Nonignorable Models for Intermittently Missing Categorical Longitudinal Responses

Summary A class of nonignorable models is presented for handling nonmonotone missingness in categorical longitudinal responses. This class of models includes the traditional selection models and shared parameter models. This allows us to perform a broader than usual sensitivity analysis. In particular, instead of considering variations to a chosen nonignorable model, we study sensitivity between different missing data frameworks. An appealing feature of the developed class is that parameters with a marginal interpretation are obtained, while algebraically simple models are considered. Specifically, marginalized mixed‐effects models ( Heagerty, 1999 , Biometrics 55, 688–698) are used for the longitudinal process that model separately the marginal mean and the correlation structure. For the correlation structure, random effects are introduced and their distribution is modeled either parametrically or non‐parametrically to avoid potential misspecifications.     

Shared parameter models under random effects misspecification

A common objective in longitudinal studies is the investigationof the association structure between a longitudinal responseprocess and the time to an event of interest. An attractiveparadigm for the joint modelling of longitudinal and survivalprocesses is the shared parameter framework, where a set ofrandom effects is assumed to induce their interdependence. Inthis work, we propose an alternative parameterization for sharedparameter models and investigate the effect of misspecifyingthe random effects distribution in the parameter estimates andtheir standard errors.     

The [Ca2+ + Mg2+]-dependent adenosine triphosphatase of SV40 transformed WI38 lung fibroblasts

The Ca2+-stimulated, Mg2+-dependent ATPase of SV40 transformed WI38 lung fibroblast homogenates exhibits a high affinity for Ca2+ (K0.5 = 0.20 microM) and moderately high affinity for ATP (Km = 28.6 microM) and Mg2+ (K0.5 = 138.5 microM). This activity was NaN3, KCN and oligomycin insensitive but very sensitive to vanadate (I50 = 0.5 microM) suggesting its being neither mitochondrial or microsomal but plasma membrane in origin. Under optimal conditions of protein, hydrogen ion and substrate concentration, 16-19 nmoles phosphate was released per min per mg protein. Hill plot analysis indicated no cooperativity to occur between Ca2+ binding sites. Nucleotides other than ATP and dATP were ineffective as substrates. The trivalent cation, lanthanum (La3+) completely inhibited hydrolysis of ATP at approximately 70 microM (I50 = 25 microM). Calmodulin antagonists trifluoperazine and calmidazolium inhibited ATP hydrolysis in a dose dependent fashion.     

Multiple-Imputation-Based Residuals and Diagnostic Plots for Joint Models of Longitudinal and Survival Outcomes

Summary .  The majority of the statistical literature for the joint modeling of longitudinal and time-to-event data has focused on the development of models that aim at capturing specific aspects of the motivating case studies. However, little attention has been given to the development of diagnostic and model-assessment tools. The main difficulty in using standard model diagnostics in joint models is the nonrandom dropout in the longitudinal outcome caused by the occurrence of events. In particular, the reference distribution of statistics, such as the residuals, in missing data settings is not directly available and complex calculations are required to derive it. In this article, we propose a multiple-imputation-based approach for creating multiple versions of the completed data set under the assumed joint model. Residuals and diagnostic plots for the complete data model can then be calculated based on these imputed data sets. Our proposals are exemplified using two real data sets.     

Pivotal and distinct role for Plasmodium actin capping protein alpha during blood infection of the malaria parasite

Accurate regulation of microfilament dynamics is central to cell growth, motility and response to environmental stimuli. Stabilizing and depolymerizing proteins control the steady‐state levels of filamentous (F‐) actin. Capping protein (CP) binds to free barbed ends, thereby arresting microfilament growth and restraining elongation to remaining free barbed ends. In all CPs characterized to date, alpha and beta subunits form the active heterodimer. Here, we show in a eukaryotic parasitic cell that the two CP subunits can be functionally separated. Unlike the beta subunit, the CP alpha subunit of the apicomplexan parasite Plasmodium is refractory to targeted gene deletion during blood infection in the mammalian host. Combinatorial complementation of Plasmodium berghei CP genes with the orthologs from Plasmodium falciparum verified distinct activities of CP alpha and CP alpha/beta during parasite life cycle progression. Recombinant Plasmodium CP alpha could be produced in Escherichia coli in the absence of the beta subunit and the protein displayed F‐actin capping activity. Thus, the functional separation of two CP subunits in a parasitic eukaryotic cell and the F‐actin capping activity of CP alpha expand the repertoire of microfilament regulatory mechanisms assigned to CPs.     

Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data

In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest. This type of research question has given rise to a rapidly developing field of biostatistics research that deals with the joint modeling of longitudinal and time-to-event data. In this article, we consider this modeling framework and focus particularly on the assessment of the predictive ability of the longitudinal marker for the time-to-event outcome. In particular, we start by presenting how survival probabilities can be estimated for future subjects based on their available longitudinal measurements and a fitted joint model. Following we derive accuracy measures under the joint modeling framework and assess how well the marker is capable of discriminating between subjects who experience the event within a medically meaningful time frame from subjects who do not. We illustrate our proposals on a real data set on human immunodeficiency virus infected patients for which we are interested in predicting the time-to-death using their longitudinal CD4 cell count measurements.     

Vaccinia Virus Infection Requires Maturation of Macropinosomes

The prototypic poxvirus, vaccinia virus (VACV), occurs in two infectious forms, mature virions (MVs) and extracellular virions (EVs). Both enter HeLa cells by inducing macropinocytic uptake. Using confocal microscopy, live‐cell imaging, targeted RNAi screening and perturbants of endosome maturation, we analyzed the properties and maturation pathway of the macropinocytic vacuoles containing VACV MVs in HeLa cells. The vacuoles first acquired markers of early endosomes [Rab5, early endosome antigen 1 and phosphatidylinositol(3)P]. Prior to release of virus cores into the cytoplasm, they contained markers of late endosomes and lysosomes (Rab7a, lysosome‐associated membrane protein 1 and sorting nexin 3). RNAi screening of endocytic cell factors emphasized the importance of late compartments for VACV infection. Follow‐up perturbation analysis showed that infection required Rab7a and PIKfyve, confirming that VACV is a late‐penetrating virus dependent on macropinosome maturation. VACV EV infection was inhibited by depletion of many of the same factors, indicating that both infectious particle forms share the need for late vacuolar conditions for penetration.      

The logistic transform for bounded outcome scores

The logistic transformation, originally suggested by Johnson (1949), is applied to analyze responses that are restricted to a finite interval (e.g. (0,1)), so-called bounded outcome scores. Bounded outcome scores often have a non-standard distribution, e.g. J- or U-shaped, precluding classical parametric statistical approaches for analysis. Applying the logistic transformation on a normally distributed random variable, gives rise to a logit-normal (LN) distribution. This distribution can take a variety of shapes on (0,1). Further, the model can be extended to correct for (baseline) covariates. Therefore, the method could be useful for comparative clinical trials. Bounded outcomes can be found in many research areas, e.g. drug compliance research, quality-of-life studies, and pain (and pain relief) studies using visual analog scores, but all these scores can attain the boundary values 0 or 1. A natural extension of the above approach is therefore to assume a latent score on 0,1) having a LN distribution. Two cases are considered: (a) the bounded outcome score is a proportion where the true probabilities have a LN distribution on (0,1) and (b) the bounded outcome score on [0,1] is a coarsened version of a latent score with a LN distribution on (0,1). We also allow the variance (on the transformed scale) to depend on treatment. The usefulness of our approach for comparative clinical trials will be assessed in this paper. It turns out to be important to distinguish the case of equal and unequal variances. For a bounded outcome score of the second type and with equal variances, our approach comes close to ordinal probit (OP) regression. However, ignoring the inequality of variances can lead to highly biased parameter estimates. A simulation study compares the performance of our approach with the two-sample Wilcoxon test and with OP regression. Finally, the different methods are illustrated on two data sets.