Calculation of nonzero-temperature Casimir forces in the time domain

We show how to compute Casimir forces at nonzero temperatures with time-domain electromagnetic simulations, for example using a finite-difference time-domain (FDTD) method. Compared to our previous zero-temperature time-domain method, only a small modification is required, but we explain that some care is required to properly capture the zero-frequency contribution. We validate the method against analytical and numerical frequency-domain calculations, and show a surprising high-temperature disappearance of a non-monotonic behavior previously demonstrated in a piston-like geometry.Comment: 5 pages, 2 figures, submitted to Physical Review A Rapid Communicatio

Single-Cell Transcriptomic Profiling of Pluripotent Stem Cell-Derived SCGB3A2+ Airway Epithelium.

Lung epithelial lineages have been difficult to maintain in pure form in vitro, and lineage-specific reporters have proven invaluable for monitoring their emergence from cultured pluripotent stem cells (PSCs). However, reporter constructs for tracking proximal airway lineages generated from PSCs have not been previously available, limiting the characterization of these cells. Here, we engineer mouse and human PSC lines carrying airway secretory lineage reporters that facilitate the tracking, purification, and profiling of this lung subtype. Through bulk and single-cell-based global transcriptomic profiling, we find PSC-derived airway secretory cells are susceptible to phenotypic plasticity exemplified by the tendency to co-express both a proximal airway secretory program as well as an alveolar type 2 cell program, which can be minimized by inhibiting endogenous Wnt signaling. Our results provide global profiles of engineered lung cell fates, a guide for improving their directed differentiation, and a human model of the developing airway

Effects of mammalian herbivore declines on plant communities: observations and experiments in an African savanna

1. Herbivores influence the structure and composition of terrestrial plant communities. However, responses of plant communities to herbivory are variable and depend on environmental conditions, herbivore identity and herbivore abundance. As anthropogenic impacts continue to drive large declines in wild herbivores, understanding the context dependence of herbivore impacts on plant communities becomes increasingly important. 2. Exclosure experiments are frequently used to assess how ecosystems reorganize in the face of large wild herbivore defaunation. Yet in many landscapes, declines in large wildlife are often accompanied by other anthropogenic activities, especially land conversion to livestock production. In such cases, exclosure experiments may not reflect typical outcomes of human-driven extirpations of wild herbivores. 3. Here, we examine how plant community responses to changes in the identity and abundance of large herbivores interact with abiotic factors (rainfall and soil properties). We also explore how effects of wild herbivores on plant communities differ between large-scale herbivore exclosures and landscape sites where anthropogenic activity has caused wildlife declines, often accompanied by livestock increases. 4. Abiotic context modulated the responses of plant communities to herbivore declines with stronger effect sizes in lower-productivity environments. Also, shifts in plant community structure, composition and species richness following wildlife declines differed considerably between exclosure experiments and landscape sites in which wild herbivores had declined and were often replaced by livestock. Plant communities in low wildlife landscape sites were distinct in both composition and physical structure from both exclosure and control sites in experiments. The power of environmental (soil and rainfall) gradients in influencing plant response to herbivores was also greatly dampened or absent in the landscape sites. One likely explanation for these observed differences is the compensatory effect of livestock associated with the depression or extirpation of wildlife. 5. Synthesis. Our results emphasize the importance of abiotic environmental heterogeneity in modulating the effects of mammalian herbivory on plant communities and the importance of such covariation in understanding effects of wild herbivore declines. They also suggest caution when extrapolating results from exclosure experiments to predict the consequences of defaunation as it proceeds in the Anthropocene

Mendelian Randomization with Incomplete Exposure Data: a Bayesian Approach

We expand Mendelian Randomization (MR) methodology to deal with randomly missing data on either the exposure or the outcome variable, and furthermore with data from nonindependent individuals (eg components of a family). Our method rests on the Bayesian MR framework proposed by Berzuini et al (2018), which we apply in a study of multiplex Multiple Sclerosis (MS) Sardinian families to characterise the role of certain plasma proteins in MS causation. The method is robust to presence of pleiotropic effects in an unknown number of instruments, and is able to incorporate inter-individual kinship information. Introduction of missing data allows us to overcome the bias introduced by the (reverse) effect of treatment (in MS cases) on level of protein. From a substantive point of view, our study results confirm recent suspicion that an increase in circulating IL12A and STAT4 protein levels does not cause an increase in MS risk, as originally believed, suggesting that these two proteins may not be suitable drug targets for MS

SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach

<p>Abstract</p> <p>Background</p> <p>Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families.</p> <p>Results</p> <p>Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest.</p> <p>Conclusion</p> <p>Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.</p

Model organisms contribute to diagnosis and discovery in the Undiagnosed Diseases Network: Current state and a future vision

Decreased sequencing costs have led to an explosion of genetic and genomic data. These data have revealed thousands of candidate human disease variants. Establishing which variants cause phenotypes and diseases, however, has remained challenging. Significant progress has been made, including advances by the National Institutes of Health (NIH)-funded Undiagnosed Diseases Network (UDN). However, 6000-13,000 additional disease genes remain to be identified. The continued discovery of rare diseases and their genetic underpinnings provides benefits to affected patients, of whom there are more than 400 million worldwide, and also advances understanding the mechanisms of more common diseases. Platforms employing model organisms enable discovery of novel gene-disease relationships, help establish variant pathogenicity, and often lead to the exploration of underlying mechanisms of pathophysiology that suggest new therapies. The Model Organism Screening Center (MOSC) of the UDN is a unique resource dedicated to utilizing informatics and functional studies in model organisms, including worm (Caenorhabditis elegans), fly (Drosophila melanogaster), and zebrafish (Danio rerio), to aid in diagnosis. The MOSC has directly contributed to the diagnosis of challenging cases, including multiple patients with complex, multi-organ phenotypes. In addition, the MOSC provides a framework for how basic scientists and clinicians can collaborate to drive diagnoses. Customized experimental plans take into account patient presentations, specific genes and variant(s), and appropriateness of each model organism for analysis. The MOSC also generates bioinformatic and experimental tools and reagents for the wider scientific community. Two elements of the MOSC that have been instrumental in its success are (1) multidisciplinary teams with expertise in variant bioinformatics and in human and model organism genetics, and (2) mechanisms for ongoing communication with clinical teams. Here we provide a position statement regarding the central role of model organisms for continued discovery of disease genes, and we advocate for the continuation and expansion of MOSC-type research entities as a Model Organisms Network (MON) to be funded through grant applications submitted to the NIH, family groups focused on specific rare diseases, other philanthropic organizations, industry partnerships, and other sources of support

The Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) Mission: Design, Execution, and First Results

The NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission was conducted in two 3-week deployments based in Alaska (April 2008) and western Canada (June–July 2008). Its goal was to better understand the factors driving current changes in Arctic atmospheric composition and climate, including (1) influx of mid-latitude pollution, (2) boreal forest fires, (3) aerosol radiative forcing, and (4) chemical processes. The June–July deployment was preceded by one week of flights over California (ARCTAS-CARB) focused on (1) improving state emission inventories for greenhouse gases and aerosols, (2) providing observations to test and improve models of ozone and aerosol pollution. ARCTAS involved three aircraft: a DC-8 with a detailed chemical payload, a P-3 with an extensive aerosol and radiometric payload, and a B-200 with aerosol remote sensing instrumentation. The aircraft data augmented satellite observations of Arctic atmospheric composition, in particular from the NASA A-Train. The spring phase (ARCTAS-A) revealed pervasive Asian pollution throughout the Arctic as well as significant European pollution below 2 km. Unusually large Siberian fires in April 2008 caused high concentrations of carbonaceous aerosols and also affected ozone. Satellite observations of BrO column hotspots were found not to be related to Arctic boundary layer events but instead to tropopause depressions, suggesting the presence of elevated inorganic bromine (5–10 pptv) in the lower stratosphere. Fresh fire plumes from Canada and California sampled during the summer phase (ARCTAS-B) indicated low $NO_x$ emission factors from the fires, rapid conversion of $NO_x$ to PAN, no significant secondary aerosol production, and no significant ozone enhancements except when mixed with urban pollution.Engineering and Applied Science