Differential stimulation of monocytic cells results in distinct populations of microparticles.

BACKGROUND: Microparticles (MPs), small vesicles shed from stimulated cells, permit cross-talk between cells within a particular environment. Their composition is thought to reflect their cell of origin, and differs according to whether they are produced by stimulation or by apoptosis. Whether MP properties vary according to stimulus is not yet known. METHODS: We studied the characteristics of MPs produced from monocytic THP-1 cells upon stimulation with lipopolysaccharide or a soluble P-selectin chimera, using proteomics, flow cytometry, western blotting, and electron microscopy. RESULTS: Utilizing a novel criterion of calcein-AM staining to define MPs, we found that MP populations were similar with respect to size, presence and organization of cytoskeleton, and expression of certain antigens. The MPs shared the same level of procoagulant activity. We found that MPs also have distinct characteristics, depending on stimuli. These include differences in phosphatidylserine expression and expression of proteins from specific subcellular locations such as the mitochondria, and of unique antigens such as leukocyte-associated immunoglobin-like-receptor (LAIR)-1, which was found only upon stimulation with the soluble P-selectin chimera. CONCLUSION: We found that the properties of MPs depend on the stimulus that produced them. This supports the concept that monocytic MPs differentially modulate thrombosis, inflammation and immune regulation according to stimulus.

Usefulness of molecular markers for detecting population bottlenecks via monitoring genetic change.

It is important to detect population bottlenecks in threatened and managed species because bottlenecks can increase the risk of population extinction. Early detection is critical and can be facilitated by statistically powerful monitoring programs for detecting bottleneck-induced genetic change. We used Monte Carlo computer simulations to evaluate the power of the following tests for detecting genetic changes caused by a severe reduction in a population's effective size (Ne): a test for loss of heterozygosity, two tests for loss of alleles, two tests for change in the distribution of allele frequencies, and a test for small Ne based on variance in allele frequencies (the 'variance test'). The variance test was most powerful; it provided an 85% probability of detecting a bottleneck of size Ne = 10 when monitoring five microsatellite loci and sampling 30 individuals both before and one generation after the bottleneck. The variance test was almost 10-times more powerful than a commonly used test for loss of heterozygosity, and it allowed for detection of bottlenecks before 5% of a population's heterozygosity had been lost. The second most powerful tests were generally the tests for loss of alleles. However, these tests had reduced power for detecting genetic bottlenecks caused by skewed sex ratios. We provide guidelines for the number of loci and individuals needed to achieve high-power tests when monitoring via the variance test. We also illustrate how the variance test performs when monitoring loci that have widely different allele frequency distributions as observed in five wild populations of mountain sheep (Ovis canadensis).

A modified EM algorithm for estimation in generalized mixed models.

Application of the EM algorithm for estimation in the generalized mixed model has been largely unsuccessful because the E-step cannot be determined in most instances. The E-step computes the conditional expectation of the complete data log-likelihood and when the random effect distribution is normal, this expectation remains an intractable integral. The problem can be approached by numerical or analytic approximations; however, the computational burden imposed by numerical integration methods and the absence of an accurate analytic approximation have limited the use of the EM algorithm. In this paper, Laplace's method is adapted for analytic approximation within the E-step. The proposed algorithm is computationally straightforward and retains much of the conceptual simplicity of the conventional EM algorithm, although the usual convergence properties are not guaranteed. The proposed algorithm accommodates multiple random factors and random effect distributions besides the normal, e.g., the log-gamma distribution. Parameter estimates obtained for several data sets and through simulation show that this modified EM algorithm compares favorably with other generalized mixed model methods.

Perinatal cocaine effects on neonatal stress behavior and performance on the Brazelton Scale.

Fifty-two newborns were assessed for the effects of maternal cocaine use on their performance on the Brazelton Neonatal Behavior Assessment Scale and on their stress behaviors during the Brazelton as tapped by the Neonatal Stress Scale. The cocaine-exposed newborns experienced more obstetric complications, had smaller head circumferences, showed more limited habituation abilities on the Brazelton Scale, and exhibited more stress behaviors than control newborns.