Supraspinal And Muscular Efficiency During Isokinetic Knee Extensions At Three Different Velocities
Bibliographic record
Abstract
Increases in cerebral oxygenation (Cox) are associated with increases in neuronal activation by means of a neurovascular coupling mechanism, while declines in muscle oxygenation (Mox) imply increases in muscle oxygen extraction. PURPOSE: To compare the changes in supraspinal (SSeff) and muscular (MUeff) efficiency during three different velocities of unilateral knee extensions via Near infrared spectroscopy (NIRS). METHODS: Eleven (seven males and four females aged (mean±SD) 23.5 ±3.3 years), consented to complete a protocol of 15 unilateral isokinetic contractions at 150, 300 and 450°·sec-1 in a single testing session, with 4 mins recovery between trials. NIRS was used to examine the changes in Cox and Mox from the left prefrontal lobe and right vastus lateralis respectively. SSeff and MUeff were calculated as the ratios between average torque and the increase in Cox and decline in Mox respectively, from resting baseline values. Repeated measures ANOVA were used to compare the values among the three trials. RESULTS: The power outputs were consistent with the force-velocity curve for muscle contractions. Average torque, Cox and Mox were significantly higher (P <.05) at 150°·sec-1 compared to 300 and 450°·sec-1. This implies that the greater torque at 150°·sec-1 was accompanied by greater neuronal activation and higher muscle oxygen extraction. However, there were no significant differences (P >.05) in SSeff and MUeff among the three contraction velocities. CONCLUSIONS: Isokinetic muscle contractions which result in differing power outputs at different velocities are closely regulated by neuronal and muscular factors such that the overall efficiency remains the same.TABLE
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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) | 0.000 | 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".