Block of Inward Rectifying K <sup>+</sup> Channels (K <sub>IR</sub> ) Inhibits Bradykinin-Induced Vasodilatation in Human Forearm Resistance Vasculature
Bibliographic record
Abstract
OBJECTIVE: To investigate the possible involvement of inward rectifying K(+) channels (K(IR)) in the response of human resistance vessels to bradykinin in vivo. METHODS AND RESULTS: Drugs were administered via the brachial artery in healthy male volunteers and forearm blood flow was measured by venous occlusion plethysmography. Inhibition of K(IR) by barium chloride (4 micromol min(-1)) alone or with additional inhibition of Na(+)/K(+) ATPase (ouabain 2.7 micromol min(-1)) reduced responses to bradykinin (30 pmol min(-1)), by 26+/-8.3% and 36+/-7.2%, respectively (each P<0 0.05). Barium with ouabain plus inhibitors of prostaglandin (PG) and nitric oxide synthesis inhibited but did not abolish responses to bradykinin (51+/-2.8% inhibition; P<0.01); norepinephrine (240 pmol min(-1)) caused similar reduction of baseline blood flow, as did this combination of inhibitors, but did not significantly inhibit the response to bradykinin. Barium plus ouabain did not significantly reduce responses to acetylcholine or albuterol. CONCLUSIONS: A component of the vasodilator response to bradykinin in human forearm vasculature is mediated by K(IR). The possible involvement of inward-rectifying K+ channels (KIR) in the action of bradykinin was investigated by administering drugs via the brachial artery in healthy men. Barium selectively inhibited the forearm blood flow response to bradykinin, indicating that a component of this response is mediated by KIR.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".