The aryl hydrocarbon receptor ligands 2,3,7,8-tetrachlorodibenzo-p-dioxin and 3-methylcholanthrene regulate distinct genetic networks

The two estrogen receptor isoforms ERα and ERβ mediate biological effects of estrogens, but are also targets for endocrine disruptive chemicals (EDCs), compounds that interfere with hormonal signaling. 3-Methylcholanthrene (3-MC) and dioxin (TCDD) are EDCs and prototypical aryl hydrocarbon receptor (AhR) agonists, and can inhibit ER signaling. However, in contrast to TCDD, 3-MC gives rise to metabolites with estrogenic properties. We compared gene expression profiles in HepG2 cells after exposure to 3-MC, TCDD, and the synthetic estrogen diethylstilbestrol (DES). Interestingly, we observed little overlap between the genetic networks activated by 3-MC and TCDD, two compounds sometimes considered as interchangeable AhR ligands. Like DES, 3-MC induced a number of ER-regulated genes and lead to recruitment of ERα to the promoters of such genes. Interestingly, in contrast to DES, the estrogenic effects exerted by 3-MC were exclusively observed in ERα, but not in ERβ-expressing cells, suggesting ER isoform selectivity of 3-MC-derived metabolites.     

Cerebrospinal fluid cathepsin B and S

Cathepsins are increased in the brain of elderly animals. We investigate the presence of cathepsin B and S in human cerebrospinal fluid (CSF) plasma and the associations with cystatin C, age and sex. We measured cathepsin B and S concentrations in CSFs from 118 persons, undergoing elective surgical procedures, with ELISA. Both cathepsin B and cathepsin S were positively correlated with age. No correlation was observed between cathepsin B or S and length, height or body mass index. Both cathepsin B and S were positively correlated to the cystatin C concentration in CSF. Calculated reference intervals were 4,893–17,636 pg/mL for cathepsin B and 2,681–11,459 pg/mL for cathepsin S. Elderly individuals had significantly higher levels of both cathepsin B (r _s = 0.38, p = 0.00002) and cathepsin S (r _s = 0.35, p = 0.0001) in CSF.     

Advanced Imaging Modalities in Early Stage Breast Cancer: Preoperative Use in the United States Medicare Population

Background

Guidelines for breast cancer staging exist, but adherence remains unknown. This study evaluates patterns of imaging in early stage breast cancer usually reserved for advanced disease.

Methods

Surveillance Epidemiology, and End Results data linked to Medicare claims from 1992–2005 were reviewed for stage I/II breast cancer patients. Claims were searched for preoperative performance of computed tomography (CT), positron emission tomography (PET), bone scans, and brain magnetic resonance imaging (MRI) (“advanced imaging”).

Results

There were 67,874 stage I/II breast cancer patients; 18.8 % (n = 12,740) had preoperative advanced imaging. The proportion of patients having CT scans, PET scans, and brain MRI increased from 5.7 % to 12.4 % (P < 0.0001), 0.8 % to 3.4 % (P < 0.0001) and 0.2 % to 1.1 % (P = 0.008), respectively, from 1992 to 2005. Bone scans declined from 20.1 % to 10.7 % (P < 0.0001). “Breast cancer” (174.x) was the only diagnosis code associated with 62.1 % of PET scans, 37.7 % of bone scans, 24.2 % of CT, and 5.1 % of brain MRI. One or more symptoms or metastatic site was suggested for 19.6 % of bone scans, 13.0 % of CT, 13.0 % of PET, and 6.2 % of brain MRI. Factors associated (P < 0.05) with use of all modalities were urban setting, breast MRI and ultrasound. Breast MRI was the strongest predictor (P < 0.0001) of bone scan (odds ratio [OR] 1.63, 95 % confidence interval [CI] 1.44–1.86), Brain MRI (OR 1.74, 95 % CI 1.15–2.63), CT (OR 2.42, 95 % CI 2.12–2.76), and PET (OR 5.71, 95 % CI 4.52–7.22).

Conclusions

Aside from bone scans, performance of advanced imaging is increasing in early stage Medicare breast cancer patients, with limited rationale provided by coded diagnoses. In light of existing guidelines and increasing scrutiny about health care costs, greater reinforcement of current indications is warranted.     

Considering pharmacy workflow in the context of Australian community pharmacy: A pilot time and motion study

Background

Given time pressures on primary care physicians, utilising pharmacists for chronic disease management is of great interest. However, limited data are available on the current workflow in community pharmacies to guide these discussions.

Use of a linearization approximation facilitating stochastic model building

The objective of this work was to facilitate the development of nonlinear mixed effects models by establishing a diagnostic method for evaluation of stochastic model components. The random effects investigated were between subject, between occasion and residual variability. The method was based on a first-order conditional estimates linear approximation and evaluated on three real datasets with previously developed population pharmacokinetic models. The results were assessed based on the agreement in difference in objective function value between a basic model and extended models for the standard nonlinear and linearized approach respectively. The linearization was found to accurately identify significant extensions of the model’s stochastic components with notably decreased runtimes as compared to the standard nonlinear analysis. The observed gain in runtimes varied between four to more than 50-fold and the largest gains were seen for models with originally long runtimes. This method may be especially useful as a screening tool to detect correlations between random effects since it substantially quickens the estimation of large variance–covariance blocks. To expedite the application of this diagnostic tool, the linearization procedure has been automated and implemented in the software package PsN.