Search

Inflammatory response heterogeneity has impeded high-resolution dissection of diverse immune cell populations during activation. We characterize mouse cutaneous immune cells by single-cell RNA sequencing, after inducing inflammation using imiquimod and oxazolone dermatitis models. We identify 13 CD45+ subpopulations, which broadly represent most functionally characterized immune cell types. Oxazolone pervasively upregulates Jak2/Stat3 expression across T cells and antigen-presenting cells (APCs). Oxazolone also induces Il4/Il13 expression in newly infiltrating basophils, and Il4ra and Ccl24, most prominently in APCs. In contrast, imiquimod broadly upregulates Il17/Il22 and Ccl4/Ccl5. A comparative analysis of single-cell inflammatory transcriptional responses reveals that APC response to oxazolone is tightly restricted by cell identity, whereas imiquimod enforces shared programs on multiple APC populations in parallel. These global molecular patterns not only contrast immune responses on a systems level but also suggest that the mechanisms of new sources of inflammation can eventually be deduced by comparison to known signatures.

As noted in Wikipedia, skin in the game refers to having 'incurred risk by being involved in achieving a goal', where 'skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

The seasonal timing of seed germination determines a plant's realized environmental niche, and is important for adaptation to climate. The timing of seasonal germination depends on patterns of seed dormancy release or induction by cold and interacts with flowering-time variation to construct different seasonal life histories. To characterize the genetic basis and climatic associations of natural variation in seed chilling responses and associated life-history syndromes, we selected 559 fully sequenced accessions of the model annual species Arabidopsis thaliana from across a wide climate range and scored each for seed germination across a range of 13 cold stratification treatments, as well as the timing of flowering and senescence. Germination strategies varied continuously along 2 major axes: 1) Overall germination fraction and 2) induction vs. release of dormancy by cold. Natural variation in seed responses to chilling was correlated with flowering time and senescence to create a range of seasonal life-history syndromes. Genome-wide association identified several loci associated with natural variation in seed chilling responses, including a known functional polymorphism in the self-binding domain of the candidate gene DOG1. A phylogeny of DOG1 haplotypes revealed ancient divergence of these functional variants associated with periods of Pleistocene climate change, and Gradient Forest analysis showed that allele turnover of candidate SNPs was significantly associated with climate gradients. These results provide evidence that A. thaliana's germination niche and correlated life-history syndromes are shaped by past climate cycles, as well as local adaptation to contemporary climate.

Autism spectrum disorder is associated with sensory processing alterations, such as sensory hyper- and hypo-responsiveness. Twin studies are scarce in this field, but they are necessary in order to disentangle the genetic and environmental contributions to this association. Furthermore, it is unclear how different neurodevelopmental/psychiatric conditions contribute to altering sensory processing. We investigated the association between autistic traits/autism spectrum disorder diagnosis and sensory processing alterations in twins (N = 269), using the adult/adolescent sensory profile, which differentiates four sub-domains: Low Registration, Sensation Seeking, Sensory Sensitivity, and Sensation Avoiding. While the associations between autistic traits and "Low Registration" and "Sensation Avoiding" persisted within monozygotic (genetically identical) twins, "Sensory Sensitivity" was only associated with autistic traits within dizygotic twins. In multivariate analyses with different neurodevelopmental/psychiatric diagnoses as predictor variables, autism spectrum disorder and attention deficit hyperactivity disorder were the strongest predictors for two adult/adolescent sensory profile sub-domains each. The results suggest that the association between autistic traits and "Sensory Sensitivity" is influenced by genetics while non-shared environmental factors influence the associations between autistic traits and "Low Registration" and "Sensation Avoiding." They further indicate that altered sensory processing is not specific to autism spectrum disorder, while autism spectrum disorder is a strong predictor of certain sensory processing alterations, even when controlling for other (comorbid) neurodevelopmental/psychiatric conditions.

This study provides an overview of the coupled high-resolution Version 1 of the Energy Exascale Earth System Model (E3SMv1) and documents the characteristics of a 50-year-long high-resolution control simulation with time-invariant 1950 forcings following the HighResMIP protocol. In terms of global root-mean-squared error metrics, this high-resolution simulation is generally superior to results from the low-resolution configuration of E3SMv1 (due to resolution, tuning changes, and possibly initialization procedure) and compares favorably to models in the CMIP5 ensemble. Ocean and sea ice simulation is particularly improved, due to better resolution of bathymetry, the ability to capture more variability and extremes in winds and currents, and the ability to resolve mesoscale ocean eddies. The largest improvement in this regard is an ice-free Labrador Sea, which is a major problem at low resolution. Interestingly, several features found to improve with resolution in previous studies are insensitive to resolution or even degrade in E3SMv1. Most notable in this regard are warm bias and associated stratocumulus deficiency in eastern subtropical oceans and lack of improvement in El Niño. Another major finding of this study is that resolution increase had negligible impact on climate sensitivity (measured by net feedback determined through uniform +4K prescribed sea surface temperature increase) and aerosol sensitivity. Cloud response to resolution increase consisted of very minor decrease at all levels. Large-scale patterns of precipitation bias were also relatively unaffected by grid spacing.

Contrary to previous assumptions that most mutations are deleterious, there is increasing evidence for persistence of large-effect mutations in natural populations. A possible explanation for these observations is that mutant phenotypes and fitness may depend upon the specific environmental conditions to which a mutant is exposed. Here, we tested this hypothesis by growing large-effect flowering time mutants of Arabidopsis thaliana in multiple field sites and seasons to quantify their fitness effects in realistic natural conditions. By constructing environment-specific fitness landscapes based on flowering time and branching architecture, we observed that a subset of mutations increased fitness, but only in specific environments. These mutations increased fitness via different paths: through shifting flowering time, branching, or both. Branching was under stronger selection, but flowering time was more genetically variable, pointing to the importance of indirect selection on mutations through their pleiotropic effects on multiple phenotypes. Finally, mutations in hub genes with greater connectedness in their regulatory networks had greater effects on both phenotypes and fitness. Together, these findings indicate that large-effect mutations may persist in populations because they influence traits that are adaptive only under specific environmental conditions. Understanding their evolutionary dynamics therefore requires measuring their effects in multiple natural environments.

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERFari+aci = −1.65 W/m2) and high equilibrium climate sensitivity (ECS = 5.3 K).

Increasing temperatures during climate change are known to alter the phenology across diverse plant taxa, but the evolutionary outcomes of these shifts are poorly understood. Moreover, plant temperature-sensing pathways are known to interact with competition-sensing pathways, yet there remains little experimental evidence for how genotypes varying in temperature responsiveness react to warming in realistic competitive settings. We compared flowering time and fitness responses to warming and competition for two near-isogenic lines (NILs) of Arabidopsis thaliana transgressively segregating temperature-sensitive and temperature-insensitive alleles for major-effect flowering time genes. We grew focal plants of each genotype in intraspecific and interspecific competition in four treatments contrasting daily temperature profiles in summer and fall under contemporary and warmed conditions. We measured phenology and fitness of focal plants to quantify plastic responses to season, temperature and competition and the dependence of these responses on flowering time genotype. The temperature-insensitive NIL was constitutively early flowering and less fit, except in a future-summer climate in which its fitness was higher than the later flowering, temperature-sensitive NIL in low competition. The late-flowering NIL showed accelerated flowering in response to intragenotypic competition and to increased temperature in the summer but delayed flowering in the fall. However, its fitness fell with rising temperatures in both seasons, and in the fall its marginal fitness gain from decreasing competition was diminished in the future. Functional alleles at temperature-responsive genes were necessary for plastic responses to season, warming and competition. However, the plastic genotype was not the most fit in every experimental condition, becoming less fit than the temperature-canalized genotype in the warm summer treatment. Climate change is often predicted to have deleterious effects on plant populations, and our results show how increased temperatures can act through genotype-dependent phenology to decrease fitness. Furthermore, plasticity is not necessarily adaptive in rapidly changing environments since a nonplastic genotype proved fitter than a plastic genotype in a warming climate treatment. A plain language summary is available for this article.

This article investigates the issues and tensions involved in collecting data from audiences to describe their diversity. It uses data collected as part of a survey of festival audiences to examine (1) how people choose to describe their identity in an open-text question and (2) how classifying complex responses to questions about ethnic or cultural background has implications for analysis. First, data provided through an open-text question in the festival survey were used to establish two classification systems. The results show patterns in the relationship between how people choose to identify themselves and their arts knowledge and appetite. It also shows patterns between what they identify about themselves and their arts knowledge and appetite. The article helps researchers better understand the implications of providing open opportunities for audience members to report the way they choose to see themselves, and of establishing classification systems based on this data for analysis. [ABSTRACT FROM AUTHOR]

Light Detection and Ranging (LiDAR) sensors at signalized intersections can accurately track the movement of virtually all objects passing through at high sampling rates. This study presents methodologies to estimate vehicle and pedestrian traffic signal performance measures using LiDAR trajectory data. Over 15,000,000 vehicle and 170,000 pedestrian waypoints detected during a 24 h period at an intersection in Utah are analyzed to describe the proposed techniques. Sampled trajectories are linear referenced to generate Purdue Probe Diagrams (PPDs). Vehicle-based PPDs are used to estimate movement level turning counts, 85th percentile queue lengths (85QL), arrivals on green (AOG), highway capacity manual (HCM) level of service (LOS), split failures (SF), and downstream blockage (DSB) by time of day (TOD). Pedestrian-based PPDs are used to estimate wait times and the proportion of people that traverse multiple crosswalks. Although vehicle signal performance can be estimated from several days of aggregated connected vehicle (CV) data, LiDAR data provides the ability to measure performance in real time. Furthermore, LiDAR can measure pedestrian speeds. At the studied location, the 15th percentile pedestrian walking speed was estimated to be 3.9 ft/s. The ability to directly measure these pedestrian speeds allows agencies to consider alternative crossing times than those suggested by the Manual on Uniform Traffic Control Devices (MUTCD). [ABSTRACT FROM AUTHOR]