Fatty acid amide hydrolase (<scp>FAAH</scp>) regulates hypercapnia/ischemia‐induced increases in n‐acylethanolamines in mouse brain
Bibliographic record
Abstract
Abstract N‐acylethanolamines (NAEs) are endogenous lipid ligands for several receptors including cannabinoid receptors and peroxisome proliferator‐activated receptor‐alpha (PPAR‐α), which regulate numerous physiological functions. Fatty acid amide hydrolase (FAAH) is largely responsible for the degradation of NAEs. However, at high concentrations of ethanolamines and unesterified fatty acids, FAAH can also catalyze the reverse reaction, producing NAEs. Several brain insults such as ischemia and hypoxia increase brain unesterified fatty acids. Because FAAH can catalyze the synthesis of NAE, we aimed to test whether FAAH was necessary for CO2 ‐induced hypercapnia/ischemia increases in NAE. To test this, we examined levels of NAEs, 1‐ and 2‐arachidonoylglycerols as well as their corresponding fatty acid precursors in wild‐type and mice lacking FAAH (FAAH‐KO) with three Kill methods: (i) head‐focused, high‐energy microwave irradiation (microwave), (ii) 5 min CO2 followed by microwave irradiation (CO2 + microwave), and (iii) 5 min CO2 only (CO2). Both CO2‐induced groups increased, to a similar extent, brain levels of unesterified oleic, arachidonic, and docosahexaenoic acid and 1‐ and 2‐arachidonoylglycerols compared to the microwave group in both wild‐type and FAAH‐KO mice. Oleoylethanolamide (OEA), arachidonoylethanolamide (AEA), and docosahexaenoylethanolamide (DHEA) levels were about 8‐, 7‐, and 2.5‐fold higher, respectively, in the FAAH‐KO mice compared with the wild‐type mice. Interestingly, the concentrations of OEA, AEA, and DHEA increased 2.5‐ to 4‐fold in response to both CO2‐induced groups in wild‐type mice, but DHEA increased only in the CO2 group in FAAH‐KO mice. Our study demonstrates that FAAH is necessary for CO2‐ induced increases in OEA and AEA but not DHEA. Targeting brain FAAH could impair the production of NAEs in response to brain injuries. image
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".