Effects of tamoxifen on normal breast tissue histological composition: Results from a randomised six-arm placebo-controlled trial in healthy women

Tamoxifen prevents recurrence of breast cancer and is suggested for preventive risk-reducing therapy. Tamoxifen reduces mammographic density, a proxy for therapy response, but little is known about its effects in remodelling normal breast tissue. Our study, a substudy within the double-blinded dose-determination trial KARISMA, investigated tamoxifen-specific changes in breast tissue composition and histological markers in healthy women. We included 83 healthy women randomised to 6 months daily intake of 20, 10, 5, 2.5, 1 mg of tamoxifen or placebo. The groups were combined to “no dose” (0-1 mg), “low-dose” (2.5-5 mg) or “high-dose” (10-20 mg) of tamoxifen. Ultrasound-guided biopsies were collected before and after tamoxifen exposure. In each biopsy, epithelial, stromal and adipose tissues was quantified, and expression of epithelial and stromal Ki67, oestrogen receptor (ER) and progesterone receptor (PR) analysed. Mammographic density using STRATUS was measured at baseline and end-of-tamoxifen-exposure. We found that different doses of tamoxifen reduced mammographic density and glandular-epithelial area in premenopausal women and associated with reduced epithelium and increased adipose tissue. High-dose tamoxifen also decreased epithelial ER and PR expressions in premenopausal women. Premenopausal women with the greatest reduction in proliferation also had the greatest epithelial reduction. In postmenopausal women, high-dose tamoxifen decreased the epithelial area with no measurable density decrease. Tamoxifen at both low and high doses influences breast tissue composition and expression of histological markers in the normal breast. Our findings connect epithelial proliferation with tissue remodelling in premenopausal women and provide novel insights to understanding biological mechanisms of primary prevention with tamoxifen.     

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

Fragmentation of care as a barrier to optimal ESKD management

Caring for patients with end-stage kidney disease (ESKD) in the United States is challenging, due in part to the complex epidemiology of the disease's progression as well as the ways in which care is delivered. As CKD progresses toward ESKD, the number of comorbidities increases and care involves multiple healthcare providers from multiple subspecialties. This occurs in the context of a fragmented US healthcare delivery system that is traditionally siloed by provider specialty, organization, as well as systems of payment and administration. This article describes the role of care fragmentation in the delivery of optimal ESKD care and identifies research gaps in the evidence across the continuum of care. We then consider the impact of care fragmentation on ESKD care from the patient and health system perspectives and explore opportunities for system-level interventions aimed at improving care for patients with ESKD.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.