Effects of vasoconstriction and vasodilatation on LV and segmental circulatory energetics
Bibliographic record
Abstract
Although the hydraulic work generated by the left ventricle (LV) is not disputed, how the work was dissipated through the systemic circulation is still subject to interpretation. Recently, we proposed that the systemic circulation should be considered as waves and a reservoir system (Wk). By combining the arterial and venous reservoirs, the systemic vascular resistance can be viewed as a series of resistors, which in sequence are the large-artery resistance, arterial reservoir resistance, the microcirculatory resistance, venous reservoir resistance, and large-vein resistance, and propelling blood through these resistance elements represents resistive losses. We then studied the changes in the fraction of the work consumed by each element when infusing methoxamine (MTX), a vasoconstrictor, and sodium nitroprusside (NP), a vasodilator. Results show that, under control condition, approximately 50% of the LV stroke work was dissipated through arterial reservoir resistance (NP, approximately 36%; MTX, approximately 27%), another approximately 25% was dissipated by the microcirculation (NP, approximately 20%; MTX, approximately 66%), and approximately 20% of work by the large-artery resistances (NP, approximately 37%; MTX, approximately 6%). The energy dissipated by the venous resistances was small and had limited variation with NP and MTX, where the large-vein and venous reservoir resistances shared approximately 1 and approximately 3% of LV stroke work, respectively. Approximately 60% of LV stroke work is stored as the potential energy during systole under control, and the ratio decreases to approximately 45% with NP and approximately 80% with MTX.
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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) | 0.002 | 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".