Improved atmospheric constraints on Southern Ocean CO2 exchange.

We present improved estimates of air-sea CO2 exchange over three latitude bands of the Southern Ocean using atmospheric CO2 measurements from global airborne campaigns and an atmospheric 4-box inverse model based on a mass-indexed isentropic coordinate (Mθe). These flux estimates show two features not clearly resolved in previous estimates based on inverting surface CO2 measurements: a weak winter-time outgassing in the polar region and a sharp phase transition of the seasonal flux cycles between polar/subpolar and subtropical regions. The estimates suggest much stronger summer-time uptake in the polar/subpolar regions than estimates derived through neural-network interpolation of pCO2 data obtained with profiling floats but somewhat weaker uptake than a recent study by Long et al. [Science 374, 1275-1280 (2021)], who used the same airborne data and multiple atmospheric transport models (ATMs) to constrain surface fluxes. Our study also uses moist static energy (MSE) budgets from reanalyses to show that most ATMs tend to have excessive diabatic mixing (transport across moist isentrope, θe, or Mθe surfaces) at high southern latitudes in the austral summer, which leads to biases in estimates of air-sea CO2 exchange. Furthermore, we show that the MSE-based constraint is consistent with an independent constraint on atmospheric mixing based on combining airborne and surface CO2 observations.

Excess methane emissions from shallow water platforms elevate the carbon intensity of US Gulf of Mexico oil and gas production.

The Gulf of Mexico is the largest offshore fossil fuel production basin in the United States. Decisions on expanding production in the region legally depend on assessments of the climate impact of new growth. Here, we collect airborne observations and combine them with previous surveys and inventories to estimate the climate impact of current field operations. We evaluate all major on-site greenhouse gas emissions, carbon dioxide (CO2) from combustion, and methane from losses and venting. Using these findings, we estimate the climate impact per unit of energy of produced oil and gas (the carbon intensity). We find high methane emissions (0.60 Tg/y [0.41 to 0.81, 95% confidence interval]) exceeding inventories. This elevates the average CI of the basin to 5.3 g CO2e/MJ [4.1 to 6.7] (100-y horizon) over twice the inventories. The CI across the Gulf varies, with deep water production exhibiting a low CI dominated by combustion emissions (1.1 g CO2e/MJ), while shallow federal and state waters exhibit an extraordinarily high CI (16 and 43 g CO2e/MJ) primarily driven by methane emissions from central hub facilities (intermediaries for gathering and processing). This shows that production in shallow waters, as currently operated, has outsized climate impact. To mitigate these climate impacts, methane emissions in shallow waters must be addressed through efficient flaring instead of venting and repair, refurbishment, or abandonment of poorly maintained infrastructure. We demonstrate an approach to evaluate the CI of fossil fuel production using observations, considering all direct production emissions while allocating to all fossil products.

Cholinergic regulation of vascular endothelial function by human ChAT+ T cells.

Endothelial dysfunction and impaired vasodilation are linked with adverse cardiovascular events. T lymphocytes expressing choline acetyltransferase (ChAT), the enzyme catalyzing biosynthesis of the vasorelaxant acetylcholine (ACh), regulate vasodilation and are integral to the cholinergic antiinflammatory pathway in an inflammatory reflex in mice. Here, we found that human T cell ChAT mRNA expression was induced by T cell activation involving the PI3K signaling cascade. Mechanistically, we identified that ChAT mRNA expression was induced following the attenuation of RE-1 Silencing Transcription factor REST-mediated methylation of the ChAT promoter, and that ChAT mRNA expression levels were up-regulated by GATA3 in human T cells. In functional experiments, T cell-derived ACh increased endothelial nitric oxide-synthase activity, promoted vasorelaxation, and reduced vascular endothelial activation and promoted barrier integrity by a cholinergic mechanism. Further, we observed that survival in a cohort of patients with severe circulatory failure correlated with their relative frequency of ChAT +CD4+ T cells in blood. These findings on ChAT+ human T cells provide a mechanism for cholinergic immune regulation of vascular endothelial function in human inflammation.

In Situ Sampling of NOx Emissions from United States Natural Gas Flares Reveals Heavy-Tail Emission Characteristic.

Natural gas flaring is a common practice employed in many United States (U.S.) oil and gas regions to dispose of gas associated with oil production. Combustion of predominantly hydrocarbon gas results in the production of nitrogen oxides (NOx). Here, we present a large field data set of in situ sampling of real world flares, quantifying flaring NOx production in major U.S. oil production regions: the Bakken, Eagle Ford, and Permian. We find that a single emission factor does not capture the range of the observed NOx emission factors within these regions. For all three regions, the median emission factors fall within the range of four emission factors used by the Texas Commission for Environmental Quality. In the Bakken and Permian, the distribution of emission factors exhibits a heavy tail such that basin-average emission factors are 2-3 times larger than the value employed by the U.S. Environmental Protection Agency. Extrapolation to basin scale emissions using auxiliary satellite assessments of flare volumes indicates that NOx emissions from flares are skewed, with 20%-30% of the flares responsible for 80% of basin-wide flaring NOx emissions. Efforts to reduce flaring volume through alternative gas capture methods would have a larger impact on the NOx oil and gas budget than current inventories indicate.

Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal.

Tropical wetlands contribute ∼30% of the global methane (CH4) budget. Limited observational constraints on tropical wetland CH4 emissions lead to large uncertainties and disparities in representing emissions. In this work, we combine remote sensing observations with atmospheric and wetland models to investigate dry season wetland CH4 emissions from the Pantanal region of South America. We incorporate inundation maps generated from the Cyclone Global Navigation Satellite System (CYGNSS) satellite constellation together with traditional inundation maps to generate an ensemble of wetland CH4 emission realizations. We challenge these realizations with daily satellite observations for May-July when wetland CH4 emission predictions diverge. We find that the CYGNSS inundation products predict larger emissions in May, in better agreement with observations. We use the model ensemble to generate an empirical observational constraint on CH4 emissions independent of choice of inundation map, finding large dry season wetland CH4 emissions (31.7 ± 13.6 and 32.0 ± 20.2 mg CH4/m2/day in May and June/July during 2018/2019, respectively). These May/June/July emissions are 2-3 times higher than current models, suggesting that annual wetland emissions may be higher than traditionally simulated. Observed trends in the early dry season indicate that dynamics during this period are of importance in representing tropical wetland CH4 behaviors.

Temporal Variation and Persistence of Methane Emissions from Shallow Water Oil and Gas Production in the Gulf of Mexico.

Methane emissions from the oil and gas supply chain can be intermittent, posing challenges for monitoring and mitigation efforts. This study examines shallow water facilities in the US Gulf of Mexico with repeat atmospheric observations to evaluate temporal variation in site-specific methane emissions. We combine new and previous observations to develop a longitudinal study, spanning from days to months to almost five years, evaluating the emissions behavior of sites over time. We also define and determine the chance of subsequent detection (CSD): the likelihood that an emitting site will be observed emitting again. The average emitting central hub in the Gulf has a 74% CSD at any time interval. Eight facilities contribute 50% of total emissions and are over 80% persistent with a 96% CSD above 100 kg/h and 46% persistent with a 42% CSD above 1000 kg/h, indicating that large emissions are persistent at certain sites. Forward-looking infrared (FLIR) footage shows many of these sites exhibiting cold venting. This suggests that for offshore, a low sampling frequency over large spatial coverage can capture typical site emissions behavior and identify targets for mitigation. We further demonstrate the preliminary use of space-based observations to monitor offshore emissions over time.

Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

Single cell expression analysis reveals anatomical and cell cycle-dependent transcriptional shifts during heart development.

The heart is a complex organ composed of multiple cell and tissue types. Cardiac cells from different regions of the growing embryonic heart exhibit distinct patterns of gene expression, which are thought to contribute to heart development and morphogenesis. Single cell RNA sequencing allows genome-wide analysis of gene expression at the single cell level. Here, we have analyzed cardiac cells derived from early stage developing hearts by single cell RNA-seq and identified cell cycle gene expression as a major determinant of transcriptional variation. Within cell cycle stage-matched CMs from a given heart chamber, we found that CMs in the G2/M phase downregulated sarcomeric and cytoskeletal markers. We also identified cell location-specific signaling molecules that may influence the proliferation of other nearby cell types. Our data highlight how variations in cell cycle activity selectively promote cardiac chamber growth during development, reveal profound chamber-specific cell cycle-linked transcriptional shifts, and open the way to deeper understanding of pathogenesis of congenital heart disease.

Quantifying Regional Methane Emissions in the New Mexico Permian Basin with a Comprehensive Aerial Survey.

Limiting emissions of climate-warming methane from oil and gas (O&G) is a major opportunity for short-term climate benefits. We deploy a basin-wide airborne survey of O&G extraction and transportation activities in the New Mexico Permian Basin, spanning 35 923 km2, 26 292 active wells, and over 15 000 km of natural gas pipelines using an independently validated hyperspectral methane point source detection and quantification system. The airborne survey repeatedly visited over 90% of the active wells in the survey region throughout October 2018 to January 2020, totaling approximately 98 000 well site visits. We estimate total O&G methane emissions in this area at 194 (+72/-68, 95% CI) metric tonnes per hour (t/h), or 9.4% (+3.5%/-3.3%) of gross gas production. 50% of observed emissions come from large emission sources with persistence-averaged emission rates over 308 kg/h. The fact that a large sample size is required to characterize the heavy tail of the distribution emphasizes the importance of capturing low-probability, high-consequence events through basin-wide surveys when estimating regional O&G methane emissions.

Interpreting contemporary trends in atmospheric methane.

Atmospheric methane plays a major role in controlling climate, yet contemporary methane trends (1982-2017) have defied explanation with numerous, often conflicting, hypotheses proposed in the literature. Specifically, atmospheric observations of methane from 1982 to 2017 have exhibited periods of both increasing concentrations (from 1982 to 2000 and from 2007 to 2017) and stabilization (from 2000 to 2007). Explanations for the increases and stabilization have invoked changes in tropical wetlands, livestock, fossil fuels, biomass burning, and the methane sink. Contradictions in these hypotheses arise because our current observational network cannot unambiguously link recent methane variations to specific sources. This raises some fundamental questions: (i) What do we know about sources, sinks, and underlying processes driving observed trends in atmospheric methane? (ii) How will global methane respond to changes in anthropogenic emissions? And (iii), What future observations could help resolve changes in the methane budget? To address these questions, we discuss potential drivers of atmospheric methane abundances over the last four decades in light of various observational constraints as well as process-based knowledge. While uncertainties in the methane budget exist, they should not detract from the potential of methane emissions mitigation strategies. We show that net-zero cost emission reductions can lead to a declining atmospheric burden, but can take three decades to stabilize. Moving forward, we make recommendations for observations to better constrain contemporary trends in atmospheric methane and to provide mitigation support.

Balancing precision versus cohort transcriptomic analysis of acute and recovery phase of viral bronchiolitis.

Viral infections affecting the lower respiratory tract place enormous burdens on hospitals. As neither vaccines nor antiviral agents exist for many viruses, understanding risk factors and outcomes in each patient using minimally invasive analysis, such as blood, can lead to improved health care delivery. A cohort of PAXgene RNA sequencing of infants admitted with moderate or severe acute bronchiolitis and respiratory syncytial virus were compared with case-control statistical analysis and cohort-based outlier mapping for precision transcriptomics. Patients with severe bronchiolitis had signatures connected to the immune system, interferon signaling, and cytokine signaling, with marked sex differences in XIST, RPS4Y1, KDM5D, and LINC00278 for severity. Several patients had unique secondary infections, cytokine activation, immune responses, biological pathways, and immune cell activation, highlighting the need for defining patient-level transcriptomic signatures. Balancing relative contributions of cohort-based biomarker discoveries with patient's biological responses is needed to understand the totality of mechanisms of adverse outcomes in viral bronchiolitis.

Isolation of Cardiomyocytes Undergoing Mitosis With Complete Cytokinesis.

RATIONALE: Adult human cardiomyocytes do not complete cytokinesis despite passing through the S-phase of the cell cycle. As a result, polyploidization and multinucleation occur. To get a deeper understanding of the mechanisms surrounding division of cardiomyocytes, there is a crucial need for a technique to isolate cardiomyocytes that complete cell division/cytokinesis. OBJECTIVE: Markers of cell cycle progression based on DNA content cannot distinguish between mitotic cardiomyocytes that fail to complete cytokinesis from those cells that undergo true cell division. With the use of molecular beacons (MBs) targeting specific mRNAs, we aimed to identify truly proliferative cardiomyocytes derived from human induced pluripotent stem cells. METHODS AND RESULTS: Fluorescence-activated cell sorting combined with MBs was performed to sort cardiomyocyte populations enriched for mitotic cells. Expressions of cell cycle specific genes were confirmed by means of reverse transcription-quantitative polymerase chain reaction and single-cell RNA sequencing (scRNA-seq) combined with gene signatures of cell cycle progression. We characterized the sorted groups by proliferation assays and time-lapse microscopy which confirmed the proliferative advantage of MB-positive cell populations relative to MB-negative and G2/M populations. Gene expression analysis revealed that the MB-positive cardiomyocyte subpopulation exhibited patterns consistent with the processes of nuclear division, chromosome segregation, and transition from M to G1 phase. The use of dual-MBs targeting CDC20 and SPG20 mRNAs enabled the enrichment of cytokinetic events (CDC20highSPG20high). Interestingly, cells that did not complete cytokinesis and remained binucleated were found to be CDC20lowSPG20high while polyploid cardiomyocytes that replicated DNA but failed to complete karyokinesis were found to be CDC20lowSPG20low. CONCLUSIONS: This study demonstrates a novel alternative to existing DNA content-based approaches for sorting cardiomyocytes with true mitotic potential that can be used to study the unique dynamics of cardiomyocyte nuclei during mitosis. Our technique for sorting live cardiomyocytes undergoing cytokinesis would provide a basis for future studies to uncover mechanisms underlying the development and regeneration of heart tissue.

Drug Repurposing: Claiming the Full Benefit from Drug Development.

PURPOSE OF REVIEW: Drug development has evolved over the years from being one-at-a-time to be massive screens in an industrial manner. Bringing a new therapeutic agent from concept to bedside can take a decade and cost billions of dollars-with most concepts failing along the way. Of the few compounds that make it to clinical testing, less than one out of eight make it to approval. This traditional drug development pipeline is challenging for prevalent diseases and makes the development of new therapeutics for rare diseases financially intractable. RECENT FINDINGS: Repurposing of drugs is an alternative to identify new applications for the thousands of compounds that have already been approved for clinical use. There is now a range of strategies for such efforts that leverage clinical data, pharmacologic data, and/or genomic or transcriptomic data. These strategies, together with examples, are detailed in this review. Drug repurposing bypasses the pre-clinical work and thereby opens up the opportunity to provide targeted treatment at a fraction of the cost that is accompanied with the development from ideation to full approval. Such an approach makes drug discovery for any disease process more efficient but holds particular promise for rare diseases for which there is little to no other viable drug development channel.

Streamlined analysis of LINCS L1000 data with the slinky package for R.

SUMMARY: The L1000 dataset from the NIH LINCS program holds the promise to deconvolute a wide range of biological questions in transcriptional space. However, using this large and decentralized dataset presents its own challenges. The slinky package was created to streamline the process of identifying samples of interest and their corresponding control samples, and loading their associated expression data and metadata. The package can integrate with workflows leveraging the BioConductor collection of tools by encapsulating the L1000 data as a SummarizedExperiment object. AVAILABILITY AND IMPLEMENTATION: Slinky is freely available as an R package at http://bioconductor.org/packages/slinky.

Airborne Assessment of Methane Emissions from Offshore Platforms in the U.S. Gulf of Mexico.

Methane (CH4) emissions from oil and gas activities are large and poorly quantified, with onshore studies showing systematic inventory underestimates. We present aircraft measurements of CH4 emissions from offshore oil and gas platforms collected over the U.S. Gulf of Mexico in January 2018. Flights sampled individual facilities as well as regions of 5-70 facilities. We combine facility-level samples, production data, and inventory estimates to generate an aerial measurement-based inventory of CH4 emissions for the U.S. Gulf of Mexico. We compare our inventory and the Environmental Protection Agency Greenhouse Gas Inventory (GHGI) with regional airborne estimates. The new inventory and regional airborne estimates are consistent with the GHGI in deep water but appear higher for shallow water. For the full U.S. Gulf of Mexico our inventory estimates total emissions of 0.53 Tg CH4/yr [0.40-0.71 Tg CH4/yr, 95% CI] and corresponds to a loss rate of 2.9% [2.2-3.8%] of natural gas production. Our estimate is a factor of 2 higher than the GHGI updated with 2018 platform counts. We attribute this disagreement to incomplete platform counts and emission factors that both underestimate emissions for shallow water platforms and do not account for disproportionately high emissions from large shallow water facilities.

Daily Cropland Soil NOx Emissions Identified by TROPOMI and SMAP.

We use TROPOMI (TROPOspheric Monitoring Instrument) tropospheric nitrogen dioxide (NO2) measurements to identify cropland soil nitrogen oxide (NOx = NO + NO2) emissions at daily to seasonal scales in the U.S. Southern Mississippi River Valley. Evaluating 1.5 years of TROPOMI observations with a box model, we observe seasonality in local NOx enhancements and estimate maximum cropland soil NOx emissions (15-34 ng N m-2 s-1) early in growing season (May-June). We observe soil NOx pulsing in response to daily decreases in volumetric soil moisture (VSM) as measured by the Soil Moisture Active Passive (SMAP) satellite. Daily NO2 enhancements reach up to 0.8 × 1015 molecules cm-2 4-8 days after precipitation when VSM decreases to ~30%, reflecting emissions behavior distinct from previously defined soil NOx pulse events. This demonstrates that TROPOMI NO2 observations, combined with observations of underlying process controls (e.g., soil moisture), can constrain soil NOx processes from space.

Direct human influence on atmospheric CO2 seasonality from increased cropland productivity.

Ground- and aircraft-based measurements show that the seasonal amplitude of Northern Hemisphere atmospheric carbon dioxide (CO2) concentrations has increased by as much as 50 per cent over the past 50 years. This increase has been linked to changes in temperate, boreal and arctic ecosystem properties and processes such as enhanced photosynthesis, increased heterotrophic respiration, and expansion of woody vegetation. However, the precise causal mechanisms behind the observed changes in atmospheric CO2 seasonality remain unclear. Here we use production statistics and a carbon accounting model to show that increases in agricultural productivity, which have been largely overlooked in previous investigations, explain as much as a quarter of the observed changes in atmospheric CO2 seasonality. Specifically, Northern Hemisphere extratropical maize, wheat, rice, and soybean production grew by 240 per cent between 1961 and 2008, thereby increasing the amount of net carbon uptake by croplands during the Northern Hemisphere growing season by 0.33 petagrams. Maize alone accounts for two-thirds of this change, owing mostly to agricultural intensification within concentrated production zones in the midwestern United States and northern China. Maize, wheat, rice, and soybeans account for about 68 per cent of extratropical dry biomass production, so it is likely that the total impact of increased agricultural production exceeds the amount quantified here.

Seasonally Resolved Excess Urban Methane Emissions from the Baltimore/Washington, DC Metropolitan Region.

Urban areas are increasingly recognized as an important source of methane (CH4), but we have limited seasonally resolved observations of these regions. In this study, we quantify seasonal and annual urban CH4 emissions over the Baltimore, Maryland, and Washington, DC metropolitan regions. We use CH4 atmospheric observations from four tall tower stations and a Lagrangian particle dispersion model to simulate CH4 concentrations at these stations. We directly compare these simulations with observations and use a geostatistical inversion method to determine optimal emissions to match our observations. We use observations spanning four seasons and employ an ensemble approach considering multiple meteorological representations, emission inventories, and upwind CH4 values. Forward simulations in winter, spring, and fall underestimate observed atmospheric CH4 while in summer, simulations overestimate observations because of excess modeled wetland emissions. With ensemble geostatistical inversions, the optimized annual emissions in DC/Baltimore are 39 ± 9 Gg/month (1 δ), 2.0 ± 0.4 times higher than the ensemble mean of bottom-up emission inventories. We find a modest seasonal variability of urban CH4 emissions not captured in current inventories, with optimized summer emissions ∼41% lower than winter, broadly consistent with expectations if emissions are dominated by fugitive natural gas sources that correlate with natural gas usage.

A Multiplatform Inversion Estimation of Statewide and Regional Methane Emissions in California during 2014-2016.

California methane (CH4) emissions are quantified for three years from two tower networks and one aircraft campaign. We used backward trajectory simulations and a mesoscale Bayesian inverse model, initialized by three inventories, to achieve the emission quantification. Results show total statewide CH4 emissions of 2.05 ± 0.26 (at 95% confidence) Tg/yr, which is 1.14 to 1.47 times greater than the anthropogenic emission estimates by California Air Resource Board (CARB). Some of differences could be biogenic emissions, superemitter point sources, and other episodic emissions which may not be completely included in the CARB inventory. San Joaquin Valley (SJV) has the largest CH4 emissions (0.94 ± 0.18 Tg/yr), followed by the South Coast Air Basin, the Sacramento Valley, and the San Francisco Bay Area at 0.39 ± 0.18, 0.21 ± 0.04, and 0.16 ± 0.05 Tg/yr, respectively. The dairy and oil/gas production sources in the SJV contribute 0.44 ± 0.36 and 0.22 ± 0.23 Tg CH4/yr, respectively. This study has important policy implications for regulatory programs, as it provides a thorough multiyear evaluation of the emissions inventory using independent atmospheric measurements and investigates the utility of a complementary multiplatform approach in understanding the spatial and temporal patterns of CH4 emissions in the state and identifies opportunities for the expansion and applications of the monitoring network.

Large Fugitive Methane Emissions From Urban Centers Along the U.S. East Coast.

Urban emissions remain an underexamined part of the methane budget. Here we present and interpret aircraft observations of six old and leak-prone major cities along the East Coast of the United States. We use direct observations of methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), ethane (C2H6), and their correlations to quantify CH4 emissions and attribute to natural gas. We find the five largest cities emit 0.85 (0.63, 1.12) Tg CH4/year, of which 0.75 (0.49, 1.10) Tg CH4/year is attributed to natural gas. Our estimates, which include all thermogenic methane sources including end use, are more than twice that reported in the most recent gridded EPA inventory, which does not include end-use emissions. These results highlight that current urban inventory estimates of natural gas emissions are substantially low, either due to underestimates of leakage, lack of inclusion of end-use emissions, or some combination thereof.