Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels

ACKNOWLEDGEMENTS We thank Dennis Ojima and Daniel L. Sanchez for their encouragement on this topic. The authors gratefully acknowledge partial support as follows: J.L.F., L.R.L., T.L.R., E.A.H.S., and J.J.S., the Sao Paulo Research Foundation (FAPESP grant# 2014/26767-9); J.L.F., L.R.L., K.P., and T.L.R., The Center for Bioenergy Innovation, a U.S. Department of Energy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science (grant# DE-AC05-00OR22725); L.R.L., the Sao Paulo Research Foundation, and the Link Foundation; J.L.F. and K.P., USDA/NIFA (grant# 2013-68005-21298 and 2017-67019-26327); T.L.R., USDA/NIFA (grant# 2012-68005-19703); D.S.L. and S.P.L., the Energy Biosciences Institute. Data availability The DayCent model (https://www2.nrel.colostate.edu/projects/daycent/) is freely available upon request. Specification of DayCent model runs and automated model initialization, calibration, scenario simulation, results analysis, and figure generation were implemented in Python 2.7, using the numpy module for data processing and the matplotlib module for figure generation. Analysis code is available in a version-controlled repository (https://github.com/johnlfield/Ecosystem_dynamics). A working copy of the code, all associated DayCent model inputs, and analysis outputs are also available in an online data repository (https://figshare.com/s/4c14ec168bd550db4bad; note this URL is for accessing a private version of the repository, and will eventually be replaced with an updated URL for the public version of the repository, which will only be accessible after the journal-specified embargo date).Peer reviewedPostprintPublisher PD

The synthesis of a series of adenosine A3 receptor agonists

A series of 1′-(6-aminopurin-9-yl)-1′-deoxy-N-methyl-β-D-ribofuranuronamides that were characterised by 2-dialkylamino-7-methyloxazolo[4,5-b]pyridin-5-ylmethyl substituents on N6 of interest for screening as selective adenosine A3 receptor agonists, have been synthesised. This work involved the synthesis of 2-dialkylamino-5-aminomethyl-7-methyloxazolo[4,5-b]pyridines and analogues that were coupled with the known 1′-(6-chloropurin-9-yl)-1′-deoxy-N-methyl-β-D-ribofuranuronamide. The oxazolo[4,5-b]pyridines were synthesized by regioselective functionalisation of 2,4-dimethylpyridine N-oxides. The regioselectivities of these reactions were found to depend upon the nature of the heterocycle with 2-dimethylamino-5,7-dimethyloxazolo[4,5-b]pyridine-N-oxide undergoing regioselective functionalisation at the 7-methyl group on reaction with trifluoroacetic anhydride in contrast to the reaction of 4,6-dimethyl-3-hydroxypyridine-N-oxide with acetic anhydride that resulted in functionalisation of the 6-methyl group. To optimise selectivity for the A3 receptor, 5-aminomethyl-7-bromo-2-dimethylamino-4-[(3-methylisoxazol-5-yl)methoxy]benzo[d]oxazole was synthesised and coupled with the 1′-(6-chloropurin-9-yl)-1′-deoxy-N-methyl-β-D-ribofuranuronamide. The products were active as selective adenosine A3 agonists

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level

Spectroscopic Characterization of Galaxy Clusters in RCS-1: Spectroscopic Confirmation, Redshift Accuracy, and Dynamical Mass–Richness Relation

We present follow-up spectroscopic observations of galaxy clusters from the first Red-sequence Cluster Survey (RCS-1). This work focuses on two samples, a lower redshift sample of ∼30 clusters ranging in redshift from z ∼ 0.2–0.6 observed with multiobject spectroscopy (MOS) on 4–6.5-m class telescopes and a z ∼ 1 sample of ∼10 clusters 8-m class telescope observations. We examine the detection efficiency and redshift accuracy of the now widely used red-sequence technique for selecting clusters via overdensities of red-sequence galaxies. Using both these data and extended samples including previously published RCS-1 spectroscopy and spectroscopic redshifts from SDSS, we find that the red-sequence redshift using simple two-filter cluster photometric redshifts is accurate to σz ≈ 0.035(1 + z) in RCS-1. This accuracy can potentially be improved with better survey photometric calibration. For the lower redshift sample, ∼5 per cent of clusters show some (minor) contamination from secondary systems with the same red-sequence intruding into the measurement aperture of the original cluster. At z ∼ 1, the rate rises to ∼20 per cent. Approximately ten  per cent of projections are expected to be serious, where the two components contribute significant numbers of their red-sequence galaxies to another cluster. Finally, we present a preliminary study of the mass–richness calibration using velocity dispersions to probe the dynamical masses of the clusters. We find a relation broadly consistent with that seen in the local universe from the WINGS sample at z ∼ 0.05

Percent atheroma volume: Optimal variable to report whole-heart atherosclerotic plaque burden with coronary CTA, the PARADIGM study.

BACKGROUND AND AIMS:Different methodologies to report whole-heart atherosclerotic plaque on coronary computed tomography angiography (CCTA) have been utilized. We examined which of the three commonly used plaque burden definitions was least affected by differences in body surface area (BSA) and sex. METHODS:The PARADIGM study includes symptomatic patients with suspected coronary atherosclerosis who underwent serial CCTA >2 years apart. Coronary lumen, vessel, and plaque were quantified from the coronary tree on a 0.5 mm cross-sectional basis by a core-lab, and summed to per-patient. Three quantitative methods of plaque burden were employed: (1) total plaque volume (PV) in mm3, (2) percent atheroma volume (PAV) in % [which equaled: PV/vessel volume * 100%], and (3) normalized total atheroma volume (TAVnorm) in mm3 [which equaled: PV/vessel length * mean population vessel length]. Only data from the baseline CCTA were used. PV, PAV, and TAVnorm were compared between patients in the top quartile of BSA vs the remaining, and between sexes. Associations between vessel volume, BSA, and the three plaque burden methodologies were assessed. RESULTS:The study population comprised 1479 patients (age 60.7 ± 9.3 years, 58.4% male) who underwent CCTA. A total of 17,649 coronary artery segments were evaluated with a median of 12 (IQR 11-13) segments per-patient (from a 16-segment coronary tree). Patients with a large BSA (top quartile), compared with the remaining patients, had a larger PV and TAVnorm, but similar PAV. The relation between larger BSA and larger absolute plaque volume (PV and TAVnorm) was mediated by the coronary vessel volume. Independent from the atherosclerotic cardiovascular disease risk (ASCVD) score, vessel volume correlated with PV (P < 0.001), and TAVnorm (P = 0.003), but not with PAV (P = 0.201). The three plaque burden methods were equally affected by sex. CONCLUSIONS:PAV was less affected by patient's body surface area then PV and TAVnorm and may be the preferred method to report coronary atherosclerotic burden

A high-resolution map of human evolutionary constraint using 29 mammals.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease

Gut microbial β-glucuronidases influence endobiotic homeostasis and are modulated by diverse therapeutics

Hormones and neurotransmitters are essential to homeostasis, and their disruptions are connected to diseases ranging from cancer to anxiety. The differential reactivation of endobiotic glucuronides by gut microbial β-glucuronidase (GUS) enzymes may influence interindividual differences in the onset and treatment of disease. Using multi-omic, in vitro, and in vivo approaches, we show that germ-free mice have reduced levels of active endobiotics and that distinct gut microbial Loop 1 and FMN GUS enzymes drive hormone and neurotransmitter reactivation. We demonstrate that a range of FDA-approved drugs prevent this reactivation by intercepting the catalytic cycle of the enzymes in a conserved fashion. Finally, we find that inhibiting GUS in conventional mice reduces free serotonin and increases its inactive glucuronide in the serum and intestines. Our results illuminate the indispensability of gut microbial enzymes in sustaining endobiotic homeostasis and indicate that therapeutic disruptions of this metabolism promote interindividual response variabilities