FoxP2 isoforms delineate spatiotemporal transcriptional networks for vocal learning in the zebra finch.

Human speech is one of the few examples of vocal learning among mammals yet ~half of avian species exhibit this ability. Its neurogenetic basis is largely unknown beyond a shared requirement for FoxP2 in both humans and zebra finches. We manipulated FoxP2 isoforms in Area X, a song-specific region of the avian striatopallidum analogous to human anterior striatum, during a critical period for song development. We delineate, for the first time, unique contributions of each isoform to vocal learning. Weighted gene coexpression network analysis of RNA-seq data revealed gene modules correlated to singing, learning, or vocal variability. Coexpression related to singing was found in juvenile and adult Area X whereas coexpression correlated to learning was unique to juveniles. The confluence of learning and singing coexpression in juvenile Area X may underscore molecular processes that drive vocal learning in young zebra finches and, by analogy, humans

Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space

This article provides an example of the ways in which remote sensing, Earth observation, and machine learning can be deployed to provide the most up to date quantitative portrait of the South Asian ‘Brick Belt’, with a view to understanding the extent of the prevalence of modern slavery and exploitative labour. This analysis represents the first of its kind in estimating the spatiotemporal patterns in the Bull’s Trench Kilns across the Brick Belt, as well as its connections with various UN Sustainable Development Goals (SDGs). With a principal focus on Sustainable Development Goal Target 8.7 regarding the effective measures to end modern slavery by 2030, the article provides additional evidence on the intersections that exist between SDG 8.7 and those relating to urbanisation (SDG 11, 12), environmental degradation and pollution (SDG 3, 14, 15), and climate change (SDG 13). Our findings are then used to make a series of pragmatic suggestions for mitigating the most extreme SDG risks associated with brick production in ways that can improve human lives and human freedom

Classical Processing Requirements for a Topological Quantum Computing System

Dedicated research into the design and construction of a large scale Quantum Information Processing (QIP) system is a complicated task. The design of an experimentally feasible quantum processor must draw upon results in multiple fields; from experimental efforts in system control and fabrication through to far more abstract areas such as quantum algorithms and error correction. Recently, the adaptation of topological coding models to physical systems in optics has illustrated a possible long term pathway to truly large scale QIP. As the topological model has well defined protocols for Quantum Error Correction (QEC) built in as part of its construction, a more grounded analysis of the {\em classical} processing requirements is possible. In this paper we analyze the requirements for a classical processing system, designed specifically for the topological cluster state model. We demonstrate that via extensive parallelization, the construction of a classical "front-end" system capable of processing error correction data for a large topological computer is possible today.Comment: 14 Pages, 14 Figures (Revised version in response to referee comments

Diagnostic Accuracy of a High-Sensitivity Cardiac Troponin Assay with a Single Serum Test in the Emergency Department.

OBJECTIVES: We sought to evaluate diagnostic accuracy of a high-sensitivity cardiac troponin I (hs-cTnI) assay for acute coronary syndromes (ACS) in the emergency department (ED). The assay has high precision at low concentrations and can detect cTnI in 96.8% of healthy individuals. METHODS: In successive prospective multicenter studies ("testing" and "validation"), we included ED patients with suspected ACS. We drew blood for hs-cTnI [Singulex Clarity® cTnI; 99th percentile, 8.67 ng/L; limit of detection (LoD), 0.08 ng/L] on arrival. Patients also underwent hs-cTnT (Roche Elecsys) testing over ≥3 h. The primary outcome was an adjudicated diagnosis of ACS, defined as acute myocardial infarction (AMI; prevalent or incident), death, or revascularization within 30 days. RESULTS: The testing and validation studies included 665 and 2470 patients, respectively, of which 94 (14.1%) and 565 (22.9%) had ACS. At a 1.5-ng/L cutoff, hs-cTnI had good sensitivity for AMI in both studies (98.7% and 98.1%, respectively) and would have "ruled out" 40.1% and 48.9% patients. However, sensitivity was lower for ACS (95.7% and 90.6%, respectively). At a 0.8-ng/L cutoff, sensitivity for ACS was higher (97.5% and 97.9%, ruling out 28.6% patients in each cohort). The hs-cTnT assay had similar performance at the LoD (24.6% ruled out; 97.2% sensitivity for ACS). CONCLUSIONS: The hs-cTnI assay could immediately rule out AMI in 40% of patients and ACS in >25%, with similar accuracy to hs-cTnT at the LoD. Because of its high precision at low concentrations, this hs-cTnI assay has favorable characteristics for this clinical application

High-Throughput Analysis of Lung Immune Cells in a Combined Murine Model of Agriculture Dust-Triggered Airway Inflammation With Rheumatoid Arthritis

Rheumatoid arthritis (RA)-associated lung disease is a leading cause of mortality in RA, yet the mechanisms linking lung disease and RA remain unknown. Using an established murine model of RA-associated lung disease combining collagen-induced arthritis (CIA) with organic dust extract (ODE)-induced airway inflammation, differences among lung immune cell populations were analyzed by single cell RNA-sequencing. Additionally, four lung myeloid-derived immune cell populations including macrophages, monocytes/macrophages, monocytes, and neutrophils were isolated by fluorescence cell sorting and gene expression was determined by NanoString analysis. Unsupervised clustering revealed 14 discrete clusters among Sham, CIA, ODE, and CIA+ODE treatment groups: 3 neutrophils (inflammatory, resident/transitional, autoreactive/suppressor), 5 macrophages (airspace, differentiating/recruited, recruited, resident/interstitial, and proliferative airspace), 2 T-cells (differentiating and effector), and a single cluster each of inflammatory monocytes, dendritic cells, B-cells and natural killer cells. Inflammatory monocytes, autoreactive/suppressor neutrophils, and recruited/differentiating macrophages were predominant with arthritis induction (CIA and CIA+ODE). By specific lung cell isolation, several interferon-related and autoimmune genes were disproportionately expressed among CIA and CIA+ODE (e.g. Oasl1, Oas2, Ifit3, Gbp2, Ifi44, and Zbp1), corresponding to RA and RA-associated lung disease. Monocytic myeloid-derived suppressor cells were reduced, while complement genes (e.g. C1s1 and Cfb) were uniquely increased in CIA+ODE mice across cell populations. Recruited and inflammatory macrophages/monocytes and neutrophils expressing interferon-, autoimmune-, and complement-related genes might contribute towards pro-fibrotic inflammatory lung responses following airborne biohazard exposures in setting of autoimmune arthritis and could be predictive and/or targeted to reduce disease burden

Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space

This article provides an example of the ways in which remote sensing, Earth observation, and machine learning can be deployed to provide the most up to date quantitative portrait of the South Asian ‘Brick Belt’, with a view to understanding the extent of the prevalence of modern slavery and exploitative labour. This analysis represents the first of its kind in estimating the spatiotemporal patterns in the Bull’s Trench Kilns across the Brick Belt, as well as its connections with various UN Sustainable Development Goals (SDGs). With a principal focus on Sustainable Development Goal Target 8.7 regarding the effective measures to end modern slavery by 2030, the article provides additional evidence on the intersections that exist between SDG 8.7 and those relating to urbanisation (SDG 11, 12), environmental degradation and pollution (SDG 3, 14, 15), and climate change (SDG 13). Our findings are then used to make a series of pragmatic suggestions for mitigating the most extreme SDG risks associated with brick production in ways that can improve human lives and human freedom