Physiological basis for longitudinal motion of the arterial wall
Bibliographic record
Abstract
As opposed to arterial distension in the radial plane, longitudinal wall motion (LWM) is a multiphasic and bidirectional displacement of the arterial wall in the anterograde (i.e., in the direction of blood flow) and retrograde (i.e., opposing direction of blood flow) directions. Although initially disregarded as imaging artifact, LWM has been consistently reported in ultrasound investigations in the past decade and is reproducible beat-to-beat, albeit with large interindividual variability across healthy and diseased populations. Emerging literature has sought to examine the mechanistic control of LWM to explain the shape and variability of the motion pattern but lacks considerations for key foundational vascular principles at the level of the arterial wall ultrastructure. The purpose of this review is to summarize the potential factors that underpin the causes and control of arterial LWM, spanning considerations from the arterial extracellular matrix to systems-level integrative theories. First, an overview of LWM and relevant aspects wall composition will be discussed, including major features of the multiphasic pattern, arterial wall extracellular components, tunica fiber orientations, and arterial longitudinal prestretch. Second, current theories on the systems-level physiological mechanisms driving LWM will be discussed in the context of available evidence including experimental human research, porcine studies, and mathematical models. Throughout, we discuss implications of these observations with suggestions for future priority research areas.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.001 |
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".