Quantifying and Comparing the Accuracy of Binary Biomarkers When Predicting a Failure Time Outcome

The positive and negative predictive value are standard measures used to quantify the predictive accuracy of binary biomarkers when the outcome being predicted is also binary. When the biomarkers are instead being used to predict a failure time outcome, there is no standard way of quantifying predictive accuracy. We propose a natural extension of the traditional predictive values to accommodate censored survival data. We discuss not only quantifying predictive accuracy using these extended predictive values, but also rigorously comparing the accuracy of two biomarkers in terms of their predictive values. Using a marginal regression framework, we describe how to estimate differences in predictive accuracy and how to test whether the observed difference is statistically significant.

A BAYESIAN SHRINKAGE MODEL FOR INCOMPLETE LONGITUDINAL BINARY DATA WITH APPLICATION TO THE BREAST CANCER PREVENTION TRIAL

We consider inference in randomized studies, in which repeatedly measured outcomes may be informatively missing due to drop out. In this setting, it is well known that full data estimands are not identified unless unverified assumptions are imposed. We assume a non-future dependence model for the drop-out mechanism and posit an exponential tilt model that links non-identifiable and identifiable distributions. This model is indexed by non-identified parameters, which are assumed to have an informative prior distribution, elicited from subject-matter experts. Under this model, full data estimands are shown to be expressed as functionals of the distribution of the observed data. To avoid the curse of dimensionality, we model the distribution of the observed data using a Bayesian shrinkage model. In a simulation study, we compare our approach to a fully parametric and a fully saturated model for the distribution of the observed data. Our methodology is motivated and applied to data from the Breast Cancer Prevention Trial.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Preparation of highly-ordered TiO₂ nanotube arrays and their applications in Dye-sensitized solar cells

Titanium oxide is an important semiconductor, which is widely applied for solar cells. In this research, titanium oxide nanotube arrays were synthesized by anodization of Ti foil in the electrolyte composed of ethylene glycol containing 2 vol % H2O and 0.3 wt % NH4F. The voltages of 40V-50V were employed for the anodizing process. Pore diameters and lengths of the TiO2 nanotubes were evaluated by field emission scanning electron microscope (FESEM). The obtained highly-ordered titanium nanotube arrays were exploited to fabricate photoelectrode for the Dye-sensitized solar cells (DSSCS). The TiO2 nanotubes based DSSCS exhibited an excellent performance with a high short circuit current and open circuit voltage as well as a good power conversion efficiency. Those can be attributed to the high surface area and one dimensional structure of TiO2 nanotubes, which could hold a large amount of dyes to absorb light and help electron percolation process to hinder the recombination during the electrons diffusion in the electrolyte.

Fabrication of a Large, Ordered, Three-Dimensional Nanocup Array

Metallic nanocups provide a unique method for redirecting scattered light by creating magnetic plasmon responses at optical frequencies. Despite considerable development of nanocup fabrication processes, simultaneously achieving accurate control over the placement, orientation, and geometry of nanocups has remained a significant challenge. Here we present a technique for fabricating large, periodically ordered arrays of uniformly oriented three-dimensional gold nanocups for manipulating light at subwavelength scales. Nanoimprint lithography, soft lithography, and shadow evaporation were used to fabricate nanocups onto the tips of polydimethylsiloxane nanopillars with precise control over the shapes and optical properties of asymmetric nanocups.

On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models

OBJECTIVES: This paper is concerned with checking goodness-of-fit of binary logistic regression models. For the practitioners of data analysis, the broad classes of procedures for checking goodness-of-fit available in the literature are described. The challenges of model checking in the context of binary logistic regression are reviewed. As a viable solution, a simple graphical procedure for checking goodness-of-fit is proposed. METHODS: The graphical procedure proposed relies on pieces of information available from any logistic analysis; the focus is on combining and presenting these in an informative way. RESULTS: The information gained using this approach is presented with three examples. In the discussion, the proposed method is put into context and compared with other graphical procedures for checking goodness-of-fit of binary logistic models available in the literature. CONCLUSION: A simple graphical method can significantly improve the understanding of any logistic regression analysis and help to prevent faulty conclusions.

Epothilone analogues with benzimidazole and quinoline side chains: chemical synthesis, antiproliferative activity, and interactions with tubulin

A series of epothilone B and D analogues bearing isomeric quinoline or functionalized benzimidazole side chains has been prepared by chemical synthesis in a highly convergent manner. All analogues have been found to interact with the tubulin/microtubule system and to inhibit human cancer cell proliferation in vitro, albeit with different potencies (IC(50) values between 1 and 150 nM). The affinity of quinoline-based epothilone B and D analogues for stabilized microtubules clearly depends on the position of the N-atom in the quinoline system, while the induction of tubulin polymerization in vitro appears to be less sensitive to N-positioning. The potent inhibition of human cancer cell growth by epothilone analogues bearing functionalized benzimidazole side chains suggests that these systems might be conjugated with tumor-targeting moieties to form tumor-targeted prodrugs.

Intermolecular crosslinking of fatty acyl chains in phospholipids: Use of photoactivable carbene precursors

Phospholipids containing photolysable carhene precursors (beta-trifluoro-a-diazopropionoxy and m-diazirinophenoxy groups) in w-positions of sn-2 fatty acyl chains were prepared. Photolysis of their vesicles produced crosslinked products in 40-60 % yields. Crosslinking was mostly intermolecular and occurred bv carbene insertion into the C-H bonds of a second fatty acyl chain. Crosslinking products were characterized by (i) their gel permeation behavior, (ii) analysis of produets formed by base-catalyzed transesterification. (iii) degradation with phosphoiipases A2 and C, (iv) gas chromatography/mass spectrometry, and-(v) use of mixtures of phospholipids carrying thf' carhene precursors and a phospholipid containing radioactively labeled fatty acyl groups. Nitrenes generated from the aliphatic or aromatic azido groups in phospholipids were unsatisfactory for forming crosslinks by insertion in C-H bond