© 2020 Society of Chemical Industry. © 2020 Society of Chemical Industry.Prognosis after severe brain injury is highly uncertain, and decisions to withhold or withdraw life-sustaining treatment are often made prematurely. These decisions are often driven by a desire to avoid a situation where the patient becomes 'trapped' in a condition they would find unacceptable. Orforglipron molecular weight However, this means that a proportion of patients who would have gone on to make a good recovery, are allowed to die. I propose a shift in practice towards the routine provision of aggressive care, even in cases where the probability of survival and acceptable recovery is thought to be low. In conjunction with this shift, I argue in favour of a presumption towards withdrawing life-sustaining treatment, including artificial nutrition and hydration, when it becomes clear that a patient will not recover to a level that would be acceptable to them. I then respond to three potential objections to this proposal. © 2020 The Authors. Bioethics published by John Wiley & Sons Ltd.BACKGROUND As the primary food for nearly half of the world's population, rice is cultivated almost all over the world, especially in Asian countries. However, the farmers and planting experts have been facing many persistent agricultural challenges for centuries, such as different diseases of rice. The severe rice diseases may lead to no harvest of grains; therefore, a fast, automatic, less expensive and accurate method to detect rice diseases is highly desired in the field of agricultural information. RESULTS In this article, we study the deep learning approach for solving the task since it has shown outstanding performance in image processing and classification problem. Combining the advantages of both, the DenseNet pre-trained on ImageNet and Inception module were selected to be used in the network, and this approach presents a superior performance with respect to other state-of-the-art methods. It achieves an average predicting accuracy of no less than 94.07% in the public dataset. Even when multiple diseases were considered, the average accuracy reaches 98.63% for the class prediction of rice disease images. CONCLUSIONS The experimental results prove the validity of the proposed approach, and it is accomplished efficiently for rice disease detection. © 2020 Society of Chemical Industry. © 2020 Society of Chemical Industry.BACKGROUND Real-world biologic drug survival is an important proxy measure for effectiveness. Predictors of drug survival may help patients with psoriasis choose between biologic therapies. OBJECTIVES 1. To assess the relative drug survival of adalimumab, ustekinumab and secukinumab in patients with psoriasis; 2. To investigate for predictors for biologic drug survival. METHODS A prospective cohort study was performed in the British Association of Dermatologists Biologics and Immunomodulators Register (BADBIR) between November 2007 and August 2019. We performed survival analysis and fitted a flexible parametric survival model for biologic discontinuation due to ineffectiveness. RESULTS 5,542 starting on adalimumab (57.4%); 991, secukinumab (10.3%); and 3118 on ustekinumab (32.3%) were included. Overall drug survival of adalimumab, secukinumab and ustekinumab was 0.78 (95% CI 0.77-0.79), 0.88 (0.86-0.91) and 0.88 (0.87-0.89) in Year 1 respectively. The adjusted hazard ratios (adjHR) for discontinuation of adalimumab and secukinumab compared with ustekinumab were 2.11 (95% CI 1.76-2.54) and 0.67 (95% CI 0.40-1.11) respectively. The presence of psoriatic arthritis predicted for survival in the adalimumab and secukinumab cohorts (adjHR 0.67 (0.51-0.88); 0.70 (0.40-1.24) respectively) but for discontinuation in the ustekinumab cohort (adjHR 1.42 [1.12-1.81]). Previous exposure to biologic therapies predicted for discontinuation in the ustekinumab and secukinumab cohorts (adjHR 1.54 (1.26-1.89); 1.49 (0.91-2.45) respectively) and for survival in the adalimumab cohort (adjHR 0.71 (0.55-0.92)). CONCLUSIONS Secukinumab and ustekinumab have similar sustained drug survival, whilst adalimumab has a lower drug survival in patients with psoriasis. Psoriatic arthritis and previous biologic experience were predictors with differential effects between the biologic therapies. This article is protected by copyright. All rights reserved.BACKGROUND Approximately 8% of schoolchildren in the United States experience potentially life-threatening food allergies. They must diligently avoid allergenic foods and have prompt access to epinephrine to treat anaphylaxis. These prevention strategies must be sustained without interruption, posing a range of challenges at school. METHODS We conducted semi-structured interviews with 178 participants about their experiences managing food allergies outside the home. Interviews were transcribed and analyzed using an iterative approach in NVivo 10. RESULTS Participants reported highly varied school experiences across the ecological model. They described the need to be proactive and self-sufficient to manage food allergies. Whereas food allergy-related social exclusion was common, participants also described positive peer interactions, including intensive peer engagement and support. They perceived that formal school policies were limited in scope and inconsistently implemented. Prevention-oriented policies were more common in lower grades than in higher grades. CONCLUSIONS Poorly defined and implemented policies disrupted students' social and educational experiences at school, families' relationships with school staff, and, ultimately, the safety and wellbeing of students with allergies. Given the high prevalence of food allergies among children, these findings demonstrate the need for multiple layers of support to facilitate safe, socially inclusive food allergy management at schools. © 2020, American School Health Association.To understand the diversity and strength of predation in natural communities, researchers must quantify the total amount of prey species in the diet of predators. Metabarcoding approaches have allowed widespread characterization of predator diets with high taxonomic resolution. To determine the wider impacts of predators, researchers should combine DNA techniques with estimates of population size of predators using mark-release-recapture (MRR) methods, and with accurate metrics of food consumption by individuals. Herein, we estimate the scale of predation exerted by four damselfly species on diverse prey taxa within a well-defined 12-ha study area, resolving the prey species of individual damselflies, to what extent the diets of predatory species overlap, and which fraction of the main prey populations are consumed. We identify the taxonomic composition of diets using DNA metabarcoding and quantify damselfly population sizes by MRR. We also use predator-specific estimates of consumption rates, and independent data on prey emergence rates to estimate the collective predation pressure summed over all prey taxa and specific to their main prey (non-biting midges or chironomids) of the four damselfly species.