Systolic blood pressure as the trigger for the renal myogenic response: protective or autoregulatory?
Bibliographic record
Abstract
PURPOSE OF REVIEW: The ability of the kidney to autoregulate renal blood flow and glomerular filtration rate has long been viewed as existing to prevent fluctuations in blood pressure from causing parallel fluctuations in renal function and distal delivery of filtrate. This review, however, points out that the primary consequence of the loss of this autoregulatory capacity is not a disturbance in volume regulation, but rather an increased susceptibility to hypertensive injury. Moreover, the kinetic requirements for renal protection indicate that current views of dynamic autoregulation cannot explain how the kidney is normally protected against acute elevations in systolic blood pressure. RECENT FINDINGS: Recent findings suggest that the kinetics of the myogenic mechanism of the afferent arteriole are uniquely suited to protect against acute elevations in the systolic blood pressure, in that this vessel not only senses this rapidly oscillating blood pressure component, but that its response is exclusively dependent on this signal. SUMMARY: These new findings are consistent with recent data indicating that it is the systolic blood pressure elevations that most closely correlate with target organ damage. The fact that the myogenic mechanism is also a necessary component of renal autoregulation may explain the strong linkage between autoregulatory impairment and increased susceptibility to hypertensive injury.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".