Assessing noninferiority in a three-arm trial using the Bayesian Approach

Non-inferiority trials, which aim to demonstrate that a test product is not worse than a competitor by more than a pre-specified small amount, are of great importance to the pharmaceutical community. As a result, methodology for designing and analyzing such trials is required, and developing new methods for such analysis is an important area of statistical research. The three-arm clinical trial is usually recommended for non-inferiority trials by the Food and Drug Administration (FDA). The three-arm trial consists of a placebo, a reference, and an experimental treatment, and simultaneously tests the superiority of the reference over the placebo along with comparing this reference to an experimental treatment. In this paper, we consider the analysis of noninferiority trials using Bayesian methods which incorporate both parametric as well as semi-parametric models. The resulting testing approach is both flexible and robust. The benefit of the proposed Bayesian methods is assessed via simulation, based on a study examining Home Based Blood Pressure Interventions

High-resolution DCE-MRI of the pituitary gland using radial k-space acquisition with compressed sensing reconstruction

BACKGROUND AND PURPOSE: The pituitary gland is located outside of the blood-brain barrier. Dynamic T1 weighted contrast enhanced sequence is considered to be the gold standard to evaluate this region. However, it does not allow assessment of intrinsic permeability properties of the gland. Our aim was to demonstrate the utility of radial volumetric interpolated brain examination with the golden-angle radial sparse parallel technique to evaluate permeability characteristics of the individual components (anterior and posterior gland and the median eminence) of the pituitary gland and areas of differential enhancement and to optimize the study acquisition time. MATERIALS AND METHODS: A retrospective study was performed in 52 patients (group 1, 25 patients with normal pituitary glands; and group 2, 27 patients with a known diagnosis of microadenoma). Radial volumetric interpolated brain examination sequences with goldenangle radial sparse parallel technique were evaluated with an ROI-based method to obtain signal-time curves and permeability measures of individual normal structures within the pituitary gland and areas of differential enhancement. Statistical analyses were performed to assess differences in the permeability parameters of these individual regions and optimize the study acquisition time. RESULTS: Signal-time curves from the posterior pituitary gland and median eminence demonstrated a faster wash-in and time of maximum enhancement with a lower peak of enhancement compared with the anterior pituitary gland (P .005). Time-optimization analysis demonstrated that 120 seconds is ideal for dynamic pituitary gland evaluation. In the absence of a clinical history, differences in the signal-time curves allow easy distinction between a simple cyst and a microadenoma. CONCLUSIONS: This retrospective study confirms the ability of the golden-angle radial sparse parallel technique to evaluate the permeability characteristics of the pituitary gland and establishes 120 seconds as the ideal acquisition time for dynamic pituitary gland imaging

Link Mining for Kernel-based Compound-Protein Interaction Predictions Using a Chemogenomics Approach

Virtual screening (VS) is widely used during computational drug discovery to reduce costs. Chemogenomics-based virtual screening (CGBVS) can be used to predict new compound-protein interactions (CPIs) from known CPI network data using several methods, including machine learning and data mining. Although CGBVS facilitates highly efficient and accurate CPI prediction, it has poor performance for prediction of new compounds for which CPIs are unknown. The pairwise kernel method (PKM) is a state-of-the-art CGBVS method and shows high accuracy for prediction of new compounds. In this study, on the basis of link mining, we improved the PKM by combining link indicator kernel (LIK) and chemical similarity and evaluated the accuracy of these methods. The proposed method obtained an average area under the precision-recall curve (AUPR) value of 0.562, which was higher than that achieved by the conventional Gaussian interaction profile (GIP) method (0.425), and the calculation time was only increased by a few percent

MP20, the second most abundant lens membrane protein and member of the tetraspanin superfamily, joins the list of ligands of galectin-3

BACKGROUND: Although MP20 is the second most highly expressed membrane protein in the lens its function remains an enigma. Putative functions for MP20 have recently been inferred from its assignment to the tetraspanin superfamily of integral membrane proteins. Members of this family have been shown to be involved in cellular proliferation, differentiation, migration, and adhesion. In this study, we show that MP20 associates with galectin-3, a known adhesion modulator. RESULTS: MP20 and galectin-3 co-localized in selected areas of the lens fiber cell plasma membrane. Individually, these proteins purified with apparent molecular masses of 60 kDa and 22 kDa, respectively. A 104 kDa complex was formed in vitro upon mixing the purified proteins. A 102 kDa complex of MP20 and galectin-3 could also be isolated from detergent-solubilized native fiber cell membranes. Binding between MP20 and galectin-3 was disrupted by lactose suggesting the lectin site was involved in the interaction. CONCLUSIONS: MP20 adds to a growing list of ligands of galectin-3 and appears to be the first representative of the tetraspanin superfamily identified to possess this specificity

Sublinear-Time Algorithms for Monomer-Dimer Systems on Bounded Degree Graphs

For a graph $G$, let $Z(G,\lambda)$ be the partition function of the monomer-dimer system defined by $\sum_k m_k(G)\lambda^k$, where $m_k(G)$ is the number of matchings of size $k$ in $G$. We consider graphs of bounded degree and develop a sublinear-time algorithm for estimating $\log Z(G,\lambda)$ at an arbitrary value $\lambda>0$ within additive error $\epsilon n$ with high probability. The query complexity of our algorithm does not depend on the size of $G$ and is polynomial in $1/\epsilon$, and we also provide a lower bound quadratic in $1/\epsilon$ for this problem. This is the first analysis of a sublinear-time approximation algorithm for a # P-complete problem. Our approach is based on the correlation decay of the Gibbs distribution associated with $Z(G,\lambda)$. We show that our algorithm approximates the probability for a vertex to be covered by a matching, sampled according to this Gibbs distribution, in a near-optimal sublinear time. We extend our results to approximate the average size and the entropy of such a matching within an additive error with high probability, where again the query complexity is polynomial in $1/\epsilon$ and the lower bound is quadratic in $1/\epsilon$. Our algorithms are simple to implement and of practical use when dealing with massive datasets. Our results extend to other systems where the correlation decay is known to hold as for the independent set problem up to the critical activity

Amphotericin forms an extramembranous and fungicidal sterol sponge.

For over 50 years, amphotericin has remained the powerful but highly toxic last line of defense in treating life-threatening fungal infections in humans with minimal development of microbial resistance. Understanding how this small molecule kills yeast is thus critical for guiding development of derivatives with an improved therapeutic index and other resistance-refractory antimicrobial agents. In the widely accepted ion channel model for its mechanism of cytocidal action, amphotericin forms aggregates inside lipid bilayers that permeabilize and kill cells. In contrast, we report that amphotericin exists primarily in the form of large, extramembranous aggregates that kill yeast by extracting ergosterol from lipid bilayers. These findings reveal that extraction of a polyfunctional lipid underlies the resistance-refractory antimicrobial action of amphotericin and suggests a roadmap for separating its cytocidal and membrane-permeabilizing activities. This new mechanistic understanding is also guiding development of what are to our knowledge the first derivatives of amphotericin that kill yeast but not human cells

Oxidized phospholipids are proinflammatory and proatherogenic in hypercholesterolaemic mice.

Oxidized phospholipids (OxPL) are ubiquitous, are formed in many inflammatory tissues, including atherosclerotic lesions, and frequently mediate proinflammatory changes 1 . Because OxPL are mostly the products of non-enzymatic lipid peroxidation, mechanisms to specifically neutralize them are unavailable and their roles in vivo are largely unknown. We previously cloned the IgM natural antibody E06, which binds to the phosphocholine headgroup of OxPL, and blocks the uptake of oxidized low-density lipoprotein (OxLDL) by macrophages and inhibits the proinflammatory properties of OxPL2-4. Here, to determine the role of OxPL in vivo in the context of atherogenesis, we generated transgenic mice in the Ldlr-/- background that expressed a single-chain variable fragment of E06 (E06-scFv) using the Apoe promoter. E06-scFv was secreted into the plasma from the liver and macrophages, and achieved sufficient plasma levels to inhibit in vivo macrophage uptake of OxLDL and to prevent OxPL-induced inflammatory signalling. Compared to Ldlr-/- mice, Ldlr -/- E06-scFv mice had 57-28% less atherosclerosis after 4, 7 and even 12 months of 1% high-cholesterol diet. Echocardiographic and histologic evaluation of the aortic valves demonstrated that E06-scFv ameliorated the development of aortic valve gradients and decreased aortic valve calcification. Both cholesterol accumulation and in vivo uptake of OxLDL were decreased in peritoneal macrophages, and both peritoneal and aortic macrophages had a decreased inflammatory phenotype. Serum amyloid A was decreased by 32%, indicating decreased systemic inflammation, and hepatic steatosis and inflammation were also decreased. Finally, the E06-scFv prolonged life as measured over 15 months. Because the E06-scFv lacks the functional effects of an intact antibody other than the ability to bind OxPL and inhibit OxLDL uptake in macrophages, these data support a major proatherogenic role of OxLDL and demonstrate that OxPL are proinflammatory and proatherogenic, which E06 counteracts in vivo. These studies suggest that therapies inactivating OxPL may be beneficial for reducing generalized inflammation, including the progression of atherosclerosis, aortic stenosis and hepatic steatosis

Linkage maps of the Atlantic salmon (Salmo salar) genome derived from RAD sequencing

BACKGROUND: Genetic linkage maps are useful tools for mapping quantitative trait loci (QTL) influencing variation in traits of interest in a population. Genotyping-by-sequencing approaches such as Restriction-site Associated DNA sequencing (RAD-Seq) now enable the rapid discovery and genotyping of genome-wide SNP markers suitable for the development of dense SNP linkage maps, including in non-model organisms such as Atlantic salmon (Salmo salar). This paper describes the development and characterisation of a high density SNP linkage map based on SbfI RAD-Seq SNP markers from two Atlantic salmon reference families. RESULTS: Approximately 6,000 SNPs were assigned to 29 linkage groups, utilising markers from known genomic locations as anchors. Linkage maps were then constructed for the four mapping parents separately. Overall map lengths were comparable between male and female parents, but the distribution of the SNPs showed sex-specific patterns with a greater degree of clustering of sire-segregating SNPs to single chromosome regions. The maps were integrated with the Atlantic salmon draft reference genome contigs, allowing the unique assignment of ~4,000 contigs to a linkage group. 112 genome contigs mapped to two or more linkage groups, highlighting regions of putative homeology within the salmon genome. A comparative genomics analysis with the stickleback reference genome identified putative genes closely linked to approximately half of the ordered SNPs and demonstrated blocks of orthology between the Atlantic salmon and stickleback genomes. A subset of 47 RAD-Seq SNPs were successfully validated using a high-throughput genotyping assay, with a correspondence of 97% between the two assays. CONCLUSIONS: This Atlantic salmon RAD-Seq linkage map is a resource for salmonid genomics research as genotyping-by-sequencing becomes increasingly common. This is aided by the integration of the SbfI RAD-Seq SNPs with existing reference maps and the draft reference genome, as well as the identification of putative genes proximal to the SNPs. Differences in the distribution of recombination events between the sexes is evident, and regions of homeology have been identified which are reflective of the recent salmonid whole genome duplication