Strong anion exchange liquid chromatographic separation of protein amino acids for natural <sup>13</sup> C‐abundance determination by isotope ratio mass spectrometry
Bibliographic record
Abstract
Amino acids are the building blocks of proteins and the analysis of their (13)C abundances is greatly simplified by the use of liquid chromatography (LC) systems coupled with isotope ratio mass spectrometry (IRMS) compared with gas chromatography (GC)-based methods. To date, various cation exchange chromatography columns have been employed for amino acid separation. Here, we report strong anion exchange chromatography (SAX) coupled to IRMS with a Liquiface interface for amino acid δ(13)C determination. Mixtures of underivatised amino acids (0.1-0.5 mM) and hydrolysates of representative proteins (prawns and bovine serum albumin) were resolved by LC/IRMS using a SAX column and inorganic eluents. Background inorganic carbon content was minimised through careful preparation of alkaline reagents and use of a pre-injector on-line carbonate removal device. SAX chromatography completely resolved 11 of the 16 expected protein amino acids following acid hydrolysis in underivatised form. Basic and neutral amino acids were resolved with 35 mM NaOH in isocratic mode. Elution of the aromatic and acidic amino acids required a higher hydroxide concentration (180 mM) and a counterion (NO 3-, 5-25 mM). The total run time was 70 min. The average δ(13)C precision of baseline-resolved peaks was 0.75‰ (range 0.04 to 1.06‰). SAX is a viable alternative to cation chromatography, especially where analysis of basic amino acids is important. The technology shows promise for (13)C amino acid analysis in ecology, archaeology, forensic science, nutrition and protein metabolism.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".