An extension of an over-dispersion test for count data

While over-dispersion in capture–recapture studies is well known to lead to poor estimation of population size, current diagnostic tools to detect the presence of heterogeneity have not been specifically developed for capture–recapture studies. To address this, a simple and efficient method of testing for over-dispersion in zero-truncated count data is developed and evaluated. The proposed method generalizes an over-dispersion test previously suggested for un-truncated count data and may also be used for testing residual over-dispersion in zero-inflation data. Simulations suggest that the asymptotic distribution of the test statistic is standard normal and that this approximation is also reasonable for small sample sizes. The method is also shown to be more efficient than an existing test for over-dispersion adapted for the capture–recapture setting. Studies with zero-truncated and zero-inflated count data are used to illustrate the test procedures.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity.

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture–recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture–recapture models. Alternative methods, still under the capture–recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture–recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Mixture models for capture-recapture count data

The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.

On the question of proportionality of the count of observed Scrapie cases and the size of holding

Background: The present paper investigates the question of a suitable basic model for the number of scrapie cases in a holding and applications of this knowledge to the estimation of scrapie-ffected holding population sizes and adequacy of control measures within holding. Is the number of scrapie cases proportional to the size of the holding in which case it should be incorporated into the parameter of the error distribution for the scrapie counts? Or, is there a different - potentially more complex - relationship between case count and holding size in which case the information about the size of the holding should be better incorporated as a covariate in the modeling? Methods: We show that this question can be appropriately addressed via a simple zero-truncated Poisson model in which the hypothesis of proportionality enters as a special offset-model. Model comparisons can be achieved by means of likelihood ratio testing. The procedure is illustrated by means of surveillance data on classical scrapie in Great Britain. Furthermore, the model with the best fit is used to estimate the size of the scrapie-affected holding population in Great Britain by means of two capture-recapture estimators: the Poisson estimator and the generalized Zelterman estimator. Results: No evidence could be found for the hypothesis of proportionality. In fact, there is some evidence that this relationship follows a curved line which increases for small holdings up to a maximum after which it declines again. Furthermore, it is pointed out how crucial the correct model choice is when applied to capture-recapture estimation on the basis of zero-truncated Poisson models as well as on the basis of the generalized Zelterman estimator. Estimators based on the proportionality model return very different and unreasonable estimates for the population sizes. Conclusion: Our results stress the importance of an adequate modelling approach to the association between holding size and the number of cases of classical scrapie within holding. Reporting artefacts and speculative biological effects are hypothesized as the underlying causes of the observed curved relationship. The lack of adjustment for these artefacts might well render ineffective the current strategies for the control of the disease.

CAMCR: Computer assisted mixture model analysis for capture-recapture count data

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so. that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

From ideals to reality: The women's smallholding colony at Lingfield, 1920-39

The immediate impetus for the colony at Lingfield in Surrey was the desire by the Women's Farm and Garden Association to enable women who had worked on the land during the First World War to be able to farm on their own account. However the motivation for the colony can also be traced back to late nineteenth-century ideals. The colony soon ran into problems which were exacerbated by the adverse agricultural conditions of the early 1920s. The association responded constructively but the colony was wound down from 1929. At one level the colony could be seen as a failure, yet this article argues that the 19 colony provided a rural community where single women lived in a mutually supportive environment.

Cannabinoids stimulate fibroblastic colony formation by bone marrow cells indirectly via CB2 receptors

Recently, the cannabinoid receptors CB1 and CB2 were shown to modulate bone formation and resorption in vivo, although little is known of the mechanisms underlying this. The effects of cannabinoids on mesenchymal stem cell (MSC) recruitment in whole bone marrow were investigated using either the fibroblastic colony-forming unit (CFU-f) assay or high-density cultures of whole bone marrow. Levels of the CB1 and CB2 receptors were assessed by flow cytometry. Treatment of CFU-f cultures with the endocannabinoid 2-arachidonylglycerol (2-AG) dose-dependently increased fibroblastic and differentiated colony formation along with colony size. The nonspecific agonists CP 55,940 and WIN 55,212 both increased colony numbers, as did the CB2 agonists BML190 and JWH015. The CB1-specific agonist ACEA had no effect, whereas the CB2 antagonist AM630 blocked the effect of the natural cannabinoid tetrahydrocannabivarin, confirming mediation via the CB2 receptor. Treatment of primary bone marrow cultures with 2-AG stimulated proliferation and collagen accumulation, whereas treatment of subcultures of MSC had no effect, suggesting that the target cell is not the MSC but an accessory cell present in bone marrow. Subcultures of MSCs were negative for CB1 and CB2 receptors as shown by flow cytometry, whereas whole bone marrow contained a small population of cells positive for both receptors. These data suggest that cannabinoids may stimulate the recruitment of MSCs from the bone marrow indirectly via an accessory cell and mediated via the CB2 receptor. This recruitment may be one mechanism responsible for the increased bone formation seen after cannabinoid treatment in vivo.

Antiproliferative activity of Titanocene Y against tumor colony-forming units

Bis-[(p-methoxybenzyl)cyclopentadienyl] titanium dichloride, better known as Titanocene Y, is a newly synthesized titanium-based anticancer drug. We studied the antitumor activity of Titanocene Y with concentrations of 2.1, 21 and 210 μmol/l against a range of freshly explanted human tumors, using an in-vitro soft agar cloning system. The sensitivity against Titanocene Y was highly remarkable in the case of renal cell, ovarian, nonsmall cell lung and colon cancer. In particular the surprisingly good response of nonsmall cell lung cancer and colon cancer against Titanocene Y at its lowest concentration of 2.1 μmol/l was well comparable or better with respect to cisplatin, given at a concentration of 1.0 μmol/l. Further clinical development of Titanocene Y appears to be warranted because of the broad cytotoxic activity shown and the specific activity of Titanocene Y against renal cell cancer.

Confocal imaging of pseudomonas syringae pv. phaseolicola colony development in bean reveals reduced multiplication of strains containing the genomic island PPHGI-1.

Pseudomonas syringae pv. phaseolicola is the seed borne causative agent of halo blight in the common bean Phaseolus vulgaris. Pseudomonas syringae pv. phaseolicola race 4 strain 1302A contains the avirulence gene hopAR1 (located on a 106-kb genomic island, PPHGI-1, and earlier named avrPphB), which matches resistance gene R3 in P. vulgaris cultivar Tendergreen (TG) and causes a rapid hypersensitive reaction (HR). Here, we have fluorescently labeled selected Pseudomonas syringae pv. phaseolicola 1302A and 1448A strains (with and without PPHGI-1) to enable confocal imaging of in-planta colony formation within the apoplast of resistant (TG) and susceptible (Canadian Wonder [CW]) P. vulgaris leaves. Temporal quantification of fluorescent Pseudomonas syringae pv. phaseolicola colony development correlated with in-planta bacterial multiplication (measured as CFU/ml) and is, therefore, an effective means of monitoring Pseudomonas syringae pv. phaseolicola endophytic colonization and survival in P. vulgaris. We present advances in the application of confocal microscopy for in-planta visualization of Pseudomonas syringae pv. phaseolicola colony development in the leaf mesophyll to show how the HR defense response greatly affects colony morphology and bacterial survival. Unexpectedly, the presence of PPHGI-1 was found to cause a reduction of colony development in susceptible P. vulgaris CW leaf tissue. We discuss the evolutionary consequences that the acquisition and retention of PPHGI-1 brings to Pseudomonas syringae pv. phaseolicola in planta.

CAMCR: Computer-Assisted Mixture model analysis for Capture–Recapture count data

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.

Benchmarking and setting intervention targets for key cell count parameters

Herd Companion uses routine milk‐recording records to generate twelve‐month rolling averages that indicate performance trends. This article looks at Herd Somatic Cell Count (SCC) and four other SCC‐related parameters from 252 National Milk Records (NMR) recorded herds to assess how each parameter correlates with the Herd SCC. The analysis provides evidence for the importance of targeting individual cows with high SCC recordings (>200,000 cells/ml and >500,000 cells/ml) and/or individual cows with repeatedly high SCC recordings (chronic high SCC) and/or cows that begin lactation with a high SCC recording (dry period infection) in order to achieve bulk milk Herd SCC below 200,000 cells/ml.

Piezotolerant small-colony variants with increased thermotolerance, antibiotic susceptibility, and low invasiveness in a clonal Staphylococcus aureus population

Following a pressure treatment of a clonal Staphylococcus aureus culture with 400 MPa for 30 min, piezotolerant variants were isolated. Among 21 randomly selected survivors, 9 were piezotolerant and all formed small colonies on several agar media. The majority of the isolates showed increased thermotolerance, impaired growth, and reduced antibiotic resistance compared to the wild type. However, several nonpiezotolerant isolates also demonstrated impaired growth and the small-colony phenotype. In agglutination tests for the detection of protein A and fibrinogen, the piezotolerant variants showed weaker agglutination reactions than the wild type and the other isolates. All variants also showed defective production of the typical S. aureus golden color, a characteristic which has previously been linked with virulence. They were also less able to invade intestinal epithelial cells than the wild type. These S. aureus variants showed phenotypic similarities to previously isolated Listeria monocytogenes piezotolerant mutants that contained mutations in ctsR. Because of these similarities, possible alterations in the ctsR hypermutable regions of the S. aureus variants were investigated through amplified fragment length polymorphism analysis. No mutations were identified, and subsequently we sequenced the ctsR and hrcA genes of three representative variants, finding no mutations. This work demonstrates that S. aureus probably possesses a strategy resulting in an abundance of multiple-stressresistant variants within clonal populations. This strategy, however, seems to involve genes and regulatory mechanisms different from those previously reported for L. monocytogenes. We are in the process of identifying these mechanisms.