Second‐to‐second control of the pressure‐natriuresis mechanism following pharmacological removal of the renin‐angiotensin system (RAS)
Bibliographic record
Abstract
The kidney is a key controller of the long‐term level of arterial pressure (AP), in particular, via pressure‐natriuresis (PN). Increases in renal AP (RAP) directly result in a downstream rise of renal interstitial hydrostatic pressure (RIHP) that is linked to elevated Na + excretion. Though many studies have examined mechanisms and modulators involved in regulating the long‐term control of PN, few have characterized its second‐to‐second control. Thus, the aim was to characterize the acute component of the PN mechanism in vivo before and after pharmacological removal of the RAS. Wistar rats (355 ± 4.4g) were anesthetized (ketamine + thiobutabarbital), and RIHP was determined over a range of RAP using occluder cuffs. The response time for RIHP after a change in RAP was <2 sec. The two treatment groups were: Group 1 ‐ no treatment (n=16) and Group 2 ‐ acute AT 1 R blocker (losartan) treatment (LOS; 10mg/kg/hr iv; n=7). In addition, angiotensin II (Ang II; 250ng/kg) was infused before and after LOS. The RAP‐RIHP relationship was found to be linear over a range of AP (slope = 0.07±0.005). While acute AT 1 blockade lowered RAP (↓30%), surprisingly, the characteristics of the RAP‐RIHP relationship (i.e. slope) were not different from controls. In conclusion, despite causing a depressor response, pharmacological inhibition of the RAS did not alter second‐to‐second control of the RAP‐RIHP relationship. (Funded by CIHR; MK by NSERC)
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".