Telomere length dynamics in human lymphocyte subpopulations measured by flow cytometry.

To measure the average length of telomere repeats at chromosome ends in individual cells we developed a flow cytometry method using fluorescence in situ hybridization (flow FISH) with labeled peptide nucleic acid (PNA) probes. Results of flow FISH measurements correlated with results of conventional telomere length measurements by Southern blot analysis (R = 0.9). Consistent differences in telomere length in CD8+ T-cell subsets were identified. Naive and memory CD4+ T lymphocytes in normal adults differed by around 2.5 kb in telomere length, in agreement with known replicative shortening of telomeres in lymphocytes in vivo. T-cell clones grown in vitro showed stabilization of telomere length after an initial decline and rare clones capable of growing beyond 100 population doublings showed variable telomere length. These results show that flow FISH can be used to measure specific nucleotide repeat sequences in single cells and indicate that the very large replicative potential of lymphocytes is only indirectly related to telomere length.

Market rewards to patterns on increasing earnings: do cash flow patterns, accruals manipulation and real activities manipulation matter?

This study explores whether firms have differential price-earnings multiples associated with their means of achieving a sequential pattern of increasing positive earnings. Our main findings show that market participants assign higher price-earnings multiples to firms when their pattern of increasing earnings is supported by the same pattern of increasing cash flows. Market participants assign lower price-earnings multiples to firms suspect of having engaged in accrual-based earnings management, sales manipulation, and overproduction to achieve the earnings pattern. We find, however, that market participants do not penalize firms suspect of having achieved the earnings pattern through the opportunistic reduction of discretionary expenses.

Chromosomal rearrangements do not seem to affect the gene flow in hybrid zones between karyotypic races of the common shrew (Sorex araneus).

Chromosomal rearrangements are proposed to promote genetic differentiation between chromosomally differentiated taxa and therefore promote speciation. Due to their remarkable karyotypic polymorphism, the shrews of the Sorex araneus group were used to investigate the impact of chromosomal rearrangements on gene flow. Five intraspecific chromosomal hybrid zones characterized by different levels of karyotypic complexity were studied using 16 microsatellites markers. We observed low levels of genetic differentiation even in the hybrid zones with the highest karyotypic complexity. No evidence of restricted gene flow between differently rearranged chromosomes was observed. Contrary to what was observed at the interspecific level, the effect of chromosomal rearrangements on gene flow was undetectable within the S. araneus species.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.