Mass Spectrometric Detection and Characterization of Metabolites of Gemini Surfactants Used as Gene Delivery Vectors
Bibliographic record
Abstract
as nonviral gene delivery vectors. However, the biological fate of gemini surfactants has not been well investigated. In particular, the metabolism of gemini surfactants after they enter cells as gene delivery vehicles is unknown. In this work, we used a high-resolution quadrupole-Orbitrap mass spectrometry (Q-Exactive) instrument to detect the metabolites of three model gemini surfactants, namely, (a) unsubstituted (16-3-16), (b) with pyridinium head groups (16(Py)-S-2-S-16(Py)), and (c) substituted with a glycyl-lysine di-peptide (16-7N(GK)-16). The metabolites were characterized, and structures were proposed, based on accurate masses and characteristic product ions. The metabolism of the three gemini surfactants was very different as 16-3-16 was not metabolized in PAM 212 cells, whereas 16(Py)-S-2-S-16(Py) was metabolized primarily via phase I reactions, including oxidation and dealkylation, producing metabolites that could be linked to its observed high toxicity. The third gemini surfactant 16-7N(GK)-16 was metabolized mainly via phase II reactions, including methylation, acetylation, glucose conjugation, palmityl conjugation, and stearyl conjugation. The metabolism of gemini surfactants provides insight for future directions in the design and development of more effective gemini surfactants with lower toxicity. The reported approach can also be applied to study the metabolism of other structurally related gemini surfactants.
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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 | 0.001 |
| 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 | 0.001 | 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 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".