Multi-Trajectory Automatic Ground Collision Avoidance System with Flight Tests (Project Have ESCAPE)

Multi-trajectory automatic collision avoidance techniques for heavy-type aircraft are explored to increase aviation safety procedures and decrease losses due to controlled flight into terrain. Additionally, this research includes flight test results from the United States Test Pilot School’s Test Management Project (TMP) titled Have Emergency Safe Calculated Autonomous Preplanned Exit (ESCAPE). Currently, the heavy aircraft community lacks an automatic collision avoidance system that has proven to save lives in fighter-type aircraft. The tested algorithm includes both a 3-path and a 5-path avoidance technique that is compared to an optimal solution which minimizes aircraft control to avoid terrain. The research utilizes Level 1 Digital Terrain Elevation Data (DTED) to analyze the terrain and a 3-Degrees of Freedom (DOF) Equations of Motion (EOM) model to predict potential terrain avoidance paths for the aircraft based on current location. The algorithm then waits until all paths collide and automatically activates the path with the longest time until collision with an appropriate time safety margin. The research also characterizes terrain based on changing slope and presents a new classification of aircraft based on performance capabilities. The result was used for algorithm parameter specification of path execution times and pre-planned maneuver creation so that the system can be modified for a wide variety of aircraft. Finally, the algorithm was flight tested against DTED in a simulated environment using the Calspan Learjet to determine actual 3 and 5- path performance, parameter specification, and comparison to the optimal solution. The important recommendations include a need for flexible entry parameters based on current aircraft state, continued evaluation of the terrain during avoidance maneuver execution, and more precise control of the aircraft flight path angle. Finally, due to comparison with the optimal solution, it is concluded that an acceptable terrain avoidance algorithm is possible using only a 3-path solution given that all three paths include a climbing maneuver

Preparation of Single-Cell RNA-Seq Libraries for Next Generation Sequencing

For the past several decades, due to technical limitations, the field of transcriptomics has focused on population-level measurements that can mask significant differences between individual cells. With the advent of single-cell RNA-Seq, it is now possible to profile the responses of individual cells at unprecedented depth and thereby uncover, transcriptome-wide, the heterogeneity that exists within these populations. This unit describes a method that merges several important technologies to produce, in high-throughput, single-cell RNA-Seq libraries. Complementary DNA (cDNA) is made from full-length mRNA transcripts using a reverse transcriptase that has terminal transferase activity. This, when combined with a second “template-switch” primer, allows for cDNAs to be constructed that have two universal priming sequences. Following preamplification from these common sequences, Nextera XT is used to prepare a pool of 96 uniquely indexed samples ready for Illumina sequencing.National Institutes of Health (U.S.) (Centers of Excellence in Genomic Science 1P50HG006193-01)National Institutes of Health (U.S.) (Pioneer Award DP1OD003958-01)Broad Institute of MIT and HarvardHoward Hughes Medical InstituteKlarman Cell Observator

Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons

Single-cell RNA sequencing (RNA-Seq) provides rich information about cell types and states. However, it is difficult to capture rare dynamic processes, such as adult neurogenesis, because isolation of rare neurons from adult tissue is challenging and markers for each phase are limited. Here, we develop Div-Seq, which combines scalable single-nucleus RNA-Seq (sNuc-Seq) with pulse labeling of proliferating cells by 5-ethynyl-2′-deoxyuridine (EdU) to profile individual dividing cells. sNuc-Seq and Div-Seq can sensitively identify closely related hippocampal cell types and track transcriptional dynamics of newborn neurons within the adult hippocampal neurogenic niche, respectively. We also apply Div-Seq to identify and profile rare newborn neurons in the adult spinal cord, a noncanonical neurogenic region. sNuc-Seq and Div-Seq open the way for unbiased analysis of diverse complex tissues.National Institute of Mental Health (U.S.) (Grant U01MH105960)National Institute of Mental Health (U.S.) (Grant 5DP1-MH100706)National Institute of Mental Health (U.S.) (Grant 1R01-MH110049

Landscape of stimulation-responsive chromatin across diverse human immune cells.

A hallmark of the immune system is the interplay among specialized cell types transitioning between resting and stimulated states. The gene regulatory landscape of this dynamic system has not been fully characterized in human cells. Here we collected assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA sequencing data under resting and stimulated conditions for up to 32 immune cell populations. Stimulation caused widespread chromatin remodeling, including response elements shared between stimulated B and T cells. Furthermore, several autoimmune traits showed significant heritability in stimulation-responsive elements from distinct cell types, highlighting the importance of these cell states in autoimmunity. Allele-specific read mapping identified variants that alter chromatin accessibility in particular conditions, allowing us to observe evidence of function for a candidate causal variant that is undetected by existing large-scale studies in resting cells. Our results provide a resource of chromatin dynamics and highlight the need to characterize the effects of genetic variation in stimulated cells

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and phenotypic output1, 2, 3, 4, 5, with important functional consequences4, 5. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs1, 2 or proteins5, 6 simultaneously, because genomic profiling methods3 could not be applied to single cells until very recently7, 8, 9, 10. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.National Institutes of Health (U.S.) (NIH Postdoctoral Fellowship (1F32HD075541-01))Charles H. Hood Foundation (Postdoctoral Fellowship)National Institutes of Health (U.S.) (NIH grant U54 AI057159)National Institutes of Health (U.S.) (NIH New Innovator Award (DP2 OD002230))National Institutes of Health (U.S.) (NIH CEGS Award (1P50HG006193-01))National Institutes of Health (U.S.) (NIH Pioneer Awards (5DP1OD003893-03))National Institutes of Health (U.S.) (NIH Pioneer Awards (DP1OD003958-01))Broad Institute of MIT and HarvardBroad Institute of MIT and Harvard (Klarman Cell Observatory

Single-cell RNA-seq reveals dynamic paracrine control of cellular variation

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Here we sequence single-cell RNA-seq libraries prepared from over 1,700 primary mouse bone-marrow-derived dendritic cells spanning several experimental conditions. We find substantial variation between identically stimulated dendritic cells, in both the fraction of cells detectably expressing a given messenger RNA and the transcript’s level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a ‘core’ module of antiviral genes is expressed very early by a few ‘precocious’ cells in response to uniform stimulation with a pathogenic component, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analysing dendritic cells from knockout mice, and modulating secretion and extracellular signalling, we show that this response is coordinated by interferon-mediated paracrine signalling from these precocious cells. Notably, preventing cell-to-cell communication also substantially reduces variability between cells in the expression of an early-induced ‘peaked’ inflammatory module, suggesting that paracrine signalling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations can use to establish complex dynamic responses.National Human Genome Research Institute (U.S.). Centers of Excellence in Genomic Science (1P50HG006193-01)National Institutes of Health (U.S.). Pioneer Award (DP1OD003958-01)Howard Hughes Medical InstituteBroad Institute of MIT and Harvard. Klarman Cell Observator

Single cell RNA Seq reveals dynamic paracrine control of cellular variation

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis, and function of gene expression variation between seemingly identical cells. Here, we sequence single-cell RNA-Seq libraries prepared from over 1,700 primary mouse bone marrow derived dendritic cells (DCs) spanning several experimental conditions. We find substantial variation between identically stimulated DCs, in both the fraction of cells detectably expressing a given mRNA and the transcript’s level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a “core” module of antiviral genes is expressed very early by a few “precocious” cells, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analyzing DCs from knockout mice, and modulating secretion and extracellular signaling, we show that this response is coordinated via interferon-mediated paracrine signaling. Surprisingly, preventing cell-to-cell communication also substantially reduces variability in the expression of an early-induced “peaked” inflammatory module, suggesting that paracrine signaling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations use to establish complex dynamic responses

Whole exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two prostate cancer patients including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early-trunk and 56 metastatic-trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic

Rethinking energy, climate and security: a critical analysis of energy security in the US

Understanding the complicated relationship between energy, climate and security is vital both to the study of international relations and to ensure the continued survival of a world increasingly threatened by environmental change. Climate change is largely caused by burning fossil fuels for energy, but while discussions on the climate consider the role of energy, energy security debates largely overlook climate concerns. This article traces the separation between energy and climate through an analysis of US energy security discourse and policy. It shows that energy security is continually constructed as national security, which enables very particular policy choices and prioritises it above climate concerns. Thus, in many cases, policies undertaken in the name of energy security contribute directly to climate insecurity. The article argues that the failure to consider securing the climate as inherently linked to energy security is not just problematic, but, given global warming, potentially harmful. Consequently, any approach to dealing with climate change has to begin by rethinking energy security and security more broadly, as national (energy) security politics no longer provides security in any meaningful sense

Novel Textbook Outcomes following emergency laparotomy:Delphi exercise

Background: Textbook outcomes are composite outcome measures that reflect the ideal overall experience for patients. There are many of these in the elective surgery literature but no textbook outcomes have been proposed for patients following emergency laparotomy. The aim was to achieve international consensus amongst experts and patients for the best Textbook Outcomes for non-trauma and trauma emergency laparotomy. Methods: A modified Delphi exercise was undertaken with three planned rounds to achieve consensus regarding the best Textbook Outcomes based on the category, number and importance (Likert scale of 1–5) of individual outcome measures. There were separate questions for non-trauma and trauma. A patient engagement exercise was undertaken after round 2 to inform the final round. Results: A total of 337 participants from 53 countries participated in all three rounds of the exercise. The final Textbook Outcomes were divided into ‘early’ and ‘longer-term’. For non-trauma patients the proposed early Textbook Outcome was ‘Discharged from hospital without serious postoperative complications (Clavien–Dindo ≥ grade III; including intra-abdominal sepsis, organ failure, unplanned re-operation or death). For trauma patients it was ‘Discharged from hospital without unexpected transfusion after haemostasis, and no serious postoperative complications (adapted Clavien–Dindo for trauma ≥ grade III; including intra-abdominal sepsis, organ failure, unplanned re-operation on or death)’. The longer-term Textbook Outcome for both non-trauma and trauma was ‘Achieved the early Textbook Outcome, and restoration of baseline quality of life at 1 year’. Conclusion: Early and longer-term Textbook Outcomes have been agreed by an international consensus of experts for non-trauma and trauma emergency laparotomy. These now require clinical validation with patient data.</p