allergens) continues to be associated with an increased risk of asthma, bronchial hyperresponsiveness, and high total IgE at age 10 years. To present a comprehensive, clinically focused scoping review of therapeutic agents and practices comprising the future of allergic rhinitis (AR) management. A review of the published literature was performed using the PubMed database, published abstracts, and virtual presentations from scientific meetings and posted results on ClinicalTrials.gov. Primary manuscripts with trial results, case reports, case series, and clinical trial data from ClinicalTrials.gov, PubMed, and articles highlighting expert perspectives on management of AR were selected. Telemedicine, social media, and mHealth facilitate integrated care for AR management. GC7 chemical structure Pharmacotherapy remains the standard of care for AR management; however, treatment combinations are recommended. Intralymphatic immunotherapy and peptide immunotherapy are the most promising new allergen immunotherapy options. Studies of targeted biologics for AR are ongoing. Probiotics may be beneficial for AR management, particularly Bifidobacterium spp, and as an add-on to allergen immunotherapy. AR is a chronic and often comorbid condition that requires integrated care for optimal management. New formulations and combinations of existing AR therapies are the most promising and merit future research.AR is a chronic and often comorbid condition that requires integrated care for optimal management. New formulations and combinations of existing AR therapies are the most promising and merit future research. This analysis of the pivotal phase III HAWK and HARRIER trials aimed to provide insights on the timing of presentation, management, and outcomes of intraocular inflammation (IOI)-related adverse events (AEs), as reported by investigators in these trials. Post hoc analysis of investigator-reported IOI-related AEs in HAWK and HARRIER. Of 1088 brolucizumab-treated eyes (3 mg or 6 mg), 49 eyes experienced at least 1 IOI-related AE and were included in this analysis. Reports of IOI-related AEs were analyzed and descriptive statistics were provided for outcome measures. Incidence and description of eyes with IOI-related AEs, timing of presentation, management, clinical outcomes, and brolucizumab treatment after the first IOI-related AE. A total of 70 IOI-related AEs were reported in 49 eyes. Prior to the onset of first IOI-related AE, eyes received a mean (standard deviation [SD]) of 3.9 (2.2) brolucizumab injections. Median (25th-75th percentile) time to first IOI-related AE from the last administered DRS letters from baseline to end-of-study. Findings of this analysis highlight the need for continued vigilance and monitoring for any signs of IOI-related events in patients receiving brolucizumab.Findings of this analysis highlight the need for continued vigilance and monitoring for any signs of IOI-related events in patients receiving brolucizumab. To assess the potential of machine learning to predict low and high treatment demand in real life in patients with neovascular age-related macular degeneration (nAMD), retinal vein occlusion (RVO), and diabetic macular edema (DME) treated according to a treat-and-extend regimen (TER). Retrospective cohort study. Three hundred seventy-seven eyes (340 patients) with nAMD and 333 eyes (285 patients) with RVO or DME treated with anti-vascular endothelial growth factor agents (VEGF) according to a predefined TER from 2014 through2018. Eyes were grouped by disease into low, moderate, and high treatment demands, defined by the average treatment interval (low, ≥10 weeks; high, ≤5 weeks; moderate, remaining eyes). Two random forest models were trained to predict the probability of the long-term treatment demand of a new patient. Both models use morphological features automatically extracted from the OCT volumes at baseline and after 2 consecutive visits, as well as patient demographic information. Evaluation olow demand reasonably well at the first visit, before the first injection. Machine learning classifiers can predict treatment demand and may assist in establishing patient-specific treatment plans in the near future.Machine learning classifiers can predict treatment demand and may assist in establishing patient-specific treatment plans in the near future.G-proteins are ubiquitously expressed heterotrimeric proteins consisting of α, β and γ subunits and mediate G-protein coupled receptor signalling cascades. The β subunit is encoded by one of five highly similar paralogs (GNB1-GNB5, accordingly). The developmental importance of G-proteins is highlighted by the clinical relevance of variants in genes such as GNB1, which cause severe neurodevelopmental disease (NDD). Recently the candidacy of GNB2 was raised in association with NDD in an individual with a de novo variant affecting a codon conserved across paralogs and recurrently mutated in GNB1-related disease, c.229G>A p.(Gly77Arg), in association with global developmental delay, intellectual disability and dysmorphic features. Here, we report a patient with strikingly similar facial features and NDD in association with a de novo GNB2 variant affecting the same codon, c.229G>T p.(Gly77Trp). In addition, this individual has epilepsy and overgrowth. Our report is the second to implicate a de novo GNB2 variant with a severe yet variable NDD.Reductionist strategies aim to understand the mechanisms of complex systems by studying individual parts and their interactions. In this review, we discuss how reductionist approaches have shed light on the structure, function, and production of a complex biomaterial - hagfish defensive slime. Hagfish slime is an extremely dilute hydrogel-like material composed of seawater, mucus, and silk-like proteins that can deploy rapidly. Despite being composed almost entirely of water, hagfish slime has remarkable physical properties, including high strength and toughness. While hagfish slime has a promising future in biomimetics, including the development of eco-friendly high-performance fibers, recreating hagfish slime in the lab has been a difficult challenge. Over the past two decades, reductionist experiments have provided a wealth of information about the individual components of hagfish slime. However, a reductionist approach provides a limited understanding because hagfish defensive slime, like most biological phenomena, is more than just the sum of its parts.