Electrophoresis assisted time-of-flow mass spectrometry using hollow nanomechanical resonators
Bibliographic record
Abstract
This report discusses the first demonstration of electrophoresis assisted time-of-flow mass spectrometry using 'U' shaped hollow nanomechanical resonators (HNR). Capillary electrophoresis was coupled with the HNR based mass detection to overcome low ionic conductivity of channels embedded in the HNR preventing direct in-situ electrophoretic separation. The flow of analytes through the HNR was achieved by balancing the hydrodynamic pressure to override the electromotive force and inhibit the motion of analytes towards the anode for capillary electrophoresis. The resonance frequency shifts of the HNR vibrating around 1.5 MHz were correlated with the time of the passage of the protein bands to construct the mass spectrum. The proposed concept was demonstrated by constructing a mass spectrum of egg white proteins in the molecular weight range of 14-250 kDa. When compared to regular polyacrylamide gel electrophoresis, our method not only provides a precise and fast readout but also avoids the use of chemical staining. This study paves a new route for low-cost and on-chip mass spectrometers with ultra-miniaturized dimensions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".