Comparison of CID versus ETD‐based MS/MS fragmentation for the analysis of doubly derivatized steroids
Bibliographic record
Abstract
Electrospray ionization coupled with collision-induced dissociation (CID) and tandem mass spectrometry (MS/MS) is a commonly used technique to analyze the chemical composition of steroids. However, steroids are structurally similar compounds, making it difficult to interpret their product-ion spectra. Electron transfer dissociation (ETD), a relatively new technique for protein and peptide fragmentation, has been shown to provide more detailed structural information. In this study, we compared the ability of CID with that of ETD to differentiate between eight 3,20-dioxosteroids that had been derivatizated with a quaternary ammonium salt, Girard reagent P (GirP), at room temperature or after exposure to microwave irradiation to generate doubly charged ions. We found that the derivatization of steroid with GirP hydrazine occurred in less than 10 min when the reaction was carried out in the presence of microwave irradiation compared to 30 min when the reaction was carried out at room temperature. According to the MS/MS spectra, CID provided rich, structurally informative ions; however, the spectra were complex, thereby complicating the peak assignment. In contrast, ETD generated simpler spectra, making it easier to recognize individual peaks. Remarkably, both CID and ETD were allowed to differentiate of steroid isomers, 17α-hydroxyprogesterone (17OHP) and deoxycorticosterone (DOC), but the signature ions obtained from CID were less intense than those generated by ETD, which generated much clearer spectra. These results indicate that ETD in conjunction with CID can provide more structural information for precise characterization of steroids.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".