Emx2 underlies the development and evolution of marsupial gliding membranes.

Phenotypic variation among species is a product of evolutionary changes to developmental programs1,2. However, how these changes generate novel morphological traits remains largely unclear. Here we studied the genomic and developmental basis of the mammalian gliding membrane, or patagium-an adaptative trait that has repeatedly evolved in different lineages, including in closely related marsupial species. Through comparative genomic analysis of 15 marsupial genomes, both from gliding and non-gliding species, we find that the Emx2 locus experienced lineage-specific patterns of accelerated cis-regulatory evolution in gliding species. By combining epigenomics, transcriptomics and in-pouch marsupial transgenics, we show that Emx2 is a critical upstream regulator of patagium development. Moreover, we identify different cis-regulatory elements that may be responsible for driving increased Emx2 expression levels in gliding species. Lastly, using mouse functional experiments, we find evidence that Emx2 expression patterns in gliders may have been modified from a pre-existing program found in all mammals. Together, our results suggest that patagia repeatedly originated through a process of convergent genomic evolution, whereby regulation of Emx2 was altered by distinct cis-regulatory elements in independently evolved species. Thus, different regulatory elements targeting the same key developmental gene may constitute an effective strategy by which natural selection has harnessed regulatory evolution in marsupial genomes to generate phenotypic novelty.

Drosophila embryos spatially sort their nutrient stores to facilitate their utilization.

Animal embryos are provided by their mothers with a diverse nutrient supply that is crucial for development. In Drosophila, the three most abundant nutrients (triglycerides, proteins and glycogen) are sequestered in distinct storage structures: lipid droplets (LDs), yolk vesicles (YVs) and glycogen granules (GGs). Using transmission electron microscopy as well as live and fixed sample fluorescence imaging, we find that all three storage structures are dispersed throughout the egg but are then spatially allocated to distinct tissues by gastrulation: LDs largely to the peripheral epithelium, YVs and GGs to the central yolk cell. To confound the embryo's ability to sort its nutrients, we employ Jabba and mauve mutants to generate LD-GG and LD-YV compound structures. In these mutants, LDs are mis-sorted to the yolk cell and their turnover is delayed. Our observations demonstrate dramatic spatial nutrient sorting in early embryos and provide the first evidence for its functional importance.

Adipose triglyceride lipase promotes prostaglandin-dependent actin remodeling by regulating substrate release from lipid droplets.

Lipid droplets (LDs), crucial regulators of lipid metabolism, accumulate during oocyte development. However, their roles in fertility remain largely unknown. During Drosophila oogenesis, LD accumulation coincides with the actin remodeling necessary for follicle development. Loss of the LD-associated Adipose Triglyceride Lipase (ATGL) disrupts both actin bundle formation and cortical actin integrity, an unusual phenotype also seen when the prostaglandin (PG) synthase Pxt is missing. Dominant genetic interactions and PG treatment of follicles indicate that ATGL acts upstream of Pxt to regulate actin remodeling. Our data suggest that ATGL releases arachidonic acid (AA) from LDs to serve as the substrate for PG synthesis. Lipidomic analysis detects AA-containing triglycerides in ovaries, and these are increased when ATGL is lost. High levels of exogenous AA block follicle development; this is enhanced by impairing LD formation and suppressed by reducing ATGL. Together, these data support the model that AA stored in LD triglycerides is released by ATGL to drive the production of PGs, which promote the actin remodeling necessary for follicle development. We speculate that this pathway is conserved across organisms to regulate oocyte development and promote fertility.

Methane Venting at Cold Heavy Oil Production with Sand (CHOPS) Facilities Is Significantly Underreported and Led by High-Emitting Wells with Low or Negative Value.

Cold Heavy Oil Production with or without Sand, CHOP(S), facilities produce a significant portion of Canada's conventional oil. Methane venting from single-well CHOPS facilities in Saskatchewan, Canada was measured (i) using Bridger Photonics' airborne Gas Mapping LiDAR (GML) at 962 sites and (ii) on-site using an optical mass flux meter (VentX), ultrasonic flow meter, and QOGI camera at 11 sites. The strong correlation between ground measurements and airborne GML supported subsequent detailed analysis of the aerial data and to our knowledge is the first study to directly test the ability of airplane surveys to accurately reproduce mean emission rates of unsteady sources. Actual methane venting was found to be nearly four times greater than the industry-reported levels used in emission inventories, with ∼80% of all emissions attributed to casing gas venting. Further analysis of site-total emissions revealed potential gaps in regulations, with 14% of sites appearing to exceed regulated limits while accounting for 61% of measured methane emissions. Finally, the concept of marginal wells was adapted to consider the inferred cost of methane emissions under current carbon pricing. Results suggest that almost a third of all methane is emitted from environmentally marginal wells, where the inferred methane cost negates the value of the oil produced. Overall, the present results illustrate the importance of independent monitoring, reporting, and verification (MRV) to ensure accuracy in reporting and regulatory compliance, and to ensure mitigation targets are not foiled by a collection of disproportionately high-emitting sites.

Origins of Oil and Gas Sector Methane Emissions: On-Site Investigations of Aerial Measured Sources.

Success in reducing oil and gas sector methane emissions is contingent on understanding the sources driving emissions, associated options for mitigation, and the effectiveness of regulations in achieving intended outcomes. This study combines high-resolution, high-sensitivity aerial survey data with subsequent on-site investigations of detected sources to examine these points. Measurements were performed in British Columbia, Canada, an active oil- and gas-producing province with modern methane regulations featuring mandatory three times per year leak detection and repair (LDAR) surveys at most facilities. Derived emission factors enabled by source attribution show that significant methane emissions persist under this regulatory framework, dominated by (i) combustion slip (compressor exhaust and also catalytic heaters, which are not covered in current regulations), (ii) intentional venting (uncontrolled tanks, vent stacks or intentionally unlit flares, and uncontrolled compressors), and (iii) unintentional venting (controlled tanks, unintentionally unlit/blown out flares, and abnormally operating pneumatics). Although the detailed analysis shows mitigation options exist for all sources, the importance of combustion slip and the persistently large methane contributions from controlled tanks and unlit flares demonstrate the limits of current LDAR programs and the critical need for additional monitoring and verification if regulations are to have the intended impacts, and reduction targets of 75% and greater are to be met.

The Futility of Relative Methane Reduction Targets in the Absence of Measurement-Based Inventories.

Under the Global Methane Pledge, Canada is developing oil and gas sector methane regulations targeting 75% reductions from 2012 levels by 2030. Without measured baselines and inventories, such policies are ultimately unverifiable and unenforceable. Using the major oil and gas producing province of Saskatchewan as a case study, we derive first-ever measurement-based methane inventories for the region and comprehensively model previous emissions back to the 2012 baseline. Although relative reductions of 23-69% have likely occurred, the dispersion of modeled possibilities and the high emissions from continuing production illustrate the limits of this approach as a meaningful policy metric. Moreover, nearly 90% of apparent reductions are explained by decreased production at heavy oil facilities, suggesting emissions have potential to rebound if production resumes. By contrast, derived measurement-based methane emissions intensities facilitate quantitative assessment and show that despite any past reductions, Saskatchewan's 0.41 ± 0.03 g/MJ intensity remains among the highest in North America. This highlights how relative reduction targets absent measured baselines and inventories are inherently futile and risk rewarding high emitters while obscuring ongoing mitigation potential. Ultimately, required global methane reductions will only be achieved by adopting objectively and independently verifiable emission metrics while measuring and tracking progress toward a net zero future.

A Wavelength Modulation Spectroscopy-Based Methane Flux Sensor for Quantification of Venting Sources at Oil and Gas Sites.

An optical sensor employing tunable diode laser absorption spectroscopy with wavelength modulation and 2f harmonic detection was designed, prototyped, and tested for applications in quantifying methane emissions from vent sources in the oil and gas sector. The methane absorption line at 6026.23 cm−1 (1659.41 nm) was used to measure both flow velocity and methane volume fraction, enabling direct measurement of the methane emission rate. Two configurations of the sensor were designed, tested, and compared; the first used a fully fiber-coupled cell with multimode fibers to re-collimate the laser beams, while the second used directly irradiated photodetectors protected by Zener barriers. Importantly, both configurations were designed to enable measurements within regulated Class I / Zone 0 hazardous locations, in which explosive gases are expected during normal operations. Controlled flows with methane volume fractions of 0 to 100% and a velocity range of 0 to 4 m/s were used to characterize sensor performance at a 1 Hz sampling rate. The measurement error in the methane volume fraction was less than 10,000 ppm (1%) across the studied range for both configurations. The short-term velocity measurement error with pure methane was <0.3 m/s with a standard deviation of 0.14 m/s for the fiber-coupled configuration and <0.15 m/s with a standard deviation of 0.07 m/s for the directly irradiated detector configuration. However, modal noise in the multimode fibers of the first configuration contributed to an unstable performance that was highly sensitive to mechanical disturbances. The second configuration showed good potential for an industrial sensor, successfully quantifying methane flow rates up to 11 kg/h within ±2.1 kg/h at 95% confidence over a range of methane fractions from 25−100%, and as low as ±0.85 kg/h in scenarios where the source methane fraction is initially unknown within this range and otherwise invariant.

Reduction of Signal Drift in a Wavelength Modulation Spectroscopy-Based Methane Flux Sensor.

Accurately quantifying unsteady methane venting from key oil and gas sector sources such as storage tanks and well casing vents is a critical challenge. Recently, we presented an optical sensor to meet this need that combines volume fraction and Doppler shift measurements using wavelength modulation spectroscopy with 2f harmonic detection to quantify mass flux of methane through a vent line. This paper extends the previous effort through a methodical component-by-component investigation of potential sources of thermally-induced measurement drift to guide the design of an updated sensor. Test data were analyzed using an innovative signal processing technique that permitted quantification of background wavelength modulation spectroscopy signal drift linked to specific components, and the results were successfully used to design a drift-resistant sensor. In the updated sensor, background signal strength was reduced, and stability improved, such that the empirical methane-fraction dependent velocity correction necessary in the original sensor was no longer required. The revised sensor improves previously reported measurement uncertainties on flow velocity from 0.15 to 0.10 m/s, while markedly reducing thermally-induced velocity drift from 0.44 m/s/K to 0.015 m/s/K. In the most general and challenging application, where both flow velocity and methane fraction are independently varying, the updated design reduces the methane mass flow rate uncertainty by more than a factor of six, from ±2.55 kg/h to ±0.40 kg/h. This new design also maintains the intrinsic safety of the original sensor and is ideally suited for unsteady methane vent measurements within hazardous locations typical of oil and gas facilities.

Reward impacts visual statistical learning.

Humans automatically detect and remember regularities in the visual environment-a type of learning termed visual statistical learning (VSL). Many aspects of learning from reward resemble VSL in certain respects, yet whether and how reward learning impacts VSL is largely unexamined. In two studies, we found that reward contingencies affect VSL, with high-value associated with stronger behavioral and neural signatures of such learning than low-value images. In Experiment 1, participants learned values (high or low) of images through a trial-and-error risky choice task. Unbeknownst to them, images were paired as four types-High-High, High-Low, Low-High, and Low-Low. In subsequent recognition and reward memory tests, participants chose the more familiar of two pairs (a target and a foil) and recalled the value of images. We found better recognition when the first images of pairs have high-values, with High-High pairs showing the highest recognition rate. In Experiment 2, we provided evidence that both value and statistical contingencies affected brain responses. When we compared responses between the high-value first image and the low-value first image, greater activation in regions that included inferior frontal gyrus, anterior cingulate gyrus, hippocampus, among other regions, were found. These findings were driven by the interaction between statistically structured information and reward-the same value contrast yielded no regions for second-image contrasts and for singletons. Our results suggest that when reward information is embedded in stimulus-stimulus associations, it may alter the learning process; specifically, the higher-value first image potentially enables better memory for statistically learned pairs and reward information.

Where the Methane Is-Insights from Novel Airborne LiDAR Measurements Combined with Ground Survey Data.

Airborne LiDAR measurements, parallel controlled releases, and on-site optical gas imaging (OGI) survey and pneumatic device count data from 1 year prior, were combined to derive a new measurement-based methane inventory for oil and gas facilities in British Columbia, Canada. Results reveal a surprising distinction in the higher magnitudes, different types, and smaller number of sources seen by the plane versus OGI. Combined data suggest methane emissions are 1.6-2.2 times current federal inventory estimates. More importantly, analysis of high-resolution geo-located aerial imagery, facility schematics, and equipment counts allowed attribution to major source types revealing key drivers of this difference. More than half of emissions were attributed to three main sources: tanks (24%), reciprocating compressors (15%), and unlit flares (13%). These are the sources driving upstream oil and gas methane emissions, and specifically, where emerging regulations must focus to achieve meaningful reductions. Pneumatics accounted for 20%, but this contribution is lower than recent Canadian and U.S. inventory estimates, possibly reflecting a growing shift toward more low- and zero-emitting devices. The stark difference in the aerial and OGI results indicates key gaps in current inventories and suggests that policy and regulations relying on OGI surveys alone may risk missing a significant portion of emissions.

Convolutional neural networks can decode eye movement data: A black box approach to predicting task from eye movements.

Previous attempts to classify task from eye movement data have relied on model architectures designed to emulate theoretically defined cognitive processes and/or data that have been processed into aggregate (e.g., fixations, saccades) or statistical (e.g., fixation density) features. Black box convolutional neural networks (CNNs) are capable of identifying relevant features in raw and minimally processed data and images, but difficulty interpreting these model architectures has contributed to challenges in generalizing lab-trained CNNs to applied contexts. In the current study, a CNN classifier was used to classify task from two eye movement datasets (Exploratory and Confirmatory) in which participants searched, memorized, or rated indoor and outdoor scene images. The Exploratory dataset was used to tune the hyperparameters of the model, and the resulting model architecture was retrained, validated, and tested on the Confirmatory dataset. The data were formatted into timelines (i.e., x-coordinate, y-coordinate, pupil size) and minimally processed images. To further understand the informational value of each component of the eye movement data, the timeline and image datasets were broken down into subsets with one or more components systematically removed. Classification of the timeline data consistently outperformed the image data. The Memorize condition was most often confused with Search and Rate. Pupil size was the least uniquely informative component when compared with the x- and y-coordinates. The general pattern of results for the Exploratory dataset was replicated in the Confirmatory dataset. Overall, the present study provides a practical and reliable black box solution to classifying task from eye movement data.

Not-so-working Memory: Drift in Functional Magnetic Resonance Imaging Pattern Representations during Maintenance Predicts Errors in a Visual Working Memory Task.

Working memory (WM) is critical to many aspects of cognition, but it frequently fails. Much WM research has focused on capacity limits, but even for single, simple features, the fidelity of individual representations is limited. Why is this? One possibility is that, because of neural noise and interference, neural representations do not remain stable across a WM delay, nor do they simply decay, but instead, they may "drift" over time to a new, less accurate state. We tested this hypothesis in a functional magnetic resonance imaging study of a match/nonmatch WM recognition task for a single item with a single critical feature: orientation. We developed a novel pattern-based index of "representational drift" to characterize ongoing changes in brain activity patterns throughout the WM maintenance period, and we were successfully able to predict performance on the match/nonmatch recognition task using this representational drift index. Specifically, in trials where the target and probe stimuli matched, participants incorrectly reported more nonmatches when their activity patterns drifted away from the target. In trials where the target and probe did not match, participants incorrectly reported more matches when their activity patterns drifted toward the probe. On the basis of these results, we contend that neural noise does not cause WM errors merely by degrading representations and increasing random guessing; instead, one means by which noise introduces errors is by pushing WM representations away from the target and toward other meaningful (yet incorrect) configurations. Thus, we demonstrate that behaviorally meaningful drift within representation space can be indexed by neuroimaging.

Periodic patterns in Rodentia: Development and evolution.

Mammalian periodic pigment patterns, such as spots and stripes, have long interested mathematicians and biologists because they arise from non-random developmental processes that are programmed to be spatially constrained, and can therefore be used as a model to understand how organized morphological structures develop. Despite such interest, the developmental and molecular processes underlying their formation remain poorly understood. Here, we argue that Arvicanthines, a clade of African rodents that naturally evolved a remarkable array of coat patterns, represent a tractable model system in which to dissect the mechanistic basis of pigment pattern formation. Indeed, we review recent insights into the process of stripe formation that were obtained using an Arvicanthine species, the African striped mouse (Rhabdomys pumilio), and discuss how these rodents can be used to probe deeply into our understanding of the factors that specify and implement positional information in the skin. By combining naturally evolved pigment pattern variation in rodents with classic and novel experimental approaches, we can substantially advance our understanding of the processes by which spatial patterns of cell differentiation are established during embryogenesis, a fundamental question in developmental biology.

Total Synthesis of Clavatadine B.

The first total synthesis of clavatadine B (2), a natural product found to be a selective human blood coagulation factor XIa inhibitor, is described. A convergent approach that exemplifies the advantages of direct, early stage guanidinylation provided an immediate clavatadine B precursor, which was assembled in an efficient manner using known synthetic precursors of the structurally related natural product clavatadine A (1). Global deprotection cleanly provided clavatadine B in only four steps from a known derivative of homogentisic acid lactone (longest linear sequence, 75% overall yield).

A Techno-Economic Analysis of Methane Mitigation Potential from Reported Venting at Oil Production Sites in Alberta.

The technical and economic potential for reducing methane emissions from reported venting and flaring volumes in 2015 at 9422 upstream oil production sites in Alberta, Canada was evaluated in a comprehensive site-by-site analysis. For each site, up to six different technologies for mitigation were considered, based on conserving gas into pipelines, combusting gas on site, or using gas for on-site fuel. Economic viability of mitigation was calculated using current economic parameters and gas price projections on a net present cost basis. Monte Carlo simulations suggest that a 45% reduction in methane emissions (consistent with current federal and provincial targets) from reported flaring and venting is technically and economically feasible at overall average costs ranging from $-2.98 CAD/tCO2e (i.e., a profit) to $2.51 CAD/tCO2e with no one site paying more than $11.02 CAD/tCO2e. If the reported baseline emissions are augmented to reflect results of recent airborne measurements, overall economics of mitigation generally improve due to larger available gas volumes at many sites. Considering federal carbon price targets of $50 CAD/tCO2e by 2022, there are relevant economic opportunities for mitigating methane from reported venting and flaring volumes well beyond a 45% reduction. This could partially offset the challenge in addressing the additional methane emissions from fugitive and unreported venting sources.

Field Measurements of Black Carbon Yields from Gas Flaring.

Black carbon (BC) emissions from gas flaring in the oil and gas industry are postulated to have critical impacts on climate and public health, but actual emission rates remain poorly characterized. This paper presents in situ field measurements of BC emission rates and flare gas volume-specific BC yields for a diverse range of flares. Measurements were performed during a series of field campaigns in Mexico and Ecuador using the sky-LOSA optical measurement technique, in concert with comprehensive Monte Carlo-based uncertainty analyses. Parallel on-site measurements of flare gas flow rate and composition were successfully performed at a subset of locations enabling direct measurements of fuel-specific BC yields from flares under field conditions. Quantified BC emission rates from individual flares spanned more than 4 orders of magnitude (up to 53.7 g/s). In addition, emissions during one notable ∼24-h flaring event (during which the plume transmissivity dropped to zero) would have been even larger than this maximum rate, which was measured as this event was ending. This highlights the likely importance of superemitters to global emission inventories. Flare gas volume-specific BC yields were shown to be strongly correlated with flare gas heating value. A newly derived correlation fitting current field data and previous lab data suggests that, in the context of recent studies investigating transport of flare-generated BC in the Arctic and globally, impacts of flaring in the energy industry may in fact be underestimated.

Comparisons of Airborne Measurements and Inventory Estimates of Methane Emissions in the Alberta Upstream Oil and Gas Sector.

Airborne measurements of methane emissions from oil and gas infrastructure were completed over two regions of Alberta, Canada. These top-down measurements were directly compared with region-specific bottom-up inventories that utilized current industry-reported flaring and venting volumes (reported data) and quantitative estimates of unreported venting and fugitive sources. For the 50 × 50 km measurement region near Red Deer, characterized by natural gas and light oil production, measured methane fluxes were more than 17 times greater than that derived from directly reported data but consistent with our region-specific bottom-up inventory-based estimate. For the 60 × 60 km measurement region near Lloydminster, characterized by significant cold heavy oil production with sand (CHOPS), airborne measured methane fluxes were five times greater than directly reported emissions from venting and flaring and four times greater than our region-specific bottom up inventory-based estimate. Extended across Alberta, our results suggest that reported venting emissions in Alberta should be 2.5 ± 0.5 times higher, and total methane emissions from the upstream oil and gas sector (excluding mined oil sands) are likely at least 25-50% greater than current government estimates. Successful mitigation efforts in the Red Deer region will need to focus on the >90% of methane emissions currently unmeasured or unreported.

Using precise word timing information improves decoding accuracy in a multiband-accelerated multimodal reading experiment.

The blood-oxygen-level-dependent (BOLD) signal measured in functional magnetic resonance imaging (fMRI) experiments is generally regarded as sluggish and poorly suited for probing neural function at the rapid timescales involved in sentence comprehension. However, recent studies have shown the value of acquiring data with very short repetition times (TRs), not merely in terms of improvements in contrast to noise ratio (CNR) through averaging, but also in terms of additional fine-grained temporal information. Using multiband-accelerated fMRI, we achieved whole-brain scans at 3-mm resolution with a TR of just 500 ms at both 3T and 7T field strengths. By taking advantage of word timing information, we found that word decoding accuracy across two separate sets of scan sessions improved significantly, with better overall performance at 7T than at 3T. The effect of TR was also investigated; we found that substantial word timing information can be extracted using fast TRs, with diminishing benefits beyond TRs of 1000 ms.

Electrophysiological Correlates of Refreshing: Event-related Potentials Associated with Directing Reflective Attention to Face, Scene, or Word Representations.

Refreshing is the component cognitive process of directing reflective attention to one of several active mental representations. Previous studies using fMRI suggested that refresh tasks involve a component process of initiating refreshing as well as the top-down modulation of representational regions central to refreshing. However, those studies were limited by fMRI's low temporal resolution. In this study, we used EEG to examine the time course of refreshing on the scale of milliseconds rather than seconds. ERP analyses showed that a typical refresh task does have a distinct electrophysiological response as compared to a control condition and includes at least two main temporal components: an earlier (∼400 msec) positive peak reminiscent of a P3 response and a later (∼800-1400 msec) sustained positivity over several sites reminiscent of the late directing attention positivity. Overall, the evoked potentials for refreshing representations from three different visual categories (faces, scenes, words) were similar, but multivariate pattern analysis showed that some category information was nonetheless present in the EEG signal. When related to previous fMRI studies, these results are consistent with a two-phase model, with the first phase dominated by frontal control signals involved in initiating refreshing and the second by the top-down modulation of posterior perceptual cortical areas that constitutes refreshing a representation. This study also lays the foundation for future studies of the neural correlates of reflective attention at a finer temporal resolution than is possible using fMRI.

Emission factors for hydraulically fractured gas wells derived using well- and battery-level reported data for Alberta, Canada.

A comprehensive technical analysis of available industry-reported well activity and production data for Alberta in 2011 has been used to derive flaring, venting, and diesel combustion greenhouse gas and criteria air contaminant emission factors specifically linked to drilling, completion, and operation of hydraulically fractured natural gas wells. Analysis revealed that in-line ("green") completions were used at approximately 53% of wells completed in 2011, and in other cases the majority (99.5%) of flowback gases were flared rather than vented. Comparisons with limited analogous data available in the literature revealed that reported total flared and vented natural gas volumes attributable to tight gas well-completions were ∼ 6 times larger than Canadian Association of Petroleum Producers (CAPP) estimates for natural gas well-completion based on wells ca. 2000, but 62% less than an equivalent emission factor that can be derived from U.S. EPA data. Newly derived emission factors for diesel combustion during well drilling and completion are thought to be among the first such data available in the open literature, where drilling-related emissions for tight gas wells drilled in Alberta in 2011 were found to have increased by a factor of 2.8 relative to a typical well drilled in Canada in 2000 due to increased drilling lengths. From well-by-well analysis of production phase flared, vented, and fuel usage natural gas volumes reported at 3846 operating tight gas wells in 2011, operational emission factors were developed. Overall results highlight the importance of operational phase GHG emissions at upstream well sites (including on-site natural gas fuel use), and the critical levels of uncertainty in current estimates of liquid unloading emissions.