Improved Steroids Detection and Evidence for Their Regiospecific Decompositions Using Anion Attachment Mass Spectrometry
Bibliographic record
Abstract
Nonpolar anabolic steroids are doping agents that typically do not provide strong signals by electrospray ionization-mass spectrometry (ESI-MS) owing especially to the low polarity of the functional groups present. We have investigated the addition of anions, in ammonium salt form, to anabolic steroid samples as ionization enhancers and have confirmed that lower instrumental limits of detection (as low as 10 ng/mL for fluoxymesterone-M) are obtained by fluoride anion attachment mass spectrometry, as compared to ESI(+)/(-) or atmospheric pressure photoionization (APPI)(+). Moreover, collision-induced decomposition (CID) spectra of precursor fluoride adducts of the bifunctional steroid "reduced pregnenolone" (containing two hydroxyl groups) and its d4-analogue provide evidence of regiospecific decompositions after attachment of fluoride anion to a specific hydroxyl group of the steroid. This type of charting of specific CID reaction pathways can offer value to selected reaction monitoring experiments (SRM) as it may result in a gain in selectivity in detection as well as in improvements in quantification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".