PubMed Health⌕ Search

Biomedical subjects

D B Dunson

Publications and source records attributed to D B Dunson.

21 records · Page 2Linked to original sources

Summarizing the motion of self-propelled cells: applications to sperm motility.

Proper characterization of the motion of spermatozoa is an important prerequisite for interpreting differences in sperm motility that might arise from exposure to toxicants. Patterns of sperm movement can be extremely complex. On the basis of an exponential model that relates the discretely approximated curvilinear velocity to the tracking rate, we develop a statistic that indexes the predictability of the path for individual sperm. We summarize the path of each sperm using this and two other statistics: (1) the path displacement velocity and (2) linearity of movement. We apply the method to a set of rat sperm tracks representative of both normal and abnormal motion characteristics.

Animals↗

Modeling tumor onset and multiplicity using transition models with latent variables.

We describe a method for modeling carcinogenicity from animal studies where the data consist of counts of the number of tumors present over time. The research is motivated by applications to transgenic rodent studies, which have emerged as an alternative to chronic bioassays for screening possible carcinogens. In transgenic mouse studies, the endpoint of interest is frequently skin papilloma, with weekly examinations determining how many papillomas each animal has at a particular point in time. It is assumed that each animal has two unobservable latent variables at each time point. The first indicates whether or not the tumors are in a multiplying state and the second is the potential number of additional tumors if the tumors are in a multiplying state. The product of these variables follows a zero-inflated Poisson distribution, and the EM algorithm can be used to maximize the observed-data pseudo-likelihood, based on the latent variables. A generalized estimating equations robust variance estimator adjusts for dependency among outcomes within individual animals. The method is applied to testing for a dose-related trend in both tumor incidence and multiplicity in carcinogenicity studies.

Algorithms↗

Dose-dependent number of implants and implications in developmental toxicity.

This paper proposes a method for assessing risk in developmental toxicity studies with exposure prior to implantation. The method proposed in this paper was developed to account for a dose-dependent trend in the number of implantation sites per dam, which is a common problem in studies with exposure prior to implantation. Toxins may have the effect of interfering with the early reproductive process, which can prevent implantation in the uterine wall. An imputation procedure is presented for estimating the number of potential fetuses by sampling from the empirical distribution of the number of implants per litter in the control group. The marginal death outcomes and the joint malformation and survival outcomes for each potential fetus can be estimated using multiple imputation or the chained data augmentation algorithm. Logit models can then be fit and used to estimate the effect of dose on reducing the probability of a normal birth. These models accommodate multiple covariate effects and can be applied to low-dose extrapolation. A simulation study is done to evaluate the properties of model-based estimators of the mean response and the virtually safe dose level (VSD). It was found that both estimates were good approximations of the underlying dose effect. A dominant lethal assay data set (Luning et al., 1966, Mutation Research 3, 444-451) is analyzed, and the results are compared with those of Rai and Van Ryzin.

Animals↗