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By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.

The presence and abundance of organisms within an ecosystem often correlate with habitat variables that may have few, or unknown, functional values. Understanding the functional role of these variables is especially important for organisms occupying landscapes managed for timber production and containing diverse habitat patches of different quantities and structures of vegetation. We investigated the strength of associations reported in the literature between small mammal generalists and vegetation. On an industrially logged landscape in northern CA, we used occupancy and mark-recapture analyses across three years to estimate the presence and total numbers for woodrats (Neotoma fuscipes Baird, 1858) and deer mice (Peromyscus maniculatus (Wagner, 1845)) related to vegetative attributes on coniferous and non-coniferous sites. Abundances of the small mammals correlated positively with shrub cover and hardwoods for woodrats and with shrubs and masting species for deer mice. Indices describing the value of vegetation features for both food and cover, but not these resources independently, described both species' presence and abundances best. We demonstrated that shrubs and non-coniferous trees are particularly important for small mammals and should be of particular focus to forest managers in the Sierras and mountains with similar forest structures. Key words: cover, food, forest management, functional value, Neotomafuscipes, Peromyscus maniculatus, Introduction Managed landscapes provide roughly replicate environmental conditions on sites with native vegetation. Using such sites, we can test previously hypothesized associations between forest features and the sizes of populations [...]

The type 2 cytokine-high asthma endotype (T2H) is characterized by IL-13-driven mucus obstruction of the airways. To further investigate this incompletely understood pathobiology, we characterize IL-13 effects on human airway epithelial cell cultures using single-cell RNA sequencing, finding that IL-13 generates a distinctive transcriptional state for each cell type. Specifically, we discover a mucus secretory program induced by IL-13 in all cell types which converts both mucus and defense secretory cells into a metaplastic state with emergent mucin production and secretion, while leading to ER stress and cell death in ciliated cells. The IL-13-remodeled epithelium secretes a pathologic, mucin-imbalanced, and innate immunity-depleted proteome that arrests mucociliary motion. Signatures of IL-13-induced cellular remodeling are mirrored by transcriptional signatures characteristic of the nasal airway epithelium within T2H versus T2-low asthmatic children. Our results reveal the epithelium-wide scope of T2H asthma and present candidate therapeutic targets for restoring normal epithelial function.

Drawing from a five-year longitudinal data set following thirteen college writers through undergraduate writing and beyond, we explore the impact of students' emotions and emotional dispositions on their ability to transfer writing knowledge and on their overall writing development. Participants experienced a range of emotions concerning their writing, but those emotions could be broadly categorized as generative, disruptive, or circumstantial. Students managed these emotions in different ways, with some approaching their learning less emotionally (rational interpreters), others more so (emotional interpreters), and a final group using metacognitive practices to manage their emotions (emotional managers). Our results suggest that metacognitive concepts of monitoring and control are keys to students' navigation of the complex emotional landscape of writing in higher education. Our discussion posits ways that faculty can help students become emotional managers and work with students' emotions in the classroom, and it suggests further avenues for research.

Initial radioactive disequilibrium amongst intermediate nuclides of the U decay chains can have a significant impact on the accuracy of U – Pb ages, especially in young samples. For samples that can reasonably be assumed to have attained radioactive equilibrium at the time of analysis, a relatively straightforward correction may be applied. However, in younger materials where this assumption is unreasonable, it is necessary to replace the familiar U – Pb age equations with more complete expressions that account for growth and decay of intermediate nuclides through time. DQPB is software for calculating U – Pb ages while accounting for the effects of radioactive disequilibrium among intermediate nuclides of the U decay chains. The software is written in Python and distributed as both a pure Python package and a stand-alone graphical user interface (GUI) application that integrates with standard Microsoft Excel spreadsheets. The software implements disequilibrium U – Pb equations to compute ages using various approaches, including concordia intercept ages on a Tera–Wasserburg diagram, U – Pb isochron ages, Pb*/U ages based on single aliquots, and 207Pb -corrected ages. While these age-calculation approaches are tailored toward young samples that cannot reasonably be assumed to have attained radioactive equilibrium at the time of analysis, they may also be applied to older materials where disequilibrium is no longer analytically resolvable. The software allows users to implement a variety of regression algorithms based on both classical and robust statistical approaches, compute weighted average ages and construct customisable, publication-ready plots of U – Pb age data. The regression and weighted average algorithms implemented in DQPB may also be applicable to other (i.e. non- U – Pb) geochronological datasets. [ABSTRACT FROM AUTHOR]