Method for Absolute Quantification of Short Chain Fatty Acids via Reverse Phase Chromatography Mass Spectrometry
Bibliographic record
Abstract
Short chain fatty acids (SCFAs; including acetate, propionate, and butyrate) are an important class of biological molecules that play a major role in modulating host-microbiome interactions. Despite significant research into SCFA-mediated biological mechanisms, absolute quantification of these molecules by liquid chromatography mass spectrometry (LC-MS) is challenging due to their relatively poor chromatographic properties and low mass. Herein, we introduce SQUAD, a quantitative strategy for analyzing SCFAs using an aniline-based derivatization approach in conjunction with reverse-phase LC-MS/MS analysis. We show that this approach, when coupled to quantification by stable isotope dilution (SID), enables absolute quantification of biologically relevant SCFAs in complex biological samples. We evaluate the limits of detection using this approach, analyze sources of error affecting quantification, and provide practical guidelines for using this strategy. Moreover, we illustrate the utility of this technique via two representative biological applications where SCFA analysis is common: 1) SCFA quantification in the caecal contents of germ free versus conventionally raised specific pathogen free mice and 2) in an analysis of in vitro microbial cultures.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".