Inactivation of Kv3.3 Potassium Channels in Heterologous Expression Systems
Bibliographic record
Abstract
Kv3.3 K+ channels are believed to incorporate an NH2-terminal domain to produce an intermediate rate of inactivation relative to the fast inactivating K+ channels Kv3.4 and Kv1.4. The rate of Kv3.3 inactivation has, however, been difficult to establish given problems in obtaining consistent rates of inactivation in expression systems. This study characterized the properties of AptKv3.3, the teleost homologue of Kv3.3, when expressed in Chinese hamster ovary (CHO) or human embryonic kidney (HEK) cells. We show that the properties of AptKv3.3 differ significantly between CHO and HEK cells, with the largest difference occurring in the rate and voltage dependence of inactivation. While AptKv3.3 in CHO cells showed a fast and voltage-dependent rate of inactivation consistent with N-type inactivation, currents in HEK cells showed rates of inactivation that were voltage-independent and more consistent with a slower C-type inactivation. Examination of the mRNA sequence revealed that the first methionine start site had a weak Kozak consensus sequence, suggesting that the lack of inactivation in HEK cells could be due to translation at a second methionine start site downstream of the NH2-terminal coding region. Mutating the nucleotide sequence surrounding the first methionine start site to one more closely resembling a Kozak consensus sequence produced currents that inactivated with a fast and voltage-dependent rate of inactivation in both CHO and HEK cells. These results indicate that under the appropriate conditions Kv3.3 channels can exhibit fast and reliable inactivation that approaches that more typically expected of "A"-type K+ currents.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".