On the feasibility of quantifying sodium channel Na <sub>v</sub> 1.6 protein in mouse brain using targeted ultra‐high‐performance/electrospray ionization multiple reaction monitoring mass spectrometry
Bibliographic record
Abstract
Rationale Na v 1.6 is a transmembrane voltage gated sodium channel implicated in various forms of epilepsy. Modulation of its activity in epilepsy animal models can be accomplished using inhibitors which may result in changes in its expression. There is a need to generate reliable quantitative measurements of Na v 1.6 expression in animal models. This research explores the feasibility of quantifying Na v 1.6 expression in mouse brains using targeted multiple reaction monitoring (MRM) mass spectrometry. Methods A combination of in silico tryptic Na v 1.6 peptides and MRM transitions were used to select target peptides. This was followed by a simple proteomic work‐up including plasma membrane isolation, trypsin‐based proteolysis and ultra‐high‐performance/electrospray ionization tandem mass spectrometry (UHPLC/ESI‐MS/MS) to detect the presence of Na v 1.6 in induced HEK293 cells. The unique Na v 1.6 peptide, DSLFIPR, was selected as probe for quantifying Na v 1.6 levels in brains from C57BL/6J wild‐type mice as well as two kinds of mutants including Scn8a N1768D/+ and heterozygous null Scn8a +/− mice using isotope dilution targeted mass spectrometry. Results The feasibility of using targeted MRM for quantifying Na v 1.6 expression in mice brains was demonstrated. Expression of Na v 1.6 in brains (hippocampi) from wild‐type and mutant Scn8a N1768D/+ mice were found to be around 0.40 fmol/μg. Mutant null Scn8a +/− heterozygous mice, on the other hand, showed levels of 0.22 fmol/μg as expected based on this particular mutation which only generates 50% of the expression in wild‐type mice. Na v 1.6‐overexpressed HEK293 cells showed 3.7 fmol/μg of Na v 1.6 expression, suitable for screening new compounds for Na v 1.6 blocking activity. Conclusions The results of the present feasibility study support the use of DSLFIPIR for quantification of Nav1.6 in brain tissues using UHPL/ESI‐MS/MS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".