Slower conduction velocity and motor unit discharge frequency are associated with muscle fatigue during isometric exercise in type 1 diabetes mellitus
Bibliographic record
Abstract
Type 1 diabetes mellitus (T1DM) is associated with a peripheral neuropathy that reduces nerve conduction velocity. This may impair high motor-unit discharge frequencies (MUDF), decrease muscle activation, and curtail the ability to sustain repetitive contractile tasks. We examined (1) whether MUDF, the contractile properties of the knee extensors, and the conduction velocity of persons with T1DM differed from controls; (2) whether persons with T1DM can maintain adequate MUDF during a fatigue protocol; and (3) the relationship between these parameters and impaired glycemic control. We studied male and female subjects with T1DM and controls matched for age, height, weight, and gender. Single motor unit recordings were made from vastus lateralis during maximal and submaximal contractions and during a fatigue protocol. Glycemic control was assessed from blood glucose concentration and glycosylated hemoglobin (HbA1c). Control femoral conduction velocities were comparable to literature values and those of the T1DM subjects were slower. These values correlated with plasma glucose and HbA1c. T1DM subjects fatigued 45% sooner than controls, and time to fatigue and conduction velocity were correlated (r = 0.54, P < 0.05). Discharge frequencies tended to be slower during 50% maximal voluntary contractile force in the T1DM subjects at task failure. Persons with T1DM had slower conduction velocities and lower MUDF than their controls, which apparently leads to impaired activation of muscle and decreased endurance during isometric fatigue.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".