Time-resolved electrospray mass spectrometry — a brief history
Bibliographic record
Abstract
This review describes the evolution of time-resolved electrospray ionization mass spectrometry (TRESI-MS), a technology that was developed in large part at Western University. TRESI-MS was initially designed to characterize rapid chemical and biochemical reactions occurring on the millisecond time scale without need for a chromophore. Early TRESI-MS setups usually consisted of continuous-flow rapid mixers with a fixed tee for analysis of a single time point, and later adjustable reaction chamber devices allowing for automatic tracking of the reaction over time. Advances in instrumentation design over the years have resulted in improved time resolution, with microfluidic device implementation allowing for coupling to hydrogen−deuterium exchange (HDX) experiments. Areas of application that will be discussed include the investigation of protein folding intermediates, identification of enzyme−substrate intermediates in the pre-steady state, and the use of time-resolved HDX to study the dynamics of weakly structured protein regions. While some limitations still persist with the method, the continued development of TRESI-MS and related approaches paves the way to a promising future and the study of unexplored application areas.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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".