Enhanced Sensitivity in Proteomics Experiments Using FAIMS Coupled with a Hybrid Linear Ion Trap/Orbitrap Mass Spectrometer
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Bibliographic record
Abstract
We describe the use and application of high-field asymmetric waveform ion mobility spectrometry combined with nanoscale liquid chromatography mass spectrometry (nanoLC-FAIMS-MS) to improve the sensitivity and dynamic range of proteomics analyses on a hybrid LTQ-Orbitrap mass spectrometer. The ability of FAIMS to enrich multiply protonated peptides against background ions confers a marked advantage in proteomics analyses by decreasing the limits of detection to facilitate the identification of low-abundance peptide ions. These multiply charged ions are recorded into separate acquisition channels to enhance the overall population of detectable peptide ions from a single analysis. NanoLC-FAIMS-MS experiments performed on peptides spiked into complex proteins digests provided more than 10-fold improvement in limits of detection compared to conventional nanoelectrospray mass spectrometry. This enhancement of sensitivity is reflected by a 55% increase in the number of assigned MS/MS spectra contributing to an overall improvement in protein identification and sequence coverage. The application of FAIMS in label-free quantitative proteomics is demonstrated for the identification of differentially abundant proteins from human U937 monocytic cells exposed to phorbol ester.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it