NEAR-INFRARED MONITORING OF THE LUMBAR ERECTOR SPINAE MUSCLE IN HEALTHY MEN AND WOMEN DURING STATIC AND DYNAMIC ENDURANCE WORK
Bibliographic record
Abstract
Understanding muscle hemodynamics using near-infrared spectroscopy is increasingly evident in the recent spinal disorders-related literature. However, none of these human studies addressed the issue of physiological limits for the lumbar muscle within the same participants during various exercise modes. The purpose of this study is to evaluate physiological limits for the lumbar muscle during dynamic and static endurance tests. On three separate days, 22 healthy men and women performed three endurance protocols (static prone trunk extension, arm cranking, and pushing–pulling) until volitional exhaustion. For each protocol, minimum and maximum oxygenation and blood volume responses from the right lumbar erector spinae were obtained using a continuous dual wavelength near-infrared spectroscopy (Micro-Runman, NIM Inc., PA, USA). Statistical analysis showed that greatest reduction in oxygenation (minimum) were obtained during dynamic exercises: pushing–pulling (2.1 times) and arm cranking (2.03 times) versus static test (P < 0.05). Physiological change (calculated as the difference between maximum during recovery and minimum at the point of volitional exhaustion) during static test was lower [(66–75% for oxygenation) and (34–46% for blood volume)] than dynamic exercises (P < 0.05). Contrary to the theory that sufficient occlusion of blood flow to the lumbar muscle is possible with static trunk extension, it was concluded that a dynamic protocol until volitional exhaustion might be a good alternative in establishing near-infrared spectroscopy-derived physiological limits to the lumbar muscle. Further research is essential to identify an optimal calibration procedure for establishing true hypoxic values for the human lumbar muscle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".