Genome-Wide Profiling of Cis-regulatory Elements in Mammalian Skin.

The modulation of cis-regulatory elements (e.g., enhancers and promoters) is a major mechanism by which gene expression can be controlled in a temporal and spatially restricted manner. However, methods for both identifying these elements and inferring their activity are limited and often require a substantial investment of time, money, and resources. Here, using mammalian skin as a model, we demonstrate a streamlined protocol by which these hurdles can be overcome using a novel chromatin profiling technique (CUT&RUN) to map histone modifications genome-wide. This protocol can be used to map the location and activity of putative cis-regulatory elements, providing mechanistic insight into how differential gene expression is controlled in mammalian tissues.

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.

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.

Individualized Ultrasound-Guided Intervention Phantom Development, Fabrication, and Proof of Concept.

Commercial ultrasound vascular phantoms lack the anatomic diversity required for robust pre-clinical interventional device testing. We fabricated individualized phantoms to test an artificial intelligence enabled ultrasound-guided surgical robotic system (AI-GUIDE) which allows novices to cannulate deep vessels. After segmenting vessels on computed tomography scans, vessel cores, bony anatomy, and a mold tailored to the skin contour were 3D-printed. Vessel cores were coated in silicone, surrounded in tissue-mimicking gel tailored for ultrasound and needle insertion, and dissolved with water. One upper arm and four inguinal phantoms were constructed. Operators used AI-GUIDE to deploy needles into phantom vessels. Two groin phantoms were tested due to imaging artifacts in the other two phantoms. Six operators (medical experience: none, 3; 1-5 years, 2; 5+ years, 1) inserted 27 inguinal needles with 81% (22/27) success in a median of 48 seconds. Seven operators performed 24 arm injections, without tuning the AI for arm anatomy, with 71% (17/24) success. After excluding failures due to motor malfunction and a defective needle, success rate was 100% (22/22) in the groin and 85% (17/20) in the arm. Individualized 3D-printed phantoms permit testing of surgical robotics across a large number of operators and different anatomic sites. AI-GUIDE operators rapidly and reliably inserted a needle into target vessels in the upper arm and groin, even without prior medical training. Virtual device trials in individualized 3-D printed phantoms may improve rigor of results and expedite translation.Clinical Relevance- Individualized phantoms enable rigorous and efficient evaluation of interventional devices and reduce the need for animal and human subject testing.

Fence-Line Spectroscopic Measurements Suggest Carry-Over of Salt-Laden Aerosols into Flare Systems Is Common.

Pollutant emissions from gas flares in the upstream oil and gas (UOG) industry can be exacerbated by aerosols of coproduced liquid hydrocarbons and formation water that survive separation and enter the flare. Of noteworthy concern is the potential impact of salt-laden aerosols, since the associated chlorine may adversely affect combustion and emissions. Here, we use a novel approach to remotely detect carry-over of salt-laden aerosols into field-operational flares via flame emission spectroscopy targeting two of the most abundant species in produced water samples, sodium and potassium. Ninety-five UOG flares were examined during field campaigns in the Bakken (U.S.A. and Canada) and Amazon (Ecuador) basins. For the first time, carry-over of salt species into flares is definitively detected and further found to be concerningly common, with 74% of studied flares having detectable sodium and/or potassium signatures. Additional analysis reveals that carry-over strongly correlates with reported flared gas volume (positive) and well age (negative), but carry-over was also observed in flares linked to older wells and those flaring relatively little gas. Given the scale of global UOG flaring and the risk of salt-laden aerosols affecting emissions, these findings emphasize the need to review separation standards and re-evaluate pollutant emissions from flares experiencing carry-over.

A multifunctional Wnt regulator underlies the evolution of rodent stripe patterns.

Animal pigment patterns are excellent models to elucidate mechanisms of biological organization. Although theoretical simulations, such as Turing reaction-diffusion systems, recapitulate many animal patterns, they are insufficient to account for those showing a high degree of spatial organization and reproducibility. Here, we study the coat of the African striped mouse (Rhabdomys pumilio) to uncover how periodic stripes form. Combining transcriptomics, mathematical modelling and mouse transgenics, we show that the Wnt modulator Sfrp2 regulates the distribution of hair follicles and establishes an embryonic prepattern that foreshadows pigment stripes. Moreover, by developing in vivo gene editing in striped mice, we find that Sfrp2 knockout is sufficient to alter the stripe pattern. Strikingly, mutants exhibited changes in pigmentation, revealing that Sfrp2 also regulates hair colour. Lastly, through evolutionary analyses, we find that striped mice have evolved lineage-specific changes in regulatory elements surrounding Sfrp2, many of which may be implicated in modulating the expression of this gene. Altogether, our results show that a single factor controls coat pattern formation by acting both as an orienting signalling mechanism and a modulator of pigmentation. More broadly, our work provides insights into how spatial patterns are established in developing embryos and the mechanisms by which phenotypic novelty originates.

TIGER: Single-step in vivo genome editing in a non-traditional rodent.

Rodents are taxonomically diverse and have evolved a variety of traits. A mechanistic understanding of such traits has remained elusive, however, largely because genome editing in non-traditional model species remains challenging. Here, using the African striped mouse (Rhabdomys pumilio), we describe TIGER (targeted in vivo genome editing in rodents), a method that relies on a simple intraoviductal injecting technique and uses recombinant adeno-associated viruses (rAAVs) as the sole vehicle to deliver reagents into pregnant females. We demonstrate that TIGER generates knockout and knockin (up to 3 kb) lines with high efficiency. Moreover, we engineer a double-cleaving repair rAAV template and find that it significantly increases knockin frequency and germline transmission rates. Lastly, we show that an oversized double-cleaving rAAV template leads to an insertion of 3.8 kb. Thus, TIGER constitutes an attractive alternative to traditional ex vivo genome-editing methods and has the potential to be extended to a broad range of species.

The genomic basis of temporal niche evolution in a diurnal rodent.

Patterns of diel activity-how animals allocate their activity throughout the 24-h daily cycle-play key roles in shaping the internal physiology of an animal and its relationship with the external environment.1,2,3,4,5 Although shifts in diel activity patterns have occurred numerous times over the course of vertebrate evolution,6 the genomic correlates of such transitions remain unknown. Here, we use the African striped mouse (Rhabdomys pumilio), a species that transitioned from the ancestrally nocturnal diel niche of its close relatives to a diurnal one,7,8,9,10,11 to define patterns of naturally occurring molecular variation in diel niche traits. First, to facilitate genomic analyses, we generate a chromosome-level genome assembly of the striped mouse. Next, using transcriptomics, we show that the switch to daytime activity in this species is associated with a realignment of daily rhythms in peripheral tissues with respect to the light:dark cycle and the central circadian clock. To uncover selection pressures associated with this temporal niche shift, we perform comparative genomic analyses with closely related rodent species and find evidence of relaxation of purifying selection on striped mouse genes in the rod phototransduction pathway. In agreement with this, electroretinogram measurements demonstrate that striped mice have functional differences in dim-light visual responses compared with nocturnal rodents. Taken together, our results show that striped mice have undergone a drastic change in circadian organization and provide evidence that the visual system has been a major target of selection as this species transitioned to a novel temporal niche.

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.

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.

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.

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.

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.

Development of a Sub-ppb Resolution Methane Sensor Using a GaSb-Based DFB Diode Laser near 3270 nm for Fugitive Emission Measurement.

A challenge for mobile measurement of fugitive methane emissions is the availability of portable sensors that feature high sensitivity and fast response times, simultaneously. A methane gas sensor to measure fugitive emissions was developed using a continuous-wave, thermoelectrically cooled, GaSb-based distributed feedback diode laser emitting at a wavelength of 3.27 µm to probe methane in its strong ν3 vibrational band. Direct absorption spectra (DAS) as well as wavelength-modulated spectra (WMS) of pressure-broadened R(3) manifold lines of methane were recorded through a custom-developed open-path multipass cell with an effective optical path length of 6.8 m. A novel metrological approach was taken to characterize the sensor response in terms of the linearity of different WMS metrics, namely, the peak-to-peak amplitude of the X2f component and the peak and/or the integrated area of the background-subtracted quadrature signal (i.e., Q(2f - 2f0)) and the background-subtracted 1f-normalized quadrature signal (i.e., Q(2f/1f - 2f0/1f0)). Comparison with calibration gas concentrations spanning 1.5 to 40 ppmv indicated that the latter WMS metric showed the most linear response, while fitting DAS provides a traceable reference. In the WMS mode, a sensitivity better than 1 ppbv was achieved at a 1 s integration time. The sensitivity and response time are well-suited to measure enhancements in ambient methane levels caused by fugitive emissions.

Development of mRNA manufacturing for vaccines and therapeutics: mRNA platform requirements and development of a scalable production process to support early phase clinical trials.

The remarkable success of SARS CoV-2 mRNA-based vaccines and the ensuing interest in mRNA vaccines and therapeutics have highlighted the need for a scalable clinical-enabling manufacturing process to produce such products, and robust analytical methods to demonstrate safety, potency, and purity. To date, production processes have either not been disclosed or are bench-scale in nature and cannot be readily adapted to clinical and commercial scale production. To address these needs, we have advanced an aqueous-based scalable process that is readily adaptable to GMP-compliant manufacturing, and developed the required analytical methods for product characterization, quality control release, and stability testing. We also have demonstrated the products produced at manufacturing scale under such approaches display good potency and protection in relevant animal models with mRNA products encoding both vaccine immunogens and antibodies. Finally, we discuss continued challenges in raw material identification, sourcing and supply, and the cold chain requirements for mRNA therapeutic and vaccine products. While ultimate solutions have yet to be elucidated, we discuss approaches that can be taken that are aligned with regulatory guidance.

AI-Enabled, Ultrasound-Guided Handheld Robotic Device for Femoral Vascular Access.

Hemorrhage is a leading cause of trauma death, particularly in prehospital environments when evacuation is delayed. Obtaining central vascular access to a deep artery or vein is important for administration of emergency drugs and analgesics, and rapid replacement of blood volume, as well as invasive sensing and emerging life-saving interventions. However, central access is normally performed by highly experienced critical care physicians in a hospital setting. We developed a handheld AI-enabled interventional device, AI-GUIDE (Artificial Intelligence Guided Ultrasound Interventional Device), capable of directing users with no ultrasound or interventional expertise to catheterize a deep blood vessel, with an initial focus on the femoral vein. AI-GUIDE integrates with widely available commercial portable ultrasound systems and guides a user in ultrasound probe localization, venous puncture-point localization, and needle insertion. The system performs vascular puncture robotically and incorporates a preloaded guidewire to facilitate the Seldinger technique of catheter insertion. Results from tissue-mimicking phantom and porcine studies under normotensive and hypotensive conditions provide evidence of the technique's robustness, with key performance metrics in a live porcine model including: a mean time to acquire femoral vein insertion point of 53 ± 36 s (5 users with varying experience, in 20 trials), a total time to insert catheter of 80 ± 30 s (1 user, in 6 trials), and a mean number of 1.1 (normotensive, 39 trials) and 1.3 (hypotensive, 55 trials) needle insertion attempts (1 user). These performance metrics in a porcine model are consistent with those for experienced medical providers performing central vascular access on humans in a hospital.

A new tool for equating lexical stimuli across experimental conditions.

In cognitive psychology and psycholinguistics, lexical characteristics can drive large effects, which can create confounds when word stimuli are intended to be unrelated to the effect of interest. Thus, it is critical to control for these potential confounds. As an alternative to randomly assigning word bank items to stimulus lists, we present LIBRA (Lexical Item Balancing & Resampling Algorithm), a MATLAB-based toolbox for quickly generating stimulus lists of user-determined length and number that can be closely equated on any number of lexical properties. The toolbox comprises two scripts: a genetic algorithm that performs the inter-list balancing, and a tool for filtering/trimming long omnibus word lists based on simple criteria, prior to balancing. Relying on randomized procedures often results in substantially unbalanced experimental conditions, but our method guarantees that the lists used for each experimental condition contain no meaningful differences. Thus, the lexical characteristics of the specific words used will add an absolute minimum of bias/noise to the experiment in which they are applied.•Our toolbox balances word lists for arbitrary lexical properties to control confounds in cognitive psychology research.•Our toolbox performs more efficiently than pure randomization or balancing manually.•A graphical user interface is provided for ease of use.

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.

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.