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.

Quantitative and carbon isotope ratio analysis of fatty acids isolated from human brain hemispheres.

Our knowledge surrounding the overall fatty acid profile of the adult human brain has been largely limited to extrapolations from brain regions in which the distribution of fatty acids varies. This is especially problematic when modeling brain fatty acid metabolism, therefore, an updated estimate of whole-brain fatty acid concentration is necessitated. Here, we sought to conduct a comprehensive quantitative analysis of fatty acids from entire well-characterized human brain hemispheres (n = 6) provided by the Douglas-Bell Canada Brain Bank. Additionally, exploratory natural abundance carbon isotope ratio (CIR; δ13 C, 13 C/12 C) analysis was performed to assess the origin of brain fatty acids. Brain fatty acid methyl esters (FAMEs) were quantified by gas chromatography (GC)-flame ionization detection and minor n-6 and n-3 polyunsaturated fatty acid pentafluorobenzyl esters by GC-mass spectrometry. Carbon isotope ratio values of identifiable FAMEs were measured by GC-combustion-isotope ratio mass spectrometry. Overall, the most abundant fatty acid in the human brain was oleic acid, followed by stearic acid (STA), palmitic acid (PAM), docosahexaenoic acid (DHA), and arachidonic acid (ARA). Interestingly, cholesterol as well as saturates including PAM and STA were most enriched in 13 C, while PUFAs including DHA and ARA were most depleted in 13 C. These findings suggest a contribution of endogenous synthesis utilizing dietary sugar substrates rich in 13 C, and a combination of marine, animal, and terrestrial PUFA sources more depleted in 13 C, respectively. These results provide novel insights on cerebral fatty acid origin and concentration, the latter serving as a valuable resource for future modeling of fatty acid metabolism in the human brain.

The majority of brain palmitic acid is maintained by lipogenesis from dietary sugars and is augmented in mice fed low palmitic acid levels from birth.

Previously, results from studies investigating if brain palmitic acid (16:0; PAM) was maintained by either dietary uptake or de novo lipogenesis (DNL) varied. Here, we utilize naturally occurring carbon isotope ratios (13 C/12 C; δ13 C) to uncover the origin of brain PAM. Additionally, we explored brain and liver fatty acid concentration, brain metabolomics, and behavior. BALB/c dams were equilibrated onto either a low PAM diet (LP; <2%) or high PAM diet (HP; >95%) prior to producing one generation of offspring. Offspring stayed on the respective diet of the dam until 15-weeks of age, at which time the Open Field test was conducted, prior to euthanasia and tissue lipid extraction. Although liver PAM was lower in mice fed the LP diet, as well as female mice, brain PAM was not affected by diet or sex. Across mice of either sex on both diets, brain 13 C-PAM revealed compared to dietary uptake, DNL from dietary sugars contributed 68.8%-79.5% and 46.6%-58.0% to the total brain PAM pool by both peripheral and local brain DNL, and local brain DNL alone, respectively. DNL was augmented in mice fed the LP diet, and the ability to up-regulate DNL in the liver or the brain depended on sex. Anxiety-like behaviors were decreased in mice fed the LP diet and were correlated with markers of LP diet consumption including increased liver 13 C-PAM, warranting further investigation. Altogether, our results indicate that DNL from dietary sugars is a compensatory mechanism to maintain brain PAM in response to the LP diet.

Reconciling Multiple Methane Detection and Quantification Systems at Oil and Gas Tank Battery Sites.

Emission rates were estimated for >100 oil and gas production sites with significant liquid-handling equipment (tank battery sites) in the Permian Basin of west Texas. Emission estimates based on equipment counts and emission factors, but not accounting for large uninventoried emission events, led to ensemble average emission rates of 1.8-3.6 kg/h per site. None of the site-specific emission estimates for individual sites, based on equipment counts, exceeded 10 kg/h. On-site drone-based emission measurements led to similar emission estimates for inventoried sources. Multiple aircraft measurement platforms were deployed and reported emissions exceeding 10 kg/h at 14-27% of the sites, and these high-emission rate sites accounted for 80-90% of total emissions for the ensemble of sites. The aircraft measurement systems were deployed asynchronously but within a 5 day period. At least half of the sites with emission rates above 10 kg/h detected by aircraft had emissions that did not persist at a level above 10 kg/h for repeat measurements, suggesting typical high-emission rate durations of a few days or less for many events. The two aircraft systems differed in their estimates of total emissions from the ensembles of sites sampled by more than a factor of 2; however, the normalized distributions of emissions for sites with emission rates of >10 kg/h were comparable for the two aircraft-based methods. The differences between the two aircraft-based platforms are attributed to a combination of factors; however, both aircraft-based emission measurement systems attribute a large fraction of emissions to sites with an emission rate of >10 kg/h.

Deep-learning-assisted algorithm for catheter reconstruction during MR-only gynecological interstitial brachytherapy.

Magnetic resonance imaging (MRI) offers excellent soft-tissue contrast enabling the contouring of targets and organs at risk during gynecological interstitial brachytherapy procedure. Despite its advantage, one of the main obstacles preventing a transition to an MRI-only workflow is that implanted plastic catheters are not reliably visualized on MR images. This study aims to evaluate the feasibility of a deep-learning-based algorithm for semiautomatic reconstruction of interstitial catheters during an MR-only workflow. MR images of 20 gynecological patients were used in this study. Note that 360 catheters were reconstructed using T1- and T2-weighted images by five experienced brachytherapy planners. The mean of the five reconstructed paths were used for training (257 catheters), validation (15 catheters), and testing/evaluation (88 catheters). To automatically identify and localize the catheters, a two-dimensional (2D) U-net algorithm was used to find their approximate location in each image slice. Once localized, thresholding was applied to those regions to find the extrema, as catheters appear as bright and dark regions in T1- and T2-weighted images, respectively. The localized dwell positions of the proposed algorithm were compared to the ground truth reconstruction. Reconstruction time was also evaluated. A total of 34 009 catheter dwell positions were evaluated between the algorithm and all planners to estimate the reconstruction variability. The average variation was 0.97 ± 0.66 mm. The average reconstruction time for this approach was 11 ± 1 min, compared with 46 ± 10 min for the expert planners. This study suggests that the proposed deep learning, MR-based framework has potential to replace the conventional manual catheter reconstruction. The adoption of this approach in the brachytherapy workflow is expected to improve treatment efficiency while reducing planning time, resources, and human errors.

Intranasal anti-caspase-1 therapy preserves myelin and glucose metabolism in a model of progressive multiple sclerosis.

Inflammatory demyelination and axonal injury in the central nervous system (CNS) are cardinal features of progressive multiple sclerosis (MS), and linked to activated brain macrophage-like cells (BMCs) including resident microglia and trafficking macrophages. Caspase-1 is a pivotal mediator of inflammation and cell death in the CNS. We investigated the effects of caspase-1 activation and its regulation in models of MS. Brains from progressive MS and non-MS patients, as well as cultured human oligodendrocytes were examined by transcriptomic and morphological methods. Next generation transcriptional sequencing of progressive MS compared to non-MS patients' normal appearing white matter (NAWM) showed induction of caspase-1 as well as other inflammasome-associated genes with concurrent suppression of neuron-specific genes. Oligodendrocytes exposed to TNFα exhibited upregulation of caspase-1 with myelin gene suppression in a cell differentiation state-dependent manner. Brains from cuprizone-exposed mice treated by intranasal delivery of the caspase-1 inhibitor, VX-765 or its vehicle, were investigated in morphological and molecular studies, as well as by fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging. Cuprizone exposure resulted in BMC and caspase-1 activation accompanied by demyelination and axonal injury, which was abrogated by intranasal VX-765 treatment. FDG-PET imaging revealed suppressed glucose metabolism in the thalamus, hippocampus and cortex of cuprizone-exposed mice that was restored with VX-765 treatment. These studies highlight the caspase-1 dependent interactions between inflammation, demyelination, and glucose metabolism in progressive MS and associated models. Intranasal delivery of an anti-caspase-1 therapy represents a promising therapeutic approach for progressive MS and other neuro-inflammatory diseases.

A Scoping Review of Clinical Studies in Infants Fed Formulas Containing Palm Oil or Palm Olein and Sn-2 Palmitate.

BACKGROUND: Palmitic acid (PA; 16:0) is added to infant formula in the form of palm oil/palm olein (PO/POL) and stereospecific numbered-2 palmitate (SN2). Several studies have examined the effects of PO/POL and or SN2 in formulas on health outcomes, mainly growth, digestion, and absorption of nutrients. However, the roles of PA, PO/POL, and SN2 on neurodevelopment remains unknown. OBJECTIVES: The objective of this scoping review was to map out studies in infants fed formula with PO/POL or SN2 to identify current knowledge on the role of PA in infant nutrition, specifically neurodevelopment. METHODS: Data sources, including Medline, Embase, CAB Abstracts, and the Cochrane Database, were searched. Eligible articles were randomized controlled trials (RCTs) and observational studies examining outcomes in term singleton infants fed formula containing PO/POL or SN2. Studies examining preterm infants or infants with infections, mixed-feeding interventions, or outcomes not concerned with PO/POL or SN2 were excluded. Screening and data extraction were performed by 2 independent reviewers, and results were charted into 10 outcome categories. RESULTS: We identified 28 RCTs and 2 observational studies. Only 1 RCT examined a neurodevelopmental outcome, reporting infants fed SN2 formula had higher fine motor skill scores compared to those fed a vegetable oil formula with a lower amount of SN2; however, only after adjustment for maternal education and at an earlier, but not a later time point. Anthropometric measures do not appear to be influenced by PO/POL or SN2 within formulas. Alternatively, it was reported that infants fed PO/POL within formulas had a decreased absorption of calcium, total fat, and PA compared to those fed vegetable oil formulas. However, studies were heterogenous, making it difficult to isolate the effects of PO/POL or SN2 in formulas. CONCLUSIONS: Our review reiterates the need for future studies to address the effects of PO/POL and SN2 on neurodevelopment in infants. This study is registered at Open Science Framework as osf.io/697he.

Impacts of lake breeze meteorology on ozone gradient observations along Lake Michigan Shorelines in Wisconsin.

Daytime onshore lake breezes are a critical factor controlling ozone abundance at coastal sites around Lake Michigan. Coastal counties along the western shore of Lake Michigan have historically observed high ozone episodes dating to the 1970s. We classified ozone episode days based on the extent or absence of the lake breeze (i.e., "inland", "near-shore" or "no" lake breeze) to establish a climatology of these events. This work demonstrated variable gradients in ozone abundances based on these different types of meteorology, with the sharpest ozone concentration gradients on days with a near-shore lake breeze. On 76-82% of days in which ozone reached 70 ppb for at least 1 hour, a lake breeze was present. Evidence of ozone gradients from multiple observation platforms during the 2017 Lake Michigan Ozone Study (LMOS 2017) are shown for two days with different depths of lake breezes.

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.

Assessment of Regional Methane Emission Inventories through Airborne Quantification in the San Francisco Bay Area.

This study derives methane emission rates from 92 airborne observations collected over 23 facilities including 5 refineries, 10 landfills, 4 wastewater treatment plants (POTWs), 2 composting operations, and 2 dairies in the San Francisco Bay Area. Emission rates are measured using an airborne mass-balance technique from a low-flying aircraft. Annual measurement-based sectorwide methane emissions are 19,000 ± 2300 Mg for refineries, 136,700 ± 25,900 Mg for landfills, 11,900 ± 1,500 Mg for POTWs, and 11,100 ± 3,400 Mg for composting. The average of measured emissions for each refinery ranges from 4 to 23 times larger than the corresponding emissions reported to regulatory agencies, while measurement-derived landfill and POTW estimates are approximately twice the current inventory estimates. Significant methane emissions at composting facilities indicate that a California mandate to divert organics from landfills to composting may not be an effective measure for mitigating methane emissions unless best management practices are instituted at composting facilities. Complementary evidence from airborne remote sensing imagery indicates atmospheric venting from refinery hydrogen plants, landfill working surfaces, composting stockpiles, etc., to be among the specific source types responsible for the observed discrepancies. This work highlights the value of multiple measurement approaches to accurately estimate facility-scale methane emissions and perform source attribution at subfacility scales to guide and verify effective mitigation policy and action.

Observations of Methane Emissions from Natural Gas-Fired Power Plants.

Current research efforts on the atmospheric impacts of natural gas (NG) have focused heavily on the production, storage/transmission, and processing sectors, with less attention paid to the distribution and end use sectors. This work discusses 23 flights at 14 natural gas-fired power plants (NGPPs) using an aircraft-based mass balance technique and methane/carbon dioxide enhancement ratios (ΔCH4/ΔCO2) measured from stack plumes to quantify the unburned fuel. By comparing the ΔCH4/ΔCO2 ratio measured in stack plumes to that measured downwind, we determined that, within uncertainty of the measurement, all observed CH4 emissions were stack-based, that is, uncombusted NG from the stack rather than fugitive sources. Measured CH4 emission rates (ER) ranged from 8 (±5) to 135 (±27) kg CH4/h (±1σ), with the fractional CH4 throughput lost (loss rate) ranging from -0.039% (±0.076%) to 0.204% (±0.054%). We attribute negative values to partial combustion of ambient CH4 in the power plant. The average calculated emission factor (EF) of 5.4 (+10/-5.4) g CH4/million British thermal units (MMBTU) is within uncertainty of the Environmental Protection Agency (EPA) EFs. However, one facility measured during startup exhibited substantially larger stack emissions with an EF of 440 (+660/-440) g CH4/MMBTU and a loss rate of 2.5% (+3.8/-2.5%).

Capuchin monkeys (Sapajus [Cebus] apella) play Nash equilibria in dynamic games, but their decisions are likely not influenced by oxytocin.

Comparative approaches to experimental economics have shed light on the evolution of social decision-making across a range of primate species, including humans. Here we replicate our previous work looking at six pairs of capuchin monkeys' (Sapajus [Cebus] apella) responses to scenarios requiring both coordination (Assurance Game) and anti-coordination (Hawk-Dove Game). This then provides a foundation for assessing their responses to two additional games, one with a scenario of beneficial cooperation with a temptation to defect (Prisoner's Dilemma) and one with an environment requiring changing strategies within short temporal proximity (Alternating Economic Game). We additionally explored the effects of exogenous oxytocin on decision-making. Oxytocin did not affect decisions in any of our games. Results from the first two games largely replicated our previous findings. Responses to the Prisoner's Dilemma were more varied than was seen in previous games, with pairs respectively cooperating, defecting, and failing to establish stable strategies. Such variability indicates that this game may be a good assay for individual differences in social decision-making. Finally, capuchins were able to flexibly switch between their previously established strategies within each of the different games, even when the games were presented within the same session, requiring strategy adjustments within short temporal proximity. These results build on earlier findings showing that capuchins can alter decision-making strategies as the context demands, which is likely essential for decision-making in naturally occurring contexts.

A dynamic loop provides dual control over the catalytic and membrane binding activity of a bacterial serine hydrolase.

The bacterial acyl protein thioesterase (APT) homologue FTT258 from the gram-negative pathogen Francisella tularensis exists in equilibrium between a closed and open state. Interconversion between these two states is dependent on structural rearrangement of a dynamic loop overlapping its active site. The dynamics and structural properties of this loop provide a simple model for how the catalytic activity of FTT258 could be spatiotemporally regulated within the cell. Herein, we characterized the dual roles of this dynamic loop in controlling its catalytic and membrane binding activity. Using a comprehensive library of loop variants, we determined the relative importance of each residue in the loop to these two biological functions. For the catalytic activity, a centrally located tryptophan residue (Trp66) was essential, with the resulting alanine variant showing complete ablation of enzyme activity. Detailed analysis of Trp66 showed that its hydrophobicity in combination with spatial arrangement defined its essential role in catalysis. Substitution of other loop residues congregated along the N-terminal side of the loop also significantly impacted catalytic activity, indicating a critical role for this loop in controlling catalytic activity. For membrane binding, the centrally located hydrophobic residues played a surprising minor role in membrane binding. Instead general electrostatic interactions regulated membrane binding with positively charged residues bracketing the dynamic loop controlling membrane binding. Overall for FTT258, this dynamic loop dually controlled its biological activities through distinct residues within the loop and this regulation provides a new model for the spatiotemporal control over FTT258 and potentially homologous APT function.

Methane, Black Carbon, and Ethane Emissions from Natural Gas Flares in the Bakken Shale, North Dakota.

Incomplete combustion during flaring can lead to production of black carbon (BC) and loss of methane and other pollutants to the atmosphere, impacting climate and air quality. However, few studies have measured flare efficiency in a real-world setting. We use airborne data of plume samples from 37 unique flares in the Bakken region of North Dakota in May 2014 to calculate emission factors for BC, methane, ethane, and combustion efficiency for methane and ethane. We find no clear relationship between emission factors and aircraft-level wind speed or between methane and BC emission factors. Observed median combustion efficiencies for methane and ethane are close to expected values for typical flares according to the US EPA (98%). However, we find that the efficiency distribution is skewed, exhibiting log-normal behavior. This suggests incomplete combustion from flares contributes almost 1/5 of the total field emissions of methane and ethane measured in the Bakken shale, more than double the expected value if 98% efficiency was representative. BC emission factors also have a skewed distribution, but we find lower emission values than previous studies. The direct observation for the first time of a heavy-tail emissions distribution from flares suggests the need to consider skewed distributions when assessing flare impacts globally.

Airborne Quantification of Methane Emissions over the Four Corners Region.

Methane (CH4) is a potent greenhouse gas and the primary component of natural gas. The San Juan Basin (SJB) is one of the largest coal-bed methane producing regions in North America and, including gas production from conventional and shale sources, contributed ∼2% of U.S. natural gas production in 2015. In this work, we quantify the CH4 flux from the SJB using continuous atmospheric sampling from aircraft collected during the TOPDOWN2015 field campaign in April 2015. Using five independent days of measurements and the aircraft-based mass balance method, we calculate an average CH4 flux of 0.54 ± 0.20 Tg yr-1 (1σ), in close agreement with the previous space-based estimate made for 2003-2009. These results agree within error with the U.S. EPA gridded inventory for 2012. These flights combined with the previous satellite study suggest CH4 emissions have not changed. While there have been significant declines in natural gas production between measurements, recent increases in oil production in the SJB may explain why emission of CH4 has not declined. Airborne quantification of outcrops where seepage occurs are consistent with ground-based studies that indicate these geological sources are a small fraction of the basin total (0.02-0.12 Tg yr-1) and cannot explain basinwide consistent emissions from 2003 to 2015.

Airborne Ethane Observations in the Barnett Shale: Quantification of Ethane Flux and Attribution of Methane Emissions.

We present high time resolution airborne ethane (C2H6) and methane (CH4) measurements made in March and October 2013 as part of the Barnett Coordinated Campaign over the Barnett Shale formation in Texas. Ethane fluxes are quantified using a downwind flight strategy, a first demonstration of this approach for C2H6. Additionally, ethane-to-methane emissions ratios (C2H6:CH4) of point sources were observationally determined from simultaneous airborne C2H6 and CH4 measurements during a survey flight over the source region. Distinct C2H6:CH4 × 100% molar ratios of 0.0%, 1.8%, and 9.6%, indicative of microbial, low-C2H6 fossil, and high-C2H6 fossil sources, respectively, emerged in observations over the emissions source region of the Barnett Shale. Ethane-to-methane correlations were used in conjunction with C2H6 and CH4 fluxes to quantify the fraction of CH4 emissions derived from fossil and microbial sources. On the basis of two analyses, we find 71-85% of the observed methane emissions quantified in the Barnett Shale are derived from fossil sources. The average ethane flux observed from the studied region of the Barnett Shale was 6.6 ± 0.2 × 10(3) kg hr(-1) and consistent across six days in spring and fall of 2013.

Aircraft-Based Estimate of Total Methane Emissions from the Barnett Shale Region.

We present estimates of regional methane (CH4) emissions from oil and natural gas operations in the Barnett Shale, Texas, using airborne atmospheric measurements. Using a mass balance approach on eight different flight days in March and October 2013, the total CH4 emissions for the region are estimated to be 76 ± 13 × 10(3) kg hr(-1) (equivalent to 0.66 ± 0.11 Tg CH4 yr(-1); 95% confidence interval (CI)). We estimate that 60 ± 11 × 10(3) kg CH4 hr(-1) (95% CI) are emitted by natural gas and oil operations, including production, processing, and distribution in the urban areas of Dallas and Fort Worth. This estimate agrees with the U.S. Environmental Protection Agency (EPA) estimate for nationwide CH4 emissions from the natural gas sector when scaled by natural gas production, but it is higher than emissions reported by the EDGAR inventory or by industry to EPA's Greenhouse Gas Reporting Program. This study is the first to show consistency between mass balance results on so many different days and in two different seasons, enabling better quantification of the related uncertainty. The Barnett is one of the largest production basins in the United States, with 8% of total U.S. natural gas production, and thus, our results represent a crucial step toward determining the greenhouse gas footprint of U.S. onshore natural gas production.

Images reveal that atmospheric particles can undergo liquid-liquid phase separations.

A large fraction of submicron atmospheric aerosol particles contains both organic material and inorganic salts. As the relative humidity cycles in the atmosphere and the water content of the particles correspondingly changes, these mixed particles can undergo a range of phase transitions, possibly including liquid-liquid phase separation. If liquid-liquid phase separation occurs, the gas-particle partitioning of atmospheric semivolatile organic compounds, the scattering and absorption of solar radiation, and the reactive uptake of gas species on atmospheric particles may be affected, with important implications for climate predictions. The actual occurrence of liquid-liquid phase separation within individual atmospheric particles has been considered uncertain, in large part because of the absence of observations for real-world samples. Here, using optical and fluorescence microscopy, we present images that show the coexistence of two noncrystalline phases for real-world samples collected on multiple days in Atlanta, GA as well as for laboratory-generated samples under simulated atmospheric conditions. These results reveal that atmospheric particles can undergo liquid-liquid phase separations. To explore the implications of these findings, we carried out simulations of the Atlanta urban environment and found that liquid-liquid phase separation can result in increased concentrations of gas-phase NO(3) and N(2)O(5) due to decreased particle uptake of N(2)O(5).

Blood and tissue docosahexaenoic acid (DHA, 22:6n-3) turnover rates from Ahiflower® oil are not different than from DHA ethyl ester oil in a diet switch mouse model.

Ahiflower® oil is high in α-linolenic and stearidonic acids, however, tissue/blood docosahexaenoic acid (DHA, 22:6n-3) turnover from dietary Ahiflower oil has not been investigated. In this study, we use compound-specific isotope analysis to determine tissue DHA synthesis/turnover from Ahiflower, flaxseed and DHA oils. Pregnant BALB/c mice (13-17 days) were placed on a 2 % algal DHA oil diet of high carbon-13 content (δ13C) and pups (n = 132) were maintained on the diet until 9 weeks old. Mice were then randomly allocated to a low δ13C-n-3 PUFA diet of either: 1) 4 % Ahiflower oil, 2) 4.35 % flaxseed oil or 3) 1 % fish DHA ethyl ester oil for 1, 3, 7, 14, 30, 60 or 120 days (n = 6). Serum, liver, adipose and brains were collected and DHA levels and δ13C were determined. DHA concentrations were highest (p < 0.05) in the liver and adipose of DHA-fed animals with no diet differences in serum or brain (p > 0.05). Based on the presence or absence of overlapping 95 % C.I.'s, DHA half-lives and synthesis/turnover rates were not different between Ahiflower and DHA diets in the liver, adipose or brain. DHA half-lives and synthesis/turnover rates from flaxseed oil were significantly slower than from the DHA diet in all serum/tissues. These findings suggest that the distinct Ahiflower oil n-3 PUFA composition could support tissue DHA needs at a similar rate to dietary DHA, making it a unique plant-based dietary option for maintaining DHA turnover comparably to dietary DHA.

An Automated Tool to Classify and Transform Unstructured MRI Data into BIDS Datasets.

The increasing use of neuroimaging in clinical research has driven the creation of many large imaging datasets. However, these datasets often rely on inconsistent naming conventions in image file headers to describe acquisition, and time-consuming manual curation is necessary. Therefore, we sought to automate the process of classifying and organizing magnetic resonance imaging (MRI) data according to acquisition types common to the clinical routine, as well as automate the transformation of raw, unstructured images into Brain Imaging Data Structure (BIDS) datasets. To do this, we trained an XGBoost model to classify MRI acquisition types using relatively few acquisition parameters that are automatically stored by the MRI scanner in image file metadata, which are then mapped to the naming conventions prescribed by BIDS to transform the input images to the BIDS structure. The model recognizes MRI types with 99.475% accuracy, as well as a micro/macro-averaged precision of 0.9995/0.994, a micro/macro-averaged recall of 0.9995/0.989, and a micro/macro-averaged F1 of 0.9995/0.991. Our approach accurately and quickly classifies MRI types and transforms unstructured data into standardized structures with little-to-no user intervention, reducing the barrier of entry for clinical scientists and increasing the accessibility of existing neuroimaging data.