Transcriptomic signatures across human tissues identify functional rare genetic variation

© 2020 American Association for the Advancement of Science. All rights reserved. INTRODUCTION: The human genome contains tens of thousands of rare (minor allele frequency 800 genomes matched with transcriptomes across 49 tissues, we were able to study RVs that underlie extreme changes in the transcriptome. To capture the diversity of these extreme changes, we developed and integrated approaches to identify expression, allele-specific expression, and alternative splicing outliers, and characterized the RV landscape underlying each outlier signal. We demonstrate that personal genome interpretation and RV discovery is enhanced by using these signals. This approach provides a new means to integrate a richer set of functional RVs into models of genetic burden, improve disease gene identification, and enable the delivery of precision genomics

Mesophilic and Thermophilic Conditions Select for Unique but Highly Parallel Microbial Communities to Perform Carboxylate Platform Biomass Conversion

The carboxylate platform is a flexible, cost-effective means of converting lignocellulosic materials into chemicals and liquid fuels. Although the platform's chemistry and engineering are well studied, relatively little is known about the mixed microbial communities underlying its conversion processes. In this study, we examined the metagenomes of two actively fermenting platform communities incubated under contrasting temperature conditions (mesophilic 40°C; thermophilic 55°C), but utilizing the same inoculum and lignocellulosic feedstock. Community composition segregated by temperature. The thermophilic community harbored genes affiliated with Clostridia, Bacilli, and a Thermoanaerobacterium sp, whereas the mesophilic community metagenome was composed of genes affiliated with other Clostridia and Bacilli, Bacteriodia, γ-Proteobacteria, and Actinobacteria. Although both communities were able to metabolize cellulosic materials and shared many core functions, significant differences were detected with respect to the abundances of multiple Pfams, COGs, and enzyme families. The mesophilic metagenome was enriched in genes related to the degradation of arabinose and other hemicellulose-derived oligosaccharides, and the production of valerate and caproate. In contrast, the thermophilic community was enriched in genes related to the uptake of cellobiose and the transfer of genetic material. Functions assigned to taxonomic bins indicated that multiple community members at either temperature had the potential to degrade cellulose, cellobiose, or xylose and produce acetate, ethanol, and propionate. The results of this study suggest that both metabolic flexibility and functional redundancy contribute to the platform's ability to process lignocellulosic substrates and are likely to provide a degree of stability to the platform's fermentation processes

A connectome and analysis of the adult Drosophila central brain.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain

Chromatic periodic activity down to 120 MHz in a Fast Radio Burst

Fast radio bursts (FRBs) are extragalactic astrophysical transients whose brightness requires emitters that are highly energetic, yet compact enough to produce the short, millisecond-duration bursts. FRBs have thus far been detected between 300 MHz and 8 GHz, but lower-frequency emission has remained elusive. A subset of FRBs is known to repeat, and one of those sources, FRB 20180916B, does so with a 16.3 day activity period. Using simultaneous Apertif and LOFAR data, we show that FRB 20180916B emits down to 120 MHz, and that its activity window is both narrower and earlier at higher frequencies. Binary wind interaction models predict a narrower periodic activity window at lower frequencies, which is the opposite of our observations. Our detections establish that low-frequency FRB emission can escape the local medium. For bursts of the same fluence, FRB 20180916B is more active below 200 MHz than at 1.4 GHz. Combining our results with previous upper-limits on the all-sky FRB rate at 150 MHz, we find that there are 3-450 FRBs/sky/day above 50 Jy ms at 90% confidence. We are able to rule out the scenario in which companion winds cause FRB periodicity. We also demonstrate that some FRBs live in clean environments that do not absorb or scatter low-frequency radiation.Comment: 50 pages, 14 figures, 3 tables, submitte

Deep submarine infiltration of altered geothermal groundwater on the south Chilean Margin

Submarine groundwater discharge is increasingly recognized as an important component of the oceanic geochemical budget, but knowledge of the distribution of this phenomenon is limited. To date, reports of meteoric inputs to marine sediments are typically limited to shallow shelf and coastal environments, whereas contributions of freshwater along deeper sections of tectonically active margins have generally been attributed to silicate diagenesis, mineral dehydration, or methane hydrate dissociation. Here, using geochemical fingerprinting of pore water data from Site J1003 recovered from the Chilean Margin during D/V JOIDES Resolution Expedition 379 T, we show that substantial offshore freshening reflects deep and focused contributions of meteorically modified geothermal groundwater, which is likely sourced from a reservoir ~2.8 km deep in the Aysén region of Patagonia and infiltrated marine sediments during or shortly after the last glacial period. Emplacement of fossil groundwaters reflects an apparently ubiquitous phenomenon in margin sediments globally, but our results now identify an unappreciated locus of deep submarine groundwater discharge along active margins with potential implications for coastal biogeochemical processes and tectonic instability.publishedVersio

Recruitment and Activation of Pancreatic Stellate Cells from the Bone Marrow in Pancreatic Cancer: A Model of Tumor-Host Interaction

BACKGROUND AND AIMS: Chronic pancreatitis and pancreatic cancer are characterised by extensive stellate cell mediated fibrosis, and current therapeutic development includes targeting pancreatic cancer stroma and tumor-host interactions. Recent evidence has suggested that circulating bone marrow derived stem cells (BMDC) contribute to solid organs. We aimed to define the role of circulating haematopoietic cells in the normal and diseased pancreas. METHODS: Whole bone marrow was harvested from male β-actin-EGFP donor mice and transplanted into irradiated female recipient C57/BL6 mice. Chronic pancreatitis was induced with repeat injections of caerulein, while carcinogenesis was induced with an intrapancreatic injection of dimethylbenzanthracene (DMBA). Phenotype of engrafted donor-derived cells within the pancreas was assessed by immunohistochemistry, immunofluorescence and in situ hybridisation. RESULTS: GFP positive cells were visible in the exocrine pancreatic epithelia from 3 months post transplantation. These exhibited acinar morphology and were positive for amylase and peanut agglutinin. Mice administered caerulein developed chronic pancreatitis while DMBA mice exhibited precursor lesions and pancreatic cancer. No acinar cells were identified to be donor-derived upon cessation of cerulein treatment, however rare occurrences of bone marrow-derived acinar cells were observed during pancreatic regeneration. Increased recruitment of BMDC was observed within the desmoplastic stroma, contributing to the activated pancreatic stellate cell (PaSC) population in both diseases. Expression of stellate cell markers CELSR3, PBX1 and GFAP was observed in BMD cancer-associated PaSCs, however cancer-associated, but not pancreatitis-associated BMD PaSCs, expressed the cancer PaSC specific marker CELSR3. CONCLUSIONS: This study demonstrates that BMDC can incorporate into the pancreas and adopt the differentiated state of the exocrine compartment. BMDC that contribute to the activated PaSC population in chronic pancreatitis and pancreatic cancer have different phenotypes, and may play important roles in these diseases. Further, bone marrow transplantation may provide a useful model for the study of tumor-host interactions in cancer and pancreatitis

Women's Preferences for Treatment of Perinatal Depression and Anxiety : A Discrete Choice Experiment

Perinatal depression and anxiety (PNDA) are an international healthcare priority, associated with significant short- and long-term problems for women, their children and families. Effective treatment is available but uptake is suboptimal: some women go untreated whilst others choose treatments without strong evidence of efficacy. Better understanding of women's preferences for treatment is needed to facilitate uptake of effective treatment. To address this issue, a discrete choice experiment (DCE) was administered to 217 pregnant or postnatal women in Australia, who were recruited through an online research company and had similar sociodemographic characteristics to Australian data for perinatal women. The DCE investigated preferences regarding cost, treatment type, availability of childcare, modality and efficacy. Data were analysed using logit-based models accounting for preference and scale heterogeneity. Predicted probability analysis was used to explore relative attribute importance and policy change scenarios, including how these differed by women's sociodemographic characteristics. Cost and treatment type had the greatest impact on choice, such that a policy of subsidising effective treatments was predicted to double their uptake compared with the base case. There were differences in predicted uptake associated with certain sociodemographic characteristics: for example, women with higher educational attainment were more likely to choose effective treatment. The findings suggest policy directions for decision makers whose goal is to reduce the burden of PNDA on women, their children and families

Buses, cars, bicycles and walkers the influence of the type of human transport on the flight responses of waterbirds

One way to manage disturbance to waterbirds in natural areas where humans require access is to promote the occurrence of stimuli for which birds tolerate closer approaches, and so cause fewer responses. We conducted 730 experimental approaches to 39 species of waterbird, using five stimulus types (single walker, three walkers, bicycle, car and bus) selected to mimic different human management options available for a controlled access, Ramsar-listed wetland. Across species, where differences existed (56% of 25 cases), motor vehicles always evoked shorter flight-initiation distances (FID) than humans on foot. The influence of stimulus type on FID varied across four species for which enough data were available for complete cross-stimulus analysis. All four varied FID in relation to stimuli, differing in 4 to 7 of 10 possible comparisons. Where differences occurred, the effect size was generally modest, suggesting that managing stimulus type (e.g. by requiring people to use vehicles) may have species-specific, modest benefits, at least for the waterbirds we studied. However, different stimulus types have different capacities to reduce the frequency of disturbance (i.e. by carrying more people) and vary in their capacity to travel around important habita

Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software

We provide a user guide on the analysis of data (including best–worst and best–best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a ‘way in’ for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks