A structure-function analysis of the left ventricle
Bibliographic record
Abstract
This study presents a structure-function analysis of the mammalian left ventricle and examines the performance of the cardiac capillary network, mitochondria, and myofibrils at rest and during simulated heavy exercise. Left ventricular external mechanical work rate was calculated from cardiac output and systemic mean arterial blood pressure in resting sheep ( Ovis aries; n = 4) and goats ( Capra hircus; n = 4) under mild sedation, followed by perfusion-fixation of the left ventricle and quantification of the cardiac capillary-tissue geometry and cardiomyocyte ultrastructure. The investigation was then extended to heavy exercise by increasing cardiac work according to published hemodynamics of sheep and goats performing sustained treadmill exercise. Left ventricular work rate averaged 0.017 W/cm3of tissue at rest and was estimated to increase to ∼0.060 W/cm3during heavy exercise. According to an oxygen transport model we applied to the left ventricular tissue, we predicted that oxygen consumption increases from 195 nmol O2·s−1·cm−3of tissue at rest to ∼600 nmol O2·s−1·cm−3during heavy exercise, which is within 90% of the oxygen demand rate and consistent with work remaining predominantly aerobic. Mitochondria represent 21-22% of cardiomyocyte volume and consume oxygen at a rate of 1,150 nmol O2·s−1·cm−3of mitochondria at rest and ∼3,600 nmol O2·s−1·cm−3during heavy exercise, which is within 80% of maximum in vitro rates and consistent with mitochondria operating near their functional limits. Myofibrils represent 65–66% of cardiomyocyte volume, and according to a Laplacian model of the left ventricular chamber, generate peak fiber tensions in the range of 50 to 70 kPa at rest and during heavy exercise, which is less than maximum tension of isolated cardiac tissue (120–140 kPa) and is explained by an apparent reserve capacity for tension development built into the left ventricle.
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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 | 0.000 |
| 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 | 0.000 |
| 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".