Development and Application of an MRM Method for Simultaneous Quantification of Sodium Channels Na v 1.1, Na v 1.2 and Na v 1.6 in Stable HEK293 cell lines, and Solubilized Membrane Proteins from Rodents and Human Brain Tissues.
Bibliographic record
Abstract
Rationale Na v 1.1, 1.2 and 1.6 are transmembrane proteins acting as voltage gated sodium channels implicated in various forms of epilepsy. There is a need for knowing their actual concentration in target tissues during drug development. Methods Unique peptides for Na v 1.1, Na v 1.2 and Na v 1.6 were selected as quantotropic peptides for each protein and used for their quantification in plasma membranes from stably transfected HEK293 cells and rodent and human brain samples using ultra‐high‐performance liquid chromatography/electrospray ionization tandem mass spectrometry. Results Na v 1.1, 1.2 and 1.6 protein expressions in three stably individually transfected HEK293 cell lines were found to be 2.1±0.2, 6.4±1.2 and 4.0±0.6 fmole/µg membrane protein respectively. Na v 1.2 showed the highest expression, with approximately 3 times higher (p<0.003) in rodents than in human at 3.05±0.57, 3.35±0.56 in mouse and rat brains and 1.09±0.27 fmole/µg in human, respectively. Both Na v 1.1 and 1.6 expressions were much lower than Na v 1.2, with approximately 40% less expression in human Na v 1.1 when compared with rodents Na v 1.1 at 0.49±0.1 (mouse), 0.43±0.3 (rat), and 0.28±0.04 (human); while Na v 1.6 was approximately 60% less expression in human when compared to rodents at 0.27±0.09 (mouse), 0.26±0.06 (rat) and 0.11±0.02 (human) fmole/µg membrane proteins. Conclusions MRM was used to quantify sodium channels Na v 1.1, 1.2 and 1.6 expressed in stably transfected HEK293 cells and brain tissues from mouse, rat, and human. We found significant differences in the expression of these channels in mouse, rat, and human brains. Na v expression ranking among the three species was Na v 1.2 >> Na v 1.1> Na v 1.6, with the human brain expressing much lower concentrations overall in comparison to rodents.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".