Modifying Fragility and Collective Motion in Polymer Melts with Nanoparticles

We investigate the impact of nanoparticles (NP) on the fragility and cooperative string-like motion in a model glass-forming polymer melt by molecular dynamics simulation. The NP cause significant changes to both the fragility and the average length of string-like motion, where the effect depends on the NP-polymer interaction and the NP concentration. We interpret these changes via the Adam-Gibbs (AG) theory, assuming the strings can be identified with the "cooperatively rearranging regions" of AG. Our findings indicate fragility is primarily a measure of the temperature dependence of the cooperativity of molecular motion.Comment: To appear in Physical Review Letter

Type I error control in biomarker-stratified clinical trials

Biomarker-stratified clinical trials assess the biomarker signature of subjects and split them into subgroups so that treatment is of benefit to those who are likely to respond. Since multiple hypotheses are tested, it becomes important to control the type I error. Current methods control the false positive rate where one rejects the null hypothesis while in reality that was true. For two subgroups, the false positive rate is controlled across the two hypotheses as a Family Wise Error Rate (FWER) to an overall predetermined significance level

Adaptive enrichment in biomarker-stratified clinical trial design

In Phase II oncology trials, targeted therapies are being constantly evaluated for their efficacy in specific populations of interest. Such trials require designs that allow for stratification based on the participants' biomarker signature. One of the disadvantages of a targeted design (defined as enrichment in biomarker-positive sub-population) is that if the drug has at least some activity in the biomarker-negative subjects, then their effect in the biomarker-negative population may never be known. Jones and Holmgren (JH) have proposed a design to determine whether drug has activity only in target population or the general population. Their design is an enrichment adaptation based on two parallel Simon two-stage designs. Unfortunately, there are several pitfalls in the JH design: the issue of hypothesis testing is not properly addressed and the type I error, power calculations and expected sample size formulae are wrong too. We study the JH design in detail, appropriately control the type I and type II error probabilities that yield novel optimal designs. We also discuss various alternative Family Wise Error Rates (FWER) and the Individual Hypothesis (IH) error rates in the weak sense as well as the strong sense. For each option of the error controls, we search for designs over a 10 trillion search space and obtain optimal designs that minimise the expected sample size. For the particular example trial that JH consider, our optimal design requires 38% fewer subjects in comparison with the two parallel Simon two-stage design thereby offering substantial efficiency in terms of the expected sample size. In conclusion, our rectified design provides a robust framework for adaptive enrichment in biomarker-stratified Phase II trial design

Safety in Iowa Science Programs: A Status Report

School science laboratories are active sites of learning. They may also be areas of potential danger from fire, explosives, caustic chemicals, poisons, noxious fumes, and projectiles. Science teachers are charged with the responsibility of establishing an environment in which students shall have relevant, practical science experiences. In addition, certain segments of the subject matter will require that students develop particular attitudes, knowledge, and skills. Inevitably students will periodically be exposed to potentially dangerous situations

Origin of particle clustering in a simulated polymer nanocomposite and its impact on rheology

Many nanoparticles have short-range interactions relative to their size, and these interactions tend to be “patchy” since the interatomic spacing is comparable to the nanoparticle size. For a dispersion of such particles, it is not a priori obvious what mechanism will control the clustering of the nanoparticles, and how the clustering will be affected by tuning various control parameters. To gain insight into these questions, we perform molecular dynamics simulations of polyhedral nanoparticles in a dense bead–spring polymer melt under both quiescent and steady shear conditions. We explore the mechanism that controls nanoparticle clustering and find that the crossover from dispersed to clustered states is consistent with the predictions for equilibrium particle association or equilibrium polymerization, and that the crossover does not appear to match the expectations for first-order phase separation typical for binary mixtures in the region of the phase diagram where we can equilibrate the system. At the same time, we cannot rule out the possibility of phase separation at a lower temperature. Utilizing the existing framework for dynamic clustering transitions offers the possibility of more rationally controlling the dispersion and properties of nanocomposite materials. Finally, we examine how nanocomposite rheology depends on the state of equilibrium clustering. We find that the shear viscosity for dispersed configurations is larger than that for clustered configurations, in contrast to expectations based on macroscopic colloidal dispersions. We explain this result by the alteration of the polymer matrix properties in the vicinity of the nanoparticles. We also show that shear tends to disperse clustered nanoparticle configurations in our system, an effect particularly important for processing. © 2003 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70472/2/JCPSA6-119-3-1777-1.pd

An optimal stratified Simon two-stage design

In Phase II oncology trials, therapies are increasingly being evaluated for their effectiveness in specific populations of interest. Such targeted trials require designs that allow for stratification based on the participants’ molecular characterisation. A targeted design proposed by Jones and Holmgren (JH) Jones CL, Holmgren E: ‘An adaptive Simon two-stage design for phase 2 studies of targeted therapies’, Contemporary Clinical Trials 28 (2007) 654-661.determines whether a drug only has activity in a disease sub-population or in the wider disease population. Their adaptive design uses results from a single interim analysis to decide whether to enrich the study population with a subgroup or not; it is based on two parallel Simon two-stage designs. We study the JH design in detail and extend it by providing a few alternative ways to control the familywise error rate, in the weak sense as well as the strong sense. We also introduce a novel optimal design by minimising the expected sample size. Our extended design contributes to the much needed framework for conducting Phase II trials in stratified medicine