While the field of polymer mechanochemistry has traditionally focused on the use of mechanical forces to accelerate chemical processes, theoretical considerations predict an underexplored alternative: the suppression of reactivity through mechanical perturbation. Here, we use electronic structure calculations to analyze the mechanical reactivity of six mechanophores, or chemical functionalities that respond to mechanical stress in a controlled manner. Our computational results indicate that appropriately directed tensile forces could attenuate (as opposed to facilitate) mechanochemical phenomena. Accompanying experimental studies supported the theoretical predictions and demonstrated that relatively simple computational models may be used to design new classes of mechanically responsive materials. In addition, our computational studies and theoretical considerations revealed the prevalence of the anti-Hammond (as opposed to Hammond) effect (i.e., the increased structural dissimilarity between the reactant and transition state upon lowering of the reaction barrier) in the mechanical activation of polyatomic molecules.

Short-acting injectable testosterone is associated with greater risk of erythrocytosis compared with other formulations. The mechanism of the pathophysiology and its role on thromboembolic events remain unclear, although some data support an increased risk of cardiovascular events resulting from testosterone-induced erythrocytosis. Ohlander SJ, Varghese B, Pastuszak AW. Erythrocytosis Following Testosterone Therapy. Sex Med Rev 2018;6:77-85.

IMPORTANCE Low-density lipoprotein cholesterol (LDL-C) is typically estimated with the Friedewald or Martin/Hopkins equation; however, if triglyceride levels are 400 mg/dL or greater, laboratories reflexively perform direct LDL-C (dLDL-C) measurement. The use of direct chemical LDL-C assays and estimation of LDL-C via the National Institutes of Health Sampson equation are not well validated, and data on the accuracy of LDL-C estimation at higher triglyceride levels are limited. OBJECTIVE To compare an extended Martin/Hopkins equation for triglyceride values of 400 to 799 mg/dL with the Friedewald and Sampson equations. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study evaluated consecutive patients at clinical sites across the US with patient lipid distributions representative of the US population in

BACKGROUNDRadiation exposure increases the risk of coronary artery disease (CAD). We explored the association of CAD with coronary artery dose-volume parameters in patients treated with 3D-planned radiation therapy (RT).METHODSPatients who received thoracic RT and were evaluated by cardiac computed tomography ≥ 1 year later were included. Demographic data and cardiac risk factors were retrospectively collected. Dosimetric data (mean heart dose, dmax, dmean, V50 - V5) were collected for the whole heart and for each coronary artery. A coronary artery calcium (CAC) Agatston score was calculated on a per-coronary basis and as a total score. Multivariable generalized linear mixed models were generated. The predicted probabilities were used for receiver operating characteristic analyses.RESULTSTwenty patients with a median age of 53 years at the time of RT were included. Nine patients (45%) had ≥ 3/6 conventional cardiac risk factors. Patients received RT for breast cancer (10, 50%), lung cancer (6, 30%), or lymphoma/myeloma (4, 20%) with a median dose of 60 Gy. CAC scans were performed a median of 32 months after RT. CAC score was significantly associated with radiation dose and presence of diabetes. In a multivariable model adjusted for diabetes, segmental coronary artery dosimetric parameters (dmax, dmean, V50, V40 V30, V20, V10, and V5) were significantly associated with CAC score > 0. V50 had the highest area under the ROC curve (0.89, 95% confidence interval, 0.80-0.97).CONCLUSIONSCoronary artery radiation exposure is strongly correlated with subsequent segmental CAC score. Coronary calcification may occur soon after RT and in individuals with conventional cardiac risk factors.