Effects of Posture and Walking on Tibial Vascular Hemodynamics Before and After 14 Days of Head‐Down Bed Rest
Bibliographic record
Abstract
ABSTRACT Human skeletal hemodynamics remain understudied. Neither assessments in weight‐bearing bones during walking nor following periods of immobility exist, despite knowledge of altered nutrient‐artery characteristics after short‐duration unloading in rodents. We studied 12 older adults (8 females, aged 59 ± 3 years) who participated in ambulatory near‐infrared spectroscopy (NIRS) assessments of tibial hemodynamics before (PRE) and after (POST) 14 days of head‐down bed rest (HDBR), with most performing daily resistance and aerobic exercise countermeasures during HDBR. Continual simultaneous NIRS recordings were acquired over the proximal anteromedial tibial prominence of the right lower leg and ipsilateral lateral head of the gastrocnemius muscle during supine rest, walking, and standing. During 10 minutes of walking, desaturation kinetics in the tibia were slower (time to 95% nadir values 125.4 ± 56.8 s versus 55.0 ± 30.1 s, p = 0.0014). Tibial tissue saturation index (TSI) immediately fell (−9.9 ± 4.55) and did not completely recover by the end of 10 minutes of walking (−7.4 ± 6.7%, p = 0.027). Upon standing, total hemoglobin (tHb) kinetics were faster in the tibia ( p < 0.0001), whereas HDBR resulted in faster oxygenated hemoglogin (O 2 Hb) kinetics in both tissues ( p = 0.039). After the walk‐to‐stand transition, changes in O 2 Hb ( p = 0.0022) and tHb ( p = 0.0047) were attenuated in the tibia alone after bed rest. Comparisons of NIRS‐derived variables during ambulation and changes in posture revealed potentially deleterious adaptations of feed vessels after HDBR. We identify important and novel tibial hemodynamics in humans during ambulation before and after bed rest, necessitating further investigation. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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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".