Multiplex multidimensional nanoLC‐MS system for targeted proteomic analyses
Bibliographic record
Abstract
The present work describes a dual-column and dual-sprayer LC-MS system for high-throughput proteomic analyses. This system consists of two precolumns for sample desalting and two analytical columns. Each column is terminated by a nanoelectrospray emitter mounted on a robotic arm enabling their sequential positioning in front of the sampling cone of the mass spectrometer. The effluent from each emitter is recorded in separate acquisition channels without detectable crosstalk. Gradient elution to both nanoLC columns is delivered by a single HPLC system via a flow splitter. The reproducibility of retention time and peak intensity of the present multiplex system were comparable to those obtainable using a single emitter configuration. Replicate injections of complex tryptic digests (n = 10) indicated that this system provided good reproducibility of retention time and peak intensity on both columns with RSD values of less than 0.9 and 18.6%, respectively. The application of this system is demonstrated for the monitoring of protein expression changes in U937 human monocyte cells with and without phorbol ester administration. Furthermore, we also demonstrated the use of this multiplex system in a 2-D LC configuration to increase sample loading and throughput for the analysis of biomarker samples of higher complexity. Variations in peptide abundance down to two-fold change were identified across salt fractions for spiked tryptic digests present at a level of 50 fmol in 1.5 microg of plasma samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".