Safety, tolerability, pharmacokinetic, pharmacodynamic and immunogenicity profiles of Exendin-4-IgG4-Fc in healthy subjects: A phase 1, single-centre, randomized, double-blind, dose escalation study.

AIM: Novel long-acting drugs for type 2 diabetes mellitus may optimize patient compliance and glycaemic control. Exendin-4-IgG4-Fc (E4F4) is a long-acting glucagon-like peptide-1 receptor agonist. This first-in-human study investigated the safety, tolerability, pharmacokinetic, pharmacodynamic and immunogenicity profiles of a single subcutaneous injection of E4F4 in healthy subjects. METHODS: This single-centre, randomized, double-blind, placebo-controlled phase 1 clinical trial included 96 subjects in 10 sequential cohorts that were provided successively higher doses of E4F4 (0.45, 0.9, 1.8, 3.15, 4.5, 6.3, 8.1, 10.35, 12.6 and 14.85 mg) or placebo (ChinaDrugTrials.org.cn: ChiCTR2100049732). The primary endpoint was safety and tolerability of E4F4. Secondary endpoints were pharmacokinetic, pharmacodynamic and immunogenicity profiles of E4F4. Safety data to day 15 after the final subject in a cohort had been dosed were reviewed before commencing the next dose level. RESULTS: E4F4 was safe and well tolerated among healthy Chinese participants in this study. There was no obvious dose-dependent relationship between frequency, severity or causality of treatment-emergent adverse events. Cmax and area under the curve of E4F4 were dose proportional over the 0.45-14.85 mg dose range. Median Tmax and t1/2 ranged from 146 to 210 h and 199 to 252 h, respectively, across E4F4 doses, with no dose-dependent trends. For the intravenous glucose tolerance test, area under the curve of glucose in plasma from time 0 to 180 min showed a dose-response relationship in the 1.8-10.35 mg dose range, with an increased response at the higher doses. CONCLUSION: E4F4 exhibited an acceptable safety profile and linear pharmacokinetics in healthy subjects. The recommended phase 2 dose is 4.5-10.35 mg once every 2 weeks.

Development and validation of a fully automatic tissue delineation model for brain metastasis using a deep neural network.

Background: Stereotactic radiosurgery (SRS) treatment planning requires accurate delineation of brain metastases, a task that can be tedious and time-consuming. Although studies have explored the use of convolutional neural networks (CNNs) in magnetic resonance imaging (MRI) for automatic brain metastases delineation, none of these studies have performed clinical evaluation, raising concerns about clinical applicability. This study aimed to develop an artificial intelligence (AI) tool for the automatic delineation of single brain metastasis that could be integrated into clinical practice. Methods: Data from 426 patients with postcontrast T1-weighted MRIs who underwent SRS between March 2007 and August 2019 were retrospectively collected and divided into training, validation, and testing cohorts of 299, 42, and 85 patients, respectively. Two Gamma Knife (GK) surgeons contoured the brain metastases as the ground truth. A novel 2.5D CNN network was developed for single brain metastasis delineation. The mean Dice similarity coefficient (DSC) and average surface distance (ASD) were used to assess the performance of this method. Results: The mean DSC and ASD values were 88.34%±5.00% and 0.35±0.21 mm, respectively, for the contours generated with the AI tool based on the testing set. The DSC measure of the AI tool's performance was dependent on metastatic shape, reinforcement shape, and the existence of peritumoral edema (all P values <0.05). The clinical experts' subjective assessments showed that 415 out of 572 slices (72.6%) in the testing cohort were acceptable for clinical usage without revision. The average time spent editing an AI-generated contour compared with time spent with manual contouring was 74 vs. 196 seconds, respectively (P<0.01). Conclusions: The contours delineated with the AI tool for single brain metastasis were in close agreement with the ground truth. The developed AI tool can effectively reduce contouring time and aid in GK treatment planning of single brain metastasis in clinical practice.

Identification of priority pollutants and key factors affecting environmental risks of lead­zinc mine tailing sites.

Lead­zinc mine tailing sites are widely distributed in China. Tailing sites with different hydrological settings tend to have different susceptibilities toward pollution and hence different priority pollutants and environmental risks. This paper aims to identify priority pollutants and key factors influencing environmental risks of lead­zinc mine tailing sites with different types of hydrological settings. A database with detailed information on hydrological settings, pollution, etc. of 24 typical lead­zinc mine tailing sites in China was built. A rapid classification method of hydrological settings was proposed considering the groundwater recharge and migration of pollutants in the aquifer. Priority pollutants in leach liquor of tailings, soil, and groundwater of sites were identified using the osculating value method. The key factors affecting environmental risks of lead­zinc mine tailing sites were identified using the random forest algorithm. Four types of hydrological settings were classified. Pb/Zn/As/Cd/Sb, Fe/Pb/As/Co/Cd, and nitrate/iodide/As/Pb/Cd are identified as priority pollutants of leach liquor, soil, and groundwater, respectively. The lithology of the surface soil media, slope, and groundwater depth were identified as the top 3 key factors that affect the environmental risks of sites. Priority pollutants and key factors identified in this study can provide benchmarks for the risk management of lead­zinc mine tailing sites.

Soil heavy metal pollution of industrial legacies in China and health risk assessment.

Rapid urbanization in China has brought about large-scale factory relocation. Severe environmental ecological and human health risks are caused by a large number of contaminated legacies left in the city. To comprehensively review the pollution and assess the health risk of industrial legacies in China, a total of 625 polluted industrial legacies were compiled by document retrieval. Legacies are mainly located in the southwest of China, the North China Plain, Yangtze River Basin, Yangtze River Delta, and Pearl River Delta with a mean operation time of 35 years, and legacies of chemical manufacturing take the biggest proportion of all sites. Health risk assessments considering the uncertainty of exposure and toxic factors reveal that the soil heavy metal pollution in China is serious, with Pb, Cd, Zn, Ni, and As as dominant pollutants. Legacies of chemical manufacturing, ferrous metal processing, non-ferrous metal processing, and mines should be priority controlled for their large number and serious risks. Children are the most vulnerable people with more serious non-carcinogenic and carcinogenic risks, while males are slightly surpassed by females. Insights for better risk management of legacies are provided based on the comprehensive assessment of pollution and human health risk in this study.