Mass Spectrometry-Based Profiling of Deuterium-Labeled Sex Steroids Enables Non-Invasive Mapping of Steroid Dynamics in Intact Mice
Bibliographic record
Abstract
Abstract Background and purpose Sex steroids play central roles in endocrine regulation and are major therapeutic targets in multiple hormone-dependent disorders. However, understanding the tissue-specific pharmacokinetics, distribution and metabolism of these hormones remains challenging in vivo , as most experimental approaches rely on surgical castration, which profoundly disrupts endocrine homeostasis and limits translational relevance for pharmacological studies. We therefore developed a strategy enabling quantitative analysis of steroid dynamics in physiologically intact animals. Experimental approach We established a mass spectrometry-based platform combining systemic administration of deuterium-labelled sex steroids (E2-d 4 , Testo-d 3 and DHEA-d 5 ) with high-sensitivity GC-MS/MS to simultaneously quantify exogenous tracers, endogenous steroids and their metabolites in serum and multiple tissues of intact, non-castrated mice. Key results This approach enabled temporally resolved tracking of steroid uptake, distribution and biotransformation in gonadally intact animals, providing a baseline that is closer to native physiology than in castration-based paradigms. In male and female mice, the method revealed organ-specific accumulation patterns of the metabolites of injected deuterium-labelled sex steroids, including E2-to-E1 conversion in ovary and hippocampus and Testo-to-DHT conversion in prostate and seminal vesicle, that are consistent with the distribution of steroidogenic enzymes in these tissues. Conclusion and implications This methodology provides a physiologically relevant framework for investigating steroid pharmacokinetics and pharmacodynamics in vivo , in which local versus systemic contributions can be dissected in future perturbation studies. By enabling quantitative mapping of steroid metabolism across tissues, it offers a powerful tool for endocrine pharmacology and for the development and evaluation of therapies targeting steroid pathways. It may, thus, facilitate mechanistic studies and preclinical evaluation of anti-androgen therapies, steroidogenesis inhibitors, and other treatments used in hormone-dependent cancers.
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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) | 0.000 | 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) | 0.001 | 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 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".