Dupilumab Improves Nasal Polyp Burden and Asthma Control in Patients With CRSwNP and AERD

In the difficult-to-treat subgroup of patients with chronic rhinosinusitis with nasal polyps (CRSwNP) and comorbid aspirin-exacerbated respiratory disease, dupilumab significantly improved CRSwNP disease outcomes, along with asthma control and lung function. This is preliminary evidence of the effect of dupilumab in patients with CRSwNP and comorbid aspirin- exacerbated respiratory disease

Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space

Automatic segmentation of 3D tooth models into individual teeth is an important step in orthodontic CAD systems. 3D tooth segmentation is a mesh instance segmentation task. Complex geometric features on the surface of 3D tooth models often lead to failure of tooth boundary detection, so it is difficult to achieve automatic and accurate segmentation by traditional mesh segmentation methods. We propose a novel solution to address this problem. We map a 3D tooth model isomorphically to a 2D harmonic parameter space and convert it into an image. This allows us to use a CNN to learn a highly robust image segmentation model to achieve automated and accurate segmentation of 3D tooth models. Finally, we map the image segmentation mask back to the 3D tooth model and refine the segmentation result using an improved Fuzzy Clustering-and-Cuts algorithm. Our method has been incorporated into an orthodontic CAD system, and performs well in practice

Methods for Missing Data Handling in Randomized Clinical Trials With Nonnormal Endpoints With Application to a Phase III Clinical Trial

<p>In randomized clinical trials, when the endpoint is the change from baseline at the last scheduled visit, various parametric, semiparametric, and nonparametric methods have been developed to handle the possible missing data due to dropouts. Although the last observation carried forward (LOCF) and the mixed-effects model for repeated measures (MMRM) have been extensively compared and widely used, they may lead to biased results when the required distributional or missing mechanism assumptions are not satisfied. Nonparametric missing data handling methods including the last rank carried forward (LRCF) and mean rank imputation (MRI) relax the underlying distributional assumptions; however, conditions for them to be valid have been investigated to a very limited extent. This article rigorously derives asymptotic properties of the MRI method and proves its validity to test the primary endpoint under certain mild distributional and missing mechanism assumptions. The test-based estimator for the location difference between the treatment and the control groups is also derived when the randomized clinical trial has two arms under a location shift assumption. The investigated methods are applied to an illustrative phase III clinical trial. Simulation studies based on the empirical distributions from the illustrative clinical trial and additional intensive simulation studies, based on various prespecified distributions and missing mechanisms, were conducted to compare the MRI method with selected traditional methods including LOCF, MMRM, and LRCF and they confirmed the better performance of the MRI method in terms of the Type I error rate control and the power under certain mild conditions.</p

Melatonin treatment maintains the quality and delays senescence of postharvest cattails (Typha latifolia L.) during cold storage

Melatonin treatment was investigated for the sensory quality and senescence in postharvest cattails (Typha latifolia L.) during cold storage. The 0.75 mM melatonin treatment reduced surface browning and delaying lignification of Cattails stored at 4 °C. The results showed that melatonin treatment slowed weight loss and firmness, maintained sensory quality and reducing sugar content. Melatonin treatment reduced browning by inhibiting the increase of MDA and H2O2 contents and POD activity. Melatonin treatment maintained high non-enzymatic antioxidant components (Vitamin C and total phenolic content) and antioxidant enzyme activities (SOD, CAT, and APX), thereby alleviating the browning and senescence of postharvest cattails. These findings indicate that melatonin treatment can maintain postharvest cattails quality

Quantifying delta channel network changes with Landsat time-series data

Delta channel networks (DCNs) are highly complex and dynamic systems that are governed by natural and anthropogenic perturbations. Challenges remain in quickly quantifying the length, width, migration, and pattern changes of deltaic channels accurately and with a high frequency. Here, we develop a quantitative framework, which introduces a water occurrence algorithm based on Landsat time-series data and spatial morphological delineation methods, in order to measure DCN structures and associated changes. In examining the Pearl River Delta (PRD) and Irrawaddy River Delta (IRD) as case studies, we analyze their conditions and trends between 1986–2018 at ten-year intervals. Both study areas have undergone various human interventions, including dam construction, sand mining, and land use change driven by urbanization. Our results show the following: (1) the use of a 0.5 water occurrence extraction based on Landsat time-series data, morphological delineation, and spatial change analysis methods can quantify the morphodynamics of DCNs effectively with a root-mean-square error of 15.1 m; (2) there was no evident channel migration in either PRD or IRD with average channel widths of 387.6 and 300.9 m, respectively. Most channels in the PRD underwent remarkable shrinkage, with average rates of 0.4–6.4 m/year, while there were only slight changes in the IRD, which is consistent with observed trends in sediment load variation. The results of this research have the potential to contribute to sustainable river management in terms of flood prevention, riparian tideland reclamation, and water and sediment regulation. Moreover, the proposed framework can be used to develop a new global river width dataset and can be generalized to remotely sensed water discharge and river depth estimation