Decreased motor unit discharge rate in the potentiated human tibialis anterior muscle
Bibliographic record
Abstract
AIM: The purpose of this study was to examine the influence of post-activation potentiation (PAP), the transient increase in low-frequency isometric force observed after muscle activity, on motor unit discharge rates measured during submaximal contractions. METHODS: A quadrifilar needle electrode was inserted into the tibialis anterior muscle to determine discharge rate of individual motor units while monopolar electrodes were used to monitor the root-mean-square (RMS) and mean power frequency (MPF) of the surface EMG signal. Control (unpotentiated) and experimental (potentiated) measures were obtained during a 5 s voluntary contraction at 50% of maximal. In between these measures, subjects performed a 10 s maximal voluntary contraction (MVC) to induce PAP. RESULTS: All subjects data are reported as means ± SEM (n = 10). Compared to baseline values measured prior to the MVC, isometric twitch force measured immediately after the MVC was increased by 260 ± 16% (day 3). Motor unit discharge rate in the potentiated tibialis anterior muscle decreased by approx. 10%, from 20.3 ± 0.8 (before) to 18.3 ± 0.99 pps (P = 0.01) (after). Moreover, the MPF was decreased by approx. 9% (from 58.1 ± 2.84 to 53.6 ± 2.85 Hz; P = 0.01) in the potentiated tibialis anterior. On the other hand, consistent with the absence of fatigue during the MVC, the RMS signal was not altered in the potentiated tibialis anterior (0.29 ± 0.03 vs. 0.33 ± 0.04 mV; P = 0.07). CONCLUSION: Motor unit discharge rates determined during a brief, submaximal contraction were decreased in the potentiated human tibialis anterior muscle.
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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) | 0.002 | 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".