of three separate tumour regions at recurrence was carried out and interpreted relative to WGS of two regions of the primary tumour. Results: We found extensive mutational and copy-number heterogeneity within the primary tumour. We identified a TP53 mutation and two focal amplifications involving PDGFRA, KIT and CDK4, on chromosomes 4 and 12. A clonal IDH1 R132H mutation in the primary, a known GBM driver event, was detectable at only very low frequency in the recurrent tumour. After sub-clonal diversification, evidence was found for a whole-genome doubling event and a translocation between the amplified regions of PDGFRA, KIT and CDK4, encoded within a double-minute chromosome also incorporating miR26a-2. The WGS analysis uncovered progressive evolution of the double-minute chromosome converging on the KIT/PDGFRA/PI3K/mTOR axis, superseding the IDH1 mutation in dominance in a mutually exclusive manner at recurrence, consequently the patient was treated with imatinib. Despite rapid sequencing and cancer genome-guided therapy against amplified oncogenes, the disease progressed, and the patient died shortly after. Conclusion: This case sheds light on the dynamic evolution of a GBM tumour, defining the origins of the lethal sub-clone, the macro-evolutionary genomic events dominating the disease at recurrence and the loss of a clonal driver. Even in the era of rapid WGS analysis, cases such as this illustrate the significant hurdles for precision medicine success

Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome

In a glioblastoma tumour with multi-region sequencing before and after recurrence, we find an IDH1 mutation that is clonal in the primary but lost at recurrence. We also describe the evolution of a double-minute chromosome encoding regulators of the PI3K signalling axis that dominates at recurrence, emphasizing the challenges of an evolving and dynamic oncogenic landscape for precision medicin

Novel Feature for Catalytic Protein Residues Reflecting Interactions with Other Residues

Owing to their potential for systematic analysis, complex networks have been widely used in proteomics. Representing a protein structure as a topology network provides novel insight into understanding protein folding mechanisms, stability and function. Here, we develop a new feature to reveal correlations between residues using a protein structure network. In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues. The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues. The spatial environment surrounding a catalytic residue was analyzed in a layered manner. We present evidence that correlation between residues is related to their distance apart most environmental parameters of the outer layer make a smaller contribution to prediction and ii catalytic residues tend to be located near key positions in enzyme folds. Feature analysis revealed satisfactory performance for our features, which were combined with several conventional features in a prediction model for catalytic residues using a comprehensive data set from the Catalytic Site Atlas. Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10fold crossvalidation. These results suggest that these features reveal the mutual dependence of residues and are promising for further study of structurefunction relationship

Recruitment of rare 3-grams at functional sites: Is this a mechanism for increasing enzyme specificity?

<p>Abstract</p> <p>Background</p> <p>A wealth of unannotated and functionally unknown protein sequences has accumulated in recent years with rapid progresses in sequence genomics, giving rise to ever increasing demands for developing methods to efficiently assess functional sites. Sequence and structure conservations have traditionally been the major criteria adopted in various algorithms to identify functional sites. Here, we focus on the distributions of the 20³different types of <it>3</it>-grams (or triplets of sequentially contiguous amino acid) in the entire space of sequences accumulated to date in the UniProt database, and focus in particular on the rare <it>3</it>-grams distinguished by their high entropy-based information content.</p> <p>Results</p> <p>Comparison of the UniProt distributions with those observed near/at the active sites on a non-redundant dataset of 59 enzyme/ligand complexes shows that the active sites preferentially recruit <it>3</it>-grams distinguished by their low frequency in the UniProt. Three cases, Src kinase, hemoglobin, and tyrosyl-tRNA synthetase, are discussed in details to illustrate the biological significance of the results.</p> <p>Conclusion</p> <p>The results suggest that recruitment of rare <it>3</it>-grams may be an efficient mechanism for increasing specificity at functional sites. Rareness/scarcity emerges as a feature that may assist in identifying key sites for proteins function, providing information complementary to that derived from sequence alignments. In addition it provides us (for the first time) with a means of identifying potentially functional sites from sequence information alone, when sequence conservation properties are not available.</p

Partial Order Optimum Likelihood (POOL): Maximum Likelihood Prediction of Protein Active Site Residues Using 3D Structure and Sequence Properties

A new monotonicity-constrained maximum likelihood approach, called Partial Order Optimum Likelihood (POOL), is presented and applied to the problem of functional site prediction in protein 3D structures, an important current challenge in genomics. The input consists of electrostatic and geometric properties derived from the 3D structure of the query protein alone. Sequence-based conservation information, where available, may also be incorporated. Electrostatics features from THEMATICS are combined with multidimensional isotonic regression to form maximum likelihood estimates of probabilities that specific residues belong to an active site. This allows likelihood ranking of all ionizable residues in a given protein based on THEMATICS features. The corresponding ROC curves and statistical significance tests demonstrate that this method outperforms prior THEMATICS-based methods, which in turn have been shown previously to outperform other 3D-structure-based methods for identifying active site residues. Then it is shown that the addition of one simple geometric property, the size rank of the cleft in which a given residue is contained, yields improved performance. Extension of the method to include predictions of non-ionizable residues is achieved through the introduction of environment variables. This extension results in even better performance than THEMATICS alone and constitutes to date the best functional site predictor based on 3D structure only, achieving nearly the same level of performance as methods that use both 3D structure and sequence alignment data. Finally, the method also easily incorporates such sequence alignment data, and when this information is included, the resulting method is shown to outperform the best current methods using any combination of sequence alignments and 3D structures. Included is an analysis demonstrating that when THEMATICS features, cleft size rank, and alignment-based conservation scores are used individually or in combination THEMATICS features represent the single most important component of such classifiers

Drying Shrinkage Mechanisms in Portland Cement Paste

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65426/1/j.1151-2916.1987.tb05002.x.pd

Role of Active Site Rigidity in Activity: MD Simulation and Fluorescence Study on a Lipase Mutant

Relationship between stability and activity of enzymes is maintained by underlying conformational flexibility. In thermophilic enzymes, a decrease in flexibility causes low enzyme activity while in less stable proteins such as mesophiles and psychrophiles, an increase in flexibility is associated with enhanced enzyme activity. Recently, we identified a mutant of a lipase whose stability and activity were enhanced simultaneously. In this work, we probed the conformational dynamics of the mutant and the wild type lipase, particularly flexibility of their active site using molecular dynamic simulations and time-resolved fluorescence techniques. In contrast to the earlier observations, our data show that active site of the mutant is more rigid than wild type enzyme. Further investigation suggests that this lipase needs minimal reorganization/flexibility of active site residues during its catalytic cycle. Molecular dynamic simulations suggest that catalytically competent active site geometry of the mutant is relatively more preserved than wild type lipase, which might have led to its higher enzyme activity. Our study implies that widely accepted positive correlation between conformation flexibility and enzyme activity need not be stringent and draws attention to the possibility that high enzyme activity can still be accomplished in a rigid active site and stable protein structures. This finding has a significant implication towards better understanding of involvement of dynamic motions in enzyme catalysis and enzyme engineering through mutations in active site

MAPK pathway activation in the embryonic pituitary results in stem cell compartment expansion, differentiation defects and provides insights into the pathogenesis of papillary craniopharyngioma.

Despite the importance of the RAS-RAF-MAPK pathway in normal physiology and disease of numerous organs, its role during pituitary development and tumourigenesis remains largely unknown. Here we show that the over-activation of the MAPK pathway, through conditional expression of the gain-of-function alleles BrafV600E and KrasG12D in the developing mouse pituitary, results in severe hyperplasia and abnormal morphogenesis of the gland by the end of gestation. Cell-lineage commitment and terminal differentiation are disrupted, leading to a significant reduction in numbers of most of the hormone-producing cells before birth, with the exception of corticotrophs. Of note, Sox2+ve stem cells and clonogenic potential are drastically increased in the mutant pituitaries. Finally, we reveal that papillary craniopharyngioma (PCP), a benign human pituitary tumour harbouring BRAF p.V600E also contains Sox2+ve cells with sustained proliferative capacity and disrupted pituitary differentiation. Together, our data demonstrate a critical function of the MAPK pathway in controlling the balance between proliferation and differentiation of Sox2+ve cells and suggest that persistent proliferative capacity of Sox2+ve cells may underlie the pathogenesis of PCP