Improved semi-parametric inference for a mixture model of responses from a control versus treatment group trial.

The mixture of a distribution of responses from untreated patients and a shift of that distribution is a useful model for the responses from a group of treated patients. The mixture model accounts for the fact that not all the patients in the treated group will respond to the treatment and consequently their responses follow the same distribution as the responses from untreated patients. The treatment effect in this context consists of both the fraction of the treated patients that are responders and the magnitude of the shift in the distribution for the responders. In this article, we introduce inference based on a pseudo-likelihood approach and compare it with an existing method of moment approach. An extensive simulation study is used to compare robust performance of the two approaches regarding point estimation, confidence regions, and confidence intervals. The methods are demonstrated on an illustrative blood pressure data set.

Wilcoxon rank-sum tests to detect one-sided mixture alternatives in group sequential clinical trials.

Traditional methods based on the assumption that the treatment distribution is a pure shift of the control distribution may not always hold. The possibility that an individual from the treatment group may not respond to the treatment motivates the use of a mixture distribution for the treatment group. This paper considers two test procedures based on the Wilcoxon rank-sum statistic for a group sequential design to detect the one-sided mixture alternative. Error spending functions are used for the allocation of error rates at each stage. The two tests are evaluated individually in determination of critical values and arm sizes and asymptotic multivariate normality is shown to hold for both. Upon comparison, the tests are presented to be asymptotically equivalent. Both test statistics maintain the Type I error rate even if F is misspecified in the design alternative. A more general definition of the treatment effect is used with the mixture distribution. Method of moments estimators and constrained k-means estimators for the treatment effect are evaluated.

Priming grapevine with lipopolysaccharide confers systemic resistance to Pierce's disease and identifies a peroxidase linked to defense priming.

Priming is an adaptive mechanism that fortifies plant defense by enhancing activation of induced defense responses following pathogen challenge. Microorganisms have signature microbe-associated molecular patterns (MAMPs) that induce the primed state. The lipopolysaccharide (LPS) MAMP isolated from the xylem-limited pathogenic bacterium, Xylella fastidiosa, acts as a priming stimulus in Vitis vinifera grapevines. Grapevines primed with LPS developed significantly less internal tyloses and external disease symptoms than naive vines. Differential gene expression analysis indicated major transcriptomic reprogramming during the priming and postpathogen challenge phases. Furthermore, the number of differentially expressed genes increased temporally and spatially in primed vines, but not in naive vines during the postpathogen challenge phase. Using a weighted gene co-expression analysis, we determined that primed vines have more genes that are co-expressed in both local and systemic petioles than naive vines indicating an inherent synchronicity that underlies the systemic response to this vascular pathogen specific to primed plants. We identified a cationic peroxidase, VviCP1, that was upregulated during the priming and postpathogen challenge phases in an LPS-dependent manner. Transgenic expression of VviCP1 conferred significant disease resistance, thus, demonstrating that grapevine is a robust model for mining and expressing genes linked to defense priming and disease resistance.

A Bayesian longitudinal trend analysis of count data with Gaussian processes.

The context of comparing two different groups of subjects that are measured repeatedly over time is considered. Our specific focus is on highly variable count data which have a nonnegligible frequency of zeros and have time trends that are difficult to characterize. These challenges are often present when analyzing bacteria or gene expression data sets. Traditional longitudinal data analysis methods, including generalized estimating equations, can be challenged by the features present in these types of data sets. We propose a Bayesian methodology that effectively confronts these challenges. A key feature of the methodology is the use of Gaussian processes to flexibly model the time trends. Inference procedures based on both sharp and interval null hypotheses are discussed, including for the important hypotheses that test for group differences at individual time points. The proposed methodology is illustrated with next-generation sequencing (NGS) data sets corresponding to two different experimental conditions. In particular, the method is applied to a case study containing bacteria counts of mice with chronic and nonchronic wounds to identify potential wound-healing probiotics. The methodology can be applied to similar NGS data sets comparing two groups of subjects.

High Levels of Oxidative Stress Create a Microenvironment That Significantly Decreases the Diversity of the Microbiota in Diabetic Chronic Wounds and Promotes Biofilm Formation.

Diabetics chronic wounds are characterized by high levels of oxidative stress (OS) and are often colonized by biofilm-forming bacteria that severely compromise healing and can result in amputation. However, little is known about the role of skin microbiota in wound healing and chronic wound development. We hypothesized that high OS levels lead to chronic wound development by promoting the colonization of biofilm-forming bacteria over commensal/beneficial bacteria. To test this hypothesis, we used our db/db-/- mouse model for chronic wounds where pathogenic biofilms develop naturally after induction of high OS immediately after wounding. We sequenced the bacterial rRNA internal transcribed spacer (ITS) gene of the wound microbiota from wound initiation to fully developed chronic wounds. Indicator species analysis, which considers a species' fidelity and specificity, was used to determine which bacterial species were strongly associated with healing wounds or chronic wounds. We found that healing wounds were colonized by a diverse and dynamic bacterial microbiome that never developed biofilms even though biofilm-forming bacteria were present. Several clinically relevant species that are present in human chronic wounds, such as Cutibacterium acnes, Achromobacter sp., Delftia sp., and Escherichia coli, were highly associated with healing wounds. These bacteria may serve as bioindicators of healing and may actively participate in the processes of wound healing and preventing pathogenic bacteria from colonizing the wound. In contrast, chronic wounds, which had high levels of OS, had low bacterial diversity and were colonized by several clinically relevant, biofilm-forming bacteria such as Pseudomonas aeruginosa, Enterobacter cloacae, Corynebacterium frankenforstense, and Acinetobacter sp. We observed unique population trends: for example, P. aeruginosa associated with aggressive biofilm development, whereas Staphylococcus xylosus was only present early after injury. These findings show that high levels of OS in the wound significantly altered the bacterial wound microbiome, decreasing diversity and promoting the colonization of bacteria from the skin microbiota to form biofilm. In conclusion, bacteria associated with non-chronic or chronic wounds could function as bioindicators of healing or non-healing (chronicity), respectively. Moreover, a better understanding of bacterial interactions between pathogenic and beneficial bacteria within an evolving chronic wound microbiota may lead to better solutions for chronic wound management.

Construction, visualization and application of neutral zone classifiers.

When the potential for making accurate classifications with a statistical classifier is limited, a neutral zone classifier can be constructed by adding a no-decision option as a classification outcome. We show how a neutral zone classifier can be constructed from a receiving operating characteristic (ROC) curve. We extend the ROC curve graphic to highlight important performance characteristics of a neutral zone classifier. Additional utility of neutral zone classifiers is illustrated by showing how they can be incorporated into the first stage of a two-stage classification process. At the first stage, a classification is attempted from easily collected or inexpensive features. If the classification falls into the neutral zone, additional relatively more expensive features can be obtained and used to make a definitive classification at the second stage. The methods discussed in the paper are illustrated with an application pertaining to prostate cancer.

Xylella fastidiosa Endoglucanases Mediate the Rate of Pierce's Disease Development in Vitis vinifera in a Cultivar-Dependent Manner.

Xylella fastidiosa is a gram-negative bacterium that causes Pierce's disease (PD) in grapevine. X. fastidiosa is xylem-limited and interfaces primarily with pit membranes (PMs) that separate xylem vessels from one another and from adjacent xylem parenchyma cells. PMs are composed of both pectic and cellulosic substrates, and dissolution of PMs is facilitated by X. fastidiosa cell wall-degrading enzymes. A polygalacturonase, which hydrolyzes the pectin component of PMs, is required for both movement and pathogenicity in grapevines. Here, we demonstrate that two X. fastidiosa ß-1,4-endoglucanases (EGases), EngXCA1 and EngXCA2, also play a role in how X. fastidiosa interfaces with grapevine PMs. The loss of EngXCA1 and EngXCA2 in tandem reduces both X. fastidiosa virulence and population size and slows the rate of PD symptom development and progression. Moreover, we demonstrate that single and double EGases mutants alter the rate of PD progression differently in two grapevine cultivars, Cabernet Sauvignon and Chardonnay, and that Chardonnay is significantly more susceptible to PD than Cabernet Sauvignon. Interestingly, we determined that there are quantitative differences in the amount of fucosylated xyloglucans that make up the surface of PMs in these cultivars. Fucosylated xyloglucans are targets of the X. fastidiosa EGases, and xyloglucan abundance could impact PM dissolution and affect PD symptom development. Taken together, these results indicate that X. fastidiosa EGases and the PM carbohydrate composition of different grape cultivars are important factors that influence PD symptom development and progression.

Author Correction: Infection with the Makona variant results in a delayed and distinct host immune response compared to previous Ebola virus variants.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

A copula model for joint modeling of longitudinal and time-invariant mixed outcomes.

Motivated by a preclinical study in a mouse model of breast cancer, we suggest a joint modeling framework for outcomes of mixed type and measurement structures (longitudinal versus single time/time-invariant). We present an approach based on the time-varying copula models, which is used to jointly model longitudinal outcomes of mixed types via a time-varying copula, and extend the scope of these models to handle outcomes with mixed measurement structures. Our framework allows the parameters corresponding to the longitudinal outcome to be time varying and thereby enabling researchers to investigate how the response-predictor relationships change with time. We investigate the finite sample performance of this new approach via a Monte Carlo simulation study and illustrate its usefulness by an empirical analysis of the motivating preclinical study, comparing the effect of various treatments on tumor volume (longitudinal continuous response) and the number of days until tumor volume triples (time-invariant count response). Through the real-life application and the simulation study, we demonstrate that, compared with marginal modeling, the joint modeling framework offers more precision in the estimation of model parameters.

Incidence of Grapevine Leafroll Disease: Effects of Grape Mealybug (Pseudococcus maritimus) Abundance and Pathogen Supply.

Studies of spatiotemporal dynamics are central to efforts to characterize the epidemiology of infectious disease, such as mechanism of pathogen spread and pathogen or vector sources in the landscape, and are critical to the development of effective disease management programs. To that end, we conducted a multi-year study of 20 vineyard blocks in coastal northern California to relate the dynamics of a mealybug vector, Pseudococcus maritimus (Ehrhorn) (Hemiptera: Pseudococcidae), to incidence of grapevine leafroll disease (GLD). In each vineyard block, a subset of vines were scored visually for relative mealybug abundance, disease was quantified by visual assessment, and virus presence was verified using standard laboratory molecular assays. GLD incidence was analyzed with a classification and regression tree, and with a hierarchical model that also captured variability among blocks and heterogeneity within blocks. Both analyses found strong interannual variability in incidence, with the hierarchical model also capturing substantial between- and within-block heterogeneity, but with significant contributions of vector abundance and pathogen supply (prior disease incidence) to the frequency of newly diseased vines. These results strengthen further the conclusion that mealybug vectors are causally related to pathogen spread in this system and are therefore an important target for management. Moreover, they are consistent with relatively efficient secondary spread of the pathogen, suggesting an important role for the removal of diseased vines as a tool to mitigate further damage.

Maximizing the usefulness of statistical classifiers for two populations with illustrative applications.

The usefulness of two-class statistical classifiers is limited when one or both of the conditional misclassification rates is unacceptably high. Incorporating a neutral zone region into the classifier provides a mechanism to refer ambiguous cases to follow-up where additional information might be obtained to clarify the classification decision. Through the use of the neutral zone region, the conditional misclassification rates can be controlled and the classifier becomes useful. Three real-life examples, including applications to prostate cancer and kidney dysfunction following heart surgery, are used to illustrate how neutral zone regions can extract utility from disappointing classifiers that might otherwise be abandoned.

Two-stage classifiers that minimize PCA3 and the PSA proteolytic activity testing in the prediction of prostate cancer recurrence after radical prostatectomy.

INTRODUCTION: Early biochemical recurrence after prostate cancer surgery is associated with higher risk of aggressive disease and cancer specific death. Many new tests are being developed that will predict the presence of indicators of aggressive disease like early biochemical recurrence. Since recurrence occurs in less than 10% of patients treated for prostate cancer, validation of such tests will require expensive testing on large patient groups. Moreover, clinical application of the validated test requires that each new patient be tested. In this report we introduce a two-stage classifier system that minimizes the number of patients that must be tested in both the validation and clinical application of any new test for recurrence. MATERIALS AND METHODS: Expressed prostatic secretion specimens were prospectively collected from 450 patients prior to robot-assisted radical prostatectomy for prostate cancer. Patients were followed for 2.5 years for evidence of biochemical recurrence. Standard clinical parameters, the levels proteolytic activity of prostate specific antigen (PSA) and the levels of PCA3 RNA, PSA RNA and TMPRSS2:ERG fusion RNA were determined in each prospective patient specimen for subsequent correlation with biochemical recurrence. RESULTS: While levels of PCA3 and PSA proteolytic activity (PPA) in prostatic secretions provided an effective pre-surgical predictor of early biochemical recurrence in prostate cancer, application of the two-stage classifier shows that only 60% of the patients need these tests. CONCLUSION: Two-stage classifiers can provide a parsimonious approach to both the validation and clinical application of biomarker-based tests. Adoption of the two-stage neutral zone classifier can reduce unnecessary testing in prostate cancer treatment.

Infection with the Makona variant results in a delayed and distinct host immune response compared to previous Ebola virus variants.

Zaire Ebolavirus (ZEBOV) continues to pose a significant threat to human health as highlighted by the recent epidemic that originated in West Africa and the ongoing outbreak in the Democratic Republic of the Congo. Although the ZEBOV variant responsible for this epidemic (Makona) shares significant genetic similarity with previously identified variants (Kikwit and Mayinga), recent reports suggest slower disease progression in nonhuman primates. However, the pathogenesis caused by the new variant is not fully understood. We present the first comprehensive approach in understanding ZEBOV-Makona pathogenesis in cynomolgus macaques by measuring changes in immune cell frequencies, plasma levels of immune mediators, and differentially expressed genes (DEGs) within whole blood (WB) and peripheral blood mononuclear cells (PBMC). Our combined approach revealed a link between: 1) increased interferon-stimulated gene expression, IFNα levels, and activated plasmacytoid dendritic cells; 2) higher proinflammatory gene expression, cytokine and chemokine levels, and non-classical monocytes; 3) gene signature of leukocyte activation and increased granulocytes; and 4) decreased expression of lymphocyte related genes and lymphopenia. In addition, our data strongly indicate delayed disease progression as well as limited overlap (~30%) in host transcriptome changes following ZEBOV-Makona infection compared to ZEBOV-Kikwit. These observations provide novel insight into the molecular mechanisms of ZEBOV-Makona pathogenesis.

Presurgical Biomarker Performance in the Detection of Gleason Upgrading in Prostate Cancer.

BACKGROUND: Gleason Score (GS) upgrading is generally considered a trigger for exit to definitive treatment during active surveillance (AS). Predicting the potential for GS upgrading would be of value in assessing AS eligibility. METHODS: We assessed the performance of biomarkers in presurgical specimens of expressed prostatic secretion (EPS) in this setting. RESULTS: Although EPS volume, total recovered RNA, and RNA expression biomarkers (TMPRSS2: ERG, PCA3, PSA) have been successful in both biopsy outcome prediction, and in the prediction of upstaging in active surveillance eligible patients, they were unable to predict upgrading in patients eligible for active surveillance under National Comprehensive Cancer Network guidelines. CONCLUSIONS: These biomarkers do not improve the prediction of upgrading over indications from standard clinical parameters. IMPACT: Additional biomarkers will be needed in this area. Cancer Epidemiol Biomarkers Prev; 25(12); 1643-5. ©2016 AACR.

Estimated Maximal Safe Dosages of Tumescent Lidocaine.

BACKGROUND: Tumescent lidocaine anesthesia consists of subcutaneous injection of relatively large volumes (up to 4 L or more) of dilute lidocaine (≤1 g/L) and epinephrine (≤1 mg/L). Although tumescent lidocaine anesthesia is used for an increasing variety of surgical procedures, the maximum safe dosage is unknown. Our primary aim in this study was to measure serum lidocaine concentrations after subcutaneous administration of tumescent lidocaine with and without liposuction. Our hypotheses were that even with large doses (i.e., >30 mg/kg), serum lidocaine concentrations would be below levels associated with mild toxicity and that the concentration-time profile would be lower after liposuction than without liposuction. METHODS: Volunteers participated in 1 to 2 infiltration studies without liposuction and then one study with tumescent liposuction totally by local anesthesia. Serum lidocaine concentrations were measured at 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, and 24 hours after each tumescent lidocaine infiltration. Area under the curve (AUC∞) of the serum lidocaine concentration-time profiles and peak serum lidocaine concentrations (Cmax) were determined with and without liposuction. For any given milligram per kilogram dosage, the probability that Cmax >6 µg/mL, the threshold for mild lidocaine toxicity was estimated using tolerance interval analysis. RESULTS: In 41 tumescent infiltration procedures among 14 volunteer subjects, tumescent lidocaine dosages ranged from 19.2 to 52 mg/kg. Measured serum lidocaine concentrations were all <6 µg/mL over the 24-hour study period. AUC∞s with liposuction were significantly less than those without liposuction (P = 0.001). The estimated risk of lidocaine toxicity without liposuction at a dose of 28 mg/kg and with liposuction at a dose of 45 mg/kg was ≤1 per 2000. CONCLUSIONS: Preliminary estimates for maximum safe dosages of tumescent lidocaine are 28 mg/kg without liposuction and 45 mg/kg with liposuction. As a result of delayed systemic absorption, these dosages yield serum lidocaine concentrations below levels associated with mild toxicity and are a nonsignificant risk of harm to patients.

Maternal obesity alters immune cell frequencies and responses in umbilical cord blood samples.

BACKGROUND: Maternal obesity is one of the several key factors thought to modulate neonatal immune system development. Data from murine studies demonstrate worse outcomes in models of infection, autoimmunity, and allergic sensitization in offspring of obese dams. In humans, children born to obese mothers are at increased risk for asthma. These findings suggest a dysregulation of immune function in the children of obese mothers; however, the underlying mechanisms remain poorly understood. The aim of this study was to examine the relationship between maternal body weight and the human neonatal immune system. METHODS: Umbilical cord blood samples were collected from infants born to lean, overweight, and obese mothers. Frequency and function of major innate and adaptive immune cell populations were quantified using flow cytometry and multiplex analysis of circulating factors. RESULTS: Compared to babies born to lean mothers, babies of obese mothers had fewer eosinophils and CD4 T helper cells, reduced monocyte and dendritic cell responses to Toll-like receptor ligands, and increased plasma levels of IFN-α2 and IL-6 in cord blood. CONCLUSION: These results support the hypothesis that maternal obesity influences programming of the neonatal immune system, providing a potential link to increased incidence of chronic inflammatory diseases such as asthma and cardiovascular disease in the offspring.

A chi-square goodness-of-fit test for autoregressive logistic regression models with applications to patient screening.

We propose a chi-square goodness-of-fit test for autoregressive logistic regression models. General guidelines for a two-dimensional binning strategy are provided, which make use of two types of maximum likelihood parameter estimates. For smaller sample sizes, a bootstrap p-value procedure is discussed. Simulation studies indicate that the test procedure satisfactorily approximates the correct size and has good power for detecting model misspecification. In particular, the test is very good at detecting the need for an additional lag. An application to a dataset relating to screening patients for late-onset Alzheimer's disease is provided.

Intrabronchial infection of rhesus macaques with simian varicella virus results in a robust immune response in the lungs.

UNLABELLED: Varicella-zoster virus (VZV) is the etiological agent of varicella (chickenpox) and herpes zoster (shingles). Primary VZV infection is believed to occur via the inhalation of virus either in respiratory droplets or from shedding varicella lesions or by direct contact with infectious vesicular fluid. However, the ensuing immune response in the lungs remains incompletely understood. We have shown that intrabronchial inoculation of rhesus macaques with simian varicella virus (SVV), a homolog of VZV, recapitulates the hallmarks of acute and latent VZV infection in humans. In this study, we performed an in-depth analysis of the host immune response to acute SVV infection in the lungs and peripheral blood. We report that acute SVV infection results in a robust innate immune response in the lungs, characterized by the production of inflammatory cytokines, chemokines, and growth factors as well as an increased frequency of plasmacytoid dendritic cells (DCs) that corresponded with alpha interferon (IFN-α) production and a rapid decrease in viral loads in the lungs. This is followed by T and B cell proliferation, antibody production, T cell differentiation, and cytokine production, which correlate with the complete cessation of viral replication. Although terminally differentiated CD8 T cells became the predominant T cell population in bronchoalveolar lavage cells, a higher percentage of CD4 T cells were SVV specific, which suggests a critical role for these cells in the resolution of primary SVV infection in the lungs. Given the homology between SVV and VZV, our data provide insight into the immune response to VZV within the lung. IMPORTANCE: Although primary VZV infection occurs primarily via the respiratory route, the host response in the lungs and its contribution to the cessation of viral replication and establishment of latency remain poorly understood. The difficulty in accessing lung tissue and washes from individuals infected with VZV has hampered efforts to address this knowledge gap. SVV infection of rhesus macaques is an important model of VZV infection of humans; therefore, we utilized this animal model to gain a comprehensive view of the kinetics of the immune response to SVV in the lung and its relationship to the resolution of acute infection in respiratory tissues. These data not only advance our understanding of host immunity to VZV, a critical step in developing new vaccines, but also provide additional insight into immunity to respiratory pathogens.

ß1-Adrenergic receptor blockade extends the life span of Drosophila and long-lived mice.

Chronic treatment with ß-adrenergic receptor (ßAR) agonists increases mortality and morbidity while ßAR antagonists (ß-blockers) decrease all-cause mortality for those at risk of cardiac disease. Levels of sympathetic nervous system ßAR agonists and ßAR activity increase with age, and this increase may hasten the development of age-related mortality. Here, we show that ß-blockers extend the life span of healthy metazoans. The ß-blockers metoprolol and nebivolol, administered in food daily beginning at 12 months of age, significantly increase the mean and median life span of isocalorically fed, male C3B6F1 mice, by 10 and 6.4%, respectively (P < 0.05). Neither drug affected the weight or food intake of the mice, indicating that induced CR is not responsible for these effects, and that energy absorption and utilization are not altered by the drugs. Both ß-blockers were investigated to control for their idiosyncratic, off-target effects. Metoprolol and nebivolol extended Drosophila life span, without affecting food intake or locomotion. Thus, ßAR antagonists are capable of directly extending the life span of two widely divergent metazoans, suggesting that these effects are phylogenetically highly conserved. Thus, long-term use of ß-blockers, which are generally well-tolerated, may enhance the longevity of healthy humans.

Sequential hypothesis testing with spatially correlated presence-absence data.

A pest management decision to initiate a control treatment depends upon an accurate estimate of mean pest density. Presence-absence sampling plans significantly reduce sampling efforts to make treatment decisions by using the proportion of infested leaves to estimate mean pest density in lieu of counting individual pests. The use of sequential hypothesis testing procedures can significantly reduce the number of samples required to make a treatment decision. Here we construct a mean-proportion relationship for Oligonychus perseae Tuttle, Baker, and Abatiello, a mite pest of avocados, from empirical data, and develop a sequential presence-absence sampling plan using Bartlett's sequential test procedure. Bartlett's test can accommodate pest population models that contain nuisance parameters that are not of primary interest. However, it requires that population measurements be independent, which may not be realistic because of spatial correlation of pest densities across trees within an orchard. We propose to mitigate the effect of spatial correlation in a sequential sampling procedure by using a tree-selection rule (i.e., maximin) that sequentially selects each newly sampled tree to be maximally spaced from all other previously sampled trees. Our proposed presence-absence sampling methodology applies Bartlett's test to a hypothesis test developed using an empirical mean-proportion relationship coupled with a spatial, statistical model of pest populations, with spatial correlation mitigated via the aforementioned tree-selection rule. We demonstrate the effectiveness of our proposed methodology over a range of parameter estimates appropriate for densities of O. perseae that would be observed in avocado orchards in California.