Assessment of the targeting specificity of a fluorescent albumin conceived as a preclinical agent of the liver function

International audienceIn the context of increasing liver diseases, no contrast agent is currently available in Europe and the United States to directly assess the liver function. Only neolactosylated human serum albumin is being clinically used in Asia. In order to perform preclinical studies in the context of liver diseases, we conceived a fluorescent lactosylated albumin for the quantification of liver functional cells (l-Cyal). Precise characterization was achieved in order to determine the amounts of lactose and Cyanine 5 (Cy5) coupled to the albumin. In addition, potential aggregation was characterized by asymmetrical flow field-flow fractionation hyphenated to multi-angle light scattering (AF4-MALS). The optimal functionalized albumin exhibited a mass greater than 87 kDa which corresponds to the addition of 34 lactose moieties per protein and 1-2 Cy5 labels. Also, no significant formation of aggregates could be identified due to the modification of the native albumin. In healthy mice, the accumulation of l-Cyal in the liver and its selectivity for hepatocyte cells were shown by optical imaging and flow cytometry. Administration of l-Cyal to mice bearing liver metastases showed a reduced signal in the liver related to a decrease in the number of hepatocytes. The l-Cyal bioimaging contrast agent could be particularly useful for assessing the state of liver related diseases

Testing for a finite mixture model with two components

We consider a finite mixture model with "k" components and a kernel distribution from a general one-parameter family. The problem of testing the hypothesis "k"=2 "versus""k"⩾3 is studied. There has been no general statistical testing procedure for this problem. We propose a modified likelihood ratio statistic where under the null and the alternative hypotheses the estimates of the parameters are obtained from a modified likelihood function. It is shown that estimators of the support points are consistent. The asymptotic null distribution of the modified likelihood ratio test proposed is derived and found to be relatively simple and easily applied. Simulation studies for the asymptotic modified likelihood ratio test based on finite mixture models with normal, binomial and Poisson kernels suggest that the test proposed performs well. Simulation studies are also conducted for a bootstrap method with normal kernels. An example involving foetal movement data from a medical study illustrates the testing procedure. Copyright 2004 Royal Statistical Society.

On finite mixture models

Finite mixture models are widely used in scientific investigations. Due to their non-regularity, there are many technical challenges concerning inference problems on various aspects of the finite mixture models. After decades of effort by statisticians, substantial progresses are recorded recently in characterising large sample properties of some classical inference methods when applied to finite mixture models, providing effective numerical solutions for mixture model-based data analysis, and the invention of novel inference approaches. This paper aims to provide a comprehensive summary on large sample properties of some classical statistical methods and recently developed modified likelihood ratio test and EM-test for the order of the finite mixture model. The presentation de-emphasises the rigour in order to gain some insights behind some complex technical issues. The paper wishes to recommend the EM-test as the most promising approach to data analysis problems from all models with mixture structures

Asymptotic properties of conditional quantile estimator for censored dependent observations

Strong uniform convergence, Asymptotic normality, Censored data, α-mixing sequence, Conditional quantile estimator,