The transient receptor potential channel antagonist SKF96365 is a potent blocker of low‐voltage‐activated T‐type calcium channels
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: SKF96365 (SKF), originally identified as a blocker of receptor-mediated calcium entry, is widely used diagnostically, as a blocker of transient receptor potential canonical type (TRPC) channels. While SKF has been used as a tool to define the functional roles of TRPC channels in various cell and tissue types, there are notable overlapping physiological and pathophysiological associations between TRPC channels and low-voltage-activated (LVA) T-type calcium channels. The activity of SKF against T-type Ca channels has not been previously explored, and here we systematically investigated the effects of SKF on recombinant and native voltage-gated Ca channel-mediated currents. EXPERIMENTAL APPROACH: Effects of SKF on recombinant Ca channels were studied under whole-cell patch clamp conditions after expression in HEK293 cells. The effect of SKF on cerebellar Purkinje cells (PCs) expressing native T-type Ca channels was also assessed. KEY RESULTS: SKF blocked recombinant Ca channels, representative of each of the three main molecular genetic classes (Ca(V)1, Ca(V)2 and Ca(V)3) at concentrations typically utilized to assay TRPC function (10 microM). Particularly, human Ca(V)3.1 T-type Ca channels were more potently inhibited by SKF (IC(50) approximately 560 nM) in our experiments than previously reported for similarly expressed TRPC channels. SKF also inhibited native Ca(V)3.1 T-type currents in a rat cerebellar PC slice preparation. CONCLUSIONS AND IMPLICATIONS: SKF was a potent blocker of LVA T-type Ca channels. We suggest caution in the interpretation of results using SKF alone as a diagnostic agent for TRPC activity in native tissues.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".