The effects of biological sex on estimates of persistent inward currents in the human lower limb
Bibliographic record
Abstract
ABSTRACT Non-invasive recordings of motor unit (MU) spike trains help us understand how the nervous system controls movement and how it adapts to various physiological conditions. The majority of study participants in human and non-human animal physiology studies are male, and it is assumed mechanisms uncovered in these studies are shared between males and females. However, sex differences in neurological impairment and physical performance warrant the study of sex as a biological variable in human physiology and performance. To begin addressing this gap in the study of biophysical properties of human motoneurons, we quantified MU discharge rates and estimates of persistent inward current (PIC) magnitude in both sexes by quantifying ΔF. We decomposed MU spike trains from the tibialis anterior (TA), medial gastrocnemius (MG), and soleus (SOL) using high-density surface electromyography and blind source separation algorithms. Ten participants of each sex performed slow triangular (10s up and down) isometric contractions to a peak of 30% of their maximum voluntary contraction. We then used linear mixed effects models to determine if peak discharge rate and ΔF were predicted by the fixed effects of sex, muscle, and their interaction. Despite a lack of significant sex-differences in peak discharge rates across all muscles, ΔF was larger (χ 2 (1) = 6.26, p = 0.012) in females (4.73 ± 0.242 pps) than males (3.81 ± 0.240 pps). These findings suggest that neuromodulatory drive, inhibitory input, and/or biophysical properties of motoneurons differ between the sexes and may contribute to differences in MU discharge patterns. KEY POINTS – Sex differences in motor unit studies have been revealed with greater inclusion of female participants, however, mechanisms for these differences remain unclear . – Estimates of persistent inward currents (i.e ., ΔF) were greater in females than males in the tibialis anterior, medial gastrocnemius, and soleus muscles. – This suggests that neuromodulatory drive, monoaminergic signaling, or descending control may differ between the sexes. – Therefore, sex differences in estimates of PICs may provide a mechanism behind previously reported sex differences in motoneuron discharge patterns. .
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".