Bibliographic record
Abstract
The kinetic attributes of the afferent arteriole myogenic response were investigated using the in vitro perfused hydronephrotic rat kidney. Equations describing the time course for pressure-dependent vasoconstriction and vasodilation, and steady-state changes in diameter were combined to develop a mathematical model of autoregulation. Transfer functions were constructed by passing sinusoidal pressure waves through the model. These findings were compared with results derived using data from instrumented conscious rats. In each case, a reduction in gain and increase in phase were observed at frequencies of 0.2 to 0.3 Hz. We then examined the impact of oscillating pressure signals. The model predicted that pressure signals oscillating at frequencies above the myogenic operating range would elicit a sustained vasoconstriction the magnitude of which was dependent on peak pressure. These predictions were directly confirmed in the hydronephrotic kidney. Pressure oscillations presented at frequencies of 1 to 6 Hz elicited sustained afferent vasoconstrictions and the magnitude of the response depended exclusively on the peak pressure. Elevated systolic pressure elicited vasoconstriction even if mean pressure was reduced. These findings challenge the view that the renal myogenic response exists to maintain glomerular capillary pressure constant, but rather imply a primary role in protecting against elevated systolic pressures. Thus, the kinetic features of the afferent arteriole allow this vessel to adjust tone in response to changes in systolic pressures presented at the pulse rate. We suggest that the primary function of this mechanism is to protect the glomerulus from the blood pressure power that is normally present at the pulse frequency.
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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 | 0.000 | 0.001 |
| 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".