Measurement of Steroid Fatty Acyl Esters in Blood and Brain
Bibliographic record
Abstract
Abstract Steroid fatty acyl esters (FAEs) are a class of steroid conjugates that are abundant in circulation, have long half-lives, and are stored in lipid-rich tissues. Steroid-FAEs are present in many species, but their functions are poorly understood. They can be metabolized to active, unconjugated steroids and therefore may act as a reservoir of steroids. Dehydroepiandrosterone (DHEA) is an androgen precursor that can be conjugated to various fatty acids. DHEA also modulates aggression in several species, including songbirds, rodents and humans. Recent studies suggest that DHEA-FAEs might be present in songbird blood and/or brain, in part, to regulate aggression. Here, we (1) investigated the abundance of multiple fatty acids in songbird blood and (2) developed an indirect method to measure DHEA-FAEs in songbird blood and brain. First, preliminary work demonstrated high circulating levels of total (esterified and non-esterified) fatty acids, especially oleic, linoleic, and palmitic acids. These data, in conjunction with previous research, suggest that these fatty acids might be conjugated to steroids, including DHEA. Second, we successfully developed a saponification technique to indirectly measure DHEA-FAEs. Saponification cleaves the bond between the steroid molecule and the fatty acid, and we then measure the unconjugated steroid. DHEA-FAEs were incubated in 0.5M potassium hydroxide in ethanol for 30 min at room temperature, and steroids were subsequently extracted twice with dichloromethane. Unconjugated DHEA was quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS), the gold standard in steroid measurement. DHEA recovery was 88% using reference standards in neat solution. We validated this method with song sparrow plasma and chicken serum and obtained recoveries of 94-105% with intra-assay variation of 2.6%. Future research will directly measure specific DHEA-FAEs (e.g. DHEA-oleate) in blood and brain using LC-MS/MS. This research will elucidate the possible roles of steroid-FAEs in brain function and the regulation of steroid-dependent behavior. This work may also clarify the identities, levels and functions of steroid-FAEs in other species, including rodent models and humans. These data have implications for basic and clinical neuroendocrinology, offering insights into a possible storage system for steroids that may influence social behaviour.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".