Depressive effectiveness of vigabatrin (γ-vinyl-GABA), an antiepileptic drug, in intermediate-conductance calcium-activated potassium channels in human glioma cells
Bibliographic record
Abstract
Abstract Background Vigabatrin (VGB) is an approved non-traditional antiepileptic drug that has been revealed to have potential for treating brain tumors; however, its effect on ionic channels in glioma cells remains largely unclear. Methods With the aid of patch-clamp technology, we investigated the effects of VGB on various ionic currents in the glioblastoma multiforme cell line 13–06-MG. Results In cell-attached configuration, VGB concentration-dependently reduced the activity of intermediate-conductance Ca 2+ -activated K + (IK Ca ) channels, while DCEBIO (5,6-dichloro-1-ethyl-1,3-dihydro-2H-benzimidazol-2-one) counteracted the VGB-induced inhibition of IK Ca channels. However, the activity of neither large-conductance Ca 2+ -activated (BK Ca ) nor inwardly rectifying K + (K IR ) channels were affected by the presence of VGB in human 13–06-MG cells. However, in the continued presence of VGB, the addition of GAL-021 or BaCl 2 effectively suppressed BK Ca and K IR channels. Conclusions The inhibitory effect of VGB on IK Ca channels demonstrated in the current study could be an important underlying mechanism of VGB-induced antineoplastic (e.g., anti-glioma) actions.
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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".