Motor Unit Firing Rate And Nerve Conduction Velocity In Type 1 Diabetes In Response To A Fatigue Protocol
Bibliographic record
Abstract
Persons with Type 1 diabetes commonly develop a peripheral neuropathy that reduces nerve conduction velocity (NCV) the severity of which is apparently related to the quality of the person's glycemic control. Reduced NCV could impair high motor unit firing rates, decrease the ability to maximally activate muscle and potentially attenuate muscle endurance. PURPOSE To determine: 1) if firing rates and contractile properties of vastus lateralis and the NCV of the femoral nerve of persons with Type 1 diabetes differ from controls, 2) whether persons with Type 1 diabetes can maintain adequate firing rates during progressive fatigue and, 3) the relationship between these parameters and impaired glycemic control. METHODS Male and female subjects, ranging in age from 19–52 years (mean 27.8 ± 11.4 SD years), with Type 1 diabetes, and their age and weight matched controls were used for this study. NCV was measured in the femoral nerve. Motor unit firing rates from vastus lateralis were recorded during brief contractions at 25%, 50% and 75% of the subject's maximal voluntary contraction (MVC) and also continuously during a fatigue protocol. Glycemic control was assessed from blood glucose concentration on experimental days and from glycosylated hemoglobin (HbA1c) at the start of the experiment. RESULTS The control subjects had nerve conduction velocities comparable to those found in the literature of 68.4 ± 5.8 SD m/s, whereas the diabetic subjects had a lower NCV of 45.4 ± 9.3 SD m/s and these values were related to both acute blood glucose concentration (r = −0.69) and HbA1c (r = −0.64). Firing rates at MVC in both groups decreased during fatigue but there was a greater percent decrease (∼ 8%) in the controls due to the higher initial motor unit firing rates in these subjects. CONCLUSIONS The slowing of NCV decreases maximal motor unit firing rates in persons with Type 1 diabetes and these effects are more profound in those persons exhibiting the poorest glycemic control. Supported by NSERC grants to EC and MCR.
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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 | 0.001 |
| 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".