How to build a lower-body differential pressure chamber integrated on a tilt-table: A pedagogy tool to demonstrate the cardiovagal baroreflex
Bibliographic record
Abstract
The cardiovagal baroreflex is an important physiological reflex that is commonly taught in health-related university physiology courses. This reflex is responsible for the rapid maintenance of blood pressure through dynamic changes in heart rate (HR) and vascular resistance. The use of lower-body negative pressure (LBNP) and lower-body positive pressure (LBPP) can manipulate these stretch sensitive baroreceptors. High performance and relatively inexpensive homemade LBNP and LBPP chambers can be easily constructed providing a valuable tool for both research and teaching purposes. There has been previous documentation of how to build a LBNP chamber; however, the information available usually lacks appropriate construction details, and there is currently no literature on how to build a chamber that can accommodate both LBNP and LBPP. In addition, a recently developed novel LBNP/LBPP chamber positioned on a 360° tilt-table provided the unique utility of superimposing both LBNP/LBPP and body position as independent or combined stressors to alter central blood volume. The primary purposes of this manuscript are to (1) provide step-by-step instructions on how to build a tilt-table LBNP/LBPP chamber, and (2) demonstrate the effectiveness of a tilt-table LBNP/LBPP chamber to facilitate undergraduate and graduate learning in the laboratory by effectively demonstrating the cardiovagal baroreflex.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".