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The radiolytic behaviors of aqueous ammonia solutions under γ-ray irradiation were investigated, focusing on several factors, including initial ammonia concentration, absorbed dose, and H3BO3 concentration. The main species including ammonia, H2O2, nitrogen oxides, and H2, were quantitatively analyzed. The results revealed the significant influence of the initial ammonia concentration on the radiolytic behavior of the aqueous ammonia solution. The existence of ammonia in the solution exhibited suppression of the concentrations of H2O2 and O2. Furthermore, the radiolysis of aerated aqueous ammonia solution led to the formation of nitrogen oxides (NO2− and NO3−). This process was driven by multiple oxidation reactions, in which O2 and ·OH played crucial roles. Interestingly, the addition of H3BO3 provided protection to ammonia during γ irradiation, while the concentration of H2O2 was increased. [ABSTRACT FROM AUTHOR]

In this work, the effects of the tungsten (W) converter and molybdenum target thickness on the 99Mo yield in the production of 99Mo via 100Mo(γ, n)99Mo photonuclear reaction were studied. The FLUKA program was applied to simulate the optimal size of the targets for the production of 99Mo under 50 MeV electron conditions, where the thicknesses of the W and Mo targets were 0.3 and 1.4 cm, respectively. The relative error between the calculation and the experimental results was less than 8%. The process of irradiating natural (natMo) and enriched (100Mo) molybdenum targets using electrons with a 1 mA average beam current was further simulated. The specific activity of enriched 100Mo is nearly ten times higher than that of natMo. The use of 100Mo targets also produces fewer radioactive impurities. This study provides a guidance on the size of W conversion and molybdenum targets, as well as the selection of molybdenum species, when producing 99Mo via photonuclear reaction. [ABSTRACT FROM AUTHOR]

A mathematical model of co-decontamination process (1A) containing U(VI), Pu(IV), Zr(IV), and Ru(III) was developed with a high-performance Iteration of Extraction Equilibrium (ITEE) algorithm. ITEE algorithm not only guarantees the positive solution set but also possesses better computational efficiency than L-BFGS-B and fsolve algorithms. This model was used to study the effects of the HNO3 concentration and the location of the feed stage on the extraction and decontamination efficiencies. The results show HNO3 is beneficial to the extraction of U, Pu, and Zr. More extraction stages boost the extraction of U and Pu into the organic phase. [ABSTRACT FROM AUTHOR]

Background: Many people infected with hepatitis C virus have comorbidities, including hypercholesterolemia, that are treated with statins. In this study, we evaluated the drug–drug interaction potential of the hepatitis C virus inhibitors elbasvir (EBR) and grazoprevir (GZR) with statins. Pitavastatin, rosuvastatin, pravastatin, and atorvastatin are substrates of organic anion-transporting polypeptide 1B, whereas rosuvastatin and atorvastatin are also breast cancer resistance protein substrates. Methods: Three open-label, phase I clinical trials in healthy adults were conducted with multiple daily doses of oral GZR or EBR/GZR and single oral doses of statins. Trial 1: GZR 200 mg plus pitavastatin 10 mg. Trial 2: Part 1, GZR 200 mg plus rosuvastatin 10 mg, then EBR 50 mg/GZR 200 mg plus rosuvastatin 10 mg; Part 2, EBR 50 mg/GZR 200 mg plus pravastatin 40 mg. Trial 3: EBR 50 mg/GZR 200 mg plus atorvastatin 10 mg. Results: Neither GZR nor EBR pharmacokinetics were meaningfully affected by statins. Coadministration of EBR/GZR did not result in clinically relevant changes in the exposure of pitavastatin or pravastatin. However, EBR/GZR increased exposure to rosuvastatin (126%) and atorvastatin (94%). Coadministration of statins plus GZR or EBR/GZR was generally well tolerated. Conclusions: Although statins do not appreciably affect EBR or GZR pharmacokinetics, EBR/GZR can impact the pharmacokinetics of certain statins, likely via inhibition of breast cancer resistance protein but not organic anion-transporting polypeptide 1B. Coadministration of EBR/GZR with pitavastatin or pravastatin does not require adjustment of either dose of statin, whereas the dose of rosuvastatin and atorvastatin should be decreased when coadministered with EBR/GZR. [ABSTRACT FROM AUTHOR]

Purpose: To describe the phase 1 and population pharmacokinetic investigations that support dosing recommendations for elbasvir/grazoprevir (EBR/GZR) in hepatitis C virus-infected people with advanced chronic kidney disease. Methods: This was an open-label, two-part, multiple-dose trial (MK-5172 PN050; NCT01937975) in 24 non–HCV-infected participants with end-stage renal disease (ESRD) or severe renal impairment who received once-daily EBR 50 mg and GZR 100 mg for 10 days. Population pharmacokinetic analyses from the phase 3 C-SURFER study (PN052, NCT02092350) were also conducted. Results: When comparing haemodialysis (HD) and non-HD days in participants with ESRD, geometric mean ratios (GMRs) (90% confidence intervals [CIs]) for EBR and GZR AUC0–24 were 1.14 (1.08–1.21) and 0.97 (0.87–1.09). When comparing ESRD and healthy participants, GMRs (90% CIs) for EBR and GZR AUC0–24 were 0.99 (0.75–1.30) and 0.83 (0.56–1.22) on HD days, and 0.86 (0.65–1.14) and 0.85 (0.58–1.25) on non-HD days. GMRs (90% CIs) for AUC0–24 in participants with severe renal impairment relative to healthy controls were 1.65 (1.09–2.49) for GZR and 1.86 (1.38–2.51) for EBR. In population modelling of data from C-SURFER, absolute geometric means of steady-state EBR AUC0–24 were 2.78 and 3.07 μM*h (HD and non-HD recipients) and GZR AUC0–24 were 1.80 and 2.34 μM*h (HD and non-HD recipients). Conclusions: EBR/GZR represents an important treatment option for HCV infection in people with severe renal impairment and those with ESRD. No dosage adjustment of EBR/GZR is required in people with any degree of renal impairment, including those receiving dialysis. [ABSTRACT FROM AUTHOR]

Purpose: Oral contraceptive pills (OCPs) are an important element of hepatitis C virus (HCV) treatment in women of childbearing potential. These studies evaluated the safety and pharmacokinetic interactions between elbasvir (EBR) and grazoprevir (GZR) and ethinyl estradiol/levonorgestrel (EE/LNG). Methods: Both studies were open-label, single-site, two-period, fixed-sequence, one-way interaction studies. In period 1, subjects received one tablet of EE/LNG (0.03 mg/0.15 mg). In period 2, subjects received EBR (50 mg once daily) for 13 days or GZR (200 mg once daily) for 10 days, with one tablet of EE/LNG on day 7 (GZR group) or 10 (EBR group). Each study enrolled 20 healthy, nonsmoking adult females. Results: There was no clinically meaningful effect of multiple doses of EBR or GZR on the pharmacokinetics of EE or LNG. Geometric mean ratios (GMRs) for AUC and C in the presence and absence of EBR were 1.01 and 1.10 for EE and 1.14 and 1.02 for LNG, with 90% confidence intervals (CIs) that were contained in the interval [0.80, 1.25]. Similarly, the AUC and C GMRs in the presence and absence of GZR were 1.10 and 1.05 for EE and 1.23 and 0.93 for LNG, respectively. The 90% CIs for EE AUC and for EE and LNG C were contained in the interval [0.80, 1.25]; however, the 90% CI for the LNG AUC [1.15, 1.32] slightly exceeded the upper bound. Conclusions: These results suggest that EBR/GZR can be co-administered to female patients with HCV of childbearing potential who are on OCPs to prevent pregnancy. [ABSTRACT FROM AUTHOR]

Despite enormous development on variable selection approaches in recent years, modeling and selection of high dimensional censored regression remains a challenging question. When the number of predictors $$p$$ far exceeds the number of observational units $$n$$ and the outcome is censored, computations of existing solutions often become difficult, or even infeasible in some situations, while performances frequently deteriorate. In this article, we aim at simultaneous model estimation and variable selection for Cox proportional hazards models with high dimensional covariates. We propose a forward stagewise shrinkage and addition approach for that purpose. Our proposal extends a popular statistical learning technique, the boosting method. It inherits the flexible nature of boosting and is straightforward to extend to nonlinear Cox models. Meanwhile, it advances the classical boosting method by adding explicit variable selection and substantially reducing the number of iterations to the algorithm convergence. Our intensive simulations have showed that the new method enjoys a competitive performance in Cox models with both $$p < n$$ and $$p \ge n$$ scenarios. The new method was also illustrated with analysis of two real microarray survival datasets. [ABSTRACT FROM AUTHOR]