Ultrasensitive Quantification of Multiple Estrogens in Songbird Blood and Microdissected Brain by LC-MS/MS
Bibliographic record
Abstract
Abstract Neuroestrogens are synthesized within the brain and regulate social behavior, learning and memory, and cognition. In song sparrows, Melospiza melodia , 17β-estradiol (17β-E 2 ) promotes aggressive behavior, including during the nonbreeding season when circulating steroid levels are low. Estrogens are challenging to measure because they are present at very low levels, and current techniques often lack the sensitivity required. Furthermore, current methods often focus on 17β-E 2 and disregard other estrogens. Here, we developed and validated a method to measure four estrogens [estrone (E 1 ), 17β-E 2 , 17α-estradiol (17α-E 2 ), estriol (E 3 )] simultaneously in microdissected songbird brain, with high specificity, sensitivity, accuracy, and precision. We used liquid chromatography tandem mass spectrometry (LC-MS/MS), and to improve sensitivity, we derivatized estrogens using 1,2-dimethylimidazole-5-sulfonyl-chloride (DMIS). The straightforward protocol improved sensitivity by 10-fold for some analytes. There is substantial regional variation in neuroestrogen levels in brain areas that regulate social behavior in male song sparrows. For example, the auditory area NCM, which has high aromatase levels, has the highest E 1 and 17β-E 2 levels. In contrast, estrogen levels in blood are very low. Estrogen levels in both brain and circulation are lower in the nonbreeding season than in the breeding season. This technique will be useful for estrogen measurement in songbirds and potentially other animal models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".