Mammographic Density Change With Estrogen and Progestin Therapy and Breast Cancer Risk

Background: Estrogen plus progestin therapy increases both mammographic density and breast cancer incidence. Whether mammographic density change associated with estrogen plus progestin initiation predicts breast cancer risk is unknown. Methods: We conducted an ancillary nested case-control study within the Women's Health Initiative trial that randomly assigned postmenopausal women to daily conjugated equine estrogen 0.625 mg plus medroxyprogesterone acetate 2.5 mg or placebo. Mammographic density was assessed from mammograms taken prior to and one year after random assignment for 174 women who later developed breast cancer (cases) and 733 healthy women (controls). Logistic regression analyses included adjustment for confounders and baseline mammographic density when appropriate. Results: Among women in the estrogen plus progestin arm (97 cases/378 controls), each 1% positive change in percent mammographic density increased breast cancer risk 3% (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.01 to 1.06). For women in the highest quintile of mammographic density change (>19.3% increase), breast cancer risk increased 3.6-fold (95% CI = 1.52 to 8.56). The effect of estrogen plus progestin use on breast cancer risk (OR = 1.28, 95% CI = 0.90 to 1.82) was eliminated in this study, after adjusting for change in mammographic density (OR = 1.00, 95% CI = 0.66 to 1.51). Conclusions: We found the one-year change in mammographic density after estrogen plus progestin initiation predicted subsequent increase in breast cancer risk. All of the increased risk from estrogen plus progestin use was mediated through mammographic density change. Doctors should evaluate changes in mammographic density with women who initiate estrogen plus progestin therapy and discuss the breast cancer risk implications

Immigration and Internal Migration 'Flight' from US Metropolitan Areas: Toward a New Demographic Balkanisation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68704/2/10.1080_00420989550012861.pd

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

Long-acting β2-adrenoceptor agonists enhance glucocorticoid receptor (GR)-mediated transcription by gene-specific mechanisms rather than generic effects via GR

In asthma, the clinical efficacy of inhaled corticosteroids (ICSs) is enhanced by long-acting β2-adrenoceptor agonists (LABAs). ICSs, or more accurately, glucocorticoids, promote therapeutically relevant changes in gene expression, and, in primary human bronchial epithelial cells (pHBECs) and airway smooth muscle cells, this genomic effect can be enhanced by a LABA. Modeling this interaction in human bronchial airway epithelial BEAS-2B cells transfected with a 2× glucocorticoid response element (2×GRE)-driven luciferase reporter showed glucocorticoid-induced transcription to be enhanced 2- to 3-fold by LABA. This glucocorticoid receptor (GR; NR3C1)-dependent effect occurred rapidly, was insensitive to protein synthesis inhibition, and was maximal when glucocorticoid and LABA were added concurrently. The ability of LABA to enhance GR-mediated transcription was not associated with changes in GR expression, serine (Ser203, Ser211, Ser226) phosphorylation, ligand affinity, or nuclear translocation. Chromatin immunoprecipitation demonstrated that glucocorticoid-induced recruitment of GR to the integrated 2×GRE reporter and multiple gene loci, whose mRNAs were unaffected or enhanced by LABA, was also unchanged by LABA. Transcriptomic analysis revealed glucocorticoid-induced mRNAs were variably enhanced, unaffected, or repressed by LABA. Thus, events leading to GR binding at target genes are not the primary explanation for how LABAs modulate GR-mediated transcription. As many glucocorticoid-induced genes are independently induced by LABA, gene-specific control by GR- and LABA-activated transcription factors may explain these observations. Because LABAs promote similar effects in pHBECs, therapeutic relevance is likely. These data illustrate the need to understand gene function(s), and the mechanisms leading to gene-specific induction, if existing ICS/LABA combination therapies are to be improved.FWN – Publicaties zonder aanstelling Universiteit Leide