Data Assimilation Enhancements to Air Force Weathers Land Information System

The United States Air Force (USAF) has a proud and storied tradition of enabling significant advancements in the area of characterizing and modeling land state information. 557th Weather Wing (557 WW; DoDs Executive Agent for Land Information) provides routine geospatial intelligence information to warfighters, planners, and decision makers at all echelons and services of the U.S. military, government and intelligence community. 557 WW and its predecessors have been home to the DoDs only operational regional and global land data analysis systems since January 1958. As a trusted partner since 2005, Air Force Weather (AFW) has relied on the Hydrological Sciences Laboratory at NASA/GSFC to lead the interagency scientific collaboration known as the Land Information System (LIS). LIS is an advanced software framework for high performance land surface modeling and data assimilation of geospatial intelligence (GEOINT) information

Superoxide Dismutase 1 and tgSOD1G93A Mouse Spinal Cord Seed Fibrils, Suggesting a Propagative Cell Death Mechanism in Amyotrophic Lateral Sclerosis

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that specifically affects motor neurons and leads to a progressive and ultimately fatal loss of function, resulting in death typically within 3 to 5 years of diagnosis. The disease starts with a focal centre of weakness, such as one limb, and appears to spread to other parts of the body. Mutations in superoxide dismutase 1 (SOD1) are known to cause disease and it is generally accepted they lead to pathology not by loss of enzymatic activity but by gain of some unknown toxic function(s). Although different mutations lead to varying tendencies of SOD1 to aggregate, we suggest abnormal proteins share a common misfolding pathway that leads to the formation of amyloid fibrils.Methodology/Principal Findings: Here we demonstrate that misfolding of superoxide dismutase 1 leads to the formation of amyloid fibrils associated with seeding activity, which can accelerate the formation of new fibrils in an autocatalytic cascade. The time limiting event is nucleation to form a stable protein "seed" before a rapid linear polymerisation results in amyloid fibrils analogous to other protein misfolding disorders. This phenomenon was not confined to fibrils of recombinant protein as here we show, for the first time, that spinal cord homogenates obtained from a transgenic mouse model that overexpresses mutant human superoxide dismutase 1 (the TgSOD1(G93A) mouse) also contain amyloid seeds that accelerate the formation of new fibrils in both wildtype and mutant SOD1 protein in vitro.Conclusions/Significance: These findings provide new insights into ALS disease mechanism and in particular a mechanism that could account for the spread of pathology throughout the nervous system. This model of disease spread, which has analogies to other protein misfolding disorders such as prion disease, also suggests it may be possible to design assays for therapeutics that can inhibit fibril propagation and hence, possibly, disease progression

The neuropeptide NMU amplifies ILC2-driven allergic lung inflammation

Type 2 innate lymphoid cells (ILC2s) both contribute to mucosal homeostasis and initiate pathologic inflammation in allergic asthma. However, the signals that direct ILC2s to promote homeostasis versus inflammation are unclear. To identify such molecular cues, we profiled mouse lung-resident ILCs using single-cell RNA sequencing at steady state and after in vivo stimulation with the alarmin cytokines IL-25 and IL-33. ILC2s were transcriptionally heterogeneous after activation, with subpopulations distinguished by expression of proliferative, homeostatic and effector genes. The neuropeptide receptor Nmur1 was preferentially expressed by ILC2s at steady state and after IL-25 stimulation. Neuromedin U (NMU), the ligand of NMUR1, activated ILC2s in vitro, and in vivo co-administration of NMU with IL-25 strongly amplified allergic inflammation. Loss of NMU-NMUR1 signalling reduced ILC2 frequency and effector function, and altered transcriptional programs following allergen challenge in vivo. Thus, NMUR1 signalling promotes inflammatory ILC2 responses, highlighting the importance of neuro-immune crosstalk in allergic inflammation at mucosal surfaces

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Reconstructing and Reprogramming the Tumor-Propagating Potential of Glioblastoma Stem-like Cells

Developmental fate decisions are dictated by master transcription factors (TFs) that interact with cis-regulatory elements to direct transcriptional programs. Certain malignant tumors may also depend on cellular hierarchies reminiscent of normal development but superimposed on underlying genetic aberrations. In glioblastoma (GBM), a subset of stem-like tumor-propagating cells (TPCs) appears to drive tumor progression and underlie therapeutic resistance, yet remain poorly understood. Here, we identify a core set of neurodevelopmental TFs (POU3F2, SOX2, SALL2, OLIG2) essential for GBM propagation. These TFs coordinately bind and activate TPC-specific regulatory elements, and are sufficient to fully reprogram differentiated GBM cells to ‘induced’ TPCs, recapitulating the epigenetic landscape and phenotype of native TPCs. We reconstruct a network model that highlights critical interactions and identifies novel therapeutic targets for eliminating TPCs. Our study establishes the epigenetic basis of a developmental hierarchy in GBM, provides detailed insight into underlying gene regulatory programs, and suggests attendant therapeutic strategies

Seven Sisters: a mission to study fundamental plasma physical processes in the solar wind and a pathfinder to advance space weather prediction

This paper summarizes the Seven Sisters solar wind mission concept and the outstanding science questions motivating the mission science objectives. The Seven Sisters mission includes seven individual spacecraft designed to uncover fundamental physical processes in the solar wind and provides up to ≈ 2 days of advanced space weather warnings for 550 Earth days during the mission. The mission will collect critical measurements of the thermal and suprathermal plasma and magnetic fields, utilizing, for the first time, Venus–Sun Lagrange points. The multi-spacecraft configuration makes it possible to distinguish between spatial and temporal changes, define gradients, and quantify cross-scale transport in solar wind structures. Seven Sisters will determine the 3-D structure of the solar wind and its transient phenomena and their evolution in the inner heliosphere. Data from the Seven Sisters mission will allow the identification of physical processes and the quantification of the relative contribution of different mechanisms responsible for suprathermal particle energization in the solar wind

Associations between social support, mental wellbeing, self-efficacy and technology use in first-time antenatal women: data from the BaBBLeS cohort study

Background: Information and communication technologies are used increasingly to facilitate social networks and support women during the perinatal period. This paper presents data on how technology use affects the association between women’s social support and, (i) mental wellbeing and, (ii) self-efficacy in the antenatal period. Methods: Data were collected as part of an ongoing study - the BaBBLeS study - exploring the effect of a pregnancy and maternity software application (app) on maternal wellbeing and self-efficacy. Between September 2016 and February 2017, we aimed to recruit first-time pregnant women at 12–16 gestation weeks in five maternity sites across England and asked them to complete questionnaires. Outcomes included maternal mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale), and antenatal self-efficacy (antenatal version of the Tool to Measure Parenting Self-Efficacy). Other variables assessed were perceived social support (Multidimensional Scale of Perceived Social Support), general technology use (adapted from Media and Technology Usage and Attitudes Scale). Potential confounders were age, ethnicity, education, socioeconomic deprivation, employment, relationship status and recruitment site. Linear regression models were developed to analyse the relationship between social support and the outcomes. Results: Participants (n = 492, median age = 28 years) were predominantly white British (64.6%). Half of them had a degree or higher degree (49.3%), most were married/living with a partner (83.6%) and employed (86.2%). Median (LQ-UQ) overall scores were 81.0 (74.0–84.0) for social support (range 12–84), 5.1 (4.7–5.4) for technology use (range 1–6), 54.0 (48.0–60.0) for mental well-being (range 14–70), and 319.0 (295.5–340) for self-efficacy (range 0–360). Social support was significantly associated with antenatal mental well-being adjusting for confounders [adj R2 = 0.13, p < .001]. The addition of technology use did not alter this model [adj R2 = 0.13, p < .001]. Social support was also significantly associated with self-efficacy after adjustment [adj R2 = 0.14, p < .001]; technology had limited impact on this association [adj R2 = 0.13, p < .001]. Conclusions: Social support is associated with mental well-being and self-efficacy in antenatal first-time mothers. This association was not significantly affected by general technology use as measured in our survey. Future work should investigate whether pregnancy-specific technologies yield greater potential to enhance the perceived social support, wellbeing and self-efficacy of antenatal women

Correction to: A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer’s disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity

The IPDGC (The International Parkinson Disease Genomics Consortium) and EADB (Alzheimer Disease European DNA biobank) are listed correctly as an author to the article, however, they were incorrectly listed more than once