Eicosatetraynoic acid (ETYA), a non-metabolizable analogue of arachidonic acid, blocks the fast-inactivating potassium current of rat pituitary melanotrophs
Bibliographic record
Abstract
The effects of arachidonic acid (5,8,11,14-eicosatetraenoic acid, AA) and 5,8,11,14-eicosatetraynoic acid (ETYA), a non-metabolizable analogue of AA, were examined on the transient [I(K)(f)] and the delayed rectifier-like [I(K)(S)] voltage-gated potassium currents in rat pituitary melanotrophs. The main questions addressed were whether AA and ETYA blocked I(K)(f) and if any blocking action was specific. Macroscopic currents were measured using the patch clamp technique. Bath application of 20 microM AA reduced I(K)(f), however, the degree of the block varied between cells. In contrast, ETYA consistently inhibited I(K)(f). Fitting of the charge transfer or the peak current amplitude yielded KD estimates for ETYA of 1.2 microM and 3.3 microM, respectively. The reduction by ETYA of peak I(K)(f) was always associated with an increased rate of current decay, but there was no detectable change of the kinetics of activation. ETYA caused a small left shift of the I(K)(f) steady-state inactivation curve and significantly slowed recovery from inactivation. At 20 microM, ETYA also reduced I(K)(s), indicating that it is not specific. The possibility that ETYA acts as an open-channel blocker is discussed.
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) | 0.000 | 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".